From 2a2ad0bf36cab0dcc18ec333018df57cc96c1426 Mon Sep 17 00:00:00 2001 From: zhanghongqing Date: Wed, 19 Jun 2024 13:56:52 +0800 Subject: [PATCH 1/4] =?UTF-8?q?GAL-578=20=E6=9B=B4=E6=96=B0groot=E4=BB=BB?= =?UTF-8?q?=E5=8A=A1=E6=A8=A1=E6=9D=BF?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../templates/data_transporter.yaml.j2 | 5 ++- .../datapath_telemetry_record.yaml.j2 | 5 ++- ..._kafka_to_clickhouse => dos_event.yaml.j2} | 31 ++++++++++++++----- .../templates/proxy_event.yaml.j2 | 12 ++----- .../templates/session_record.yaml.j2 | 10 ++---- .../templates/traffic_sketch_metric.yaml.j2 | 9 +++--- .../templates/transaction_record.yaml.j2 | 4 +-- .../templates/voip_record.yaml.j2 | 10 ++---- .../templates/data_transporter.yaml.j2 | 5 ++- .../datapath_telemetry_record.yaml.j2 | 5 ++- ..._kafka_to_clickhouse => dos_event.yaml.j2} | 31 ++++++++++++++----- .../templates/proxy_event.yaml.j2 | 12 ++----- .../templates/session_record.yaml.j2 | 10 ++---- .../templates/traffic_sketch_metric.yaml.j2 | 9 +++--- .../templates/transaction_record.yaml.j2 | 4 +-- .../templates/voip_record.yaml.j2 | 10 ++---- 16 files changed, 78 insertions(+), 94 deletions(-) rename tsg_olap/installation/flink/groot_stream/templates/{dos_event_kafka_to_clickhouse => dos_event.yaml.j2} (59%) rename tsg_olap/upgrade/TSG-24.06/groot_stream/templates/{dos_event_kafka_to_clickhouse => dos_event.yaml.j2} (59%) diff --git a/tsg_olap/installation/flink/groot_stream/templates/data_transporter.yaml.j2 b/tsg_olap/installation/flink/groot_stream/templates/data_transporter.yaml.j2 index e5c6273..5ad1d25 100644 --- a/tsg_olap/installation/flink/groot_stream/templates/data_transporter.yaml.j2 +++ b/tsg_olap/installation/flink/groot_stream/templates/data_transporter.yaml.j2 @@ -19,7 +19,7 @@ sinks: type: kafka properties: topic: {{ kafka_sink_topic }} - kafka.bootstrap.servers: { { kafka_sink_servers } } + kafka.bootstrap.servers: {{ kafka_sink_servers }} kafka.retries: 0 kafka.linger.ms: 10 kafka.request.timeout.ms: 30000 @@ -35,7 +35,7 @@ sinks: clickhouse_sink: type: clickhouse properties: - host: {{ clickhouse_servers }} + host: {{ clickhouse_sink_host }} table: tsg_galaxy_v3.traffic_sketch_metric_local batch.size: 100000 batch.interval: 30s @@ -48,7 +48,6 @@ application: shade.identifier: aes pipeline: object-reuse: true - topology: {{ topology }} diff --git a/tsg_olap/installation/flink/groot_stream/templates/datapath_telemetry_record.yaml.j2 b/tsg_olap/installation/flink/groot_stream/templates/datapath_telemetry_record.yaml.j2 index 58da17c..06058b8 100644 --- a/tsg_olap/installation/flink/groot_stream/templates/datapath_telemetry_record.yaml.j2 +++ b/tsg_olap/installation/flink/groot_stream/templates/datapath_telemetry_record.yaml.j2 @@ -2,7 +2,7 @@ sources: kafka_source: type: kafka properties: - topic: DATAPATH-TELEMETRY-RECORD + topic: {{ kafka_source_topic }} kafka.bootstrap.servers: {{ kafka_source_servers }} kafka.session.timeout.ms: 60000 kafka.max.poll.records: 3000 @@ -37,7 +37,7 @@ sinks: kafka_sink: type: kafka properties: - topic: DATAPATH-TELEMETRY-RECORD + topic: {{ kafka_sink_topic }} kafka.bootstrap.servers: {{ kafka_sink_servers }} kafka.retries: 0 kafka.linger.ms: 10 @@ -71,7 +71,6 @@ application: shade.identifier: aes pipeline: object-reuse: true - topology: {{ topology }} diff --git a/tsg_olap/installation/flink/groot_stream/templates/dos_event_kafka_to_clickhouse b/tsg_olap/installation/flink/groot_stream/templates/dos_event.yaml.j2 similarity index 59% rename from tsg_olap/installation/flink/groot_stream/templates/dos_event_kafka_to_clickhouse rename to tsg_olap/installation/flink/groot_stream/templates/dos_event.yaml.j2 index 49a3d1a..e44b182 100644 --- a/tsg_olap/installation/flink/groot_stream/templates/dos_event_kafka_to_clickhouse +++ b/tsg_olap/installation/flink/groot_stream/templates/dos_event.yaml.j2 @@ -2,7 +2,7 @@ sources: kafka_source: type: kafka properties: - topic: DOS-EVENT + topic: {{ kafka_source_topic }} kafka.bootstrap.servers: "{{ kafka_source_servers }}" kafka.session.timeout.ms: 60000 kafka.max.poll.records: 3000 @@ -22,12 +22,30 @@ sources: kafka.compression.type: none format: json - sinks: + kafka_sink: + type: kafka + properties: + topic: {{ kafka_sink_topic }} + kafka.bootstrap.servers: {{ kafka_sink_servers }} + kafka.retries: 0 + kafka.linger.ms: 10 + kafka.request.timeout.ms: 30000 + kafka.batch.size: 262144 + kafka.buffer.memory: 134217728 + kafka.max.request.size: 10485760 + kafka.compression.type: snappy + kafka.security.protocol: SASL_PLAINTEXT + kafka.sasl.mechanism: PLAIN + kafka.sasl.jaas.config: 454f65ea6eef1256e3067104f82730e737b68959560966b811e7ff364116b03124917eb2b0f3596f14733aa29ebad9352644ce1a5c85991c6f01ba8a5e8f177a7ff0b2d3889a424249967b3870b50993d9644f239f0de82cdb13bdb502959e16afadffa49ef1e1d2b9c9b5113e619817 + format: json + json.ignore.parse.errors: false + log.failures.only: true + clickhouse_sink: type: clickhouse properties: - host: "{{ clickhouse_servers }}" + host: {{ clickhouse_sink_host }} table: tsg_galaxy_v3.dos_event_local batch.size: 100000 batch.interval: 30s @@ -37,13 +55,10 @@ sinks: application: env: - name: dos_event_kafka_to_clickhouse + name: {{ job_name }} shade.identifier: aes pipeline: object-reuse: true # [boolean] Object Reuse, default is false - topology: - - name: kafka_source - downstream: [clickhouse_sink] - - name: clickhouse_sink + {{ topology }} diff --git a/tsg_olap/installation/flink/groot_stream/templates/proxy_event.yaml.j2 b/tsg_olap/installation/flink/groot_stream/templates/proxy_event.yaml.j2 index cee0548..6c750e2 100644 --- a/tsg_olap/installation/flink/groot_stream/templates/proxy_event.yaml.j2 +++ b/tsg_olap/installation/flink/groot_stream/templates/proxy_event.yaml.j2 @@ -2,7 +2,7 @@ sources: kafka_source: type: kafka properties: - topic: PROXY-EVENT + topic: {{ kafka_source_topic }} kafka.bootstrap.servers: {{ kafka_source_servers }} kafka.session.timeout.ms: 60000 kafka.max.poll.records: 3000 @@ -50,12 +50,6 @@ processing_pipelines: parameters: value_expression: recv_time - - function: DOMAIN - lookup_fields: [http_host, ssl_sni, dtls_sni, quic_sni] - output_fields: [server_domain] - parameters: - option: FIRST_SIGNIFICANT_SUBDOMAIN - - function: BASE64_DECODE_TO_STRING output_fields: [mail_subject] parameters: @@ -107,7 +101,7 @@ sinks: kafka_sink: type: kafka properties: - topic: PROXY-EVENT + topic: {{ kafka_sink_topic }} kafka.bootstrap.servers: {{ kafka_sink_servers }} kafka.retries: 0 kafka.linger.ms: 10 @@ -141,6 +135,4 @@ application: shade.identifier: aes pipeline: object-reuse: true - topology: {{ topology }} - diff --git a/tsg_olap/installation/flink/groot_stream/templates/session_record.yaml.j2 b/tsg_olap/installation/flink/groot_stream/templates/session_record.yaml.j2 index 8938cd2..7970a95 100644 --- a/tsg_olap/installation/flink/groot_stream/templates/session_record.yaml.j2 +++ b/tsg_olap/installation/flink/groot_stream/templates/session_record.yaml.j2 @@ -2,7 +2,7 @@ sources: kafka_source: type: kafka properties: - topic: SESSION-RECORD + topic: {{ kafka_source_topic }} kafka.bootstrap.servers: {{ kafka_source_servers }} kafka.session.timeout.ms: 60000 kafka.max.poll.records: 3000 @@ -50,12 +50,6 @@ processing_pipelines: parameters: value_expression: recv_time - - function: DOMAIN - lookup_fields: [http_host, ssl_sni, dtls_sni, quic_sni] - output_fields: [server_domain] - parameters: - option: FIRST_SIGNIFICANT_SUBDOMAIN - - function: BASE64_DECODE_TO_STRING output_fields: [mail_subject] parameters: @@ -107,7 +101,7 @@ sinks: kafka_sink: type: kafka properties: - topic: SESSION-RECORD + topic: {{ kafka_sink_topic }} kafka.bootstrap.servers: {{ kafka_sink_servers }} kafka.retries: 0 kafka.linger.ms: 10 diff --git a/tsg_olap/installation/flink/groot_stream/templates/traffic_sketch_metric.yaml.j2 b/tsg_olap/installation/flink/groot_stream/templates/traffic_sketch_metric.yaml.j2 index 0a048a0..571c1af 100644 --- a/tsg_olap/installation/flink/groot_stream/templates/traffic_sketch_metric.yaml.j2 +++ b/tsg_olap/installation/flink/groot_stream/templates/traffic_sketch_metric.yaml.j2 @@ -2,7 +2,7 @@ sources: kafka_source: type: kafka properties: - topic: TRAFFIC-SKETCH-METRIC + topic: {{ kafka_source_topic }} kafka.bootstrap.servers: {{ kafka_source_servers }} kafka.session.timeout.ms: 60000 kafka.max.poll.records: 3000 @@ -62,12 +62,11 @@ processing_pipelines: parameters: data_center_id_num: 1 - sinks: kafka_sink: type: kafka properties: - topic: TRAFFIC-SKETCH-METRIC + topic: {{ kafka_sink_topic }} kafka.bootstrap.servers: {{ kafka_sink_servers }} kafka.retries: 0 kafka.linger.ms: 10 @@ -86,7 +85,7 @@ sinks: clickhouse_sink: type: clickhouse properties: - host: {{ clickhouse_servers }} + host: {{ clickhouse_sink_host }} table: tsg_galaxy_v3.traffic_sketch_metric_local batch.size: 100000 batch.interval: 30s @@ -97,7 +96,7 @@ sinks: application: env: # [object] Environment Variables - name: etl_traffic_sketch_metric # [string] Job Name + name: {{ job_name }} shade.identifier: aes pipeline: object-reuse: true # [boolean] Object Reuse, default is false diff --git a/tsg_olap/installation/flink/groot_stream/templates/transaction_record.yaml.j2 b/tsg_olap/installation/flink/groot_stream/templates/transaction_record.yaml.j2 index 9c8fa4b..49d1782 100644 --- a/tsg_olap/installation/flink/groot_stream/templates/transaction_record.yaml.j2 +++ b/tsg_olap/installation/flink/groot_stream/templates/transaction_record.yaml.j2 @@ -2,7 +2,7 @@ sources: kafka_source: type: kafka properties: - topic: TRANSACTION-RECORD + topic: {{ kafka_source_topic }} kafka.bootstrap.servers: {{ kafka_source_servers }} kafka.session.timeout.ms: 60000 kafka.max.poll.records: 3000 @@ -107,7 +107,7 @@ sinks: kafka_sink: type: kafka properties: - topic: TRANSACTION-RECORD + topic: {{ kafka_sink_topic }} kafka.bootstrap.servers: {{ kafka_sink_servers }} kafka.retries: 0 kafka.linger.ms: 10 diff --git a/tsg_olap/installation/flink/groot_stream/templates/voip_record.yaml.j2 b/tsg_olap/installation/flink/groot_stream/templates/voip_record.yaml.j2 index 1a561f2..a37d469 100644 --- a/tsg_olap/installation/flink/groot_stream/templates/voip_record.yaml.j2 +++ b/tsg_olap/installation/flink/groot_stream/templates/voip_record.yaml.j2 @@ -2,7 +2,7 @@ sources: kafka_source: type: kafka properties: - topic: VOIP-CONVERSATION-RECORD + topic: {{ kafka_source_topic }} kafka.bootstrap.servers: {{ kafka_source_servers }} kafka.session.timeout.ms: 60000 kafka.max.poll.records: 3000 @@ -50,12 +50,6 @@ processing_pipelines: parameters: value_expression: recv_time - - function: DOMAIN - lookup_fields: [http_host, ssl_sni, dtls_sni, quic_sni] - output_fields: [server_domain] - parameters: - option: FIRST_SIGNIFICANT_SUBDOMAIN - - function: BASE64_DECODE_TO_STRING output_fields: [mail_subject] parameters: @@ -107,7 +101,7 @@ sinks: kafka_sink: type: kafka properties: - topic: VOIP-CONVERSATION-RECORD + topic: {{ kafka_sink_topic }} kafka.bootstrap.servers: {{ kafka_sink_servers }} kafka.retries: 0 kafka.linger.ms: 10 diff --git a/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/data_transporter.yaml.j2 b/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/data_transporter.yaml.j2 index e5c6273..5ad1d25 100644 --- a/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/data_transporter.yaml.j2 +++ b/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/data_transporter.yaml.j2 @@ -19,7 +19,7 @@ sinks: type: kafka properties: topic: {{ kafka_sink_topic }} - kafka.bootstrap.servers: { { kafka_sink_servers } } + kafka.bootstrap.servers: {{ kafka_sink_servers }} kafka.retries: 0 kafka.linger.ms: 10 kafka.request.timeout.ms: 30000 @@ -35,7 +35,7 @@ sinks: clickhouse_sink: type: clickhouse properties: - host: {{ clickhouse_servers }} + host: {{ clickhouse_sink_host }} table: tsg_galaxy_v3.traffic_sketch_metric_local batch.size: 100000 batch.interval: 30s @@ -48,7 +48,6 @@ application: shade.identifier: aes pipeline: object-reuse: true - topology: {{ topology }} diff --git a/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/datapath_telemetry_record.yaml.j2 b/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/datapath_telemetry_record.yaml.j2 index 58da17c..06058b8 100644 --- a/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/datapath_telemetry_record.yaml.j2 +++ b/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/datapath_telemetry_record.yaml.j2 @@ -2,7 +2,7 @@ sources: kafka_source: type: kafka properties: - topic: DATAPATH-TELEMETRY-RECORD + topic: {{ kafka_source_topic }} kafka.bootstrap.servers: {{ kafka_source_servers }} kafka.session.timeout.ms: 60000 kafka.max.poll.records: 3000 @@ -37,7 +37,7 @@ sinks: kafka_sink: type: kafka properties: - topic: DATAPATH-TELEMETRY-RECORD + topic: {{ kafka_sink_topic }} kafka.bootstrap.servers: {{ kafka_sink_servers }} kafka.retries: 0 kafka.linger.ms: 10 @@ -71,7 +71,6 @@ application: shade.identifier: aes pipeline: object-reuse: true - topology: {{ topology }} diff --git a/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/dos_event_kafka_to_clickhouse b/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/dos_event.yaml.j2 similarity index 59% rename from tsg_olap/upgrade/TSG-24.06/groot_stream/templates/dos_event_kafka_to_clickhouse rename to tsg_olap/upgrade/TSG-24.06/groot_stream/templates/dos_event.yaml.j2 index 49a3d1a..e44b182 100644 --- a/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/dos_event_kafka_to_clickhouse +++ b/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/dos_event.yaml.j2 @@ -2,7 +2,7 @@ sources: kafka_source: type: kafka properties: - topic: DOS-EVENT + topic: {{ kafka_source_topic }} kafka.bootstrap.servers: "{{ kafka_source_servers }}" kafka.session.timeout.ms: 60000 kafka.max.poll.records: 3000 @@ -22,12 +22,30 @@ sources: kafka.compression.type: none format: json - sinks: + kafka_sink: + type: kafka + properties: + topic: {{ kafka_sink_topic }} + kafka.bootstrap.servers: {{ kafka_sink_servers }} + kafka.retries: 0 + kafka.linger.ms: 10 + kafka.request.timeout.ms: 30000 + kafka.batch.size: 262144 + kafka.buffer.memory: 134217728 + kafka.max.request.size: 10485760 + kafka.compression.type: snappy + kafka.security.protocol: SASL_PLAINTEXT + kafka.sasl.mechanism: PLAIN + kafka.sasl.jaas.config: 454f65ea6eef1256e3067104f82730e737b68959560966b811e7ff364116b03124917eb2b0f3596f14733aa29ebad9352644ce1a5c85991c6f01ba8a5e8f177a7ff0b2d3889a424249967b3870b50993d9644f239f0de82cdb13bdb502959e16afadffa49ef1e1d2b9c9b5113e619817 + format: json + json.ignore.parse.errors: false + log.failures.only: true + clickhouse_sink: type: clickhouse properties: - host: "{{ clickhouse_servers }}" + host: {{ clickhouse_sink_host }} table: tsg_galaxy_v3.dos_event_local batch.size: 100000 batch.interval: 30s @@ -37,13 +55,10 @@ sinks: application: env: - name: dos_event_kafka_to_clickhouse + name: {{ job_name }} shade.identifier: aes pipeline: object-reuse: true # [boolean] Object Reuse, default is false - topology: - - name: kafka_source - downstream: [clickhouse_sink] - - name: clickhouse_sink + {{ topology }} diff --git a/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/proxy_event.yaml.j2 b/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/proxy_event.yaml.j2 index cee0548..6c750e2 100644 --- a/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/proxy_event.yaml.j2 +++ b/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/proxy_event.yaml.j2 @@ -2,7 +2,7 @@ sources: kafka_source: type: kafka properties: - topic: PROXY-EVENT + topic: {{ kafka_source_topic }} kafka.bootstrap.servers: {{ kafka_source_servers }} kafka.session.timeout.ms: 60000 kafka.max.poll.records: 3000 @@ -50,12 +50,6 @@ processing_pipelines: parameters: value_expression: recv_time - - function: DOMAIN - lookup_fields: [http_host, ssl_sni, dtls_sni, quic_sni] - output_fields: [server_domain] - parameters: - option: FIRST_SIGNIFICANT_SUBDOMAIN - - function: BASE64_DECODE_TO_STRING output_fields: [mail_subject] parameters: @@ -107,7 +101,7 @@ sinks: kafka_sink: type: kafka properties: - topic: PROXY-EVENT + topic: {{ kafka_sink_topic }} kafka.bootstrap.servers: {{ kafka_sink_servers }} kafka.retries: 0 kafka.linger.ms: 10 @@ -141,6 +135,4 @@ application: shade.identifier: aes pipeline: object-reuse: true - topology: {{ topology }} - diff --git a/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/session_record.yaml.j2 b/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/session_record.yaml.j2 index 8938cd2..7970a95 100644 --- a/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/session_record.yaml.j2 +++ b/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/session_record.yaml.j2 @@ -2,7 +2,7 @@ sources: kafka_source: type: kafka properties: - topic: SESSION-RECORD + topic: {{ kafka_source_topic }} kafka.bootstrap.servers: {{ kafka_source_servers }} kafka.session.timeout.ms: 60000 kafka.max.poll.records: 3000 @@ -50,12 +50,6 @@ processing_pipelines: parameters: value_expression: recv_time - - function: DOMAIN - lookup_fields: [http_host, ssl_sni, dtls_sni, quic_sni] - output_fields: [server_domain] - parameters: - option: FIRST_SIGNIFICANT_SUBDOMAIN - - function: BASE64_DECODE_TO_STRING output_fields: [mail_subject] parameters: @@ -107,7 +101,7 @@ sinks: kafka_sink: type: kafka properties: - topic: SESSION-RECORD + topic: {{ kafka_sink_topic }} kafka.bootstrap.servers: {{ kafka_sink_servers }} kafka.retries: 0 kafka.linger.ms: 10 diff --git a/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/traffic_sketch_metric.yaml.j2 b/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/traffic_sketch_metric.yaml.j2 index 0a048a0..571c1af 100644 --- a/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/traffic_sketch_metric.yaml.j2 +++ b/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/traffic_sketch_metric.yaml.j2 @@ -2,7 +2,7 @@ sources: kafka_source: type: kafka properties: - topic: TRAFFIC-SKETCH-METRIC + topic: {{ kafka_source_topic }} kafka.bootstrap.servers: {{ kafka_source_servers }} kafka.session.timeout.ms: 60000 kafka.max.poll.records: 3000 @@ -62,12 +62,11 @@ processing_pipelines: parameters: data_center_id_num: 1 - sinks: kafka_sink: type: kafka properties: - topic: TRAFFIC-SKETCH-METRIC + topic: {{ kafka_sink_topic }} kafka.bootstrap.servers: {{ kafka_sink_servers }} kafka.retries: 0 kafka.linger.ms: 10 @@ -86,7 +85,7 @@ sinks: clickhouse_sink: type: clickhouse properties: - host: {{ clickhouse_servers }} + host: {{ clickhouse_sink_host }} table: tsg_galaxy_v3.traffic_sketch_metric_local batch.size: 100000 batch.interval: 30s @@ -97,7 +96,7 @@ sinks: application: env: # [object] Environment Variables - name: etl_traffic_sketch_metric # [string] Job Name + name: {{ job_name }} shade.identifier: aes pipeline: object-reuse: true # [boolean] Object Reuse, default is false diff --git a/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/transaction_record.yaml.j2 b/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/transaction_record.yaml.j2 index 9c8fa4b..49d1782 100644 --- a/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/transaction_record.yaml.j2 +++ b/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/transaction_record.yaml.j2 @@ -2,7 +2,7 @@ sources: kafka_source: type: kafka properties: - topic: TRANSACTION-RECORD + topic: {{ kafka_source_topic }} kafka.bootstrap.servers: {{ kafka_source_servers }} kafka.session.timeout.ms: 60000 kafka.max.poll.records: 3000 @@ -107,7 +107,7 @@ sinks: kafka_sink: type: kafka properties: - topic: TRANSACTION-RECORD + topic: {{ kafka_sink_topic }} kafka.bootstrap.servers: {{ kafka_sink_servers }} kafka.retries: 0 kafka.linger.ms: 10 diff --git a/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/voip_record.yaml.j2 b/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/voip_record.yaml.j2 index 1a561f2..a37d469 100644 --- a/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/voip_record.yaml.j2 +++ b/tsg_olap/upgrade/TSG-24.06/groot_stream/templates/voip_record.yaml.j2 @@ -2,7 +2,7 @@ sources: kafka_source: type: kafka properties: - topic: VOIP-CONVERSATION-RECORD + topic: {{ kafka_source_topic }} kafka.bootstrap.servers: {{ kafka_source_servers }} kafka.session.timeout.ms: 60000 kafka.max.poll.records: 3000 @@ -50,12 +50,6 @@ processing_pipelines: parameters: value_expression: recv_time - - function: DOMAIN - lookup_fields: [http_host, ssl_sni, dtls_sni, quic_sni] - output_fields: [server_domain] - parameters: - option: FIRST_SIGNIFICANT_SUBDOMAIN - - function: BASE64_DECODE_TO_STRING output_fields: [mail_subject] parameters: @@ -107,7 +101,7 @@ sinks: kafka_sink: type: kafka properties: - topic: VOIP-CONVERSATION-RECORD + topic: {{ kafka_sink_topic }} kafka.bootstrap.servers: {{ kafka_sink_servers }} kafka.retries: 0 kafka.linger.ms: 10 From 899e65c14b9be1dbb38ee4b86b621ae0607b8aa1 Mon Sep 17 00:00:00 2001 From: wangchengcheng Date: Tue, 13 Aug 2024 10:35:06 +0800 Subject: [PATCH 2/4] 1.Fix the expression of the alert rule 2.Optimizing chart expressions --- .../TSG-OLAP-AlertRule-temp-v24.02.xlsx | Bin 14170 -> 14153 bytes .../TSG-OLAP-Dashboard-temp-v24.02.json | 1122 +++++++++++++---- .../TSG-OLAP-Module-temp-v24.02.xlsx | Bin 9148 -> 8913 bytes .../TSG-OLAP-AlertRule-temp-v24.05.xlsx | Bin 14170 -> 14153 bytes .../TSG-OLAP-Dashboard-temp-v24.05.json | 1122 +++++++++++++---- .../TSG-OLAP-Module-temp-v24.05.xlsx | Bin 9148 -> 8913 bytes .../TSG-OLAP-AlertRule-temp-v24.06.xlsx | Bin 0 -> 14153 bytes .../TSG-OLAP-AlertRule-temp-v24.06xlsx | Bin 14170 -> 0 bytes .../TSG-OLAP-Dashboard-temp-v24.06.json | 1122 +++++++++++++---- .../TSG-OLAP-Module-temp-v24.06.xlsx | Bin 9148 -> 8913 bytes 10 files changed, 2619 insertions(+), 747 deletions(-) create mode 100644 tsg_olap/installation/monitoring/TSG-24.06/TSG-OLAP-AlertRule-temp-v24.06.xlsx delete mode 100644 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z%<)k2&SU!!L~#3G|8pzJ?;lDs-Fhm@YV8&P0Du8H0Kj^4{ohYZGJ*I*>`jqd&wl`C CH&I0Z diff --git a/tsg_olap/installation/monitoring/TSG-24.02/TSG-OLAP-Dashboard-temp-v24.02.json b/tsg_olap/installation/monitoring/TSG-24.02/TSG-OLAP-Dashboard-temp-v24.02.json index 27583dc..c418f42 100644 --- a/tsg_olap/installation/monitoring/TSG-24.02/TSG-OLAP-Dashboard-temp-v24.02.json +++ b/tsg_olap/installation/monitoring/TSG-24.02/TSG-OLAP-Dashboard-temp-v24.02.json @@ -1,6 +1,6 @@ [ { - "name":"[24.05] OLAP Component Status Template", + "name":"OLAP Component Status Template", "type":"template", "varType":0, "param":{ @@ -124,20 +124,37 @@ "label":"" }, "stack":false, - "thresholds":[ - { - "val":"80", - "color":"#d64f40", - "id":"4a4faa2b", - "value":80 - } - ], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "avg", @@ -146,17 +163,26 @@ ], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[ + { + "val":"80", + "color":"#d64f40", + "id":"a85bb03", + "value":80 + } + ], "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -194,20 +220,37 @@ "label":"" }, "stack":false, - "thresholds":[ - { - "val":"100", - "color":"#d64f40", - "id":"d690d63", - "value":100 - } - ], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "min", @@ -217,17 +260,26 @@ ], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[ + { + "val":"100", + "color":"#d64f40", + "id":"62fbf61", + "value":100 + } + ], "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -308,7 +360,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -355,35 +407,61 @@ "label":"" }, "stack":false, - "thresholds":[ - { - "val":"100000", - "color":"#d64f40", - "id":"32d9b8b", - "value":100000 - } - ], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[ + { + "val":"100000", + "color":"#d64f40", + "id":"58f8e1ad", + "value":100000 + } + ], "enable":{ "thresholds":false, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -463,7 +541,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -554,7 +632,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -664,19 +742,37 @@ "label":"" }, "stack":false, - "thresholds":[ - { - "color":"#C4162AFF", - "id":"74e960f", - "value":0.8 - } - ], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "avg", @@ -684,17 +780,25 @@ ], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[ + { + "color":"#C4162AFF", + "id":"884bf8a", + "value":0.8 + } + ], "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -732,20 +836,37 @@ "label":"" }, "stack":false, - "thresholds":[ - { - "val":"0.7", - "color":"#d64f40", - "id":"24d5201a", - "value":0.8 - } - ], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "avg", @@ -753,17 +874,26 @@ ], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[ + { + "val":"0.7", + "color":"#d64f40", + "id":"68f1c6c2", + "value":0.8 + } + ], "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -801,20 +931,37 @@ "label":"" }, "stack":false, - "thresholds":[ - { - "val":"0.7", - "color":"#d64f40", - "id":"2aefe71f", - "value":0.8 - } - ], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "avg", @@ -822,17 +969,26 @@ ], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[ + { + "val":"0.7", + "color":"#d64f40", + "id":"a927eeb", + "value":0.8 + } + ], "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -870,20 +1026,37 @@ "label":"" }, "stack":false, - "thresholds":[ - { - "val":"0.7", - "color":"#d64f40", - "id":"861cdc1", - "value":0.8 - } - ], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "avg", @@ -891,17 +1064,26 @@ ], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[ + { + "val":"0.7", + "color":"#d64f40", + "id":"2022c819", + "value":0.8 + } + ], "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -945,6 +1127,31 @@ "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "avg", @@ -957,12 +1164,12 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[ { "color":"#7f4ee8", - "id":"83df9f" + "id":"b6ef207" } ], "thresholdShow":true, @@ -970,6 +1177,7 @@ "thresholds":false, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":false }, "valueMapping":[], @@ -1051,12 +1259,12 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[ { "color":"#bd00f2", - "id":"79b38bc5" + "id":"da71837" } ], "thresholdShow":true, @@ -1146,12 +1354,12 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[ { "color":"#bd00f2", - "id":"5914f097" + "id":"2781ca5" } ], "thresholdShow":true, @@ -1241,12 +1449,12 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[ { "color":"#bd00f2", - "id":"52d63244" + "id":"40f9b83" } ], "thresholdShow":true, @@ -1336,12 +1544,12 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[ { "color":"#bd00f2", - "id":"25d8cf84" + "id":"393c4a57" } ], "thresholdShow":true, @@ -2009,13 +2217,37 @@ "label":"" }, "stack":false, - "thresholds":[], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "avg", @@ -2024,17 +2256,19 @@ ], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[], "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -2072,13 +2306,37 @@ "label":"" }, "stack":false, - "thresholds":[], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "avg", @@ -2087,17 +2345,19 @@ ], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[], "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -2135,13 +2395,37 @@ "label":"" }, "stack":false, - "thresholds":[], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "avg", @@ -2150,17 +2434,19 @@ ], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[], "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -2198,13 +2484,37 @@ "label":"" }, "stack":false, - "thresholds":[], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "avg", @@ -2213,17 +2523,19 @@ ], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[], "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -2460,7 +2772,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -2551,7 +2863,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -2757,13 +3069,37 @@ "label":"" }, "stack":false, - "thresholds":[], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "min", @@ -2773,17 +3109,19 @@ ], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[], "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -3858,7 +4196,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -3948,7 +4286,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -4038,7 +4376,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -4123,7 +4461,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -4170,13 +4508,37 @@ "label":"" }, "stack":false, - "thresholds":[], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "avg", @@ -4185,17 +4547,19 @@ ], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[], "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -4233,13 +4597,37 @@ "label":"" }, "stack":false, - "thresholds":[], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "avg", @@ -4248,17 +4636,19 @@ ], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[], "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -4296,13 +4686,37 @@ "label":"" }, "stack":false, - "thresholds":[], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "max", @@ -4310,17 +4724,19 @@ ], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[], "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -4358,19 +4774,37 @@ "label":"" }, "stack":false, - "thresholds":[ - { - "color":"#7dd1ed", - "id":"3367fad4" - } - ], - "thresholdShow":true, "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "max", @@ -4379,17 +4813,25 @@ "show":true, "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[ + { + "color":"#7dd1ed", + "id":"2ab3239d" + } + ], + "thresholdShow":true, "enable":{ "thresholds":false, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":false }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "valueMapping":[], "dataLink":[], "nullType":"zero" @@ -4515,13 +4957,37 @@ "label":"" }, "stack":false, - "thresholds":[], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "avg", @@ -4530,17 +4996,19 @@ ], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[], "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -4855,6 +5323,31 @@ "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[], "show":true, @@ -4864,12 +5357,12 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[ { "color":"#0c4dff", - "id":"2403cb83" + "id":"1978b85f" } ], "thresholdShow":true, @@ -4877,6 +5370,7 @@ "thresholds":false, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":false }, "valueMapping":[], @@ -4921,6 +5415,31 @@ "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[], "show":true, @@ -4930,12 +5449,12 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[ { "color":"#0c4dff", - "id":"15f3d50d" + "id":"266c1168" } ], "thresholdShow":true, @@ -4943,6 +5462,7 @@ "thresholds":false, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":false }, "valueMapping":[], @@ -5147,6 +5667,31 @@ "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[], "show":true, @@ -5156,12 +5701,12 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[ { "color":"#0c4dff", - "id":"2180e951" + "id":"3c37e86" } ], "thresholdShow":true, @@ -5169,6 +5714,7 @@ "thresholds":false, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":false }, "valueMapping":[], @@ -5923,36 +6469,62 @@ "label":"" }, "stack":0, - "thresholds":[ - { - "color":"#C4162AFF", - "id":"c5e0577", - "value":80 - } - ], - "thresholdShow":true, "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[], "show":true, "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[ + { + "color":"#C4162AFF", + "id":"a0c3ac9", + "value":80 + } + ], + "thresholdShow":true, "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":false }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "valueMapping":[], "dataLink":[], "nullType":"null" @@ -6199,6 +6771,31 @@ "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "avg", @@ -6211,12 +6808,12 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[ { "color":"#1c1984", - "id":"1b84559" + "id":"d62e843" } ], "thresholdShow":true, @@ -6224,6 +6821,7 @@ "thresholds":false, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":false }, "valueMapping":[], @@ -6334,6 +6932,31 @@ "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[], "show":true, @@ -6343,12 +6966,12 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[ { "color":"#1c1984", - "id":"055ee01" + "id":"b43381d" } ], "thresholdShow":true, @@ -6356,6 +6979,7 @@ "thresholds":false, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":false }, "valueMapping":[], @@ -6454,7 +7078,7 @@ "children":[] }, { - "name":"[24.05] OLAP Service Status Template", + "name":"OLAP Service Status Template", "type":"template", "varType":0, "param":{ @@ -7871,7 +8495,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -8111,7 +8735,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -8351,7 +8975,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -8440,7 +9064,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -8529,7 +9153,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -8814,7 +9438,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -8992,7 +9616,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -9080,14 +9704,14 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ "thresholds":false, "visibility":false, "legend":true, - "tooltip":false, + "tooltip":true, "valueMapping":true }, "style":"line", @@ -9780,7 +10404,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -10669,7 +11293,7 @@ "children":[] }, { - "name":"[24.05]Data Transporter Data Flow Template", + "name":"Data Transporter Data Flow Template", "type":"template", "varType":0, "param":{ @@ -10791,13 +11415,13 @@ "showHeader":1, "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "link":"", "thresholds":[ { "color":"#6339a3", - "id":"13aecc92" + "id":"7715ee9" } ], "thresholdShow":true, @@ -10924,13 +11548,13 @@ "showHeader":1, "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "link":"", "thresholds":[ { "color":"#b6a6ed", - "id":"a154cbb" + "id":"6f07e8bf" } ], "thresholdShow":true, @@ -11107,13 +11731,13 @@ "showHeader":1, "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "link":"", "thresholds":[ { "color":"#4ff9a7", - "id":"3f7e3f6f" + "id":"d57e4c9" } ], "thresholdShow":true, @@ -11628,7 +12252,7 @@ "thresholds":[ { "color":"#2ce059", - "id":"daad4cf" + "id":"22e472c9" } ], "thresholdShow":true, @@ -11669,7 +12293,7 @@ "queryType":1 }, { - "expression":"sum(\n rate(\nflink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"etl_session_record_kafka_to_ndc_kafka\",operator_name=\"Sink:_kafka_sink\",datacenter=\"$DataCenter\"}[5m]\n )+ rate( flink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"etl_session_record_kafka_to_ndc_kafka\",operator_name=\"Sink:_clickhouse_sink\",datacenter=\"$DataCenter\"}[5m]\n )\n)", + "expression":"sum(\n rate(\nflink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"etl_session_record_kafka_to_ndc_kafka\",operator_name=\"Sink:_kafka_sink\",datacenter=\"$DataCenter\"}[5m]\n ) or vector(0) )+ sum(rate( flink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"etl_session_record_kafka_to_ndc_kafka\",operator_name=\"Sink:_clickhouse_sink\",datacenter=\"$DataCenter\"}[5m]\n ) or vector(0)\n)", "legend":"Sink", "name":"D", "orderNum":2, @@ -12354,7 +12978,7 @@ "thresholds":[ { "color":"#ed0eaa", - "id":"56503a58" + "id":"2027e85c" } ], "thresholdShow":true, @@ -12395,7 +13019,7 @@ "queryType":1 }, { - "expression":"sum(\n rate(\nflink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"etl_transaction_record_kafka_to_ndc_kafka\",operator_name=\"Sink:_kafka_sink\",datacenter=\"$DataCenter\"}[5m]\n )+ rate( flink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"etl_transaction_record_kafka_to_ndc_kafka\",operator_name=\"Sink:_clickhouse_sink\",datacenter=\"$DataCenter\"}[5m]\n )\n)", + "expression":"sum(\n rate(\nflink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"etl_transaction_record_kafka_to_ndc_kafka\",operator_name=\"Sink:_kafka_sink\",datacenter=\"$DataCenter\"}[5m]\n ) or vector(0) )+ sum(rate( flink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"etl_transaction_record_kafka_to_ndc_kafka\",operator_name=\"Sink:_clickhouse_sink\",datacenter=\"$DataCenter\"}[5m]\n ) or vector(0)\n)", "legend":"Sink", "name":"D", "orderNum":2, @@ -12794,7 +13418,7 @@ "thresholds":[ { "color":"#2a16ff", - "id":"96ef601" + "id":"7dd05d48" } ], "thresholdShow":true, @@ -12835,7 +13459,7 @@ "queryType":1 }, { - "expression":"sum(\n rate(\nflink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"etl_proxy_event_kafka_to_ndc_kafka\",operator_name=\"Sink:_kafka_sink\",datacenter=\"$DataCenter\"}[5m]\n )+ rate( flink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"etl_proxy_event_kafka_to_ndc_kafka\",operator_name=\"Sink:_clickhouse_sink\",datacenter=\"$DataCenter\"}[5m]\n )\n)", + "expression":"sum(\n rate(\nflink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"etl_proxy_event_kafka_to_ndc_kafka\",operator_name=\"Sink:_kafka_sink\",datacenter=\"$DataCenter\"}[5m]\n ) or vector(0)) + sum(rate( flink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"etl_proxy_event_kafka_to_ndc_kafka\",operator_name=\"Sink:_clickhouse_sink\",datacenter=\"$DataCenter\"}[5m]\n ) or vector(0)\n)", "legend":"Sink", "name":"D", "orderNum":2, @@ -13377,7 +14001,7 @@ "thresholds":[ { "color":"#6936aa", - "id":"24d73f8" + "id":"1ed16a0e" } ], "thresholdShow":true, @@ -13418,7 +14042,7 @@ "queryType":1 }, { - "expression":"sum(\n rate(\nflink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"dos_sketch_record_kafka_to_kafka\",operator_name=\"Sink:_kafka_sink\",datacenter=\"$DataCenter\"}[5m]\n )+ rate( flink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"dos_sketch_record_kafka_to_kafka\",operator_name=\"Sink:_clickhouse_sink\",datacenter=\"$DataCenter\"}[5m]\n )\n)", + "expression":"sum(\n rate(\nflink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"dos_sketch_record_kafka_to_kafka\",operator_name=\"Sink:_kafka_sink\",datacenter=\"$DataCenter\"}[5m]\n ) or vector(0)) + sum(rate( flink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"dos_sketch_record_kafka_to_kafka\",operator_name=\"Sink:_clickhouse_sink\",datacenter=\"$DataCenter\"}[5m]\n ) or vector(0)\n)", "legend":"Sink", "name":"D", "orderNum":2, @@ -13960,7 +14584,7 @@ "thresholds":[ { "color":"#c02bdb", - "id":"637ac576" + "id":"6e96ebc8" } ], "thresholdShow":true, @@ -14011,7 +14635,7 @@ "queryType":1 }, { - "expression":"sum(\n rate(\nflink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"voip_record_kafka_to_ndc_kafka\",operator_name=\"Sink:_kafka_sink\",datacenter=\"$DataCenter\"}[5m]\n )+ rate( flink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"voip_record_kafka_to_ndc_kafka\",operator_name=\"Sink:_clickhouse_sink\",datacenter=\"$DataCenter\"}[5m]\n )\n)", + "expression":"sum(\n rate(\nflink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"voip_record_kafka_to_ndc_kafka\",operator_name=\"Sink:_kafka_sink\",datacenter=\"$DataCenter\"}[5m]\n ) or vector(0) )+ sum(rate( flink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"voip_record_kafka_to_ndc_kafka\",operator_name=\"Sink:_clickhouse_sink\",datacenter=\"$DataCenter\"}[5m]\n ) or vector(0)\n)", "legend":"Sink", "name":"E", "orderNum":3, @@ -17204,13 +17828,13 @@ "showHeader":1, "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "link":"", "thresholds":[ { "color":"#ce8c08", - "id":"73e60706" + "id":"75eb411" } ], "thresholdShow":true, @@ -17224,7 +17848,7 @@ }, "valueMapping":[], "dataLink":[], - "nullType":"null" + "nullType":"zero" }, "remark":"", "x":"6.0", @@ -17307,13 +17931,13 @@ "showHeader":1, "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "link":"", "thresholds":[ { "color":"#4740ce", - "id":"d02e4ed" + "id":"a2df341" } ], "thresholdShow":true, @@ -17327,7 +17951,7 @@ }, "valueMapping":[], "dataLink":[], - "nullType":"null" + "nullType":"zero" }, "remark":"", "x":"0.0", @@ -17400,13 +18024,13 @@ "showHeader":1, "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "link":"", "thresholds":[ { "color":"#ef2162", - "id":"e462ff9" + "id":"7c5d0cbb" } ], "thresholdShow":true, @@ -17420,7 +18044,7 @@ }, "valueMapping":[], "dataLink":[], - "nullType":"null" + "nullType":"zero" }, "remark":"", "x":"0.0", @@ -17480,10 +18104,10 @@ ] }, "visibility":{ - "result":"show", + "result":"", "varName":"", "varValue":"", - "operator":"equal" + "operator":"" }, "legend":{ "values":[], @@ -17493,13 +18117,13 @@ "showHeader":1, "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "link":"", "thresholds":[ { "color":"#4740ce", - "id":"2a8ecbc" + "id":"23e8cec" } ], "thresholdShow":true, @@ -17513,7 +18137,7 @@ }, "valueMapping":[], "dataLink":[], - "nullType":"null" + "nullType":"zero" }, "remark":"", "x":"0.0", @@ -17537,7 +18161,7 @@ "span":"6.0", "height":"2.0", "type":"Line chart", - "unit":"short", + "unit":"bytes/sec(IEC)", "weight":60, "param":{ "rightYAxis":{ @@ -17586,13 +18210,13 @@ "showHeader":1, "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "link":"", "thresholds":[ { "color":"#3c11f9", - "id":"aa3f158" + "id":"222bd78" } ], "thresholdShow":true, @@ -17606,7 +18230,7 @@ }, "valueMapping":[], "dataLink":[], - "nullType":"null" + "nullType":"zero" }, "remark":"", "x":"6.0", @@ -17689,13 +18313,13 @@ "showHeader":1, "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "link":"", "thresholds":[ { "color":"#ce8c08", - "id":"375ad3e9" + "id":"243de81a" } ], "thresholdShow":true, @@ -17709,7 +18333,7 @@ }, "valueMapping":[], "dataLink":[], - "nullType":"null" + "nullType":"zero" }, "remark":"", "x":"6.0", @@ -17744,7 +18368,7 @@ "children":[] }, { - "name":"[24.05] TSG OLAP Data Flow Template", + "name":"TSG OLAP Data Flow Template", "type":"template", "varType":0, "param":{ diff --git a/tsg_olap/installation/monitoring/TSG-24.02/TSG-OLAP-Module-temp-v24.02.xlsx b/tsg_olap/installation/monitoring/TSG-24.02/TSG-OLAP-Module-temp-v24.02.xlsx index 2817ef5d2b7dbba82ddd7a1917e90cfd9aee8312..18c84e0f1be2ea1d100543921dfc188049eb9700 100644 GIT binary patch delta 4578 zcmZ8lXHXN`)(th3P^3h9fKYOU1W=@R1jI=1ReDEyF9AV92Z=x^LMYOtgA_qJN>z~# z(jvWzf=KmoukV}hy?18L%wB8uK6}nO=g->hYGW$Y+DIZ|1^^iu8Q_GT%A}5(lYsc| zpy4(_>7NL*Ksfvlg{dThqPidS3Dd?LgvFZDADbm z{VefI!mVdydB{0jc?aaG9#KzGnHpg28KBy_%~9L8EQ>R@&jX_E6EA8xc2}?1jisN-yy4RQA>-&%=WPvD&3o*z zKfN}t2yaGq`90|o&=3NbC^%4e=l 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zZE$d##(GpxC|hVi#bSCp`nXZ0-AY);b0_i5rUuiF33jt;n!+w3ctOiE5-lxX+(|Y- z0Z=Aon=}OZ$qUN(;GO2ts?uzevhyR)Ny3+7?m>#)lN9Qv7tkWku2@me04O-dCF3Km zu+n+K)|DiKF7kYIY{N;6RnAdbFagYk#ZsBuVZw&!