gfwleak/galaxy-tsg-olap-log-completion-schema
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1：修改配置命名consumer-surce，producer-sink等

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2：增加不同方式处理日志开关
This commit is contained in:
qidaijie
2021-11-07 17:13:13 +03:00
parent 159d00cfb0
commit 8bf733385f
12 changed files with 93 additions and 106 deletions
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38
src/main/java/com/zdjizhi/topology/LogFlowWriteTopology.java
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@@ -5,9 +5,10 @@ import cn.hutool.log.LogFactory;
import com.zdjizhi.common.FlowWriteConfig;
import com.zdjizhi.utils.functions.FilterNullFunction;
import com.zdjizhi.utils.functions.MapCompletedFunction;
import com.zdjizhi.utils.functions.ObjectCompletedFunction;
import com.zdjizhi.utils.functions.TypeMapCompletedFunction;
import com.zdjizhi.utils.kafka.Consumer;
import com.zdjizhi.utils.kafka.Producer;
import org.apache.flink.streaming.api.TimeCharacteristic;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
@@ -27,26 +28,49 @@ public class LogFlowWriteTopology {
//开启Checkpoint，interval用于指定checkpoint的触发间隔(单位milliseconds)
// environment.enableCheckpointing(5000);
//
environment.setBufferTimeout(5000);
DataStreamSource<String> streamSource = environment.addSource(Consumer.getKafkaConsumer())
.setParallelism(FlowWriteConfig.CONSUMER_PARALLELISM);
.setParallelism(FlowWriteConfig.SOURCE_PARALLELISM);
if (FlowWriteConfig.LOG_NEED_COMPLETE == 1) {
//对原始日志进行处理补全转换等
DataStream<String> cleaningLog = streamSource.map(new MapCompletedFunction()).name("TransFormLogs")
.setParallelism(FlowWriteConfig.TRANSFORM_PARALLELISM);
DataStream<String> cleaningLog;
switch (FlowWriteConfig.LOG_TRANSFORM_TYPE) {
case 0:
//对原始日志进行处理补全转换等，不对日志字段类型做校验。
cleaningLog = streamSource.map(new MapCompletedFunction()).name("MapCompletedFunction")
.setParallelism(FlowWriteConfig.TRANSFORM_PARALLELISM);
break;
case 1:
//对原始日志进行处理补全转换等，强制要求日志字段类型与schema一致。
cleaningLog = streamSource.map(new ObjectCompletedFunction()).name("ObjectCompletedFunction")
.setParallelism(FlowWriteConfig.TRANSFORM_PARALLELISM);
break;
case 2:
//对原始日志进行处理补全转换等，对日志字段类型做若校验，可根据schema进行强转。
cleaningLog = streamSource.map(new TypeMapCompletedFunction()).name("TypeMapCompletedFunction")
.setParallelism(FlowWriteConfig.TRANSFORM_PARALLELISM);
break;
default:
//对原始日志进行处理补全转换等，不对日志字段类型做校验。
cleaningLog = streamSource.map(new MapCompletedFunction()).name("MapCompletedFunction")
.setParallelism(FlowWriteConfig.TRANSFORM_PARALLELISM);
}
//过滤空数据不发送到Kafka内
DataStream<String> result = cleaningLog.filter(new FilterNullFunction()).name("FilterAbnormalData")
.setParallelism(FlowWriteConfig.TRANSFORM_PARALLELISM);
//发送数据到Kafka
result.addSink(Producer.getKafkaProducer()).name("LogSinkKafka")
.setParallelism(FlowWriteConfig.TRANSFORM_PARALLELISM);
.setParallelism(FlowWriteConfig.SINK_PARALLELISM);
} else {
//过滤空数据不发送到Kafka内
DataStream<String> result = streamSource.filter(new FilterNullFunction()).name("FilterOriginalData")
.setParallelism(FlowWriteConfig.TRANSFORM_PARALLELISM);
//发送数据到Kafka
result.addSink(Producer.getKafkaProducer()).name("LogSinkKafka")
.setParallelism(FlowWriteConfig.TRANSFORM_PARALLELISM);
.setParallelism(FlowWriteConfig.SINK_PARALLELISM);
}
try {