#Druid配置
druid.url=jdbc:avatica:remote:url=http://192.168.44.12:8082/druid/v2/sql/avatica/
druid.driver=org.apache.calcite.avatica.remote.Driver
druid.table=top_server_ip_test_log
#字段映射
druid.attacktype.tcpsynflood=sessions
druid.attacktype.udpflood=bytes
druid.attacktype.icmpflood=packets
druid.attacktype.dnsamplification=packets
druid.serverip.columnname=destination
druid.attacktype.columnname=order_by
druid.recvtime.columnname=__time
#baseline生成metric
baseline.metric.type=session_num
#HBase配置
hbase.table=ddos_traffic_baselines
hbase.zookeeper.quorum=192.168.44.12
hbase.zookeeper.client.port=2181
#读取druid时间范围方式，0：读取默认范围read.druid.time.range天数；1：指定时间范围
read.druid.time.limit.type=1
#07-01
read.druid.min.time=1625068800000
#06-01
#read.druid.min.time=1622476800000
read.druid.max.time=1625673600000
#读取过去N天数据，最小值为3天（需要判断周期性）
read.historical.days=7
#历史数据汇聚粒度为10分钟
historical.grad=10
#baseline生成方法
baseline.function=KalmanFilter
#baseline时间1天
baseline.range.days=1
# 数据库Time格式
time.format=yyyy-MM-dd HH:mm:ss
#算法参数
baseline.period.correlative.threshold=0.5
baseline.historical.ratio.threshold=0.1
baseline.historical.sparse.fill.percentile=0.95
baseline.rational.percentile=0.95
#Kalman Filter
baseline.kalman.q=0.000001
baseline.kalman.r=0.002
# 每更新1000个记录打印log
log.write.count=10000
# FOR TEST
generate.batch.size=100
