内存分配问题
给map、reduce task分配合理的内存；map、reduce task处理合理的数据
map task 分配的内存大小：使用的是缺省参数每个task分配200M内存
「mapred.child.java.opts」
集群中每个节点：8 core / 32G，此处设置为：
mapred.child.java.opts = 3G
<property>
<name>mapred.child.java.opts</name>
<value>-Xmx3072m</value>
</property>
mapred.max.split.size=256000000
hive.exec.reducers.bytes.per.reducer
hive.exec.reducers.max
以下内容翻译自StackOverFlow
原文链接
https://stackoverflow.com/questions/67732977/java-lang-outofmemoryerror-java-heap-space-error-while-executing-hive-query
在使用 TEZ 执行引擎从 Hive Shell 运行 Hive 查询时，我在日志中收到 java.lang.OutOfMemoryError: Java heap space error，但查询最终完成。
ERROR : Status: Failed
ERROR : Vertex failed, vertexName=Map 3, vertexId=vertex_1622153507491_0145_1_02, diagnostics=[Task failed, taskId=task_1622153507491_0145_1_02_000006, diagnostics=[TaskAttempt 0 failed, info=[Error: Error while running task ( failure ) : java.lang.RuntimeException: Map operator initialization failed
at org.apache.hadoop.hive.ql.exec.tez.MapRecordProcessor.init(MapRecordProcessor.java:361)
at org.apache.hadoop.hive.ql.exec.tez.TezProcessor.initializeAndRunProcessor(TezProcessor.java:266)
at org.apache.hadoop.hive.ql.exec.tez.TezProcessor.run(TezProcessor.java:250)
at org.apache.tez.runtime.LogicalIOProcessorRuntimeTask.run(LogicalIOProcessorRuntimeTask.java:374)
at org.apache.tez.runtime.task.TaskRunner2Callable$1.run(TaskRunner2Callable.java:73)
at org.apache.tez.runtime.task.TaskRunner2Callable$1.run(TaskRunner2Callable.java:61)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1730)
at org.apache.tez.runtime.task.TaskRunner2Callable.callInternal(TaskRunner2Callable.java:61)
at org.apache.tez.runtime.task.TaskRunner2Callable.callInternal(TaskRunner2Callable.java:37)
at org.apache.tez.common.CallableWithNdc.call(CallableWithNdc.java:36)
at com.google.common.util.concurrent.TrustedListenableFutureTask$TrustedFutureInterruptibleTask.runInterruptibly(TrustedListenableFutureTask.java:108)
at com.google.common.util.concurrent.InterruptibleTask.run(InterruptibleTask.java:41)
at com.google.common.util.concurrent.TrustedListenableFutureTask.run(TrustedListenableFutureTask.java:77)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: org.apache.hadoop.hive.ql.metadata.HiveException: Async Initialization failed. abortRequested=false
at org.apache.hadoop.hive.ql.exec.Operator.completeInitialization(Operator.java:465)
at org.apache.hadoop.hive.ql.exec.Operator.initialize(Operator.java:399)
at org.apache.hadoop.hive.ql.exec.Operator.initialize(Operator.java:572)
at org.apache.hadoop.hive.ql.exec.Operator.initializeChildren(Operator.java:524)
at org.apache.hadoop.hive.ql.exec.Operator.initialize(Operator.java:385)
at org.apache.hadoop.hive.ql.exec.tez.MapRecordProcessor.init(MapRecordProcessor.java:342)
... 17 more
Caused by: java.lang.OutOfMemoryError: Java heap space
at org.apache.hadoop.hive.serde2.WriteBuffers.nextBufferToWrite(WriteBuffers.java:261)
at org.apache.hadoop.hive.serde2.WriteBuffers.write(WriteBuffers.java:237)
at org.apache.hadoop.hive.ql.exec.vector.mapjoin.fast.VectorMapJoinFastBytesHashMapStore.addMore(VectorMapJoinFastBytesHashMapStore.java:539)
at org.apache.hadoop.hive.ql.exec.vector.mapjoin.fast.VectorMapJoinFastBytesHashMap.add(VectorMapJoinFastBytesHashMap.java:101)
at org.apache.hadoop.hive.ql.exec.vector.mapjoin.fast.VectorMapJoinFastStringCommon.adaptPutRow(VectorMapJoinFastStringCommon.java:59)
at org.apache.hadoop.hive.ql.exec.vector.mapjoin.fast.VectorMapJoinFastStringHashMap.putRow(VectorMapJoinFastStringHashMap.java:37)
at org.apache.hadoop.hive.ql.exec.vector.mapjoin.fast.VectorMapJoinFastTableContainer.putRow(VectorMapJoinFastTableContainer.java:183)
at org.apache.hadoop.hive.ql.exec.vector.mapjoin.fast.VectorMapJoinFastHashTableLoader.load(VectorMapJoinFastHashTableLoader.java:130)
at org.apache.hadoop.hive.ql.exec.MapJoinOperator.loadHashTableInternal(MapJoinOperator.java:344)
at org.apache.hadoop.hive.ql.exec.MapJoinOperator.loadHashTable(MapJoinOperator.java:413)
at org.apache.hadoop.hive.ql.exec.MapJoinOperator.lambda$initializeOp$0(MapJoinOperator.java:215)
at org.apache.hadoop.hive.ql.exec.MapJoinOperator$$Lambda$27/55723736.call(Unknown Source)
at org.apache.hadoop.hive.ql.exec.tez.ObjectCache.retrieve(ObjectCache.java:96)
at org.apache.hadoop.hive.ql.exec.tez.ObjectCache$1.call(ObjectCache.java:113)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
... 3 more
加载 HashTable 时，在 MapJoin 运算符中出现 OOM 异常。也许没有mapjoin的替代路径已经成功，这就是它最终完成的原因。
你可以尝试以下方法：尝试增加 mapper 的并行度，如果你有更多的mapper并且 id 对这个错误解决起到作用，增加 mapper 内存。检查您当前的设置并进行相应的更改。
增加mapper并行度（如果原因实际上是因为 Map Join 加载到内存中的表太大，这可能无济于事）。set hive.input.format=org.apache.hadoop.hive.ql.io.HiveInputFormat;
set tez.grouping.max-size=32000000; --减小 max-size 会增加并行度
set tez.grouping.min-size=32000; --如果您有小于 min-size 的小文件，mapper 将另外处理其他文件
增加mapper容器大小（检查您当前的设置并相应增加）。这仅是示例：set hive.tez.container.size=2048; --以MB为单位的容器大小
set hive.tez.java.opts=-Xmx1700m; --设置为 whive.tez.container.size 的 80%
尽量禁用Map端聚合，Map端聚合会导致OOMset hive.map.aggr=false;
检查 mapjoin 设置，可能 smalltable 大小设置得太大，与您之前设置的容器大小进行比较：Hive Map-Join configuration mystery
https://stackoverflow.com/questions/54726128/hive-map-join-configuration-mystery