=p?X7oS&HQRPnXnU5AMup-YNI zObs&=fRx?tke2mmVdJD_+hyKOBc5~qJGvWl+~?nga*roWWVF0&4ZIndr8ZL#K9y%_ z1HK6xkBQ6K<=|}&CKl90eyUB}(8CUhcdvs@%iOJm=J7WKS z%<)k2&SU!!L~#3G|8pzJ?;lDs-Fhm@YV8&P0Du8H0Kj^4{ohYZGJ*I*>`jqd&wl`C CH&I0Z diff --git a/tsg_olap/installation/monitoring/TSG-24.05/TSG-OLAP-Dashboard-temp-v24.05.json b/tsg_olap/installation/monitoring/TSG-24.05/TSG-OLAP-Dashboard-temp-v24.05.json index 27583dc..c418f42 100644 --- a/tsg_olap/installation/monitoring/TSG-24.05/TSG-OLAP-Dashboard-temp-v24.05.json +++ b/tsg_olap/installation/monitoring/TSG-24.05/TSG-OLAP-Dashboard-temp-v24.05.json @@ -1,6 +1,6 @@ [ { - "name":"[24.05] OLAP Component Status Template", + "name":"OLAP Component Status Template", "type":"template", "varType":0, "param":{ @@ -124,20 +124,37 @@ "label":"" }, "stack":false, - "thresholds":[ - { - "val":"80", - "color":"#d64f40", - "id":"4a4faa2b", - "value":80 - } - ], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "avg", @@ -146,17 +163,26 @@ ], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[ + { + "val":"80", + "color":"#d64f40", + "id":"a85bb03", + "value":80 + } + ], "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -194,20 +220,37 @@ "label":"" }, "stack":false, - "thresholds":[ - { - "val":"100", - "color":"#d64f40", - "id":"d690d63", - "value":100 - } - ], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "min", @@ -217,17 +260,26 @@ ], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[ + { + "val":"100", + "color":"#d64f40", + "id":"62fbf61", + "value":100 + } + ], "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -308,7 +360,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -355,35 +407,61 @@ "label":"" }, "stack":false, - "thresholds":[ - { - "val":"100000", - "color":"#d64f40", - "id":"32d9b8b", - "value":100000 - } - ], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[ + { + "val":"100000", + "color":"#d64f40", + "id":"58f8e1ad", + "value":100000 + } + ], "enable":{ "thresholds":false, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -463,7 +541,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -554,7 +632,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -664,19 +742,37 @@ "label":"" }, "stack":false, - "thresholds":[ - { - "color":"#C4162AFF", - "id":"74e960f", - "value":0.8 - } - ], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "avg", @@ -684,17 +780,25 @@ ], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[ + { + "color":"#C4162AFF", + "id":"884bf8a", + "value":0.8 + } + ], "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -732,20 +836,37 @@ "label":"" }, "stack":false, - "thresholds":[ - { - "val":"0.7", - "color":"#d64f40", - "id":"24d5201a", - "value":0.8 - } - ], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "avg", @@ -753,17 +874,26 @@ ], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[ + { + "val":"0.7", + "color":"#d64f40", + "id":"68f1c6c2", + "value":0.8 + } + ], "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -801,20 +931,37 @@ "label":"" }, "stack":false, - "thresholds":[ - { - "val":"0.7", - "color":"#d64f40", - "id":"2aefe71f", - "value":0.8 - } - ], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "avg", @@ -822,17 +969,26 @@ ], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[ + { + "val":"0.7", + "color":"#d64f40", + "id":"a927eeb", + "value":0.8 + } + ], "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -870,20 +1026,37 @@ "label":"" }, "stack":false, - "thresholds":[ - { - "val":"0.7", - "color":"#d64f40", - "id":"861cdc1", - "value":0.8 - } - ], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "avg", @@ -891,17 +1064,26 @@ ], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[ + { + "val":"0.7", + "color":"#d64f40", + "id":"2022c819", + "value":0.8 + } + ], "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -945,6 +1127,31 @@ "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "avg", @@ -957,12 +1164,12 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[ { "color":"#7f4ee8", - "id":"83df9f" + "id":"b6ef207" } ], "thresholdShow":true, @@ -970,6 +1177,7 @@ "thresholds":false, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":false }, "valueMapping":[], @@ -1051,12 +1259,12 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[ { "color":"#bd00f2", - "id":"79b38bc5" + "id":"da71837" } ], "thresholdShow":true, @@ -1146,12 +1354,12 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[ { "color":"#bd00f2", - "id":"5914f097" + "id":"2781ca5" } ], "thresholdShow":true, @@ -1241,12 +1449,12 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[ { "color":"#bd00f2", - "id":"52d63244" + "id":"40f9b83" } ], "thresholdShow":true, @@ -1336,12 +1544,12 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[ { "color":"#bd00f2", - "id":"25d8cf84" + "id":"393c4a57" } ], "thresholdShow":true, @@ -2009,13 +2217,37 @@ "label":"" }, "stack":false, - "thresholds":[], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "avg", @@ -2024,17 +2256,19 @@ ], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[], "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -2072,13 +2306,37 @@ "label":"" }, "stack":false, - "thresholds":[], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "avg", @@ -2087,17 +2345,19 @@ ], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[], "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -2135,13 +2395,37 @@ "label":"" }, "stack":false, - "thresholds":[], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "avg", @@ -2150,17 +2434,19 @@ ], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[], "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -2198,13 +2484,37 @@ "label":"" }, "stack":false, - "thresholds":[], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "avg", @@ -2213,17 +2523,19 @@ ], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[], "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -2460,7 +2772,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -2551,7 +2863,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -2757,13 +3069,37 @@ "label":"" }, "stack":false, - "thresholds":[], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "min", @@ -2773,17 +3109,19 @@ ], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[], "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -3858,7 +4196,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -3948,7 +4286,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -4038,7 +4376,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -4123,7 +4461,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -4170,13 +4508,37 @@ "label":"" }, "stack":false, - "thresholds":[], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "avg", @@ -4185,17 +4547,19 @@ ], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[], "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -4233,13 +4597,37 @@ "label":"" }, "stack":false, - "thresholds":[], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "avg", @@ -4248,17 +4636,19 @@ ], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[], "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -4296,13 +4686,37 @@ "label":"" }, "stack":false, - "thresholds":[], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "max", @@ -4310,17 +4724,19 @@ ], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[], "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -4358,19 +4774,37 @@ "label":"" }, "stack":false, - "thresholds":[ - { - "color":"#7dd1ed", - "id":"3367fad4" - } - ], - "thresholdShow":true, "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "max", @@ -4379,17 +4813,25 @@ "show":true, "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[ + { + "color":"#7dd1ed", + "id":"2ab3239d" + } + ], + "thresholdShow":true, "enable":{ "thresholds":false, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":false }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "valueMapping":[], "dataLink":[], "nullType":"zero" @@ -4515,13 +4957,37 @@ "label":"" }, "stack":false, - "thresholds":[], "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "avg", @@ -4530,17 +4996,19 @@ ], "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[], "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":true }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "style":"line", "valueMapping":[], "dataLink":[], @@ -4855,6 +5323,31 @@ "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[], "show":true, @@ -4864,12 +5357,12 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[ { "color":"#0c4dff", - "id":"2403cb83" + "id":"1978b85f" } ], "thresholdShow":true, @@ -4877,6 +5370,7 @@ "thresholds":false, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":false }, "valueMapping":[], @@ -4921,6 +5415,31 @@ "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[], "show":true, @@ -4930,12 +5449,12 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[ { "color":"#0c4dff", - "id":"15f3d50d" + "id":"266c1168" } ], "thresholdShow":true, @@ -4943,6 +5462,7 @@ "thresholds":false, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":false }, "valueMapping":[], @@ -5147,6 +5667,31 @@ "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[], "show":true, @@ -5156,12 +5701,12 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[ { "color":"#0c4dff", - "id":"2180e951" + "id":"3c37e86" } ], "thresholdShow":true, @@ -5169,6 +5714,7 @@ "thresholds":false, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":false }, "valueMapping":[], @@ -5923,36 +6469,62 @@ "label":"" }, "stack":0, - "thresholds":[ - { - "color":"#C4162AFF", - "id":"c5e0577", - "value":80 - } - ], - "thresholdShow":true, "visibility":{ "result":"", "varName":"", "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[], "show":true, "placement":"bottom" }, + "link":"", + "tooltip":{ + "mode":"all", + "sort":"desc" + }, + "thresholds":[ + { + "color":"#C4162AFF", + "id":"a0c3ac9", + "value":80 + } + ], + "thresholdShow":true, "enable":{ "thresholds":true, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":false }, - "link":"", - "tooltip":{ - "mode":"all", - "sort":"none" - }, "valueMapping":[], "dataLink":[], "nullType":"null" @@ -6199,6 +6771,31 @@ "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[ "avg", @@ -6211,12 +6808,12 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[ { "color":"#1c1984", - "id":"1b84559" + "id":"d62e843" } ], "thresholdShow":true, @@ -6224,6 +6821,7 @@ "thresholds":false, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":false }, "valueMapping":[], @@ -6334,6 +6932,31 @@ "varValue":"", "operator":"" }, + "color":{ + "mode":"palette", + "paletteColors":[ + "#3685FF", + "#00DCA2", + "#00BFD0", + "#954Eff", + "#FFCB01", + "#f65A96", + "#FF9094", + "#00CCF5", + "#FF8BEA", + "#4D7693", + "#72577C", + "#99D750", + "#DD8270", + "#C475EE", + "#7E83FB", + "#7EB090", + "#CF6684", + "#4E55FF", + "#FF8D00", + "#FF5200" + ] + }, "legend":{ "values":[], "show":true, @@ -6343,12 +6966,12 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[ { "color":"#1c1984", - "id":"055ee01" + "id":"b43381d" } ], "thresholdShow":true, @@ -6356,6 +6979,7 @@ "thresholds":false, "visibility":false, "legend":true, + "tooltip":true, "valueMapping":false }, "valueMapping":[], @@ -6454,7 +7078,7 @@ "children":[] }, { - "name":"[24.05] OLAP Service Status Template", + "name":"OLAP Service Status Template", "type":"template", "varType":0, "param":{ @@ -7871,7 +8495,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -8111,7 +8735,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -8351,7 +8975,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -8440,7 +9064,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -8529,7 +9153,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -8814,7 +9438,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -8992,7 +9616,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -9080,14 +9704,14 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ "thresholds":false, "visibility":false, "legend":true, - "tooltip":false, + "tooltip":true, "valueMapping":true }, "style":"line", @@ -9780,7 +10404,7 @@ "link":"", "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "thresholds":[], "enable":{ @@ -10669,7 +11293,7 @@ "children":[] }, { - "name":"[24.05]Data Transporter Data Flow Template", + "name":"Data Transporter Data Flow Template", "type":"template", "varType":0, "param":{ @@ -10791,13 +11415,13 @@ "showHeader":1, "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "link":"", "thresholds":[ { "color":"#6339a3", - "id":"13aecc92" + "id":"7715ee9" } ], "thresholdShow":true, @@ -10924,13 +11548,13 @@ "showHeader":1, "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "link":"", "thresholds":[ { "color":"#b6a6ed", - "id":"a154cbb" + "id":"6f07e8bf" } ], "thresholdShow":true, @@ -11107,13 +11731,13 @@ "showHeader":1, "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "link":"", "thresholds":[ { "color":"#4ff9a7", - "id":"3f7e3f6f" + "id":"d57e4c9" } ], "thresholdShow":true, @@ -11628,7 +12252,7 @@ "thresholds":[ { "color":"#2ce059", - "id":"daad4cf" + "id":"22e472c9" } ], "thresholdShow":true, @@ -11669,7 +12293,7 @@ "queryType":1 }, { - "expression":"sum(\n rate(\nflink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"etl_session_record_kafka_to_ndc_kafka\",operator_name=\"Sink:_kafka_sink\",datacenter=\"$DataCenter\"}[5m]\n )+ rate( flink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"etl_session_record_kafka_to_ndc_kafka\",operator_name=\"Sink:_clickhouse_sink\",datacenter=\"$DataCenter\"}[5m]\n )\n)", + "expression":"sum(\n rate(\nflink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"etl_session_record_kafka_to_ndc_kafka\",operator_name=\"Sink:_kafka_sink\",datacenter=\"$DataCenter\"}[5m]\n ) or vector(0) )+ sum(rate( flink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"etl_session_record_kafka_to_ndc_kafka\",operator_name=\"Sink:_clickhouse_sink\",datacenter=\"$DataCenter\"}[5m]\n ) or vector(0)\n)", "legend":"Sink", "name":"D", "orderNum":2, @@ -12354,7 +12978,7 @@ "thresholds":[ { "color":"#ed0eaa", - "id":"56503a58" + "id":"2027e85c" } ], "thresholdShow":true, @@ -12395,7 +13019,7 @@ "queryType":1 }, { - "expression":"sum(\n rate(\nflink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"etl_transaction_record_kafka_to_ndc_kafka\",operator_name=\"Sink:_kafka_sink\",datacenter=\"$DataCenter\"}[5m]\n )+ rate( flink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"etl_transaction_record_kafka_to_ndc_kafka\",operator_name=\"Sink:_clickhouse_sink\",datacenter=\"$DataCenter\"}[5m]\n )\n)", + "expression":"sum(\n rate(\nflink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"etl_transaction_record_kafka_to_ndc_kafka\",operator_name=\"Sink:_kafka_sink\",datacenter=\"$DataCenter\"}[5m]\n ) or vector(0) )+ sum(rate( flink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"etl_transaction_record_kafka_to_ndc_kafka\",operator_name=\"Sink:_clickhouse_sink\",datacenter=\"$DataCenter\"}[5m]\n ) or vector(0)\n)", "legend":"Sink", "name":"D", "orderNum":2, @@ -12794,7 +13418,7 @@ "thresholds":[ { "color":"#2a16ff", - "id":"96ef601" + "id":"7dd05d48" } ], "thresholdShow":true, @@ -12835,7 +13459,7 @@ "queryType":1 }, { - "expression":"sum(\n rate(\nflink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"etl_proxy_event_kafka_to_ndc_kafka\",operator_name=\"Sink:_kafka_sink\",datacenter=\"$DataCenter\"}[5m]\n )+ rate( flink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"etl_proxy_event_kafka_to_ndc_kafka\",operator_name=\"Sink:_clickhouse_sink\",datacenter=\"$DataCenter\"}[5m]\n )\n)", + "expression":"sum(\n rate(\nflink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"etl_proxy_event_kafka_to_ndc_kafka\",operator_name=\"Sink:_kafka_sink\",datacenter=\"$DataCenter\"}[5m]\n ) or vector(0)) + sum(rate( flink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"etl_proxy_event_kafka_to_ndc_kafka\",operator_name=\"Sink:_clickhouse_sink\",datacenter=\"$DataCenter\"}[5m]\n ) or vector(0)\n)", "legend":"Sink", "name":"D", "orderNum":2, @@ -13377,7 +14001,7 @@ "thresholds":[ { "color":"#6936aa", - "id":"24d73f8" + "id":"1ed16a0e" } ], "thresholdShow":true, @@ -13418,7 +14042,7 @@ "queryType":1 }, { - "expression":"sum(\n rate(\nflink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"dos_sketch_record_kafka_to_kafka\",operator_name=\"Sink:_kafka_sink\",datacenter=\"$DataCenter\"}[5m]\n )+ rate( flink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"dos_sketch_record_kafka_to_kafka\",operator_name=\"Sink:_clickhouse_sink\",datacenter=\"$DataCenter\"}[5m]\n )\n)", + "expression":"sum(\n rate(\nflink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"dos_sketch_record_kafka_to_kafka\",operator_name=\"Sink:_kafka_sink\",datacenter=\"$DataCenter\"}[5m]\n ) or vector(0)) + sum(rate( flink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"dos_sketch_record_kafka_to_kafka\",operator_name=\"Sink:_clickhouse_sink\",datacenter=\"$DataCenter\"}[5m]\n ) or vector(0)\n)", "legend":"Sink", "name":"D", "orderNum":2, @@ -13960,7 +14584,7 @@ "thresholds":[ { "color":"#c02bdb", - "id":"637ac576" + "id":"6e96ebc8" } ], "thresholdShow":true, @@ -14011,7 +14635,7 @@ "queryType":1 }, { - "expression":"sum(\n rate(\nflink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"voip_record_kafka_to_ndc_kafka\",operator_name=\"Sink:_kafka_sink\",datacenter=\"$DataCenter\"}[5m]\n )+ rate( flink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"voip_record_kafka_to_ndc_kafka\",operator_name=\"Sink:_clickhouse_sink\",datacenter=\"$DataCenter\"}[5m]\n )\n)", + "expression":"sum(\n rate(\nflink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"voip_record_kafka_to_ndc_kafka\",operator_name=\"Sink:_kafka_sink\",datacenter=\"$DataCenter\"}[5m]\n ) or vector(0) )+ sum(rate( flink_taskmanager_job_task_operator_internal_metrics_out_events{job_name=\"voip_record_kafka_to_ndc_kafka\",operator_name=\"Sink:_clickhouse_sink\",datacenter=\"$DataCenter\"}[5m]\n ) or vector(0)\n)", "legend":"Sink", "name":"E", "orderNum":3, @@ -17204,13 +17828,13 @@ "showHeader":1, "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "link":"", "thresholds":[ { "color":"#ce8c08", - "id":"73e60706" + "id":"75eb411" } ], "thresholdShow":true, @@ -17224,7 +17848,7 @@ }, "valueMapping":[], "dataLink":[], - "nullType":"null" + "nullType":"zero" }, "remark":"", "x":"6.0", @@ -17307,13 +17931,13 @@ "showHeader":1, "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "link":"", "thresholds":[ { "color":"#4740ce", - "id":"d02e4ed" + "id":"a2df341" } ], "thresholdShow":true, @@ -17327,7 +17951,7 @@ }, "valueMapping":[], "dataLink":[], - "nullType":"null" + "nullType":"zero" }, "remark":"", "x":"0.0", @@ -17400,13 +18024,13 @@ "showHeader":1, "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "link":"", "thresholds":[ { "color":"#ef2162", - "id":"e462ff9" + "id":"7c5d0cbb" } ], "thresholdShow":true, @@ -17420,7 +18044,7 @@ }, "valueMapping":[], "dataLink":[], - "nullType":"null" + "nullType":"zero" }, "remark":"", "x":"0.0", @@ -17480,10 +18104,10 @@ ] }, "visibility":{ - "result":"show", + "result":"", "varName":"", "varValue":"", - "operator":"equal" + "operator":"" }, "legend":{ "values":[], @@ -17493,13 +18117,13 @@ "showHeader":1, "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "link":"", "thresholds":[ { "color":"#4740ce", - "id":"2a8ecbc" + "id":"23e8cec" } ], "thresholdShow":true, @@ -17513,7 +18137,7 @@ }, "valueMapping":[], "dataLink":[], - "nullType":"null" + "nullType":"zero" }, "remark":"", "x":"0.0", @@ -17537,7 +18161,7 @@ "span":"6.0", "height":"2.0", "type":"Line chart", - "unit":"short", + "unit":"bytes/sec(IEC)", "weight":60, "param":{ "rightYAxis":{ @@ -17586,13 +18210,13 @@ "showHeader":1, "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "link":"", "thresholds":[ { "color":"#3c11f9", - "id":"aa3f158" + "id":"222bd78" } ], "thresholdShow":true, @@ -17606,7 +18230,7 @@ }, "valueMapping":[], "dataLink":[], - "nullType":"null" + "nullType":"zero" }, "remark":"", "x":"6.0", @@ -17689,13 +18313,13 @@ "showHeader":1, "tooltip":{ "mode":"all", - "sort":"none" + "sort":"desc" }, "link":"", "thresholds":[ { "color":"#ce8c08", - "id":"375ad3e9" + "id":"243de81a" } ], "thresholdShow":true, @@ -17709,7 +18333,7 @@ }, "valueMapping":[], "dataLink":[], - "nullType":"null" + "nullType":"zero" }, "remark":"", "x":"6.0", @@ -17744,7 +18368,7 @@ "children":[] }, { - "name":"[24.05] TSG OLAP Data Flow Template", + "name":"TSG OLAP Data Flow Template", "type":"template", "varType":0, "param":{ diff --git a/tsg_olap/installation/monitoring/TSG-24.05/TSG-OLAP-Module-temp-v24.05.xlsx b/tsg_olap/installation/monitoring/TSG-24.05/TSG-OLAP-Module-temp-v24.05.xlsx index 2817ef5d2b7dbba82ddd7a1917e90cfd9aee8312..18c84e0f1be2ea1d100543921dfc188049eb9700 100644 GIT binary patch delta 4578 zcmZ8lXHXN`)(th3P^3h9fKYOU1W=@R1jI=1ReDEyF9AV92Z=x^LMYOtgA_qJN>z~# z(jvWzf=KmoukV}hy?18L%wB8uK6}nO=g->hYGW$Y+DIZ|1^^iu8Q_GT%A}5(lYsc| 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zUE<}9JgD1^ZtRK!A6Red+@-24q<#>3LFX%KbYPAM^d+G_-)}F>?%BLI5~)u}+pZAW zc?~q}wMRCI*v5-+vPm8f#%9B3WPA0w$K%;&D4)9!E$S{lBn*Lo6>NsFWK2;phuYby ze8*sox0qkplgyl%_7(Hz?G)Ch>U}PTb9V=$>F~VvJ%UMZ7HT9dedz}>vdXuQLR;I$ zs0L$6?|(AeRl```Bj`|2Y03XYrcnPTQ~q@%{>32tJ{bQWCHeO77k@Aao*ftRtxO;% z(&_tFeRQ-#)`iDl8oWkuH=9o_Xh{K zOVNpTJqH7sa?`I!1sD;HN8#Ly#G_cC@rosU4$U<`X_zx1R4kG zx4! z>!1AHBX{}Rwore%{>j$;?ffUP^+@skwp&OV5D5MU;rDl(KUahQEC@LyCrF(CN{am* m<=JFKNJ)i Date: Tue, 13 Aug 2024 17:39:54 +0800 Subject: [PATCH 4/4] =?UTF-8?q?[=E6=96=B0=E5=A2=9E]24.07=E5=88=9D=E5=A7=8B?= =?UTF-8?q?=E5=8C=96=E6=A8=A1=E6=9D=BF?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- tsg_olap/installation/hos/tsg_olap_hos_ddl.sh | 5 + .../installation/kafka/create_topic.sh.j2 | 71 ++++++ .../mariadb/galaxy-job-service/xxl_job.sql.j2 | 197 ++++++++++++++++ .../galaxy-qgw-service/R__init_datasets.sql | 212 ++++++++++++++++++ .../V23.12__init_saved_query_job.sql | 28 +++ .../V24.07__init_sys_storage_event.sql | 22 ++ 6 files changed, 535 insertions(+) create mode 100644 tsg_olap/installation/hos/tsg_olap_hos_ddl.sh create mode 100644 tsg_olap/installation/kafka/create_topic.sh.j2 create mode 100644 tsg_olap/installation/mariadb/galaxy-job-service/xxl_job.sql.j2 create mode 100644 tsg_olap/installation/mariadb/galaxy-qgw-service/R__init_datasets.sql create mode 100644 tsg_olap/installation/mariadb/galaxy-qgw-service/V23.12__init_saved_query_job.sql create mode 100644 tsg_olap/installation/mariadb/galaxy-qgw-service/V24.07__init_sys_storage_event.sql diff --git a/tsg_olap/installation/hos/tsg_olap_hos_ddl.sh b/tsg_olap/installation/hos/tsg_olap_hos_ddl.sh new file mode 100644 index 0000000..2c3c15c --- /dev/null +++ b/tsg_olap/installation/hos/tsg_olap_hos_ddl.sh @@ -0,0 +1,5 @@ +curl -X PUT http://{{ vrrp_instance.oss.virtual_ipaddress }}:9098/hos/traffc_file_bucket -H 'token:{{ hos_token }}' -H 'x-hos-region-count:64*hbase服务器数' +curl -X PUT http://{{ vrrp_instance.oss.virtual_ipaddress }}:9098/hos/troubleshooting_file_bucket -H 'token:{{ hos_token }}' -H 'x-hos-region-count:16' +curl -X PUT http://{{ vrrp_instance.oss.virtual_ipaddress }}:9098/hos/knowledge_base_bucket -H 'token:{{ hos_token }}' -H 'x-hos-region-count:16' -H 'x-hos-wal:open' +curl -X PUT http://{{ vrrp_instance.oss.virtual_ipaddress }}:9098/hos/report_snapshot_bucket -H 'token:{{ hos_token }}' -H 'x-hos-region-count:16' -H 'x-hos-wal:open' +curl -X PUT http://{{ vrrp_instance.oss.virtual_ipaddress }}:9098/hos/assessment_file_bucket -H 'token:{{ hos_token }}' -H 'x-hos-region-count:16' -H 'x-hos-wal:open' diff --git a/tsg_olap/installation/kafka/create_topic.sh.j2 b/tsg_olap/installation/kafka/create_topic.sh.j2 new file mode 100644 index 0000000..ca20eb2 --- /dev/null +++ b/tsg_olap/installation/kafka/create_topic.sh.j2 @@ -0,0 +1,71 @@ +#!