hive在tez上error:java.lang.outofmemoryerror

0pizxfdo 于 2021-07-15 发布在 Hadoop

关注(0)|答案(1)|浏览(624)

在对包含70多列的配置单元表执行按日期分区时，我遇到了这个错误：
错误：状态：失败错误：vertex失败，vertexname=map 1，vertexid=vertex\u 1612203694878\u 0265\u 4\u 00，diagnostics=[任务失败，taskid=task\u 1612203694878\u 0265\u 4\u 00\u 000058，diagnostics=[任务尝试0失败，信息=[容器容器\u e16\u 1612203694878\u 0265\u 01\u 000167完成，诊断设置为[容器失败，exitcode=-104][2021-02-02 11:00:58.498]容器[pid=1577，containerid=container\u e16\u 1612203694878\u 0265\u 01\u 000167]正在运行3022848b，超出了“物理”内存限制。当前使用情况：使用1 gb物理内存中的1.0 gb；使用了2.7 gb的2.1 gb虚拟内存。杀人容器。容器的进程树转储\u e16 \u 1612203694878 \u 0265 \u 01 \u 000167:|-pid ppid pgrpid sessid cmd \u name user \u mode \u time（millis）system \u time（millis）vmem \u usage（bytes）rssmem \u usage（pages）full \u cmd \u line |-1577 1567 1577（bash）0 0 116011008 301/bin/bash-c/usr/jdk64/jdk1.8.0 \u 112/bin/java-xmx819m-server-djava.net.preferipv4stack=true-dhdp.version=3.1.4.0-315-xx:+printgc详细信息-verbose:gc -xx：+printgctimestamps-xx:+usenuma-xx:+useg1gc-xx:+resizetlab-server-djava.net.preferipv4stack=true-xx:newratio=8-xx:+usenuma-xx:+useg1gc-xx:+resizetlab-xx:+printgcdetails-verbose:gc -xx用法：+printgctimestamps-dlog4j.configuratorclass=org.apache.tez.common.tezlog4jconfigurator-dlog4j.configuration=tez-container-log4j.properties-dyarn.app.container.log.dir=/usr/hadoop/yarn/log/application\u 1612203694878\u 0265/container\u e16\u 1612203694878\u 0265\u 01\u 000167-dtez.root.logger=info，cla-djava.io.tmpdir=/usr/hadoop/yarn/local/usercache/hive/appcache/application\u 1612203694878\u 0265/container\u e16\u 1612203694878\u 0265\u 01\u 000167/tmp org.apache.tez.runtime.task.tezchild slave-06-n.fawryhq.corp 43250 container\u e16\u 1612203694878\u 0265\u 01\u 000167 application\u 1612203694878\u 0265 11> /usr/hadoop/yarn/log/application\u 1612203694878\u 0265/container\u e16\u 1612203694878\u 0265\u 01\u 000167/stdout 2>/usr/hadoop/yarn/log/application\u 1612203694878\u 0265/container\u e16\u 1612203694878\u 0265\u 01\u 000167/stderr |-1658 1577 1577（java）1414 128 2788896768 262581/usr/jdk64/jdk1.8.0\u 112/bin/java-x819m-server-djava.net.preferipv4stack=true-dhdp.version=3.1.4.0-315-xx:+printgc详细信息-verbose:gc -xx：+printgctimestamps-xx:+usenuma-xx:+useg1gc-xx:+resizetlab-server-djava.net.preferipv4stack=true-xx:newratio=8-xx:+usenuma-xx:+useg1gc-xx:+resizetlab-xx:+printgcdetails-verbose:gc -xx用法：+printgctimestamps-dlog4j.configuratorclass=org.apache.tez.common.tezlog4jconfigurator-dlog4j.configuration=tez-container-log4j.properties-dyarn.app.container.log.dir=/usr/hadoop/yarn/log/application\u 1612203694878\u 0265/container\u e16\u 1612203694878\u 0265\u 01\u 000167-dtez.root.logger=info，cla-djava.io.tmpdir=/usr/hadoop/yarn/local/usercache/hive/appcache/application\u 1612203694878\u 0265/container\u e16\u 1612203694878\u 0265\u 01\u 000167/tmp org.apache.tez.runtime.task.tezchild slave-06-n.fawryhq.corp 43250 container\u e16\u 1612203694878\u 0265\u 01\u 000167 application\u 1612203694878\u 0265 1[2021-02 11:00:58.512]应请求终止容器。出口代码为143[2021-02-02 11:00:58.521]集装箱出口代码为非零143。]，任务尝试1失败，info=[错误：运行任务时出错（失败）：java.lang.outofmemoryerror:java.nio.heapbytebuffer.（heapbytebuffer）处的java堆空间。java:57)在java.nio.bytebuffer.allocate（bytebuffer。java:335)位于org.apache.tez.runtime.library.common.sort.impl.pipelinedsorter.allocatespace（pipelinedsorter）。java:256)在org.apache.tez.runtime.library.common.sort.impl.pipelinedsorter.（pipelinedsorter。java:205)在org.apache.tez.runtime.library.output.orderedpartitionedkvoutput.start（orderedpartitionedkvoutput）。java:146)在org.apache.hadoop.hive.ql.exec.tez.maprecordprocessor.init（maprecordprocessor。java:193)在org.apache.hadoop.hive.ql.exec.tez.tezprocessor.initializeandrunprocessor（tezprocessor）。java:266)在org.apache.hadoop.hive.ql.exec.tez.tezprocessor.run（tezprocessor。java:250)位于org.apache.tez.runtime.logicalioprocessorruntimetask.run（logicalioprocessorruntimetask）。java:374)在org.apache.tez.runtime.task.taskrunner2callable$1.run（taskrunner2callable。java:73)在org.apache.tez.runtime.task.taskrunner2callable$1.run（taskrunner2callable。java:61)位于javax.security.auth.subject.doas（subject）的java.security.accesscontroller.doprivileged（本机方法）。