日志相关配置如下：
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status = INFO
name = HiveLog4j2
packages = org.apache.hadoop.hive.ql.log
# list of properties
property.hive.log.level = INFO
property.hive.root.logger = DRFA
property.hive.log.dir = /var/log/udp/2.0.0.0/hive/
property.hive.log.file = hive.log
property.hive.perflogger.log.level = INFO
# list of all appenders
appenders = console, DRFA
# console appender
appender.console.type = Console
appender.console.name = console
appender.console.target = SYSTEM_ERR
appender.console.layout.type = PatternLayout
appender.console.layout.pattern = %d{ISO8601} %5p [%t] %c{2}: %m%n
# daily rolling file appender
appender.DRFA.type = RollingRandomAccessFile
appender.DRFA.name = DRFA
appender.DRFA.fileName = ${sys:hive.log.dir}/${sys:hive.log.file}
# Use %pid in the filePattern to append <process-id>@<host-name> to the filename if you want separate log files for different CLI session
appender.DRFA.filePattern = ${sys:hive.log.dir}/${sys:hive.log.file}.%d{yyyy-MM-dd}-%i.log
appender.DRFA.layout.type = PatternLayout
appender.DRFA.layout.pattern = %d{ISO8601} %5p [%t] %c{2}: %m%n
appender.DRFA.policies.type = Policies
appender.DRFA.policies.time.type = TimeBasedTriggeringPolicy
appender.DRFA.policies.time.interval = 1
appender.DRFA.policies.time.modulate = true
appender.DRFA.strategy.type = DefaultRolloverStrategy
appender.DRFA.strategy.max = 2
appender.DRFA.policies.size.type = SizeBasedTriggeringPolicy
appender.DRFA.policies.size.size = 1MB
# Deletes logs IfLastModified date is greater than number of days
appender.DRFA.strategy.action.condition.nested_condition.lastMod.type = IfLastModified
appender.DRFA.strategy.action.condition.nested_condition.lastMod.age = 30D
# list of all loggers
loggers = NIOServerCnxn, ClientCnxnSocketNIO, DataNucleus, Datastore, JPOX, PerfLogger, AmazonAws, ApacheHttp
logger.NIOServerCnxn.name = org.apache.zookeeper.server.NIOServerCnxn
logger.NIOServerCnxn.level = WARN
logger.ClientCnxnSocketNIO.name = org.apache.zookeeper.ClientCnxnSocketNIO
logger.ClientCnxnSocketNIO.level = WARN
logger.DataNucleus.name = DataNucleus
logger.DataNucleus.level = ERROR
logger.Datastore.name = Datastore
logger.Datastore.level = ERROR
logger.JPOX.name = JPOX
logger.JPOX.level = ERROR
logger.AmazonAws.name=com.amazonaws
logger.AmazonAws.level = INFO
logger.ApacheHttp.name=org.apache.http
logger.ApacheHttp.level = INFO
logger.PerfLogger.name = org.apache.hadoop.hive.ql.log.PerfLogger
logger.PerfLogger.level = ${sys:hive.perflogger.log.level}
# root logger
rootLogger.level = ${sys:hive.log.level}
rootLogger.appenderRefs = root
rootLogger.appenderRef.root.ref = ${sys:hive.root.logger}日志的滚动结果如下：
-rw------- 1 omm wheel 84507 Dec 19 16:17 hive.log.2022-05-09-1.log.zip
-rw------- 1 omm wheel 93363 Dec 19 16:29 hive.log.2022-05-09-2.log.zip
-rw------- 1 omm wheel 84507 Dec 19 16:35 hive.log.2022-05-09-3.log.zip
可以看到，在时间相同的情况下日志能够正常滚动，但是时间一旦发生变化日志的编号 i 值就会从1开始重新累加。