/bin/bash +source /etc/profile + +partition_nums={{ groups.kafka | length }} +replication_nums={{ 2 if groups.kafka | length >1 else 1 }} +kafka_servers="{% for host in groups['kafka'] %}{{ host }}:9092{% if not loop.last %},{% endif %}{% endfor %}" + +common_topic=( + BGP-RECORD + DOS-EVENT + NETWORK-TRAFFIC-METRIC + OBJECT-STATISTICS-METRIC + POLICY-RULE-METRIC + PROXY-EVENT + PROXY-EVENT-PROCESSED + PXY-EXCH-INTERMEDIA-CERT + SESSION-RECORD-IPFIX + STATISTICS-RULE-METRIC + VOIP-CONVERSATION-RECORD + VOIP-RECORD + VOIP-RECORD-PROCESSED + TOPK-METRIC + DOS-PROTECTION-RULE-METRIC + DOS-SKETCH-TOP-SERVER-IP + DOS-SKETCH-METRIC + DATAPATH-TELEMETRY-RECORD + TRAFFIC-SKETCH-METRIC +) + +multi_partition_topic=( + TRANSACTION-RECORD + TRANSACTION-RECORD-PROCESSED + SESSION-RECORD + SESSION-RECORD-PROCESSED + TRAFFIC-FILE-STREAM-RECORD +) + +function getTopic() { + docker exec kafka kafka-topics.sh --bootstrap-server $kafka_servers --list +} + +function createTopic() { + exist_topic=$(echo "$exist_topic_list" | grep -wx "$3" | wc -l) + if [ $exist_topic -eq '0' ]; then + docker exec kafka kafka-topics.sh '--create' '--if-not-exists' '--bootstrap-server' "$kafka_servers" '--replication-factor' $1 '--partitions' $2 '--topic' $3 + fi +} + +function checkTopic() { + exist_topic_list=$(getTopic) + all_topic=("${common_topic[@]}" "${multi_partition_topic[@]}") + for topic_name in ${all_topic[@]}; do + exist_topic=$(echo "$exist_topic_list" | grep -wx "$topic_name" | wc -l) + if [ $exist_topic -eq '0' ]; then + echo "Topic $topic_name creation failure" + exit 1 + fi + done + +} + +exist_topic_list=$(getTopic) +for topic_name in ${common_topic[@]}; do + createTopic $replication_nums $partition_nums $topic_name +done + +for topic_name in ${multi_partition_topic[@]}; do + createTopic 1 $((partition_nums * 3)) $topic_name +done + +checkTopic diff --git a/tsg_olap/installation/mariadb/galaxy-job-service/xxl_job.sql.j2 b/tsg_olap/installation/mariadb/galaxy-job-service/xxl_job.sql.j2 new file mode 100644 index 0000000..1012759 --- /dev/null +++ b/tsg_olap/installation/mariadb/galaxy-job-service/xxl_job.sql.j2 @@ -0,0 +1,197 @@ +/* +Navicat MySQL Data Transfer + +Target Server Type : MYSQL +Target Server Version : 50505 +File Encoding : 65001 + +Date: 2021-09-23 14:05:11 +*/ + +SET FOREIGN_KEY_CHECKS=0; + +-- ---------------------------- +-- Table structure for `xxl_job_group` +-- ---------------------------- +DROP TABLE IF EXISTS `xxl_job_group`; +CREATE TABLE `xxl_job_group` ( + `id` int(11) NOT NULL AUTO_INCREMENT, + `app_name` varchar(64) NOT NULL COMMENT '执行器AppName', + `title` varchar(64) NOT NULL COMMENT '执行器名称', + `address_type` tinyint(4) NOT NULL DEFAULT 0 COMMENT '执行器地址类型：0=自动注册、1=手动录入', + `address_list` varchar(512) DEFAULT NULL COMMENT '执行器地址列表，多地址逗号分隔', + PRIMARY KEY (`id`) USING BTREE +) ENGINE=InnoDB AUTO_INCREMENT=8 DEFAULT CHARSET=utf8mb4 ROW_FORMAT=DYNAMIC; + +-- ---------------------------- +-- Table structure for `xxl_job_lock` +-- ---------------------------- +DROP TABLE IF EXISTS `xxl_job_lock`; +CREATE TABLE `xxl_job_lock` ( + `lock_name` varchar(50) NOT NULL COMMENT '锁名称', + PRIMARY KEY (`lock_name`) USING BTREE +) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 ROW_FORMAT=DYNAMIC; + +-- ---------------------------- +-- Records of xxl_job_lock +-- ---------------------------- +INSERT INTO `xxl_job_lock` VALUES ('schedule_lock'); + +-- ---------------------------- +-- Table structure for `xxl_job_log` +-- ---------------------------- +DROP TABLE IF EXISTS `xxl_job_log`; +CREATE TABLE `xxl_job_log` ( + `id` bigint(20) NOT NULL AUTO_INCREMENT, + `job_group` int(11) NOT NULL COMMENT '执行器主键ID', + `job_id` int(11) NOT NULL COMMENT '任务，主键ID', + `executor_address` varchar(255) DEFAULT NULL COMMENT '执行器地址，本次执行的地址', + `executor_handler` varchar(255) DEFAULT NULL COMMENT '执行器任务handler', + `executor_param` varchar(4000) DEFAULT '' COMMENT '执行器任务参数', + `executor_sharding_param` varchar(20) DEFAULT NULL COMMENT '执行器任务分片参数，格式如 1/2', + `executor_fail_retry_count` int(11) NOT NULL DEFAULT 0 COMMENT '失败重试次数', + `trigger_time` datetime DEFAULT NULL COMMENT '调度-时间', + `trigger_code` int(11) NOT NULL COMMENT '调度-结果', + `trigger_msg` text DEFAULT NULL COMMENT '调度-日志', + `handle_time` datetime DEFAULT NULL COMMENT '执行-时间', + `handle_code` int(11) NOT NULL COMMENT '执行-状态', + `handle_msg` text DEFAULT NULL COMMENT '执行-日志', + `alarm_status` tinyint(4) NOT NULL DEFAULT 0 COMMENT '告警状态：0-默认、1-无需告警、2-告警成功、3-告警失败', + PRIMARY KEY (`id`) USING BTREE, + KEY `I_trigger_time` (`trigger_time`) USING BTREE, + KEY `I_handle_code` (`handle_code`) USING BTREE +) ENGINE=InnoDB AUTO_INCREMENT=2077229 DEFAULT CHARSET=utf8mb4 ROW_FORMAT=DYNAMIC; + +-- ---------------------------- +-- Records of xxl_job_log +-- ---------------------------- + +-- ---------------------------- +-- Table structure for `xxl_job_logglue` +-- ---------------------------- +DROP TABLE IF EXISTS `xxl_job_logglue`; +CREATE TABLE `xxl_job_logglue` ( + `id` int(11) NOT NULL AUTO_INCREMENT, + `job_id` int(11) NOT NULL COMMENT '任务，主键ID', + `glue_type` varchar(50) DEFAULT NULL COMMENT 'GLUE类型', + `glue_source` mediumtext DEFAULT NULL COMMENT 'GLUE源代码', + `glue_remark` varchar(128) NOT NULL COMMENT 'GLUE备注', + `add_time` datetime DEFAULT NULL, + `update_time` datetime DEFAULT NULL, + PRIMARY KEY (`id`) USING BTREE +) ENGINE=InnoDB AUTO_INCREMENT=2 DEFAULT CHARSET=utf8mb4 ROW_FORMAT=DYNAMIC; + +-- ---------------------------- +-- Records of xxl_job_logglue +-- ---------------------------- + +-- ---------------------------- +-- Table structure for `xxl_job_log_report` +-- ---------------------------- +DROP TABLE IF EXISTS `xxl_job_log_report`; +CREATE TABLE `xxl_job_log_report` ( + `id` int(11) NOT NULL AUTO_INCREMENT, + `trigger_day` datetime DEFAULT NULL COMMENT '调度-时间', + `running_count` int(11) NOT NULL DEFAULT 0 COMMENT '运行中-日志数量', + `suc_count` int(11) NOT NULL DEFAULT 0 COMMENT '执行成功-日志数量', + `fail_count` int(11) NOT NULL DEFAULT 0 COMMENT '执行失败-日志数量', + PRIMARY KEY (`id`) USING BTREE, + UNIQUE KEY `i_trigger_day` (`trigger_day`) USING BTREE +) ENGINE=InnoDB AUTO_INCREMENT=786 DEFAULT CHARSET=utf8mb4 ROW_FORMAT=DYNAMIC; + +-- ---------------------------- +-- Records of xxl_job_log_report +-- ---------------------------- + +-- ---------------------------- +-- Table structure for `xxl_job_registry` +-- ---------------------------- +DROP TABLE IF EXISTS `xxl_job_registry`; +CREATE TABLE `xxl_job_registry` ( + `id` int(11) NOT NULL AUTO_INCREMENT, + `registry_group` varchar(50) NOT NULL, + `registry_key` varchar(255) NOT NULL, + `registry_value` varchar(255) NOT NULL, + `update_time` datetime DEFAULT NULL, + PRIMARY KEY (`id`) USING BTREE, + KEY `i_g_k_v` (`registry_group`,`registry_key`,`registry_value`) USING BTREE +) ENGINE=InnoDB AUTO_INCREMENT=276 DEFAULT CHARSET=utf8mb4 ROW_FORMAT=DYNAMIC; + +-- ---------------------------- +-- Table structure for `xxl_job_user` +-- ---------------------------- +DROP TABLE IF EXISTS `xxl_job_user`; +CREATE TABLE `xxl_job_user` ( + `id` int(11) NOT NULL AUTO_INCREMENT, + `username` varchar(50) NOT NULL COMMENT '账号', + `password` varchar(50) NOT NULL COMMENT '密码', + `role` tinyint(4) NOT NULL COMMENT '角色：0-普通用户、1-管理员', + `permission` varchar(255) DEFAULT NULL COMMENT '权限：执行器ID列表，多个逗号分割', + PRIMARY KEY (`id`) USING BTREE, + UNIQUE KEY `i_username` (`username`) USING BTREE +) ENGINE=InnoDB AUTO_INCREMENT=3 DEFAULT CHARSET=utf8mb4 ROW_FORMAT=DYNAMIC; + +-- ---------------------------- +-- Records of xxl_job_user +-- ---------------------------- +INSERT INTO `xxl_job_user` VALUES ('1', 'admin', 'fea191a3fdd9f68503f9fa0e8d0293ab', '1', null); +INSERT INTO `xxl_job_user` VALUES ('2', 'query', '95497ea23bf8d27d86526717578e366f', '0', '3'); + +-- ---------------------------- +-- Table structure for `xxl_job_info` +-- ---------------------------- +DROP TABLE IF EXISTS `xxl_job_info`; +CREATE TABLE `xxl_job_info` ( + `id` int(11) NOT NULL AUTO_INCREMENT, + `job_group` int(11) NOT NULL COMMENT '执行器主键ID', + `job_cron` varchar(128) NOT NULL COMMENT '任务执行CRON', + `job_desc` varchar(255) NOT NULL, + `add_time` datetime DEFAULT NULL, + `update_time` datetime DEFAULT NULL, + `author` varchar(64) DEFAULT NULL COMMENT '作者', + `alarm_email` varchar(255) DEFAULT NULL COMMENT '报警邮件', + `executor_route_strategy` varchar(50) DEFAULT NULL COMMENT '执行器路由策略', + `executor_handler` varchar(255) DEFAULT NULL COMMENT '执行器任务handler', + `executor_param` varchar(4000) DEFAULT '' COMMENT '执行器任务参数', + `executor_block_strategy` varchar(50) DEFAULT NULL COMMENT '阻塞处理策略', + `executor_timeout` int(11) NOT NULL DEFAULT 0 COMMENT '任务执行超时时间，单位秒', + `executor_fail_retry_count` int(11) NOT NULL DEFAULT 0 COMMENT '失败重试次数', + `glue_type` varchar(50) NOT NULL COMMENT 'GLUE类型', + `glue_source` mediumtext DEFAULT NULL COMMENT 'GLUE源代码', + `glue_remark` varchar(128) DEFAULT NULL COMMENT 'GLUE备注', + `glue_updatetime` datetime DEFAULT NULL COMMENT 'GLUE更新时间', + `child_jobid` varchar(255) DEFAULT NULL COMMENT '子任务ID，多个逗号分隔', + `trigger_status` tinyint(4) NOT NULL DEFAULT 0 COMMENT '调度状态：0-停止，1-运行', + `trigger_last_time` bigint(13) NOT NULL DEFAULT 0 COMMENT '上次调度时间', + `trigger_next_time` bigint(13) NOT NULL DEFAULT 0 COMMENT '下次调度时间', + PRIMARY KEY (`id`) USING BTREE +) ENGINE=InnoDB AUTO_INCREMENT=88 DEFAULT CHARSET=utf8mb4 ROW_FORMAT=DYNAMIC; + + +-- ---------------------------- +-- Records of xxl_job_group +-- ---------------------------- +INSERT INTO `xxl_job_group` VALUES (1, 'galaxy-executor', 'GDP', 1, '{{ job_executor_servers }}'); +INSERT INTO `xxl_job_group` VALUES (2, 'galaxy-executor', 'TSG_OLAP', 1, '{{ job_executor_servers }}'); +-- ---------------------------- +-- Records of xxl_job_info +-- ---------------------------- +INSERT INTO `xxl_job_info` VALUES (29, 2, '{{ cron_expression_2 }}', 'get_storage_daily_usage', '2024-06-30 14:06:48', '2024-07-12 02:06:32', 'galaxy', '', 'FAILOVER', 'getDatabaseStorageQuotaJobHandler', '[\r\n {\r\n \"source\":\r\n {\r\n \"type\": \"storage\",\r\n \"containBytes\": true,\r\n \"items\": \"Traffic Logs,Files,Metrics\"\r\n },\r\n \"sink\":\r\n {\r\n \"type\": \"mariadb\",\r\n \"ip\": \"{{ vrrp_instance.default.virtual_ipaddress }}\",\r\n \"database\": \"tsg_olap\",\r\n \"table\": \"sys_storage_event\",\r\n \"username\": \"root\",\r\n \"pin\": \"{{ mariadb_default_pin }}\"\r\n }\r\n }\r\n]', 'COVER_EARLY', 0, 0, 'BEAN', '', 'GLUE代码初始化', '2024-06-30 14:06:48', '', 1, 1721613600000, 1721700000000); +INSERT INTO `xxl_job_info` VALUES (36, 2, '0 0/10 * * * ?', 'get_database_storage_quota', '2024-06-19 03:06:04', '2024-07-04 09:29:43', 'galaxy', '', 'FAILOVER', 'getDatabaseStorageQuotaJobHandler', '[\r\n {\r\n \"source\":\r\n {\r\n \"type\": \"storage\",\r\n \"containBytes\": false,\r\n \"items\": \"Traffic Logs,Files,Metrics\"\r\n },\r\n \"sink\":\r\n {\r\n \"type\": \"mariadb\",\r\n \"ip\": \"{{ vrrp_instance.default.virtual_ipaddress }}\",\r\n \"database\": \"tsg_olap\",\r\n \"table\": \"sys_storage_event\",\r\n \"username\": \"root\",\r\n \"pin\": \"{{ mariadb_default_pin }}\"\r\n }\r\n }\r\n]', 'COVER_EARLY', 0, 0, 'BEAN', '', 'GLUE代码初始化', '2024-06-19 03:06:04', '', 1, 1721634600000, 1721635200000); + +INSERT INTO `xxl_job_info` VALUES (58, 1, '0 0 2 * * ? ', 'set_druid_table_ttl', '2020-07-30 10:34:34', '2024-02-28 03:02:15', 'galaxy', '', 'FAILOVER', 'deleteReportAndMetricsDataJobHandler', '{\"defaultMaxDays\":365,\"maxDays\":30}', 'DISCARD_LATER', 0, 0, 'BEAN', '', 'GLUE代码初始化', '2020-07-30 10:34:34', '', 1, 1709488800000, 1709575200000); +INSERT INTO `xxl_job_info` VALUES (59, 1, '0 0 0 1 * ?', 'clear_druid_table', '2020-07-30 11:32:08', '2022-04-12 02:38:39', 'galaxy', '', 'FAILOVER', 'deleteAllReportAndMetricsDataJobHandler', '{\"maxDays\":88,\"defaultMaxDays\":365}', 'DISCARD_LATER', 0, 0, 'BEAN', '', 'GLUE代码初始化', '2020-07-30 11:32:08', '', 0, 0, 0); +INSERT INTO `xxl_job_info` VALUES (62, 1, '0 0 2 * * ? ', 'set_hos_bucket_ttl', '2020-07-30 11:59:30', '2024-02-28 03:02:15', 'galaxy', '', 'FAILOVER', 'deleteFilesJobHandler', '{\"defaultMaxDays\":30,\"maxDays\":30}', 'DISCARD_LATER', 0, 0, 'BEAN', '', 'GLUE代码初始化', '2020-07-30 11:59:30', '', 1, 1709488800000, 1709575200000); +INSERT INTO `xxl_job_info` VALUES (63, 1, '0 0 0 1 * ?', 'clear_hos_file', '2020-07-30 11:59:43', '2023-10-26 10:43:46', 'galaxy', '', 'FAILOVER', 'deleteAllFilesJobHandler', '{\"defaultMaxDays\":30,\"maxDays\":30}', 'DISCARD_LATER', 0, 0, 'BEAN', '', 'GLUE代码初始化', '2020-07-30 11:59:43', '', 0, 0, 0); +INSERT INTO `xxl_job_info` VALUES (64, 1, '0 0 0 1 * ?', 'clear_clickhouse_table', '2020-07-30 13:47:25', '2022-04-12 02:38:39', 'galaxy', '', 'FAILOVER', 'deleteAllTrafficDataJobHandler', '{\"maxDays\":77,\"defaultMaxDays\":30}', 'DISCARD_LATER', 0, 0, 'BEAN', '', 'GLUE代码初始化', '2020-07-30 13:47:25', '', 0, 0, 0); +INSERT INTO `xxl_job_info` VALUES (65, 1, '0 0 0 * * ? ', 'set_clickhouse_table_ttl', '2020-07-30 13:47:38', '2024-02-28 03:02:13', 'galaxy', '', 'FAILOVER', 'deleteTrafficDataJobHandler', '{\"defaultMaxDays\":30,\"maxDays\":30}', 'DISCARD_LATER', 0, 0, 'BEAN', '', 'GLUE代码初始化', '2020-07-30 13:47:38', '', 1, 1709481600000, 1709568000000); +INSERT INTO xxl_job_info (id, job_group, job_cron, job_desc, add_time, update_time, author, alarm_email, executor_route_strategy, executor_handler, executor_param, executor_block_strategy, executor_timeout, executor_fail_retry_count, glue_type, glue_source, glue_remark, glue_updatetime, child_jobid, trigger_status, trigger_last_time, trigger_next_time) VALUES ('86', '2', '0 0 1 * * ?', 'run_druid_segment_compaction', '2021-07-21 14:13:57', '2023-12-12 02:21:05', 'galaxy', '', 'FAILOVER', 'druidCompactSegmentJobHandler', '[\r\n {\r\n \"type\": \"compact\",\r\n \"dataSource\": \"top_server_fqdns\",\r\n \"tuningConfig\": {\r\n \"type\": \"index_parallel\"\r\n }\r\n },\r\n {\r\n \"type\": \"compact\",\r\n \"dataSource\": \"top_server_domains\",\r\n \"tuningConfig\": {\r\n \"type\": \"index_parallel\"\r\n }\r\n },\r\n {\r\n \"type\": \"compact\",\r\n \"dataSource\": \"top_client_ips\",\r\n \"tuningConfig\": {\r\n \"type\": \"index_parallel\"\r\n }\r\n },\r\n {\r\n \"type\": \"compact\",\r\n \"dataSource\": \"top_server_ips\",\r\n \"tuningConfig\": {\r\n \"type\": \"index_parallel\"\r\n }\r\n },\r\n {\r\n \"type\": \"compact\",\r\n \"dataSource\": \"top_external_ips\",\r\n \"tuningConfig\": {\r\n \"type\": \"index_parallel\"\r\n }\r\n },\r\n {\r\n \"type\": \"compact\",\r\n \"dataSource\": \"top_internal_ips\",\r\n \"tuningConfig\": {\r\n \"type\": \"index_parallel\"\r\n }\r\n },\r\n {\r\n \"type\": \"compact\",\r\n \"dataSource\": \"top_client_countries\",\r\n \"tuningConfig\": {\r\n \"type\": \"index_parallel\"\r\n }\r\n },\r\n {\r\n \"type\": \"compact\",\r\n \"dataSource\": \"top_server_countries\",\r\n \"tuningConfig\": {\r\n \"type\": \"index_parallel\"\r\n }\r\n },\r\n {\r\n \"type\": \"compact\",\r\n \"dataSource\": \"security_rule_hits\",\r\n \"tuningConfig\": {\r\n \"type\": \"index_parallel\"\r\n }\r\n },\r\n {\r\n \"type\": \"compact\",\r\n \"dataSource\": \"monitor_rule_hits\",\r\n \"tuningConfig\": {\r\n \"type\": \"index_parallel\"\r\n }\r\n },\r\n {\r\n \"type\": \"compact\",\r\n \"dataSource\": \"proxy_rule_hits\",\r\n \"tuningConfig\": {\r\n \"type\": \"index_parallel\"\r\n }\r\n },\r\n {\r\n \"type\": \"compact\",\r\n \"dataSource\": \"application_protocol_stat\",\r\n \"tuningConfig\": {\r\n \"type\": \"index_parallel\",\r\n \"maxRowsInMemory\": 200000\r\n }\r\n },\r\n {\r\n \"type\": \"compact\",\r\n \"dataSource\": \"traffic_general_stat\",\r\n \"tuningConfig\": {\r\n \"type\": \"index_parallel\"\r\n }\r\n },\r\n {\r\n \"type\": \"compact\",\r\n \"dataSource\": \"dos_sketch_top_server_ip\",\r\n \"tuningConfig\": {\r\n \"type\": \"index_parallel\"\r\n }\r\n },\r\n {\r\n \"type\": \"compact\",\r\n \"dataSource\": \"dos_protection_rule_hits\",\r\n \"tuningConfig\": {\r\n \"type\": \"index_parallel\"\r\n }\r\n },\r\n {\r\n \"type\": \"compact\",\r\n \"dataSource\": \"dos_protection_rule_metric\",\r\n \"tuningConfig\": {\r\n \"type\": \"index_parallel\"\r\n }\r\n },\r\n {\r\n \"type\": \"compact\",\r\n \"dataSource\": \"service_chaining_rule_hits\",\r\n \"tuningConfig\": {\r\n \"type\": \"index_parallel\"\r\n }\r\n },\r\n {\r\n \"type\": \"compact\",\r\n \"dataSource\": \"service_function_status\",\r\n \"tuningConfig\": {\r\n \"type\": \"index_parallel\"\r\n }\r\n },\r\n {\r\n \"type\": \"compact\",\r\n \"dataSource\": \"statistics_rule_hits\",\r\n \"tuningConfig\": {\r\n \"type\": \"index_parallel\"\r\n }\r\n },\r\n {\r\n \"type\": \"compact\",\r\n \"dataSource\": \"traffic_shaping_rule_hits\",\r\n \"tuningConfig\": {\r\n \"type\": \"index_parallel\"\r\n }\r\n },\r\n {\r\n \"type\": \"compact\",\r\n \"dataSource\": \"object_statistics\",\r\n \"tuningConfig\": {\r\n \"type\": \"index_parallel\",\r\n \"maxRowsInMemory\": 250000\r\n }\r\n },\r\n {\r\n \"type\": \"compact\",\r\n \"dataSource\": \"statistics_rule\",\r\n \"tuningConfig\": {\r\n \"type\": \"index_parallel\",\r\n \"maxRowsInMemory\": 400000,\r\n \"maxBytesInMemory\": -1,\r\n \"splitHintSpec\": {\r\n \"type\": \"maxSize\",\r\n \"maxSplitSize\": \"4GiB\"\r\n },\r\n \"maxNumConcurrentSubTasks\": 2\r\n },\r\n \"context\":{\r\n \"druid.indexer.runner.javaOptsArray\": [\"-Xms4g\", \"-Xmx4g\", \"-XX:MaxDirectMemorySize=1g\"]\r\n }\r\n },\r\n {\r\n \"type\": \"compact\",\r\n \"dataSource\": \"sys_storage_log\",\r\n \"tuningConfig\": {\r\n \"type\": \"index_parallel\"\r\n }\r\n }\r\n]', 'DISCARD_LATER', '0', '0', 'BEAN', '', 'GLUE代码初始化', '2021-07-21 14:13:57', '', '1', '1708887600000', '1708974000000'); + +INSERT INTO `xxl_job_info` VALUES (101, 2, '0 0 0 1/7 * ?', 'run_web_sketch_assessment', '2022-01-27 17:40:42', '2024-03-13 05:44:06', 'galaxy', '', 'FAILOVER', 'httpToStoreJobHandler', '[{\r\n \"url\": \"http://{{ vrrp_instance.default.virtual_ipaddress }}:9999/v1/query/sql/\",\r\n \"method\": \"post\",\r\n \"requestBody\": {\r\n \"statement\": \"SELECT server_domain AS name, arrayStringConcat(groupUniqArray(decoded_as),\',\') AS protocol, count(*) AS sessions FROM tsg_galaxy_v3.session_record WHERE recv_time >= toStartOfDay(now()- INTERVAL 7 DAY) AND recv_time < toStartOfDay(now()) AND notEmpty(server_domain) GROUP BY name ORDER BY sessions DESC LIMIT 500000;\",\r\n \"exec_mode\":\"oneshot\",\r\n \"is_dry_run\": 0\r\n},\r\n \"resultKey\": \"data\",\r\n \"store\": \"all\"\r\n}, {\r\n \"url\": \"http://{{ vrrp_instance.default.virtual_ipaddress }}:9999/v1/query/sql/\",\r\n \"method\": \"post\",\r\n \"requestBody\": {\r\n \"statement\": \"SELECT server_domain AS name, arrayStringConcat(groupUniqArray(decoded_as),\',\') AS protocol, count(*) AS sessions FROM tsg_galaxy_v3.session_record WHERE recv_time >= toStartOfDay(now()- INTERVAL 7 DAY) AND recv_time < toStartOfDay(now()) AND notEmpty(server_domain) AND empty(fqdn_category_list) GROUP BY name ORDER BY sessions DESC LIMIT 500000;\",\r\n \"exec_mode\":\"oneshot\",\r\n \"is_dry_run\": 0\r\n},\r\n \"resultKey\": \"data\",\r\n \"store\": \"uncategorized\"\r\n}]', 'COVER_EARLY', 0, 0, 'BEAN', '', 'GLUE代码初始化', '2022-01-27 17:40:42', '', 1, 1709827200000, 1710432000000); +INSERT INTO `xxl_job_info` VALUES (141, 2, '0 0 2 * * ?', 'set_clickhouse_table_and_field_ttl', '2022-06-07 07:42:38', '2022-06-08 09:28:19', 'galaxy', '', 'FIRST', 'changeCkTtlJobHandler', '', 'SERIAL_EXECUTION', 0, 0, 'BEAN', '', 'GLUE代码初始化', '2022-06-07 07:42:38', '', 1, 1709488800000, 1709575200000); +INSERT INTO `xxl_job_info` VALUES (143, 2, '0 0 0/1 * * ?', 'run_ip_learning', '2022-11-09 10:29:20', '2024-02-19 02:32:54', 'galaxy', '', 'BUSYOVER', '', '', 'SERIAL_EXECUTION', 0, 0, 'GLUE_SHELL', '#!/bin/bash\nsh -c \'cd /opt/schedule-service/iplearning/ && ./start.sh\'', '0001', '2023-12-26 04:01:24', '', 1, 1709524800000, 1709528400000); +INSERT INTO `xxl_job_info` VALUES (145, 2, '0 0 2 * * ?', 'run_dos_baseline', '2022-11-10 06:15:27', '2023-11-13 05:37:41', 'galaxy', '', 'FIRST', '', '', 'SERIAL_EXECUTION', 0, 0, 'GLUE_SHELL', '#!/bin/bash\nsh -c \'cd /opt/schedule-service/dos-baseline && ./start.sh\'', '0000', '2023-11-13 05:37:41', '', 1, 1709488800000, 1709575200000); +INSERT INTO xxl_job_info (id, job_group, job_cron, job_desc, add_time, update_time, author, alarm_email, executor_route_strategy, executor_handler, executor_param, executor_block_strategy, executor_timeout, executor_fail_retry_count, glue_type, glue_source, glue_remark, glue_updatetime, child_jobid, trigger_status, trigger_last_time, trigger_next_time) VALUES ('158', '2', '0 0 2 * * ?', 'run_druid_segement_granularity_compact', '2023-02-20 05:59:59', '2023-05-11 03:39:14', 'galaxy', '', 'FAILOVER', 'druidMergeHistoryDataJobHandler', '[\r\n {\r\n \"type\": \"compact\",\r\n \"dataSource\": \"traffic_general_stat\",\r\n \"offsetDays\": 7,\r\n \"tuningConfig\": {\r\n \"type\": \"index_parallel\",\r\n \"splitHintSpec\": {\r\n \"type\": \"maxSize\",\r\n \"maxSplitSize\": \"2GiB\"\r\n },\r\n \"maxNumConcurrentSubTasks\": 1\r\n },\r\n \"granularitySpec\" : {\r\n \"segmentGranularity\": \"DAY\",\r\n \"queryGranularity\": \"MINUTE\"\r\n }\r\n },\r\n {\r\n \"type\": \"compact\",\r\n \"dataSource\": \"application_protocol_stat\",\r\n \"offsetDays\": 7,\r\n \"tuningConfig\": {\r\n \"type\": \"index_parallel\",\r\n \"maxRowsInMemory\": 200000,\r\n \"splitHintSpec\": {\r\n \"type\": \"maxSize\",\r\n \"maxSplitSize\": \"2GiB\"\r\n },\r\n \"maxNumConcurrentSubTasks\": 1\r\n },\r\n \"granularitySpec\" : {\r\n \"segmentGranularity\": \"DAY\",\r\n \"queryGranularity\": \"MINUTE\"\r\n }\r\n },\r\n {\r\n \"type\": \"compact\",\r\n \"dataSource\": \"object_statistics\",\r\n \"offsetDays\": 7,\r\n \"tuningConfig\": {\r\n \"type\": \"index_parallel\",\r\n \"maxRowsInMemory\": 250000,\r\n \"splitHintSpec\": {\r\n \"type\": \"maxSize\",\r\n \"maxSplitSize\": \"2GiB\"\r\n },\r\n \"maxNumConcurrentSubTasks\": 2\r\n },\r\n \"granularitySpec\" : {\r\n \"segmentGranularity\": \"DAY\",\r\n \"queryGranularity\": \"MINUTE\"\r\n }\r\n },\r\n {\r\n \"type\": \"compact\",\r\n \"dataSource\": \"statistics_rule\",\r\n \"offsetDays\": 7,\r\n \"tuningConfig\": {\r\n \"type\": \"index_parallel\",\r\n \"maxRowsInMemory\": 400000,\r\n \"maxBytesInMemory\": -1,\r\n \"splitHintSpec\": {\r\n \"type\": \"maxSize\",\r\n \"maxSplitSize\": \"4GiB\"\r\n },\r\n \"maxNumConcurrentSubTasks\": 2\r\n },\r\n \"granularitySpec\" : {\r\n \"segmentGranularity\": \"DAY\",\r\n \"queryGranularity\": \"MINUTE\"\r\n },\r\n \"context\":{\r\n \"druid.indexer.runner.javaOptsArray\": [\"-Xms2g\", \"-Xmx4g\", \"-XX:MaxDirectMemorySize=1g\"]\r\n }\r\n }\r\n]', 'DISCARD_LATER', '0', '0', 'BEAN', '', 'GLUE代码初始化', '2023-02-20 05:59:59', '', '1', '1708891200000', '1708977600000'); +INSERT INTO `xxl_job_info` VALUES (159, 1, '0 0 * * * ?', 'delete_clickhouse_old_log', '2024-06-24 09:02:27', '2024-07-15 03:05:03', 'galaxy', '', 'FIRST', 'deleteOldLogJobHandler', '{\r\n \"logType\": \"Traffic Logs\",\r\n \"maxUsage\": 90,\r\n \"durationMinutes\": 360,\r\n \"minIntervalMinutes\": 60,\r\n \"jdbcParam\": {\r\n \"type\": \"mariadb\",\r\n \"ip\": \"{{ vrrp_instance.default.virtual_ipaddress }}\",\r\n \"database\": \"tsg_olap\",\r\n \"table\": \"sys_storage_event\",\r\n \"username\": \"root\",\r\n \"pin\": \"{{ mariadb_default_pin }}\"\r\n }\r\n}', 'SERIAL_EXECUTION', 0, 0, 'BEAN', '', 'GLUE代码初始化', '2024-06-24 09:02:27', '', 1, 1721631600000, 1721635200000); +INSERT INTO `xxl_job_info` VALUES (160, 1, '0 0 * * * ?', 'delete_druid_old_log', '2024-06-24 09:05:37', '2024-07-15 03:04:38', 'galaxy', '', 'FIRST', 'deleteOldLogJobHandler', '{\r\n \"logType\": \"Metrics\",\r\n \"maxUsage\": 90,\r\n \"durationMinutes\": 360,\r\n \"minIntervalMinutes\": 60,\r\n \"jdbcParam\": {\r\n \"type\": \"mariadb\",\r\n \"ip\": \"{{ vrrp_instance.default.virtual_ipaddress }}\",\r\n \"database\": \"tsg_olap\",\r\n \"table\": \"sys_storage_event\",\r\n \"username\": \"root\",\r\n \"pin\": \"{{ mariadb_default_pin }}\"\r\n }\r\n}', 'SERIAL_EXECUTION', 0, 0, 'BEAN', '', 'GLUE代码初始化', '2024-06-24 09:05:37', '', 1, 1721631600000, 1721635200000); +INSERT INTO `xxl_job_info` VALUES (161, 1, '0 0 * * * ?', 'delete_hos_old_log', '2024-06-24 09:06:21', '2024-07-15 03:04:27', 'galaxy', '', 'FIRST', 'deleteOldLogJobHandler', '{\r\n \"logType\": \"Files\",\r\n \"maxUsage\": 90,\r\n \"durationMinutes\": 360,\r\n \"minIntervalMinutes\": 60,\r\n \"jdbcParam\": {\r\n \"type\": \"mariadb\",\r\n \"ip\": \"{{ vrrp_instance.default.virtual_ipaddress }}\",\r\n \"database\": \"tsg_olap\",\r\n \"table\": \"sys_storage_event\",\r\n \"username\": \"root\",\r\n \"pin\": \"{{ mariadb_default_pin }}\"\r\n }\r\n}', 'SERIAL_EXECUTION', 0, 0, 'BEAN', '', 'GLUE代码初始化', '2024-06-24 09:06:21', '', 1, 1721631600000, 1721635200000); diff --git a/tsg_olap/installation/mariadb/galaxy-qgw-service/R__init_datasets.sql b/tsg_olap/installation/mariadb/galaxy-qgw-service/R__init_datasets.sql new file mode 100644 index 0000000..62342b2 --- /dev/null +++ b/tsg_olap/installation/mariadb/galaxy-qgw-service/R__init_datasets.sql @@ -0,0 +1,212 @@ +/* + SQL Datasets +*/ + +SET NAMES utf8mb4; +SET FOREIGN_KEY_CHECKS = 0; +-- ---------------------------- +-- Table structure for dataset +-- ---------------------------- +DROP TABLE IF EXISTS `dataset`; +CREATE TABLE `dataset` ( + `id` int(64) NOT NULL AUTO_INCREMENT, + `identifier_name` varchar(128) NOT NULL, + `category` varchar(128) DEFAULT NULL, + `backend_engine` varchar(16) NOT NULL DEFAULT 'qgw' COMMENT 'qgw, clickhouse, druid, hbase', + `type` varchar(16) NOT NULL COMMENT 'dsl,sql', + `template` text NOT NULL, + `description` varchar(512) DEFAULT NULL, + `generated_time` bigint DEFAULT NULL, + `last_update_time` bigint DEFAULT NULL, + PRIMARY KEY (`id`) USING BTREE, + UNIQUE KEY `identifier_name` (`identifier_name`) +) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=utf8mb4 ROW_FORMAT=DYNAMIC; + +-- ---------------------------- +-- Trigger to set timestamps +-- ---------------------------- +DELIMITER // + +CREATE TRIGGER set_timestamps_trigger BEFORE INSERT ON `dataset` + FOR EACH ROW +BEGIN + SET NEW.generated_time = UNIX_TIMESTAMP(); + SET NEW.last_update_time = UNIX_TIMESTAMP(); +END // + +DELIMITER ; + +-- ---------------------------- +-- Records of dataset +-- ---------------------------- +BEGIN; +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('current-network-throughput-trend', 'traffic_general_stat', 'qgw', 'sql', '{ "statement": "SELECT SUM( sum_in_bytes)* 8 / 5 AS avg_in_bits_per_sec, SUM( sum_out_bytes )* 8 / 5 AS avg_out_bits_per_sec, SUM( sum_in_bytes + sum_out_bytes )* 8 / 5 AS avg_bits_per_sec, SUM( sum_in_bytes )/ 5 AS avg_in_bytes_per_sec, SUM( sum_out_bytes )/ 5 AS avg_out_bytes_per_sec, SUM( sum_in_bytes + sum_out_bytes )/ 5 AS avg_bytes_per_sec, SUM( sum_in_pkts )/ 5 AS avg_in_pkts_per_sec, SUM( sum_out_pkts )/ 5 AS avg_out_pkts_per_sec, SUM( sum_in_pkts + sum_out_pkts )/ 5 AS avg_pkts_per_sec, SUM( sum_sessions )/ 5 AS avg_sessions_per_sec, SUM( max_active_sessions ) AS active_sessions FROM( SELECT device_id, vsys_id, SUM( in_bytes ) AS sum_in_bytes, SUM( out_bytes ) AS sum_out_bytes, SUM( in_pkts ) AS sum_in_pkts, SUM( out_pkts ) AS sum_out_pkts, SUM( sessions ) AS sum_sessions, max( active_sessions ) AS max_active_sessions FROM traffic_general_stat WHERE __time >= FROM_UNIXTIME( UNIX_TIMESTAMP( now())- 15 ) AND __time < FROM_UNIXTIME( UNIX_TIMESTAMP( now())- 10 ) AND vsys_id IN ( ${vsys_id} ) AND ( ${filter} ) GROUP BY device_id, vsys_id )" }','System Overview-Traffic-Now. To calculate the current throughput, the metrics for each appliance are averaged over a 5-second interval. Additionally, the data ingestion latency is also set at 5 seconds.