java:422)在org.apache.hadoop.security.usergroupinformation.doas（用户组信息。java:1730)在org.apache.tez.runtime.task.taskrunner2callable.callinternal（taskrunner2callable。java:61)在org.apache.tez.runtime.task.taskrunner2callable.callinternal（taskrunner2callable。java:37)在org.apache.tez.common.callablewithndc.call（callablewithndc。java:36)在com.google.common.util.concurrent.trustedlistenablefuturetask$trustedFutureInterruptableTask.runInterruptbly（trustedlistenablefuturetask）。java:125)在com.google.common.util.concurrent.interruptibletask.run（interruptibletask。java:69)在com.google.common.util.concurrent.trustedlistenablefuturetask.run（trustedlistenablefuturetask。java:78)在java.util.concurrent.threadpoolexecutor.runworker（threadpoolexecutor。java:1142)在java.util.concurrent.threadpoolexecutor$worker.run（threadpoolexecutor。java:617)在java.lang.thread.run（线程。java:745) ,errormessage=无法从中恢复error:java.lang.outofmemoryerror：java.nio.heapbytebuffer处的java堆空间。（heapbytebuffer。java:57)在java.nio.bytebuffer.allocate（bytebuffer。java:335)位于org.apache.tez.runtime.library.common.sort.impl.pipelinedsorter.allocatespace（pipelinedsorter）。java:256)在org.apache.tez.runtime.library.common.sort.impl.pipelinedsorter.（pipelinedsorter。java:205)在org.apache.tez.runtime.library.output.orderedpartitionedkvoutput.start（orderedpartitionedkvoutput）。java:146)在org.apache.hadoop.hive.ql.exec.tez.maprecordprocessor.init（maprecordprocessor。java:193)在org.apache.hadoop.hive.ql.exec.tez.tezprocessor.initializeandrunprocessor（tezprocessor）。java:266)在org.apache.hadoop.hive.ql.exec.tez.tezprocessor.run（tezprocessor。java:250)位于org.apache.tez.runtime.logicalioprocessorruntimetask.run（logicalioprocessorruntimetask）。java:374)在org.apache.tez.runtime.task.taskrunner2callable$1.run（taskrunner2callable。java:73)在org.apache.tez.runtime.task.taskrunner2callable$1.run（taskrunner2callable。java:61)位于javax.security.auth.subject.doas（subject）的java.security.accesscontroller.doprivileged（本机方法）。java:422)在org.apache.hadoop.security.usergroupinformation.doas（用户组信息。java:1730)在org.apache.tez.runtime.task.taskrunner2callable.callinternal（taskrunner2callable。java:61)在org.apache.tez.runtime.task.taskrunner2callable.callinternal（taskrunner2callable。java:37)在org.apache.tez.common.callablewithndc.call（callablewithndc。java:36)在com.google.common.util.concurrent.trustedlistenablefuturetask$trustedFutureInterruptableTask.runInterruptbly（trustedlistenablefuturetask）。java:125)在com.google.common.util.concurrent.interruptibletask.run（interruptibletask。java:69)在com.google.common.util.concurrent.trustedlistenablefuturetask.run（trustedlistenablefuturetask。java:78)在java.util.concurrent.threadpoolexecutor.runworker（threadpoolexecutor。java:1142)在java.util.concurrent.threadpoolexecutor$worker.run（threadpoolexecutor。java:617)在java.lang.thread.run（线程。java:745)]]，由于自身任务失败，vertex未成功，failedtasks:1 killedtasks:17,vertex vertex_1612203694878_0265_4_00[map 1]已终止/失败，原因是：own_task_failure]错误：vertex已终止，vertexname=reducer 2，vertexid=vertex_1612203694878_0265_4_01，diagnostics=[vertex在运行状态下收到终止，vertex因其他\u vertex_失败而未成功，failedtasks:0 killedtasks:2,vertex\u 1612203694878\u 0265\u 4\u 01[减速器2]已终止/失败，原因是：其他\u vertex\u失败]错误：由于vertex\u失败，dag未成功。失败dvertices:1 killedvertices:1

hadoop Hive hiveql bigdata apache-tez

来源：https://stackoverflow.com/questions/66006769/hive-on-tez-errorjava-lang-outofmemoryerror

1条答案

按热度按时间

3xiyfsfu1#

试一下（按这个顺序）
增加Map器并行度。目标是得到更多更小的Map绘制者。检查有多少Map绘制开始和调整数字。如果有太大的不可拆分格式（如gzip）的文件，这将不起作用，请继续下面的两个步骤。

--This is example, check your current setings and adjust to get x2 or more mappers
set hive.input.format=org.apache.hadoop.hive.ql.io.HiveInputFormat;
set tez.grouping.max-size=32000000; --bigger files will be splitted
set tez.grouping.min-size=32000;    --smaller files will be combined on single mapper

禁用Map端聚合（Map端聚合通常会导致oom）

set hive.map.aggr=false;

如果以上两个步骤没有帮助，请增加Map器内存（尝试查找最小工作容器大小）

set hive.tez.container.size=9216; --Adjust figures and chose minimum working size
set hive.tez.java.opts=-Xmx6144m;

赞(0）回复(0）举报 2021-07-15

我来回答

hive在tez上error:java.lang.outofmemoryerror

1条答案

相关问题

热门标签

最新问答