资源隔离三个任务，增加spark.executor.cores、spark.cores.max资源控制参数。

ip-learning-spark/src/main/resources/application.properties

@@ -1,6 +1,8 @@
 #spark任务配置
 spark.sql.shuffle.partitions=10
 spark.executor.memory=4g
+spark.executor.cores=1
+spark.cores.max=10
 spark.app.name=test
 spark.network.timeout=300s
 spark.serializer=org.apache.spark.serializer.KryoSerializer
@@ -17,22 +19,19 @@ spark.read.clickhouse.session.table=session_record
 spark.read.clickhouse.radius.table=radius_record
 clickhouse.socket.timeout=300000
 #arangoDB配置
-#arangoDB.host=192.168.40.223
 arangoDB.host=192.168.44.12
 arangoDB.port=8529
 arangoDB.user=root
-#arangoDB.password=galaxy_2019
 arangoDB.password=ceiec2019
 arangoDB.DB.name=tsg_galaxy_v3_test
-#arangoDB.DB.name=iplearn_media_domain
 arangoDB.ttl=3600
 
 thread.pool.number=10
 
 #读取clickhouse时间范围方式，0：读取过去一小时；1：指定时间范围
-clickhouse.time.limit.type=0
-read.clickhouse.max.time=1608518990
-read.clickhouse.min.time=1604851201
+clickhouse.time.limit.type=1
+read.clickhouse.max.time=1634902508
+read.clickhouse.min.time=1631759985
 
 update.arango.batch=10000
 
@@ -40,5 +39,6 @@ distinct.client.ip.num=10000
 recent.count.hour=24
 
 update.interval=3600
-
 arangodb.total.num=20000000
+#读取radius时间范围,与radius任务执行周期一致,单位:分钟
+read.radius.granularity=-30