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('network-throughput-trend', 'traffic_general_stat', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) AS stat_time, RATE(in_bytes, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) * 8 AS avg_in_bits_per_sec, RATE(out_bytes, CHART_GRANULARITY(''${start_time}'', ''${end_time}''),1) * 8 AS avg_out_bits_per_sec, RATE(in_bytes + out_bytes, CHART_GRANULARITY(''${start_time}'', ''${end_time}''),1) * 8 AS avg_bits_per_sec, RATE(in_bytes, CHART_GRANULARITY(''${start_time}'', ''${end_time}''),1) AS avg_in_bytes_per_sec, RATE(out_bytes, CHART_GRANULARITY(''${start_time}'', ''${end_time}''),1) AS avg_out_bytes_per_sec, RATE(in_bytes + out_bytes, CHART_GRANULARITY(''${start_time}'', ''${end_time}''),1) AS avg_bytes_per_sec, RATE(in_pkts, CHART_GRANULARITY(''${start_time}'', ''${end_time}''),1) AS avg_in_pkts_per_sec, RATE(out_pkts, CHART_GRANULARITY(''${start_time}'', ''${end_time}''),1) AS avg_out_pkts_per_sec, RATE(in_pkts + out_pkts, CHART_GRANULARITY(''${start_time}'', ''${end_time}''),1) AS avg_pkts_per_sec FROM traffic_general_stat WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN(${vsys_id}) AND (${filter}) GROUP BY FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), CHART_GRANULARITY(''${start_time}'', ''${end_time}''),''zero'')) ORDER BY stat_time ASC LIMIT ${limit}" }','The calculation of average network throughput is capable of supporting two types of metrics, namely "bytes" and "packets".'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('network-throughput-packet-per-second', 'traffic_general_stat', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(stat_time, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) AS stat_time, AVG( in_pkts_per_sec) AS avg_in_pkts_per_sec, AVG( out_pkts_per_sec ) AS avg_out_pkts_per_sec, AVG( pkts_per_sec ) AS avg_pkts_per_sec, MAX( in_pkts_per_sec ) AS max_in_pkts_per_sec, MAX( out_pkts_per_sec ) AS max_out_pkts_per_sec, MAX( pkts_per_sec ) AS max_pkts_per_sec, MIN( in_pkts_per_sec ) AS min_in_pkts_per_sec, MIN( out_pkts_per_sec ) AS min_out_pkts_per_sec, MIN( pkts_per_sec ) AS min_pkts_per_sec FROM( SELECT TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), SAMPLE_GRANULARITY(''${start_time}'', ''${end_time}'')) AS stat_time, RATE( in_pkts, SAMPLE_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS in_pkts_per_sec, RATE( out_pkts, SAMPLE_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS out_pkts_per_sec, RATE( in_pkts + out_pkts, SAMPLE_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS pkts_per_sec FROM traffic_general_stat WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN ( ${vsys_id} ) AND ( ${filter} ) GROUP BY TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), SAMPLE_GRANULARITY(''${start_time}'', ''${end_time}'')) ) GROUP BY FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(stat_time, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) ORDER BY stat_time ASC LIMIT ${limit}" }','System Overview-Traffic-AVG, MAX, MIN. To calculate network throughput, supports metric types "bytes" and "packets," and offers aggregation methods including "average"(avg), "maximum" (max), and "minimum" (min). Based on MAX and MIN values can reveal abnormal traffic patterns, such as peak and valley outliers.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('network-throughput-bit-per-second', 'traffic_general_stat', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL( stat_time, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) AS stat_time, AVG( in_bytes_per_sec )* 8 AS avg_in_bits_per_sec, AVG( out_bytes_per_sec )* 8 AS avg_out_bits_per_sec, AVG( bytes_per_sec )* 8 AS avg_bits_per_sec, MAX( in_bytes_per_sec )* 8 AS max_in_bits_per_sec, MAX( out_bytes_per_sec )* 8 AS max_out_bits_per_sec, MAX( bytes_per_sec )* 8 AS max_bits_per_sec, MIN( in_bytes_per_sec )* 8 AS min_in_bits_per_sec, MIN( out_bytes_per_sec )* 8 AS min_out_bits_per_sec, MIN( bytes_per_sec )* 8 AS min_bits_per_sec FROM( SELECT TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), SAMPLE_GRANULARITY(''${start_time}'', ''${end_time}'')) AS stat_time, RATE( in_bytes, SAMPLE_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS in_bytes_per_sec, RATE( out_bytes, SAMPLE_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS out_bytes_per_sec, RATE( in_bytes + out_bytes, SAMPLE_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS bytes_per_sec FROM traffic_general_stat WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN ( ${vsys_id} ) AND ( ${filter} ) GROUP BY TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), SAMPLE_GRANULARITY(''${start_time}'', ''${end_time}'')) ) GROUP BY FROM_UNIXTIME(TIME_FLOOR_WITH_FILL( stat_time, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'' )) ORDER BY stat_time ASC LIMIT ${limit}" }','System Overview-Traffic-AVG, MAX, MIN. To calculate network throughput, supports metric types "bytes" and "packets," and offers aggregation methods including "average"(avg), "maximum" (max), and "minimum" (min). Based on MAX and MIN values can reveal abnormal traffic patterns, such as peak and valley outliers.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('network-throughput-byte-per-second', 'traffic_general_stat', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(stat_time, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) AS stat_time, AVG( in_bytes_per_sec) AS avg_in_bytes_per_sec, AVG( out_bytes_per_sec ) AS avg_out_bytes_per_sec, AVG( bytes_per_sec ) AS avg_bytes_per_sec, MAX( in_bytes_per_sec ) AS max_in_bytes_per_sec, MAX( out_bytes_per_sec ) AS max_out_bytes_per_sec, MAX( bytes_per_sec ) AS max_bytes_per_sec, MIN( in_bytes_per_sec ) AS min_in_bytes_per_sec, MIN( out_bytes_per_sec ) AS min_out_bytes_per_sec, MIN( bytes_per_sec ) AS min_bytes_per_sec FROM( SELECT TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), SAMPLE_GRANULARITY(''${start_time}'', ''${end_time}'')) AS stat_time, RATE( in_bytes, SAMPLE_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS in_bytes_per_sec, RATE( out_bytes, SAMPLE_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS out_bytes_per_sec, RATE( in_bytes + out_bytes, SAMPLE_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS bytes_per_sec FROM traffic_general_stat WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN ( ${vsys_id} ) AND ( ${filter} ) GROUP BY TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), SAMPLE_GRANULARITY(''${start_time}'', ''${end_time}'')) ) GROUP BY FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(stat_time, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) ORDER BY stat_time ASC LIMIT ${limit}" }','System Overview-Traffic-AVG, MAX, MIN. To calculate network throughput, supports metric types "bytes" and "packets," and offers aggregation methods including "average"(avg), "maximum" (max), and "minimum" (min). Based on MAX and MIN values can reveal abnormal traffic patterns, such as peak and valley outliers.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('new-sessions-per-second', 'traffic_general_stat', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(stat_time, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) AS stat_time, AVG( sessions_per_sec) AS avg_sessions_per_sec, MAX( sessions_per_sec ) AS max_sessions_per_sec, MIN( sessions_per_sec ) AS min_sessions_per_sec FROM( SELECT TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), SAMPLE_GRANULARITY(''${start_time}'', ''${end_time}'')) AS stat_time, RATE( sessions, SAMPLE_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS sessions_per_sec FROM traffic_general_stat WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN ( ${vsys_id} ) AND ( ${filter} ) GROUP BY TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), SAMPLE_GRANULARITY(''${start_time}'', ''${end_time}'')) ) GROUP BY FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(stat_time, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) ORDER BY stat_time ASC LIMIT ${limit}" }','System Overview-New-AVG, MAX, MIN.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('active-sessions', 'traffic_general_stat', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(stat_time, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) AS stat_time, AVG( active_sessions_per_sec) AS avg_active_sessions, MAX( active_sessions_per_sec ) AS max_active_sessions, MIN( active_sessions_per_sec ) AS min_active_sessions FROM( SELECT stat_time, RATE( max_active_sessions, SAMPLE_GRANULARITY(''${start_time}'', ''${end_time}''), 1) active_sessions_per_sec FROM ( SELECT TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), SAMPLE_GRANULARITY(''${start_time}'', ''${end_time}'')) AS stat_time, device_id, vsys_id, MAX( active_sessions ) AS max_active_sessions FROM traffic_general_stat WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN ( ${vsys_id} ) AND ( ${filter} ) GROUP BY TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), SAMPLE_GRANULARITY(''${start_time}'', ''${end_time}'')), device_id, vsys_id ) GROUP BY stat_time ) GROUP BY FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(stat_time, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) ORDER BY stat_time ASC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('asymmetric-flows', 'traffic_general_stat', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time),CHART_GRANULARITY(''${start_time}'', ''${end_time}''),''zero'')) AS stat_time, RATE(in_bytes + out_bytes, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) * 8 AS avg_bits_per_sec, round( CASE WHEN SUM(closed_sessions) = 0 THEN 0 ELSE SUM( asymmetric_c2s_flows + asymmetric_s2c_flows) * 100.0 / SUM(closed_sessions) END,2) AS percent_asymmetric_flows FROM traffic_general_stat WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN(${vsys_id}) AND (${filter}) GROUP BY FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time),CHART_GRANULARITY(''${start_time}'', ''${end_time}''),''zero'')) ORDER BY stat_time ASC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('traffic-statistics-metrics', 'traffic_general_stat', 'qgw', 'sql', '{ "statement": "SELECT COUNT(DISTINCT(device_id)) AS device_num, SUM(sum_bytes) AS total_bytes_transferred, SUM(sum_pkts) AS total_packets_transferred, SUM(sum_sessions) AS total_new_sessions , SUM(sum_closed_sessions) AS total_closed_sessions, SUM(sum_sessions)/ ${timestampdiff_second} AS avg_new_sessions_per_second, SUM(sum_bytes)* 8 / ${timestampdiff_second} AS avg_bits_per_second, SUM(sum_pkts)/ ${timestampdiff_second} AS avg_packets_per_second, SUM(avg_active_sessions) AS avg_active_sessions, round(CASE WHEN SUM(sum_closed_sessions) = 0 THEN 0 ELSE SUM(sum_asymmetric_flows) * 100.0 / SUM(sum_closed_sessions) END, 2) AS percent_asymmetric_flows FROM( SELECT device_id, vsys_id, SUM(in_bytes + out_bytes) AS sum_bytes, SUM(in_pkts + out_pkts) AS sum_pkts, SUM(sessions) AS sum_sessions, SUM(closed_sessions) AS sum_closed_sessions, AVG(active_sessions) AS avg_active_sessions, SUM(asymmetric_c2s_flows + asymmetric_s2c_flows) AS sum_asymmetric_flows FROM traffic_general_stat WHERE __time >= ''${start_time}'' AND __time <''${end_time}'' AND vsys_id IN ( ${vsys_id}) AND ( ${filter} ) GROUP BY device_id, vsys_id )" }','predefined dataset for the report.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('traffic-summary-throughput', 'traffic_general_stat', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time),CHART_GRANULARITY(''${start_time}'', ''${end_time}''),''zero'')) AS stat_time , RATE(in_bytes, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) * 8 AS avg_in_bits_per_sec, RATE(out_bytes, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) * 8 AS avg_out_bits_per_sec, RATE(in_bytes + out_bytes, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) * 8 AS avg_bits_per_sec FROM traffic_general_stat WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN(${vsys_id}) AND (${filter}) GROUP BY FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time),CHART_GRANULARITY(''${start_time}'', ''${end_time}''),''zero'')) ORDER BY stat_time ASC LIMIT ${limit}" }','predefined dataset for the report.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('traffic-summary-new-sessions-per-second', 'traffic_general_stat', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time),CHART_GRANULARITY(''${start_time}'', ''${end_time}''),''zero'')) AS stat_time, RATE(sessions, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS avg_sessions_per_sec FROM traffic_general_stat WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN(${vsys_id}) AND (${filter}) GROUP BY FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time),CHART_GRANULARITY(''${start_time}'', ''${end_time}''),''zero'')) ORDER BY stat_time ASC LIMIT ${limit}" }','predefined dataset for the report.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('application-and-protocol-summary', 'traffic_application_protocol_stat', 'qgw', 'dsl', '{"name": "application-and-protocol-summary", "filter": "vsys_id in (${vsys_id}) AND (${filter})", "intervals": ["${start_time}/${end_time}"] }','Application and Protocol Summary'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('application-and-protocol-tree-composition', 'traffic_application_protocol_stat', 'qgw', 'dsl', '{"name": "application-and-protocol-tree-composition", "filter": "vsys_id in (${vsys_id}) AND (${filter})", "intervals": ["${start_time}/${end_time}"] }','application and protocol tree composition'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('application-and-protocol-tree-throughput', 'traffic_application_protocol_stat', 'qgw', 'dsl', '{"name": "application-and-protocol-tree-throughput", "filter": "vsys_id in (${vsys_id}) AND (protocol_stack_id = ''${protocol_stack_id}'' OR ( protocol_stack_id LIKE ''${protocol_stack_id}.%'' AND NOT CONTAINS_STRING(REPLACE(protocol_stack_id, ''${protocol_stack_id}.'', ''''), ''.''))) AND (${filter})", "intervals": ["${start_time}/${end_time}"] }','application and protocol tree throughput'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('application-and-protocol-top-apps', 'traffic_application_protocol_stat', 'qgw', 'dsl', '{"name": "application-and-protocol-top-apps", "filter": "vsys_id in (${vsys_id}) AND (${filter})", "intervals": ["${start_time}/${end_time}"], "limit": "${limit}" }','top apps'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('application-and-protocol-app-related-internal-ips', 'traffic_application_protocol_stat', 'qgw', 'dsl', '{"name": "application-and-protocol-app-related-internal-ips", "filter": "vsys_id in (${vsys_id}) AND app in (''${app_name}'') AND (${filter})", "intervals": ["${start_time}/${end_time}"], "limit": "${limit}" }','app-related internal ips'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('application-and-protocol-app-throughput', 'traffic_application_protocol_stat', 'qgw', 'dsl', '{"name": "application-and-protocol-app-throughput", "filter": "vsys_id in (${vsys_id}) AND app_name in (''${app_name}'') AND (${filter})", "intervals": ["${start_time}/${end_time}"], "limit": "${limit}" }','app-throughput'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('application-and-protocol-app-summary', 'traffic_application_protocol_stat', 'qgw', 'dsl', '{"name": "application-and-protocol-app-summary", "filter": "vsys_id in (${vsys_id}) AND app_name in (''${app_name}'') AND (${filter})", "intervals": ["${start_time}/${end_time}"] }','app summary'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('application-usage', 'traffic_application_protocol_stat', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) AS stat_time, app_name, RATE(in_bytes, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) * 8 AS avg_in_bits_per_sec, RATE(out_bytes,CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) * 8 AS avg_out_bits_per_sec, RATE(in_bytes + out_bytes, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) * 8 AS avg_bits_per_sec, RATE(in_pkts, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS avg_in_pkts_per_sec, RATE(out_pkts, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS avg_out_pkts_per_sec, RATE(in_pkts + out_pkts, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS avg_pkts_per_sec, RATE(sessions, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS avg_sessions_per_sec FROM application_protocol_stat WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN ( ${vsys_id} ) AND ( ${filter} ) AND app_name IS NOT NULL GROUP BY FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')), app_name ORDER BY stat_time ASC LIMIT ${limit}" }','Real-time traffic sessions, bytes, and packets of favorite applications over a selected time frame.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('object-statistics-list', 'object_statistics', 'qgw', 'sql', '{ "statement": "SELECT object_id, SUM( in_bytes) AS in_bytes, SUM( out_bytes ) AS out_bytes, SUM( bytes ) AS bytes, SUM( new_in_sessions ) AS new_in_sessions, SUM( new_out_sessions ) AS new_out_sessions, SUM( sessions ) AS sessions FROM object_statistics WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN( ${vsys_id} ) AND object_type IN ( ''${object_type}'' ) AND object_id IN ( ${object_id} ) AND ( ${filter} ) GROUP BY object_id ORDER BY ${order_by} LIMIT ${limit}" }','A list of objects sorted by ${metric}. The ${metric} variable includes [ incoming_bytes| outgoing_bytes| bytes| new_incoming_sessions| new_outgoing_sessions| sessions].'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('object-statistics-summary', 'object_statistics', 'qgw', 'sql', '{ "statement": "SELECT SUM( in_bytes) AS in_bytes, SUM( out_bytes ) AS out_bytes, SUM( bytes ) AS bytes, SUM( new_in_sessions ) AS new_in_sessions, SUM( new_out_sessions ) AS new_out_sessions, SUM( sessions ) AS sessions FROM object_statistics WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN( ${vsys_id} ) AND object_type IN ( ''${object_type}'' ) AND object_id IN (${object_id}) AND item_id IN (${item_id}) AND ( ${filter} )" }','Aggregate traffic sessions and bytes based on the objects.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('object-statistics-item-list', 'object_statistics', 'qgw', 'sql', '{ "statement": "SELECT item_id, SUM( in_bytes) AS in_bytes, SUM( out_bytes ) AS out_bytes, SUM( bytes ) AS bytes, SUM( new_in_sessions ) AS new_in_sessions, SUM( new_out_sessions ) AS new_out_sessions, SUM( sessions ) AS sessions FROM object_statistics WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN( ${vsys_id} ) AND object_type IN ( ''${object_type}'' ) AND object_id IN (${object_id}) AND item_id IN (${item_id}) AND item_id > 0 AND ( ${filter} ) GROUP BY item_id ORDER BY ${order_by} LIMIT ${limit}" }','A list of items sorted by ${metric} with specific Object ID(${filters}). The ${metric} variable includes [ incoming_bytes| outgoing_bytes| bytes| new_incoming_sessions| new_outgoing_sessions| sessions].'