Hive常見問題
1. 內(nèi)存溢出
虛擬內(nèi)存溢出:
Current usage: 1.1gb of 2.0gb physical memory used; 4.6gb of 4.2gb virtual memory used. Killing container.==【即虛擬內(nèi)存溢出】==;
方法一:提高yarn.nodemanager.vmem-pmem-ratio = 5或者更高;【推薦】
方法二:yarn.nodemanager.vmem-check-enabled =false ;關(guān)閉虛擬內(nèi)存檢查;不推薦
方法三:提高物理內(nèi)存分配,相應(yīng)的虛擬內(nèi)存自然就多了,但是這樣不是最優(yōu)
物理內(nèi)存溢出:
Current usage: 2.1gb of 2.0gb physical memory used; 3.6gb of 4.2gb virtual memory used. Killing container.【即物理內(nèi)存溢出】;
方法一:mapreduce.map.memory.mb = 3GB以上,然后測試這個(gè)map/reduce task需要使用多少內(nèi)存才夠用,提高這個(gè)值直到不報(bào)錯(cuò)為止。
方法二:提高yarn.scheduler.minimum-allocation-mb = 3GB以上,同理【不推薦】
打開低版本hive報(bào)錯(cuò):
ls: cannot access /app/local/spark-2.0.2-bin-hadoop2.6/lib/spark-assembly-*.jar: No such file or directory
修改hive啟動文件
vim /app/local/hive/bin/hive
找到下面這一行:
# add Spark assembly jar to the classpath
if [[ -n "SPARK_HOME" ]]
then
# sparkAssemblyPath=`ls{SPARK_HOME}/lib/spark-assembly-*.jar`
sparkAssemblyPath=`ls {SPARK_HOME}/jars/*.jar`
CLASSPATH="{CLASSPATH}:${sparkAssemblyPath}"
fi
2. 關(guān)聯(lián)查詢
2018-11-25 14:43:04,199 main ERROR Unable to invoke factory method in class class org.apache.hadoop.hive.ql.log element HushableMutableRandomAccess. java.lang.reflect.InvocationTargetException
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.logging.log4j.core.config.plugins.util.PluginBuilder.build(PluginBuilder.java:132)
at org.apache.logging.log4j.core.config.AbstractConfiguration.createPluginObject(AbstractConfiguration.
at org.apache.logging.log4j.core.config.AbstractConfiguration.createConfiguration(AbstractConfiguration
at org.apache.logging.log4j.core.appender.routing.RoutingAppender.createAppender(RoutingAppender.java:2
at org.apache.logging.log4j.core.appender.routing.RoutingAppender.getControl(RoutingAppender.java:255)
at org.apache.logging.log4j.core.appender.routing.RoutingAppender.append(RoutingAppender.java:225)
at org.apache.logging.log4j.core.config.AppenderControl.tryCallAppender(AppenderControl.java:156)
at org.apache.logging.log4j.core.config.AppenderControl.callAppender0(AppenderControl.java:129)
at org.apache.logging.log4j.core.config.AppenderControl.callAppenderPreventRecursion(AppenderControl.ja
at org.apache.logging.log4j.core.config.AppenderControl.callAppender(AppenderControl.java:84)
at org.apache.logging.log4j.core.config.LoggerConfig.callAppenders(LoggerConfig.java:448)
at org.apache.logging.log4j.core.config.LoggerConfig.processLogEvent(LoggerConfig.java:433)
at org.apache.logging.log4j.core.config.LoggerConfig.log(LoggerConfig.java:417)
at org.apache.logging.log4j.core.config.LoggerConfig.log(LoggerConfig.java:403)
at org.apache.logging.log4j.core.config.AwaitCompletionReliabilityStrategy.log(AwaitCompletionReliabili
at org.apache.logging.log4j.core.Logger.logMessage(Logger.java:146)
at org.apache.logging.log4j.spi.AbstractLogger.logMessageSafely(AbstractLogger.java:2091)
at org.apache.logging.log4j.spi.AbstractLogger.logMessage(AbstractLogger.java:1993)
at org.apache.logging.log4j.spi.AbstractLogger.logIfEnabled(AbstractLogger.java:1852)
at org.apache.logging.slf4j.Log4jLogger.info(Log4jLogger.java:179)
at org.apache.hadoop.hive.ql.exec.mapjoin.MapJoinMemoryExhaustionHandler.<init>(MapJoinMemoryExhaustion
at org.apache.hadoop.hive.ql.exec.HashTableSinkOperator.initializeOp(HashTableSinkOperator.java:129)
at org.apache.hadoop.hive.ql.exec.Operator.initialize(Operator.java:358)
at org.apache.hadoop.hive.ql.exec.Operator.initialize(Operator.java:546)
at org.apache.hadoop.hive.ql.exec.Operator.initializeChildren(Operator.java:498)
at org.apache.hadoop.hive.ql.exec.Operator.initialize(Operator.java:368)
at org.apache.hadoop.hive.ql.exec.mr.MapredLocalTask.initializeOperators(MapredLocalTask.java:514)
at org.apache.hadoop.hive.ql.exec.mr.MapredLocalTask.startForward(MapredLocalTask.java:418)