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('object-statistics-trend', 'object_statistics', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) AS stat_time, SUM( in_bytes ) AS in_bytes, RATE(in_bytes, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) * 8 AS avg_in_bits_per_sec, SUM( out_bytes ) AS out_bytes, RATE(out_bytes, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) * 8 AS avg_out_bits_per_sec, SUM( bytes ) AS bytes, RATE(bytes, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) * 8 AS avg_bits_per_sec, SUM( new_in_sessions ) AS new_in_sessions, RATE(new_in_sessions, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS avg_new_in_sessions_per_sec, SUM( new_out_sessions ) AS new_out_sessions, RATE(new_out_sessions, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS avg_new_out_sessions_per_sec, SUM( sessions ) AS sessions, RATE(sessions, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS avg_sessions_per_sec FROM object_statistics WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN ( ${vsys_id} ) AND object_type IN ( ''${object_type}'' ) AND object_id IN (${object_id}) AND item_id IN (${item_id}) AND ( ${filter} ) GROUP BY FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) ORDER BY stat_time ASC LIMIT ${limit}"}','The traffic trend by an object or item.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('traffic-shaping-policy-rule-dropped-packets', 'traffic_shaping_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) AS stat_time, rule_id, SUM( in_drop_pkts + out_drop_pkts ) AS sum_dropped_packets FROM traffic_shaping_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN ( ${vsys_id} ) AND ( ${filter} ) GROUP BY FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')), rule_id ORDER BY stat_time ASC LIMIT ${limit}" }','The dropped packets for different traffic shaping rules over a selected time frame.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('traffic-shaping-policy-rule-throughput-by-rule-id', 'traffic_shaping_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) AS stat_time, rule_id, RATE(in_bytes + out_bytes, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) * 8 AS avg_bits_per_sec FROM traffic_shaping_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN (${vsys_id}) AND (${filter}) GROUP BY FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')), rule_id ORDER BY stat_time ASC LIMIT ${limit}" }','The throughput of traffic shaping rule by rule id over a selected time frame'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('traffic-shaping-profile-statistics', 'traffic_shaping_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT profile_id, SUM( in_bytes + out_bytes ) AS bytes, SUM( in_pkts + out_pkts ) AS packets, SUM( in_drop_pkts + out_drop_pkts ) AS drops, MAX( in_max_latency_us + out_max_latency_us ) AS max_latency_us, AVG( in_queue_len + out_queue_len ) AS avg_q, MAX( in_queue_len + out_queue_len ) AS max_q FROM traffic_shaping_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN ( ${vsys_id} ) AND profile_id IN ( ${profile_id} ) AND ( ${filter} ) GROUP BY profile_id" }','The statistics of specific shaping profiles.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('traffic-shaping-policy-rule-first-and-last-hit', 'traffic_shaping_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT rule_id, DATE_FORMAT( MAX( __time ), ''%Y-%m-%d %H:%i:%s'' ) AS last_hit, DATE_FORMAT( MIN( __time ), ''%Y-%m-%d %H:%i:%s'' ) AS first_hit FROM traffic_shaping_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN ( ${vsys_id} ) AND rule_id IN ( ${rule_id} ) AND ( ${filter} ) GROUP BY rule_id" }','The time of the first and last hit for policy rules.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('traffic-shaping-policy-rule-transferred-bytes', 'traffic_shaping_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT rule_id, SUM( in_bytes + out_bytes ) AS total_bytes FROM traffic_shaping_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN ( ${vsys_id} ) AND rule_id IN ( ${rule_id} ) AND ( ${filter} ) GROUP BY rule_id" }','The number of transferred bytes of specific shaping rules.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('traffic-shaping-profile-first-and-last-hit', 'traffic_shaping_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT profile_id, DATE_FORMAT( max( __time ), ''%Y-%m-%d %H:%i:%s'' ) AS last_hit, DATE_FORMAT( min( __time ), ''%Y-%m-%d %H:%i:%s'' ) AS first_hit, SUM( in_drop_pkts + out_drop_pkts ) AS drops FROM traffic_shaping_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN ( ${vsys_id} ) AND profile_id IN ( ${profile_id} ) AND ( ${filter} ) GROUP BY profile_id" }','The time of the first and last hit for shaping profiles.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('traffic-shaping-profile-current-throughput', 'traffic_shaping_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT SUM( in_bytes )* 8 / 5 AS in_bps, SUM( out_bytes )* 8 / 5 AS out_bps, SUM( in_pkts )* 8 / 5 AS in_pps, SUM( out_pkts )* 8 / 5 AS out_pps, MAX( in_max_latency_us + out_max_latency_us ) AS max_latency_us, AVG( in_queue_len + out_queue_len ) AS avg_q, MAX( in_queue_len + out_queue_len ) AS max_q FROM traffic_shaping_rule_hits WHERE __time >= FROM_UNIXTIME( UNIX_TIMESTAMP( now())- 15 ) AND __time < FROM_UNIXTIME( UNIX_TIMESTAMP( now())- 10 ) AND vsys_id IN ( ${vsys_id} ) AND profile_id IN ( ${profile_id} ) AND ( ${filter} )" }','To calculate the current shaping profile hit throughput, the metrics for each appliance are averaged over a 5-second interval. Additionally, the data ingestion latency is also set at 5 seconds.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('traffic-shaping-policy-rule-throughput', 'traffic_shaping_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL( UNIX_TIMESTAMP( __time ), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'' )) AS stat_time, SUM( in_bytes ) AS in_bytes, SUM( out_bytes ) AS out_bytes FROM traffic_shaping_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN ( ${vsys_id} ) AND rule_id IN ( ${rule_id} ) AND ( ${filter} ) GROUP BY FROM_UNIXTIME(TIME_FLOOR_WITH_FILL( UNIX_TIMESTAMP( __time ), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'' )) ORDER BY stat_time ASC LIMIT ${limit}" }','The throughput of traffic shaping rule over a selected time frame'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('traffic-shaping-profile-throughput', 'traffic_shaping_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL( UNIX_TIMESTAMP( __time ), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'' )) AS stat_time, SUM( in_bytes ) AS in_bytes, SUM( out_bytes ) AS out_bytes FROM traffic_shaping_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN ( ${vsys_id} ) AND profile_id IN ( ${profile_id} ) AND ( ${filter} ) GROUP BY FROM_UNIXTIME(TIME_FLOOR_WITH_FILL( UNIX_TIMESTAMP( __time ), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'' )) ORDER BY stat_time ASC LIMIT ${limit}" }','The throughput of traffic shaping profile over a selected time frame'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('service-chaining-policy-rule-throughput-by-rule-id', 'service_chaining_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) AS stat_time, rule_id, RATE(sent_bytes + recv_bytes, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) * 8 AS avg_bits_per_sec FROM service_chaining_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN (${vsys_id}) AND (${filter}) GROUP BY FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')), rule_id ORDER BY stat_time ASC LIMIT ${limit}" }','The throughput of the service chaining rule over a selected time frame.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('service-chaining-policy-rule-transferred-bytes-trend', 'service_chaining_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL( UNIX_TIMESTAMP( __time ), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'' )) AS stat_time, SUM( sent_bytes ) AS sent_bytes, SUM( recv_bytes ) AS received_bytes FROM service_chaining_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN ( ${vsys_id} ) AND rule_id IN ( ${rule_id} ) AND ( ${filter} ) GROUP BY FROM_UNIXTIME(TIME_FLOOR_WITH_FILL( UNIX_TIMESTAMP( __time ), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'' )) ORDER BY stat_time ASC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('service-chaining-function-forwarder-profile-transferred-bytes-trend', 'service_chaining_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL( UNIX_TIMESTAMP( __time ), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'' )) AS stat_time, SUM( sent_bytes ) AS sent_bytes, SUM( recv_bytes ) AS received_bytes FROM service_chaining_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN ( ${vsys_id} ) AND sff_profile_id IN ( ${sff_profile_id} ) AND ( ${filter} ) GROUP BY FROM_UNIXTIME(TIME_FLOOR_WITH_FILL( UNIX_TIMESTAMP( __time ), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'' )) ORDER BY stat_time ASC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('service-chaining-function-profile-transferred-bytes-trend', 'service_chaining_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL( UNIX_TIMESTAMP( __time ), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'' )) AS stat_time, SUM( sent_bytes ) AS sent_bytes, SUM( recv_bytes ) AS received_bytes FROM service_chaining_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN ( ${vsys_id} ) AND sf_profile_id IN ( ${sf_profile_id}) AND ( ${filter} ) GROUP BY FROM_UNIXTIME(TIME_FLOOR_WITH_FILL( UNIX_TIMESTAMP( __time ), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'' )) ORDER BY stat_time ASC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('service-chaining-policy-rule-statistics', 'service_chaining_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT rule_id, SUM(sent_bytes) as sent_bytes, SUM(recv_bytes) as received_bytes, SUM(sent_pkts) as sent_packets, SUM(recv_pkts) as received_packets FROM service_chaining_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN ( ${vsys_id} ) AND rule_id IN ( ${rule_id} ) AND ( ${filter} ) GROUP BY rule_id" }','The hit count of specific rules.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('service-chaining-function-forwarder-profile-statistics', 'service_chaining_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT sff_profile_id, SUM( sent_bytes ) AS sent_bytes, SUM( recv_bytes ) AS received_bytes, SUM( sent_pkts ) AS sent_packets, SUM( recv_pkts ) AS received_packets FROM service_chaining_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN ( ${vsys_id} ) AND sff_profile_id IN ( ${sff_profile_id} ) AND ( ${filter} ) GROUP BY sff_profile_id" }','The hit count of specific function forwarder profiles.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('service-chaining-function-profile-statistics', 'service_chaining_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT sf_profile_id, SUM( sent_bytes ) AS sent_bytes, SUM( recv_bytes ) AS received_bytes, SUM( sent_pkts ) AS sent_packets, SUM( recv_pkts ) AS received_packets FROM service_chaining_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN ( ${vsys_id} ) AND sf_profile_id IN ( ${sf_profile_id} ) AND ( ${filter} ) GROUP BY sf_profile_id" }','The hit count of specific function profiles.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('service-function-status-first-and-last-active-time', 'service_function_status', 'qgw', 'sql', '{ "statement": "SELECT sf_profile_id, sf_status, CASE WHEN last_active_time = 0 THEN '''' ELSE FROM_UNIXTIME(last_active_time) END AS last_active_time, CASE WHEN last_inactive_time = 0 THEN '''' ELSE FROM_UNIXTIME(last_inactive_time) END AS last_inactive_time FROM (SELECT sf_profile_id, LATEST(sf_status) as sf_status, MAX(CASE WHEN sf_status = 1 THEN UNIX_TIMESTAMP(__time) ELSE 0 END) as last_active_time, MAX(CASE WHEN sf_status = 0 THEN UNIX_TIMESTAMP(__time) ELSE 0 END) as last_inactive_time FROM service_function_status WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN ( ${vsys_id} ) AND sf_profile_id IN ( ${sf_profile_id} ) AND ( ${filter} ) GROUP BY sf_profile_id)" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('top-security-policy-rule', 'security_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT rule_id AS rule_id, SUM( hit_count ) AS hit_count, SUM( in_bytes + out_bytes ) AS bytes FROM security_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN ( ${vsys_id} ) AND ( ${filter} ) GROUP BY rule_id ORDER BY ${metric} DESC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('security-policy-rule-hits-by-rule-id', 'security_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) AS stat_time, rule_id, RATE(hit_count, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS avg_hit_count_per_sec, RATE(in_bytes + out_bytes, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) * 8 AS avg_bits_per_sec FROM security_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN (${vsys_id}) AND (${filter}) GROUP BY FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')), rule_id ORDER BY stat_time ASC LIMIT ${limit}" }','The hit count and bytes of the favorite security policy rule over the selected time frame.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('security-policy-rule-hits-by-action', 'security_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) AS stat_time, (CASE WHEN action = 1 THEN ''Monitor'' WHEN action = 16 THEN ''Deny'' WHEN action = 96 THEN ''Allow'' WHEN action = 128 THEN ''Shunt'' ELSE concat(action) END ) AS action, RATE(hit_count, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS avg_hit_count_per_sec, RATE(in_bytes + out_bytes, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) * 8 AS avg_bits_per_sec, RATE(in_pkts + out_pkts, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS avg_pkts_per_sec, SUM(hit_count) AS total_hit_count, SUM( in_bytes + out_bytes ) AS total_bytes, SUM( in_pkts + out_pkts ) AS total_packets FROM security_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN (${vsys_id}) AND (${filter}) GROUP BY FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')), action ORDER BY stat_time ASC LIMIT ${limit}" }','The security policy rule hits count, bytes, and packets of action over the selected time frame.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('top-security-policy-rule-with-action', 'security_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT rule_id, action, SUM( hit_count ) AS hit_count, SUM( in_bytes + out_bytes ) AS bytes FROM security_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN ( ${vsys_id} ) AND ( ${filter} ) GROUP BY rule_id, action ORDER BY ${metric} DESC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('security-policy-rule-statistics', 'security_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT rule_id, SUM(hit_count) as hits, SUM(in_bytes + out_bytes) as bytes FROM security_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND rule_id IN ( ${rule_id} ) AND vsys_id IN ( ${vsys_id} ) AND ( ${filter} ) GROUP BY rule_id" }','The statistics of specific rules.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('security-policy-rule-hits-trend', 'security_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL( UNIX_TIMESTAMP( __time ), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'' )) AS stat_time, SUM(hit_count) AS hits FROM security_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND rule_id IN (${rule_id}) AND vsys_id IN (${vsys_id}) AND ( ${filter} ) GROUP BY FROM_UNIXTIME(TIME_FLOOR_WITH_FILL( UNIX_TIMESTAMP( __time ), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'' )) LIMIT ${limit}" }','The trend of hit count by specific rule over a period of time.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('security-policy-rule-hits-first-and-last-hit', 'security_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT rule_id, DATE_FORMAT(MIN(__time) ,''%Y-%m-%d %H:%i:%s'') AS first_hit, DATE_FORMAT(MAX(__time) ,''%Y-%m-%d %H:%i:%s'') AS last_hit FROM security_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND rule_id IN ( ${rule_id} ) AND vsys_id IN ( ${vsys_id} ) AND ( ${filter} ) GROUP BY rule_id" }','The time of the first and last hit for policy rules.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('security-policy-rule-current-throughput', 'security_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT SUM(in_bytes)* 8 / 5 AS in_bps, SUM(out_bytes)* 8 / 5 AS out_bps, SUM(in_bytes + out_bytes)* 8 / 5 AS total_bps FROM security_rule_hits WHERE __time >= FROM_UNIXTIME(UNIX_TIMESTAMP(now())-15) AND __time < FROM_UNIXTIME(UNIX_TIMESTAMP(now())-10) AND vsys_id IN ( ${vsys_id} ) AND rule_id IN ( ${rule_id} ) AND ( ${filter} )" }','To calculate the current security hit throughput, the metrics for each appliance are averaged over a 5-second interval. Additionally, the data ingestion latency is also set at 5 seconds.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('monitor-policy-rule-statistics', 'monitor_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT rule_id, SUM(hit_count) as hits, SUM(in_bytes + out_bytes) as bytes FROM monitor_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND rule_id IN ( ${rule_id} ) AND vsys_id IN ( ${vsys_id} ) AND ( ${filter} ) GROUP BY rule_id" }','The statistics of specific rules.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('monitor-policy-rule-hits-trend', 'monitor_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL( UNIX_TIMESTAMP( __time ), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'' )) AS stat_time, SUM(hit_count) AS hits FROM monitor_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND rule_id IN (${rule_id}) AND vsys_id IN (${vsys_id}) AND ( ${filter} ) GROUP BY FROM_UNIXTIME(TIME_FLOOR_WITH_FILL( UNIX_TIMESTAMP( __time ), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'' )) LIMIT ${limit}" }','The trend of hit count by specific rule over some time.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('monitor-policy-rule-hits-first-and-last-hit', 'monitor_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT rule_id, DATE_FORMAT(MIN(__time) ,''%Y-%m-%d %H:%i:%s'') AS first_hit, DATE_FORMAT(MAX(__time) ,''%Y-%m-%d %H:%i:%s'') AS last_hit FROM monitor_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND rule_id IN ( ${rule_id} ) AND vsys_id IN ( ${vsys_id} ) AND ( ${filter} ) GROUP BY rule_id" }','The time of the first and last hit for policy rules.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('monitor-policy-rule-current-throughput', 'monitor_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT SUM(in_bytes)* 8 / 5 AS in_bps, SUM(out_bytes)* 8 / 5 AS out_bps, SUM(in_bytes + out_bytes)* 8 / 5 AS total_bps FROM monitor_rule_hits WHERE __time >= FROM_UNIXTIME(UNIX_TIMESTAMP(now())-15) AND __time < FROM_UNIXTIME(UNIX_TIMESTAMP(now())-10) AND vsys_id IN ( ${vsys_id} ) AND rule_id IN ( ${rule_id} ) AND ( ${filter} )" }','To calculate the current monitor hit throughput, the metrics for each appliance are averaged over a 5-second interval. Additionally, the data ingestion latency is also set at 5 seconds.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('top-proxy-policy-rule-with-manipulation-action', 'proxy_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT rule_id AS rule_id, sub_action AS sub_action, SUM( hit_count ) AS hit_count, SUM( in_bytes + out_bytes ) AS bytes FROM proxy_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND action=48 AND vsys_id IN ( ${vsys_id} ) AND ( ${filter} ) GROUP BY rule_id, sub_action ORDER BY ${metric} DESC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('proxy-policy-rule-hits-by-rule-id', 'proxy_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) AS stat_time, rule_id, RATE(hit_count, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS avg_hit_count_per_sec, RATE(in_bytes + out_bytes, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) * 8 AS avg_bits_per_sec FROM proxy_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN (${vsys_id}) AND (${filter}) GROUP BY FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')), rule_id ORDER BY stat_time ASC LIMIT ${limit}" }','The hit count and bytes of the favorite proxy policy rule over the selected time frame.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('proxy-ssl-intercept-pinning-trend', 'proxy_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(stat_time, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) AS stat_time, AVG( CASE WHEN pinning_status = ''0'' THEN hit_count_per_sec ELSE 0 END ) AS avg_not_pinning_hit_count_per_sec, AVG( CASE WHEN pinning_status = ''1'' THEN hit_count_per_sec ELSE 0 END ) AS avg_pinning_hit_count_per_sec, AVG( CASE WHEN pinning_status = ''2'' THEN hit_count_per_sec ELSE 0 END ) AS avg_maybe_pinning_hit_count_per_sec FROM (SELECT TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), SAMPLE_GRANULARITY(''${start_time}'', ''${end_time}'')) AS stat_time, pinning_status, RATE( hit_count, SAMPLE_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS hit_count_per_sec FROM proxy_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN ( ${vsys_id} ) AND action = 2 AND ( ${filter} ) GROUP BY TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), SAMPLE_GRANULARITY(''${start_time}'', ''${end_time}'')), pinning_status ) GROUP BY FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(stat_time, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) ORDER BY stat_time ASC LIMIT ${limit}" }','Monitor SSL Pinning over the selected time frame.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('proxy-ssl-intercept-pinning-statistics', 'proxy_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT ( CASE WHEN pinning_status = ''0'' THEN ''not_pinning_num'' WHEN pinning_status = ''1'' THEN ''pinning_num'' WHEN pinning_status = ''2'' THEN ''maybe_pinning_num'' ELSE concat( pinning_status ) END ) AS type, SUM( hit_count ) AS hits FROM proxy_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND action = 2 AND vsys_id IN ( ${vsys_id} ) AND ( ${filter} ) GROUP BY pinning_status ORDER BY pinning_status" }','The statistics of Proxy SSL Intercept pinning.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('proxy-policy-rule-hits-by-action', 'proxy_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) AS stat_time, (CASE WHEN action = 2 THEN ''Intercept'' WHEN action = 3 THEN ''No Intercept'' WHEN action = 48 THEN ''Manipulation'' ELSE concat(action) END ) AS action, RATE(hit_count, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS avg_hit_count_per_sec, SUM(hit_count) AS total_hit_count FROM proxy_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN (${vsys_id}) AND (${filter}) GROUP BY FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')), action ORDER BY stat_time ASC LIMIT ${limit}" }','The proxy Intercept policy hit the count of action over the selected time frame.