at org.apache.hadoop.hive.ql.exec.mr.MapredLocalTask.executeInProcess(MapredLocalTask.java:393)
at org.apache.hadoop.hive.ql.exec.mr.ExecDriver.main(ExecDriver.java:774)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.hadoop.util.RunJar.run(RunJar.java:313)
at org.apache.hadoop.util.RunJar.main(RunJar.java:227)
Caused by: java.lang.IllegalStateException: ManagerFactory [org.apache.logging.log4j.core.appender.RandomAccessctory@6dac64ea] unable to create manager for [/var/log/hive/operation_logs/5396b439-4945-483d-b8eb-b5c478e6fbb5ae-9f97-23f95080e4be] with data [org.apache.logging.log4j.core.appender.RandomAccessFileManager$FactoryData@5de
at org.apache.logging.log4j.core.appender.AbstractManager.getManager(AbstractManager.java:114)
at org.apache.logging.log4j.core.appender.OutputStreamManager.getManager(OutputStreamManager.java:114)
at org.apache.logging.log4j.core.appender.RandomAccessFileManager.getFileManager(RandomAccessFileManage
at org.apache.hadoop.hive.ql.log.HushableRandomAccessFileAppender.createAppender(HushableRandomAccessFi
... 40 more
- 異常原因:mr將數(shù)據(jù)量小的表識別成了大表,數(shù)據(jù)量大的識別成小表,導(dǎo)致將數(shù)據(jù)量大的表加入到內(nèi)存,導(dǎo)致程序異常
- 處理方法:
set hive.execution.engine=mr; set hive.mapjoin.smalltable.filesize=55000000; set hive.auto.convert.join = false; #取消小表加載至內(nèi)存中
==通常情況下==,設(shè)置取消小表加載至內(nèi)存中即可:
set hive.auto.convert.join = false;
3. hive on spark問題
Job aborted due to stage failure: Aborting TaskSet 2.0 because task 8 (partition 8) cannot run anywhere due to node and executor blacklist. Blacklisting behavior can be configured via spark.blacklist.*.
臨時(shí)解決辦法:
set hive.execution.engine = mr;
4. hive 事務(wù)表
執(zhí)行的操作
delete from hm2.history_helper_back where starttime = '2019-06-12';
報(bào)錯(cuò)信息
FAILED: SemanticException [Error 10294]: Attempt to do update or delete using transaction manager that does not support these operations.
解決辦法:
set hive.support.concurrency = true;
set hive.txn.manager = org.apache.hadoop.hive.ql.lockmgr.DbTxnManager;
5. 修復(fù)大量分區(qū)
hive> MSCK REPAIR TABLE employee;
FAILED: Execution Error, return code 1 from org.apache.hadoop.hive.ql.exec.DDLTask
設(shè)置:
set hive.msck.path.validation=ignore;
6. hiveserver2 不識別udf函數(shù)
在無法使用UDF的 HiveServer2
上,執(zhí)行 reload function
命令,將MetaStore中新增的UDF信息同步到HiveServer2
內(nèi)存中。
7. 動態(tài)分區(qū)
Caused by: org.apache.hadoop.hive.ql.metadata.HiveFatalException: [Error 20004]: Fatal error occurred when node tried to create too many dynamic partitions. The maximum number of dynamic partitions is controlled by hive.exec.max.dynamic.partitions and hive.exec.max.dynamic.partitions.pernode. Maximum was set to 100 partitions per node, number of dynamic partitions on this node: 101
at org.apache.hadoop.hive.ql.exec.FileSinkOperator.getDynOutPaths(FileSinkOperator.java:941)
at org.apache.hadoop.hive.ql.exec.FileSinkOperator.process(FileSinkOperator.java:712)
at org.apache.hadoop.hive.ql.exec.Operator.forward(Operator.java:879)
at org.apache.hadoop.hive.ql.exec.SelectOperator.process(SelectOperator.java:95)
at org.apache.hadoop.hive.ql.exec.Operator.forward(Operator.java:879)
at org.apache.hadoop.hive.ql.exec.TableScanOperator.process(TableScanOperator.java:130)
at org.apache.hadoop.hive.ql.exec.MapOperator$MapOpCtx.forward(MapOperator.java:147)
at org.apache.hadoop.hive.ql.exec.MapOperator.process(MapOperator.java:487)
... 9 more
設(shè)置每個(gè)節(jié)點(diǎn)最大動態(tài)分區(qū)個(gè)數(shù).
8. block塊丟失
Caused by: org.apache.hadoop.hdfs.BlockMissingException: Could not obtain block: BP-808991319-10.1.0.62-1541662386662:blk_1110742285_40900ile=/user/hive/warehouse/hm4.db/hm4_format_log_his_tmp/dt=2019-09-16/hour=11/product=mini/event=click/part-r-00013_copy_1
由于block
塊受損,無法恢復(fù),只能刪除。
作者:柯廣的網(wǎng)絡(luò)日志
微信公眾號:Java大數(shù)據(jù)與數(shù)據(jù)倉庫