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('proxy-manipulation-policy-rule-hits-by-action', 'proxy_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) AS stat_time, sub_action AS action, RATE(hit_count, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS avg_hit_count_per_sec, SUM(hit_count) AS total_hit_count FROM proxy_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN (${vsys_id}) AND action = 48 AND (${filter}) GROUP BY FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')), sub_action ORDER BY stat_time ASC LIMIT ${limit}" }','The proxy manipulation policy hit the count of action over the selected time frame.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('top-proxy-policy-rule', 'proxy_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT rule_id, SUM( hit_count ) AS hit_count, SUM( in_bytes + out_bytes ) AS bytes FROM proxy_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN ( ${vsys_id} ) AND ( ${filter} ) GROUP BY rule_id ORDER BY ${metric} DESC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('proxy-policy-rule-statistics', 'proxy_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT rule_id, SUM( hit_count ) AS hits, SUM( in_bytes + out_bytes ) AS bytes FROM proxy_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND rule_id IN ( ${rule_id} ) AND vsys_id IN ( ${vsys_id} ) AND ( ${filter} ) GROUP BY rule_id LIMIT ${limit}" }','The statistics of specific rules.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('proxy-policy-rule-hits-trend', 'proxy_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL( UNIX_TIMESTAMP( __time ), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'' )) AS stat_time, SUM( hit_count ) AS hits FROM proxy_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND rule_id IN ( ${rule_id} ) AND vsys_id IN ( ${vsys_id} ) AND ( ${filter} ) GROUP BY FROM_UNIXTIME(TIME_FLOOR_WITH_FILL( UNIX_TIMESTAMP( __time ), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'' )) LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('proxy-policy-rule-hits-first-and-last-hit', 'proxy_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT rule_id, DATE_FORMAT( MIN( __time ), ''%Y-%m-%d %H:%i:%s'' ) AS first_hit, DATE_FORMAT( MAX( __time ), ''%Y-%m-%d %H:%i:%s'' ) AS last_hit FROM proxy_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND rule_id IN ( ${rule_id} ) AND vsys_id IN ( ${vsys_id} ) AND ( ${filter} ) GROUP BY rule_id" }','The time of the first and last hit for policy rules.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('proxy-policy-rule-hits-current-throughput', 'proxy_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT SUM( in_bytes )* 8 / 5 AS in_bps, SUM( out_bytes )* 8 / 5 AS out_bps, SUM( in_bytes + out_bytes )* 8 / 5 AS total_bps FROM proxy_rule_hits WHERE __time >= FROM_UNIXTIME( UNIX_TIMESTAMP( now())- 15 ) AND __time < FROM_UNIXTIME( UNIX_TIMESTAMP( now())- 10 ) AND vsys_id IN ( ${vsys_id} ) AND rule_id IN ( ${rule_id} ) AND ( ${filter} )" }','To calculate the current policy hit throughput, the metrics for each appliance are averaged over a 15-second interval. Additionally, the data ingestion latency is also set at 15 seconds.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('statistics-rule-hits-first-and-last-hit', 'statistics_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT rule_id, DATE_FORMAT( min( __time ), ''%Y-%m-%d %H:%i:%s'' ) AS first_hit, DATE_FORMAT( max( __time ), ''%Y-%m-%d %H:%i:%s'' ) AS last_hit FROM statistics_rule_hits WHERE __time >= ''${start_time}'' AND __time <''${end_time}'' AND rule_id IN ( ${rule_id} ) AND vsys_id IN ( ${vsys_id} ) AND ( ${filter} ) GROUP BY rule_id" }','The time of the first and last hit for statistics policy rules.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('statistics-rule-statistics', 'statistics_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT rule_id, sum( hit_count ) AS hits, sum( in_bytes + out_bytes ) AS bytes FROM statistics_rule_hits WHERE __time >= ''${start_time}'' AND __time <''${end_time}'' AND rule_id IN ( ${rule_id} ) AND vsys_id IN ( ${vsys_id} ) AND ( ${filter} ) GROUP BY rule_id" }','The statistics of specific rules.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('statistics-rule-hits-trend', 'statistics_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) AS stat_time, RATE(in_bytes, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) * 8 AS avg_in_bits_per_sec, RATE(out_bytes, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) * 8 AS avg_out_bits_per_sec, RATE(in_bytes + out_bytes, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) * 8 AS avg_bits_per_sec, SUM(in_bytes) AS total_in_bytes, SUM(out_bytes) AS total_out_bytes, SUM( in_bytes + out_bytes ) AS total_bytes, RATE(hit_count, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS avg_hit_count_per_sec, SUM(hit_count) AS total_hit_count FROM statistics_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN (${vsys_id}) AND rule_id IN (${rule_id}) AND (${filter}) GROUP BY FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) ORDER BY stat_time ASC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('dos-protection-rule-hits-first-and-last-hit', 'dos_protection_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT rule_id, DATE_FORMAT( min( __time ), ''%Y-%m-%d %H:%i:%s'' ) AS first_hit, DATE_FORMAT( max( __time ), ''%Y-%m-%d %H:%i:%s'' ) AS last_hit FROM dos_protection_rule_hits WHERE __time >= ''${start_time}'' AND __time <''${end_time}'' AND rule_id IN ( ${rule_id} ) AND vsys_id IN ( ${vsys_id} ) AND ( ${filter} ) GROUP BY rule_id" }','The time of the first and last hit for the dos protection policy rules.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('dos-protection-rule-statistics', 'dos_protection_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT rule_id, sum( hit_count ) AS hits, sum( in_bytes + out_bytes ) AS bytes FROM dos_protection_rule_hits WHERE __time >= ''${start_time}'' AND __time <''${end_time}'' AND rule_id IN ( ${rule_id} ) AND vsys_id IN ( ${vsys_id} ) AND ( ${filter} ) GROUP BY rule_id" }','The statistics of specific rules.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('dos-protection-rule-hits-trend', 'dos_protection_rule_hits', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) AS stat_time, RATE(in_bytes, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) * 8 AS avg_in_bits_per_sec, RATE(out_bytes, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) * 8 AS avg_out_bits_per_sec, RATE(in_bytes + out_bytes, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) * 8 AS avg_bits_per_sec, SUM(in_bytes) AS total_in_bytes, SUM(out_bytes) AS total_out_bytes, SUM( in_bytes + out_bytes ) AS total_bytes, RATE(hit_count, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS avg_hit_count_per_sec, SUM(hit_count) AS total_hit_count FROM dos_protection_rule_hits WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN (${vsys_id}) AND rule_id IN (${rule_id}) AND (${filter}) GROUP BY FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) ORDER BY stat_time ASC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('statistics-rule-line-chart-template', 'statistics_rule', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) AS stat_time [[,RATE(${metric_in_bytes}, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1)*8 AS avg_in_bits_per_sec]] [[,RATE(${metric_out_bytes}, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1)*8 AS avg_out_bits_per_sec]] [[,RATE(${metric_bytes}, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1)*8 AS avg_bits_per_sec]] [[,RATE(${metric_in_pkts}, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS avg_in_pkts_per_sec]] [[,RATE(${metric_out_pkts}, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS avg_out_pkts_per_sec]] [[,RATE(${metric_pkts}, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS avg_pkts_per_sec]] [[,RATE(${metric_new_c2s_flows}, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS avg_new_c2s_flows_per_sec]] [[,RATE(${metric_new_s2c_flows}, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS avg_new_s2c_flows_per_sec]] [[,RATE(${metric_new_in_sessions}, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS avg_new_in_sessions_per_sec]] [[,RATE(${metric_new_out_sessions}, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS avg_new_out_sessions_per_sec]] [[,RATE(${metric_sessions}, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS avg_sessions_per_sec]] [[,RATE(${metric_new_unestablished_sessions}, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS avg_new_unestablished_sessions_per_sec]] [[,RATE(${metric_syn_pkts}, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) AS avg_syn_pkts_per_sec]] [[,APPROX_COUNT_DISTINCT_HLLD(${metric_session_identifier_sketch}) AS active_sessions]] [[,APPROX_COUNT_DISTINCT_HLLD(${metric_client_ip_sketch}) AS unique_client_ips]] [[,APPROX_COUNT_DISTINCT_HLLD(${metric_server_ip_sketch}) AS unique_server_ips]] [[,QUANTILE_HDR(${metric_in_latency_ms_sketch},0.5) AS median_tcp_in_latency_ms]] [[,QUANTILE_HDR(${metric_in_latency_ms_sketch},0.95) AS p95th_tcp_in_latency_ms]] [[,QUANTILE_HDR(${metric_in_latency_ms_sketch},0.99) AS p99th_tcp_in_latency_ms]] [[,QUANTILE_HDR(${metric_out_latency_ms_sketch},0.5) AS median_tcp_out_latency_ms]] [[,QUANTILE_HDR(${metric_out_latency_ms_sketch},0.95) AS p95th_tcp_out_latency_ms]] [[,QUANTILE_HDR(${metric_out_latency_ms_sketch},0.99) AS p99th_tcp_out_latency_ms]] [[,QUANTILE_HDR(${metric_latency_ms_sketch},0.5) AS median_tcp_latency_ms]] [[,QUANTILE_HDR(${metric_latency_ms_sketch},0.95) AS p95th_tcp_latency_ms]] [[,QUANTILE_HDR(${metric_latency_ms_sketch},0.99) AS p99th_tcp_latency_ms]] [[,QUANTILE_HDR(${metric_in_pkt_length_sketch},0.5) AS median_in_pkt_length]] [[,QUANTILE_HDR(${metric_in_pkt_length_sketch},0.95) AS p95th_in_pkt_length]] [[,QUANTILE_HDR(${metric_in_pkt_length_sketch},0.99) AS p99th_in_pkt_length]] [[,QUANTILE_HDR(${metric_out_pkt_length_sketch},0.5) AS median_out_pkt_length]] [[,QUANTILE_HDR(${metric_out_pkt_length_sketch},0.95) AS p95th_out_pkt_length]] [[,QUANTILE_HDR(${metric_out_pkt_length_sketch},0.99) AS p99th_out_pkt_length]] [[,QUANTILE_HDR(${metric_pkt_length_sketch},0.5) AS median_pkt_length]] [[,QUANTILE_HDR(${metric_pkt_length_sketch},0.95) AS p95th_pkt_length]] [[,QUANTILE_HDR(${metric_pkt_length_sketch},0.99) AS p99th_pkt_length]] FROM statistics_rule WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN ( ${vsys_id} ) AND rule_id = ${rule_id} AND template_id = ${template_id} AND chart_id = ${chart_id} AND version = ${version} AND ( ${filter} ) GROUP BY FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(UNIX_TIMESTAMP(__time), CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) ORDER BY stat_time ASC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('statistics-rule-histogram-chart-template', 'statistics_rule', 'qgw', 'sql', '{ "statement": "SELECT [[PERCENTILES_HDR(${metric_in_latency_ms_sketch}) AS tcp_in_latency, QUANTILE_HDR(${metric_in_latency_ms_sketch}, 0.5) as tcp_in_latency_quantiles]] [[,PERCENTILES_HDR(${metric_out_latency_ms_sketch}) AS tcp_out_latency ,QUANTILE_HDR(${metric_out_latency_ms_sketch}, 0.5) as tcp_out_latency_quantiles]] [[,PERCENTILES_HDR(${metric_latency_ms_sketch}) AS tcp_latency ,QUANTILE_HDR(${metric_latency_ms_sketch}, 0.5) as tcp_latency_quantiles]] FROM statistics_rule WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN ( ${vsys_id} ) AND rule_id = ${rule_id} AND template_id = ${template_id} AND chart_id = ${chart_id} AND version = ${version} AND ( ${filter} ) LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('statistics-rule-table-or-bar-chart-template', 'statistics_rule', 'qgw', 'sql', '{ "statement": "SELECT [[${dimension_device_group} AS device_group]] [[,${dimension_client_ip} AS client_ip]] [[,${dimension_server_ip} AS server_ip]] [[,${dimension_client_asn} AS client_asn]] [[,${dimension_server_asn} AS server_asn]] [[,${dimension_client_country} AS client_country]] [[,${dimension_server_country} AS server_country]] [[,${dimension_server_fqdn} AS server_fqdn]] [[,${dimension_server_domain} AS server_domain]] [[,${dimension_application} AS application]] [[,${dimension_fqdn_category} AS fqdn_category]] [[,${dimension_client_ip_object} AS client_ip_object]] [[,${dimension_server_ip_object} AS server_ip_object]] [[,${dimension_c2s_ttl} AS c2s_ttl]] [[,${dimension_s2c_ttl} AS s2c_ttl]] [[,${dimension_c2s_link_id} AS c2s_link_id]] [[,${dimension_s2c_link_id} AS s2c_link_id]] [[,${dimension_client_port} AS client_port]] [[,${dimension_server_port} AS server_port]] [[,sum(${metric_in_bytes}) AS in_bytes]] [[,sum(${metric_out_bytes}) AS out_bytes]] [[,sum(${metric_bytes}) AS bytes]] [[,sum(${metric_in_pkts}) AS in_pkts]] [[,sum(${metric_out_pkts}) AS out_pkts]] [[,sum(${metric_pkts}) AS pkts]] [[,sum(${metric_new_c2s_flows}) AS new_c2s_flows]] [[,sum(${metric_new_s2c_flows}) AS new_s2c_flows]] [[,sum(${metric_new_in_sessions}) AS new_in_sessions]] [[,sum(${metric_new_out_sessions}) AS new_out_sessions]] [[,sum(${metric_sessions}) AS sessions]] [[,sum(${metric_new_unestablished_sessions}) AS new_unestablished_sessions]] [[,sum(${metric_syn_pkts}) AS syn_pkts]] [[,APPROX_COUNT_DISTINCT_HLLD(${metric_session_identifier_sketch}) AS active_sessions]] [[,APPROX_COUNT_DISTINCT_HLLD(${metric_client_ip_sketch}) AS unique_client_ips]] [[,APPROX_COUNT_DISTINCT_HLLD(${metric_server_ip_sketch}) AS unique_server_ips]] FROM statistics_rule WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id in (${vsys_id}) AND rule_id = ${rule_id} AND template_id = ${template_id} AND chart_id = ${chart_id} AND version = ${version} AND ( ${filter} ) GROUP BY [[${dimension_device_group}]] [[,${dimension_client_ip}]] [[,${dimension_server_ip}]] [[,${dimension_client_asn}]] [[,${dimension_server_asn}]] [[,${dimension_client_country}]] [[,${dimension_server_country}]] [[,${dimension_server_fqdn}]] [[,${dimension_server_domain}]] [[,${dimension_application}]] [[,${dimension_fqdn_category}]] [[,${dimension_client_ip_object}]] [[,${dimension_server_ip_object}]] [[,${dimension_c2s_ttl}]] [[,${dimension_s2c_ttl}]] [[,${dimension_c2s_link_id}]] [[,${dimension_s2c_link_id}]] [[,${dimension_client_port}]] [[,${dimension_server_port}]] ORDER BY ${order_by} LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('top-client-ip', 'top_client_ips', 'qgw', 'sql', '{ "statement": "SELECT client_ip AS client_ip, SUM( sessions) AS sessions, SUM( out_bytes ) AS out_bytes, SUM( in_bytes ) AS in_bytes, SUM( bytes ) AS bytes, SUM( out_pkts ) AS out_packets, SUM( in_pkts ) AS in_packets, SUM( pkts ) AS packets FROM top_client_ips WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN( ${vsys_id} ) AND rank_by=''${metric}'' AND ( ${filter} ) GROUP BY client_ip ORDER BY ${metric} DESC LIMIT ${limit}" }','Aggregate traffic sessions, bytes, and packets based on the client''s IP address. The ${metric} variable includes three options: sessions, bytes, and packets.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('top-server-ip', 'top_server_ips', 'qgw', 'sql', '{ "statement": "SELECT server_ip AS server_ip, SUM( sessions) AS sessions, SUM( out_bytes ) AS out_bytes, SUM( in_bytes ) AS in_bytes, SUM( bytes ) AS bytes, SUM( out_pkts ) AS out_packets, SUM( in_pkts ) AS in_packets, SUM( pkts ) AS packets FROM top_server_ips WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN( ${vsys_id} ) AND rank_by=''${metric}'' AND ( ${filter} ) GROUP BY server_ip ORDER BY ${metric} DESC LIMIT ${limit}" }','Aggregate traffic sessions, bytes, and packets based on the server IP address. The ${metric} variable includes three options: sessions, bytes, and packets.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('top-internal-ip', 'top_internal_ips', 'qgw', 'sql', '{ "statement": "SELECT internal_ip AS internal_ip, SUM( sessions) AS sessions, SUM( out_bytes ) AS out_bytes, SUM( in_bytes ) AS in_bytes, SUM( bytes ) AS bytes, SUM( out_pkts ) AS out_packets, SUM( in_pkts ) AS in_packets, SUM( pkts ) AS packets FROM top_internal_ips WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN( ${vsys_id} ) AND rank_by=''${metric}'' AND ( ${filter} ) GROUP BY internal_ip ORDER BY ${metric} DESC LIMIT ${limit}" }','Aggregate traffic sessions, bytes, and packets based on the internal IP address. The ${metric} variable includes three options: sessions, bytes, and packets.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('top-external-ip', 'top_external_ips', 'qgw', 'sql', '{ "statement": "SELECT external_ip AS external_ip, SUM( sessions) AS sessions, SUM( out_bytes ) AS out_bytes, SUM( in_bytes ) AS in_bytes, SUM( bytes ) AS bytes, SUM( out_pkts ) AS out_packets, SUM( in_pkts ) AS in_packets, SUM( pkts ) AS packets FROM top_external_ips WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN( ${vsys_id} ) AND rank_by=''${metric}'' AND ( ${filter} ) GROUP BY external_ip ORDER BY ${metric} DESC LIMIT ${limit}" }','Aggregate traffic sessions, bytes, and packets based on the external IP address. The ${metric} variable includes three options: sessions, bytes, and packets.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('top-server-domain', 'top_server_domains', 'qgw', 'sql', '{ "statement": "SELECT server_domain, SUM( sessions) AS sessions, SUM( out_bytes ) AS out_bytes, SUM( in_bytes ) AS in_bytes, SUM( bytes ) AS bytes, SUM( out_pkts ) AS out_packets, SUM( in_pkts ) AS in_packets, SUM( pkts ) AS packets FROM top_server_domains WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN( ${vsys_id} ) AND rank_by=''${metric}'' AND ( ${filter} ) GROUP BY server_domain ORDER BY ${metric} DESC LIMIT ${limit}" }','Aggregate traffic sessions, bytes, and packets based on the server domains. The ${metric} variable includes three options: sessions, bytes, and packets.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('top-server-fqdn', 'top_server_fqdns', 'qgw', 'sql', '{ "statement": "SELECT server_fqdn, SUM( sessions) AS sessions, SUM( out_bytes ) AS out_bytes, SUM( in_bytes ) AS in_bytes, SUM( bytes ) AS bytes, SUM( out_pkts ) AS out_packets, SUM( in_pkts ) AS in_packets, SUM( pkts ) AS packets FROM top_server_fqdns WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN( ${vsys_id} ) AND rank_by=''${metric}'' AND ( ${filter} ) GROUP BY server_fqdn ORDER BY ${metric} DESC LIMIT ${limit}" }','Aggregate traffic sessions, bytes, and packets based on the server FQDNs. The ${metric} variable includes three options: sessions, bytes, and packets.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('top-client-country', 'top_client_countries', 'qgw', 'sql', '{ "statement": "SELECT client_country AS client_country, SUM( sessions) AS sessions, SUM( out_bytes ) AS out_bytes, SUM( in_bytes ) AS in_bytes, SUM( bytes ) AS bytes, SUM( out_pkts ) AS out_packets, SUM( in_pkts ) AS in_packets, SUM( pkts ) AS packets FROM top_client_countries WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN( ${vsys_id} ) AND rank_by=''${metric}'' AND ( ${filter} ) GROUP BY client_country ORDER BY ${metric} DESC LIMIT ${limit}" }','Aggregate traffic sessions, bytes, and packets based on the client''s country or region. The ${metric} variable includes three options: sessions, bytes, and packets.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('top-server-country', 'top_server_countries', 'qgw', 'sql', '{ "statement": "SELECT server_country AS server_country, SUM( sessions) AS sessions, SUM( out_bytes ) AS out_bytes, SUM( in_bytes ) AS in_bytes, SUM( bytes ) AS bytes, SUM( out_pkts ) AS out_packets, SUM( in_pkts ) AS in_packets, SUM( pkts ) AS packets FROM top_server_countries WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN( ${vsys_id} ) AND rank_by=''${metric}'' AND ( ${filter} ) GROUP BY server_country ORDER BY ${metric} DESC LIMIT ${limit}" }','Aggregate traffic sessions, bytes, and packets based on the server''s country or region. The ${metric} variable includes three options: sessions, bytes, and packets.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('top-application', 'application_protocol_stat', 'qgw', 'sql', '{ "statement": "SELECT app_name, SUM( sessions) AS sessions, SUM( in_bytes ) AS in_bytes, SUM( out_bytes ) AS out_bytes, SUM( in_bytes + out_bytes ) AS bytes, SUM( in_pkts ) AS in_packets, SUM( out_pkts ) AS out_packets, SUM( in_pkts + out_pkts ) AS packets FROM application_protocol_stat WHERE __time >= ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN( ${vsys_id} ) AND app_name IS NOT NULL AND ( ${filter} ) GROUP BY app_name ORDER BY ${metric} DESC LIMIT ${limit}" }','Aggregate traffic sessions, bytes, and packets based on the applications. The ${metric} variable includes three options: sessions, bytes, and packets.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('session-record-list', 'session_record', 'qgw', 'sql', '{ "statement": "SELECT ${columns} FROM session_record WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id IN(${vsys_id}) AND ( ${filter}) ORDER BY recv_time DESC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('session-record-count', 'session_record', 'qgw', 'sql', '{ "statement": "SELECT count(1) as count FROM session_record WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id IN(${vsys_id}) AND ( ${filter})" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('session-record-timeline', 'session_record', 'qgw', 'sql', '{ "statement": "select FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(recv_time, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) AS stat_time, decoded_as as type, COUNT(1) as sessions, SUM(sent_bytes + received_bytes) as bytes, SUM(sent_pkts + received_pkts) as packets FROM session_record WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id IN(${vsys_id}) AND ( ${filter}) GROUP BY stat_time, decoded_as" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('transaction-record-list', 'transaction_record', 'qgw', 'sql', '{ "statement": "SELECT ${columns} FROM transaction_record WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id IN(${vsys_id}) AND ( ${filter}) ORDER BY recv_time DESC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('transaction-record-count', 'transaction_record', 'qgw', 'sql', '{ "statement": "SELECT count(1) as count FROM transaction_record WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id IN(${vsys_id}) AND ( ${filter})" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('security-event-list', 'security_event', 'qgw', 'sql', '{ "statement": "SELECT ${columns} FROM security_event WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id IN(${vsys_id}) AND ( ${filter}) ORDER BY recv_time DESC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('security-event-count', 'security_event', 'qgw', 'sql', '{ "statement": "SELECT count(1) as count FROM security_event WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id IN(${vsys_id}) AND ( ${filter})" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('security-event-timeline', 'security_event', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(recv_time, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) AS stat_time, security_action as type, COUNT(1) as sessions, SUM(sent_bytes + received_bytes) as bytes, SUM(sent_pkts + received_pkts) as packets FROM security_event WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id IN(${vsys_id}) AND notEmpty(security_action) AND ( ${filter}) group by stat_time, security_action order by stat_time asc" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('monitor-event-list', 'monitor_event', 'qgw', 'sql', '{ "statement": "SELECT ${columns} FROM monitor_event WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id IN(${vsys_id}) AND (${filter}) ORDER BY recv_time DESC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('monitor-event-count', 'monitor_event', 'qgw', 'sql', '{ "statement": "SELECT count(1) as count FROM monitor_event WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id IN(${vsys_id}) AND (${filter})" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('monitor-event-timeline', 'monitor_event', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(recv_time,CHART_GRANULARITY(''${start_time}'', ''${end_time}''),''zero'')) AS stat_time, COUNT(1) as sessions FROM monitor_event WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id IN(${vsys_id}) AND (${filter}) GROUP BY stat_time" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('proxy-event-intercept-list', 'session_record', 'qgw', 'sql', '{ "statement": "SELECT ${columns} FROM session_record WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id IN(${vsys_id}) AND notEmpty(proxy_action) AND ( ${filter}) ORDER BY recv_time DESC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('proxy-event-intercept-count', 'session_record', 'qgw', 'sql', '{ "statement": "SELECT count(1) as count FROM session_record WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id IN(${vsys_id}) AND notEmpty(proxy_action) AND ( ${filter})" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('proxy-event-intercept-timeline', 'session_record', 'qgw', 'sql', '{ "statement": "select FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(recv_time, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) AS stat_time, decoded_as as type, COUNT(1) as sessions, SUM(sent_bytes + received_bytes) as bytes, SUM(sent_pkts + received_pkts) as packets FROM session_record WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id IN(${vsys_id}) AND notEmpty(proxy_action) AND ( ${filter}) GROUP BY stat_time, decoded_as" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('proxy-event-manipulation-list', 'proxy_event', 'qgw', 'sql', '{ "statement": "SELECT ${columns} FROM proxy_event WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id in (${vsys_id}) AND ( ${filter} ) ORDER BY recv_time DESC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('proxy-event-manipulation-count', 'proxy_event', 'qgw', 'sql', '{ "statement": "SELECT COUNT(1) as count FROM proxy_event WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id in (${vsys_id}) AND ( ${filter} )" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('proxy-event-manipulation-timeline', 'proxy_event', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(recv_time, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) AS stat_time, proxy_action as type, COUNT(1) as events FROM proxy_event WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id IN (${vsys_id}) AND notEmpty(proxy_action) AND ( ${filter} ) GROUP BY stat_time, proxy_action ORDER BY stat_time asc" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('voip-record-list', 'voip_record', 'qgw', 'sql', '{ "statement": "SELECT ${columns} FROM voip_record WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id in(${vsys_id}) AND ( ${filter}) ORDER BY recv_time DESC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('voip-record-count', 'voip_record', 'qgw', 'sql', '{ "statement": "SELECT count(1) as count FROM voip_record WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id in(${vsys_id}) AND ( ${filter})" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('voip-record-timeline', 'voip_record', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(recv_time, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) AS stat_time, decoded_as as type, COUNT(1) as count FROM voip_record WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id IN(${vsys_id}) AND ( ${filter}) GROUP BY stat_time,decoded_as ORDER BY stat_time asc" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('dos-threat-map-top-source-countries', 'dos_event', 'qgw', 'sql', '{ "statement": "SELECT arrayJoin(splitByString('','',source_country_list)) AS source_country, count(*) AS count FROM dos_event WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND notEmpty(source_country_list) AND vsys_id IN ( ${vsys_id} ) AND ( ${filter} ) GROUP BY arrayJoin(splitByString('','',source_country_list)) ORDER BY count DESC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('dos-threat-map-top-destination-countries', 'dos_event', 'qgw', 'sql', '{ "statement": "SELECT destination_country, COUNT(*) AS count FROM dos_event WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id IN (${vsys_id}) AND ( ${filter} ) GROUP BY destination_country ORDER BY count DESC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('dos-threat-map-top-victims', 'dos_event', 'qgw', 'sql', '{ "statement": "SELECT destination_ip, count(*) AS count FROM dos_event WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id IN (${vsys_id}) AND ( ${filter} ) GROUP BY destination_ip ORDER BY count DESC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('dos-threat-map-attack-type', 'dos_event', 'qgw', 'sql', '{ "statement": "SELECT attack_type, count(*) AS count FROM dos_event WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id IN (${vsys_id}) AND ( ${filter} ) GROUP BY attack_type ORDER BY attack_type LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('dos-threat-map-severity', 'dos_event', 'qgw', 'sql', '{ "statement": "SELECT severity, count(*) AS count FROM dos_event WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id IN (${vsys_id}) AND ( ${filter} ) GROUP BY severity ORDER BY severity LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('dos-threat-map-destination-ip-distribution', 'dos_event', 'qgw', 'sql', '{ "statement": "SELECT destination_ip, any(destination_country) AS destination_country, groupUniqArray(arrayJoin(splitByString('','', source_country_list))) AS source_coutries, MAX(bit_rate) AS max_bit_rate, MAX(packet_rate) AS max_packet_rate, MAX(session_rate) AS max_session_rate, FROM_UNIXTIME(MIN(start_time)) AS first_active_time, FROM_UNIXTIME(MAX(end_time)) AS last_active_time, MAX_DURATION(end_time, 600) AS max_duration, groupUniqArray(attack_type) AS attack_type, count(*) AS count FROM dos_event WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id IN (${vsys_id}) AND ( ${filter} ) GROUP BY destination_ip ORDER BY count DESC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('dos-threat-map-attack-connection', 'dos_event', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(recv_time) AS stat_time, destination_country, source_country_list, attack_type, severity, bit_rate, bytes, packet_rate, packets, session_rate, sessions FROM dos_event WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id IN (${vsys_id}) AND (${filter}) ORDER BY recv_time ASC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('dos-threat-map-attack-volume-summary', 'dos_event', 'qgw', 'sql', '{ "statement": "SELECT RATE(bytes, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) * 8 as avg_bits_per_sec FROM dos_event WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id IN (${vsys_id}) AND (${filter})" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('dos-threat-map-attack-volume-trend', 'dos_event', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(recv_time, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) AS stat_time, RATE(bytes, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), 1) * 8 as avg_bits_per_sec FROM dos_event WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id IN (${vsys_id}) AND ( ${filter} ) GROUP BY stat_time ORDER BY stat_time ASC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('dos-event-timeline', 'dos_event', 'qgw', 'sql', '{ "statement": "SELECT FROM_UNIXTIME(TIME_FLOOR_WITH_FILL(recv_time, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'')) AS stat_time, attack_type AS type, count(*) AS count FROM dos_event WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id IN (${vsys_id}) AND ( ${filter} ) GROUP BY stat_time, attack_type ORDER BY stat_time ASC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('dos-event-count', 'dos_event', 'qgw', 'sql', '{ "statement": "SELECT count(1) as count FROM dos_event WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id IN (${vsys_id}) AND ( ${filter} )" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('dos-event-list', 'dos_event', 'qgw', 'sql', '{ "statement": "SELECT ${columns} FROM dos_event WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id IN (${vsys_id}) AND ( ${filter} ) ORDER BY recv_time DESC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('datapath-telemetry-record-count', 'datapath_telemetry_record', 'qgw', 'sql', '{ "statement": "SELECT count(1) as count FROM datapath_telemetry_record WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id in(${vsys_id}) AND ( ${filter})" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('datapath-telemetry-record-list', 'datapath_telemetry_record', 'qgw', 'sql', '{ "statement": "SELECT ${columns} FROM datapath_telemetry_record WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND vsys_id IN(${vsys_id}) AND (${filter}) ORDER BY timestamp_us ASC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('datapath-telemetry-packet-combine', 'datapath_telemetry_record', 'qgw', 'dsl', '{"id":"${job_id}","name":"datapath_telemetry_packet_combine","data_source":"datapath_telemetry_record","filter":"job_id=''${job_id}'' AND vsys_id in (${vsys_id}) AND (${filter})"}',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('field-discovery', 'statistics', 'qgw', 'dsl', '{ "name": "field_discovery", "data_source": "${source}", "filter": "vsys_id in (${vsys_id}) AND (${filter})", "custom.field_discovery.metric": "${metric}", "custom.field_discovery.metric.fn": "${fn}", "custom.field_discovery.fields": ["${field_list}"] }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('field-statistics-top-values', 'statistics', 'qgw', 'sql', '{ "statement":"SELECT ${column_name}, count(*) as cnt FROM ${source} where recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND ${filter} GROUP BY ${column_name} ORDER BY cnt DESC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('field-statistics-rare-values', 'statistics', 'qgw', 'sql', '{ "statement":"SELECT ${column_name}, count(*) as cnt FROM ${source} where recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND ${filter} GROUP BY ${column_name} ORDER BY cnt ASC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('field-statistics-avg-value-over-time', 'statistics', 'qgw', 'sql', '{ "statement":"SELECT TIME_FLOOR_WITH_FILL(${unix_timestamp_column}, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'') AS stat_time, avg(${column_name_long}) FROM ${source} WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND ${filter} GROUP BY TIME_FLOOR_WITH_FILL(${unix_timestamp_column}, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'') ORDER BY stat_time ASC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('field-statistics-max-value-over-time', 'statistics', 'qgw', 'sql', '{ "statement":"SELECT TIME_FLOOR_WITH_FILL(${unix_timestamp_column}, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'') AS stat_time, max(${column_name_long}) FROM ${source} WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND ${filter} GROUP BY TIME_FLOOR_WITH_FILL(${unix_timestamp_column}, CHART_GRANULARITY(''${start_time}'', ''${end_time}''), ''zero'') ORDER BY stat_time ASC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('field-statistics-min-value-over-time', 'statistics', 'qgw', 'sql', '{ "statement":"SELECT TIME_FLOOR_WITH_FILL(${unix_timestamp_column},CHART_GRANULARITY(''${start_time}'', ''${end_time}''),''zero'') AS stat_time, min(${column_name_long}) FROM ${source} WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND ${filter} GROUP BY TIME_FLOOR_WITH_FILL(${unix_timestamp_column},CHART_GRANULARITY(''${start_time}'', ''${end_time}''),''zero'') ORDER BY stat_time ASC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('field-statistics-median-value-over-time', 'statistics', 'qgw', 'sql', '{ "statement":"SELECT TIME_FLOOR_WITH_FILL(${unix_timestamp_column},CHART_GRANULARITY(''${start_time}'', ''${end_time}''),''zero'') AS stat_time, MEDIAN(${column_name_long}) FROM ${source} WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND ${filter} GROUP BY TIME_FLOOR_WITH_FILL(${unix_timestamp_column},CHART_GRANULARITY(''${start_time}'', ''${end_time}''),''zero'') ORDER BY stat_time ASC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('field-statistics-p95-value-over-time', 'statistics', 'qgw', 'sql', '{ "statement":"SELECT TIME_FLOOR_WITH_FILL(${unix_timestamp_column},CHART_GRANULARITY(''${start_time}'', ''${end_time}''),''zero'') AS stat_time, QUANTILE(${column_name_long},0.95) FROM ${source} WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND ${filter} GROUP BY TIME_FLOOR_WITH_FILL(${unix_timestamp_column},CHART_GRANULARITY(''${start_time}'', ''${end_time}''),''zero'') ORDER BY stat_time ASC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('field-statistics-p99-value-over-time', 'statistics', 'qgw', 'sql', '{ "statement":"SELECT TIME_FLOOR_WITH_FILL(${unix_timestamp_column},CHART_GRANULARITY(''${start_time}'', ''${end_time}''),''zero'') AS stat_time, QUANTILE(${column_name_long},0.99) FROM ${source} WHERE recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND ${filter} GROUP BY TIME_FLOOR_WITH_FILL(${unix_timestamp_column},CHART_GRANULARITY(''${start_time}'', ''${end_time}''),''zero'') ORDER BY stat_time ASC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('field-statistics-top-frequent-elements-in-array', 'statistics', 'qgw', 'sql', '{ "statement":"SELECT item as ${column_name_array}, sum(cnt) as cnt FROM( SELECT arrayJoin(items) as item, cnt FROM ( SELECT IF(empty(${column_name_array}), arrayPushBack(${column_name_array}, NULL), ${column_name_array}) as items, count(*) as cnt FROM ${source} as source where recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND ${filter} GROUP BY ${column_name_array})) GROUP BY item ORDER BY cnt DESC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('field-statistics-top-frequent-elements-in-string-of-array', 'statistics', 'qgw', 'sql', '{ "statement":"SELECT item as ${column_name_string}, sum(cnt) as cnt FROM( SELECT arrayJoin(items) as item, cnt FROM ( SELECT splitByString(''${separator}'',${column_name_string}) as items, count(*) as cnt FROM ${source} as source where recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND ${filter} AND notEmpty(${column_name_string}) GROUP BY ${column_name_string})) GROUP BY item ORDER BY cnt DESC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('field-statistics-top-frequent-elements-in-long-of-bit', 'statistics', 'qgw', 'sql', '{ "statement":"SELECT item as ${column_name_long}, sum(cnt) as cnt FROM( SELECT arrayJoin(items) as item, cnt FROM ( SELECT bitmaskToArray(${column_name_long}) as items, count(*) as cnt FROM ${source} as source where recv_time >= UNIX_TIMESTAMP(''${start_time}'') AND recv_time < UNIX_TIMESTAMP(''${end_time}'') AND ${filter} GROUP BY ${column_name_long})) GROUP BY item ORDER BY cnt DESC LIMIT ${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('ip-learning-fqdn-relate-ip', 'ip_learning', 'qgw', 'dsl', '{ "name": "ip-learning-fqdn-relate-ip", "data_source":"ip_learnging_view", "filter": "vsys_id in(${vsys_id}) AND (${filter})", "intervals": ["${start_time}/${end_time}"], "limit": "${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('ip-learning-active-ip', 'ip_learning', 'qgw', 'dsl', '{ "name": "ip-learning-active-ip", "data_source":"active_ip_view", "filter": "vsys_id in(${vsys_id}) AND (${filter})", "intervals": ["${start_time}/${end_time}"], "order_by": "${order_by}", "limit": "${limit}" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('top-frequent-elements-in-long-of-bit', 'benchmark', 'qgw', 'sql', '{ "statement": "select item,sum(count) as count from( select arrayJoin(items) as item, count from ( select bitmaskToArray(flags) as items,count(*) as count from session_record as sr where recv_time >= UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time = ''${start_time}'' AND __time < ''${end_time}'' AND vsys_id IN ( 1 ) GROUP BY TIME_FLOOR_WITH_FILL ( UNIX_TIMESTAMP( __time ), CHART_GRANULARITY(''${start_time}'', ''${end_time}'')) ORDER BY stat_time ASC", "execution_mode": "oneshot" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('top-100-slowest-domains', 'benchmark', 'qgw', 'sql', '{ "statement": "select server_domain as domain, round(avg(tcp_rtt_ms),0) avg_rtt_latency_ms from session_record where recv_time >= UNIX_TIMESTAMP(''${start_time}'') and recv_time = UNIX_TIMESTAMP(''${start_time}'') and recv_time 1) union all select ''Proxy Events'' as type, count(*) as num from (select log_id,count(*) as num from proxy_event where recv_time >= UNIX_TIMESTAMP(''${start_time}'') and recv_time 1)", "execution_mode": "oneshot" }',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('traffic-spectrum-summary', 'traffic_sketch_metric', 'qgw', 'dsl', '{"name":"traffic-spectrum-summary","filter":"vsys_id in (${vsys_id}) AND (${filter})","intervals":["${start_time}/${end_time}"]}',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('traffic-spectrum-unique-client-and-server-ips', 'traffic_sketch_metric', 'qgw', 'dsl', '{"name":"traffic-spectrum-unique-client-and-server-ips","filter":"vsys_id in (${vsys_id}) AND (${filter})","intervals":["${start_time}/${end_time}"]}',null); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('traffic-spectrum-app-distribution', 'traffic_sketch_metric', 'qgw', 'dsl', '{"name":"traffic-spectrum-app-distribution","filter":"app in (''${app}'') AND vsys_id in (${vsys_id}) AND (${filter})","intervals":["${start_time}/${end_time}"]}','The traffic usage of specified applications. Include the Top Server IP and Top Server Domain. '); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('traffic-spectrum-client-ip-connect-application-usage', 'traffic_sketch_metric', 'qgw', 'dsl', '{"name":"traffic-spectrum-client-ip-connect-application-usage","filter":"vsys_id in (${vsys_id}) AND (${filter})","intervals":["${start_time}/${end_time}"]}','The traffic usage of Internal Client IP to external application and External Client IP to Internal Application.'); +INSERT INTO `dataset` (`identifier_name`, `category`, `backend_engine`, `type`, `template`, `description`) VALUES ('traffic-spectrum-network-throughput-trend', 'traffic_sketch_metric', 'qgw', 'dsl', '{"name":"traffic-spectrum-network-throughput-trend","filter":"vsys_id in (${vsys_id}) AND (${filter})","intervals":["${start_time}/${end_time}"]}',null); +COMMIT; +SET FOREIGN_KEY_CHECKS = 1; \ No newline at end of file diff --git a/tsg_olap/installation/mariadb/galaxy-qgw-service/V23.12__init_saved_query_job.sql b/tsg_olap/installation/mariadb/galaxy-qgw-service/V23.12__init_saved_query_job.sql new file mode 100644 index 0000000..b0c7ca1 --- /dev/null +++ b/tsg_olap/installation/mariadb/galaxy-qgw-service/V23.12__init_saved_query_job.sql @@ -0,0 +1,28 @@ +SET NAMES utf8mb4; +SET FOREIGN_KEY_CHECKS = 0; + +-- ---------------------------- +-- Table structure for saved_query_job +-- ---------------------------- +CREATE TABLE IF NOT EXISTS `saved_query_job` ( + `job_id` varchar(128) NOT NULL COMMENT 'Job unique identifier', + `query_sql` text NOT NULL COMMENT 'Query SQL', + `state` varchar(16) NOT NULL COMMENT 'Enums: PENDING or RUNNING or DONE', + `done_progress` float(3, 2) NOT NULL DEFAULT 0 COMMENT 'Progress: 0 - 1.0', + `is_failed` int(2) NOT NULL DEFAULT 0 COMMENT 'Failed or not', + `result_message` varchar(2000) DEFAULT NULL COMMENT 'Result message', + `elapsed` int(11) DEFAULT NULL COMMENT 'cost time(ms)', + `rows_read` bigint(20) DEFAULT NULL COMMENT 'Processed rows', + `bytes_read` bigint(20) DEFAULT NULL COMMENT 'Processed bytes', + `result_bytes` bigint(20) DEFAULT NULL COMMENT 'Result bytes', + `result_rows` bigint(20) DEFAULT NULL COMMENT 'Result rows', + `is_valid` int(2) NOT NULL DEFAULT 1 COMMENT 'Valid or not', + `start_time` bigint(20) DEFAULT NULL COMMENT 'start time: from PENDING to RUNNING or DONE', + `end_time` bigint(20) DEFAULT NULL COMMENT 'end time: state updated DONE', + `last_update_time` bigint(20) NOT NULL COMMENT 'Last Update Time', + `generated_time` bigint(20) NOT NULL COMMENT 'Generated Time', + PRIMARY KEY (`job_id`) USING BTREE, + KEY `index_job_id` (`job_id`) USING BTREE +) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 ROW_FORMAT=DYNAMIC; + +SET FOREIGN_KEY_CHECKS = 1; diff --git a/tsg_olap/installation/mariadb/galaxy-qgw-service/V24.07__init_sys_storage_event.sql b/tsg_olap/installation/mariadb/galaxy-qgw-service/V24.07__init_sys_storage_event.sql new file mode 100644 index 0000000..af20799 --- /dev/null +++ b/tsg_olap/installation/mariadb/galaxy-qgw-service/V24.07__init_sys_storage_event.sql @@ -0,0 +1,22 @@ +/* + Sys Storage Event +*/ + +SET NAMES utf8mb4; +SET FOREIGN_KEY_CHECKS = 0; +-- ---------------------------- +-- Table structure for dataset +-- ---------------------------- +CREATE TABLE IF NOT EXISTS `sys_storage_event` ( + `id` int(64) NOT NULL AUTO_INCREMENT, + `log_type` varchar(512) NOT NULL COMMENT 'Enums: Traffic Logs or Metrics or Files', + `data_center` varchar(512) NOT NULL, + `used_size` bigint NOT NULL, + `total_allocated_size` bigint NOT NULL, + `bytes` bigint NOT NULL, + `since_time` bigint NOT NULL, + `generated_time` bigint NOT NULL, + PRIMARY KEY (`id`) USING BTREE +) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=utf8mb4 ROW_FORMAT=DYNAMIC; + +SET FOREIGN_KEY_CHECKS = 1; \ No newline at end of file