requirement failed: Block broadcast_487 is already present in the MemoryStore

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#spark #设备上没有空间 #broadcast #hadoop #yarn

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本文详细解析了SparkSQL在执行过程中遇到的两个常见错误：Block已在MemoryStore中存在和磁盘空间不足的问题。通过调整Hadoop集群的配置，移除swap分区作为yarn的日志目录，成功解决了Spark任务执行失败的情况。

场景：

以往正常执行的sparksql，今天在公司执行报如下错误：

第一次执行报错如下：

Caused by: java.sql.SQLException: org.apache.spark.SparkException: Job aborted due to stage failure: Task 1382 in stage 320.0 failed 4 times, most recent failure: Lost task 1382.3 in stage 320.0 (TID 165140, leaptest-dn03.bjev.com): java.io.IOException: java.lang.IllegalArgumentException: requirement failed: Block broadcast_487 is already present in the MemoryStore
    at org.apache.spark.util.Utils$.tryOrIOException(Utils.scala:1258)
    at org.apache.spark.broadcast.TorrentBroadcast.readBroadcastBlock(TorrentBroadcast.scala:174)
    at org.apache.spark.broadcast.TorrentBroadcast._value$lzycompute(TorrentBroadcast.scala:65)
    at org.apache.spark.broadcast.TorrentBroadcast._value(TorrentBroadcast.scala:65)
    at org.apache.spark.broadcast.TorrentBroadcast.getValue(TorrentBroadcast.scala:89)
    at org.apache.spark.broadcast.Broadcast.value(Broadcast.scala:70)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:72)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47)
    at org.apache.spark.scheduler.Task.run(Task.scala:85)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:283)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
    at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.IllegalArgumentException: requirement failed: Block broadcast_487 is already present in the MemoryStore
    at scala.Predef$.require(Predef.scala:224)
    at org.apache.spark.storage.memory.MemoryStore.putIteratorAsValues(MemoryStore.scala:182)
    at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:919)
    at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:910)
    at org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:866)
    at org.apache.spark.storage.BlockManager.doPutIterator(BlockManager.scala:910)
    at org.apache.spark.storage.BlockManager.putIterator(BlockManager.scala:700)
    at org.apache.spark.storage.BlockManager.putSingle(BlockManager.scala:1213)
    at org.apache.spark.broadcast.TorrentBroadcast$$anonfun$readBroadcastBlock$1.apply(TorrentBroadcast.scala:194)
    at org.apache.spark.util.Utils$.tryOrIOException(Utils.scala:1251)
    ... 12 more

Driver stacktrace:
    at org.apache.hive.jdbc.HiveStatement.execute(HiveStatement.java:279)
    at com.lenovo.lps.farseer.priest2.ext.SparkExecDao.executeOneSql(SparkExecDao.java:370)
    at com.lenovo.lps.farseer.priest2.ext.SparkExecDao.executeOneSqlProxy(SparkExecDao.java:341)
    at com.lenovo.lps.farseer.priest2.ext.SparkExecDao.sparkExecute(SparkExecDao.java:255)
    ... 82 more

多次执行的时候偶尔会报另一个错误：

Caused by: java.sql.SQLException: org.apache.spark.SparkException: Job aborted due to stage failure: Task 3 in stage 342.0 failed 4 times, most recent failure: Lost task 3.3 in stage 342.0 (TID 166270, leaptest-dn03.bjev.com): java.io.FileNotFoundException: /swap/hadoop/yarn/local/usercache/hive/appcache/application_1557227972884_8104/blockmgr-927821e7-2b49-465d-86de-9d2707e2517b/03/temp_shuffle_be51c50d-54ac-4a5b-b840-59129fed41fb (设备上没有空间)
    at java.io.FileOutputStream.open(Native Method)
    at java.io.FileOutputStream.<init>(FileOutputStream.java:221)
    at org.apache.spark.storage.DiskBlockObjectWriter.open(DiskBlockObjectWriter.scala:88)
    at org.apache.spark.storage.DiskBlockObjectWriter.write(DiskBlockObjectWriter.scala:181)
    at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:150)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79)
    at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47)
    at org.apache.spark.scheduler.Task.run(Task.scala:85)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:283)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
    at java.lang.Thread.run(Thread.java:745)

Driver stacktrace:
    at org.apache.hive.jdbc.HiveStatement.execute(HiveStatement.java:279)
    at com.lenovo.lps.farseer.priest2.ext.SparkExecDao.executeOneSql(SparkExecDao.java:370)
    at com.lenovo.lps.farseer.priest2.ext.SparkExecDao.executeOneSqlProxy(SparkExecDao.java:341)
    at com.lenovo.lps.farseer.priest2.ext.SparkExecDao.sparkExecute(SparkExecDao.java:255)
    ... 100 more

从第二次的异常中发现，部署hadoop集群的时候，实施人员将swap分区的目录配置成yarn的任务日志目录中了。即yarn-site.xml的这两个配置（yarn.nodemanager.log-dirs和yarn.nodemanager.local-dirs）。

<property>
<name>yarn.nodemanager.local-dirs</name>
<value>/swap/hadoop/yarn/local,/data/hadoop/yarn/local</value>
</property>

<property>
<name>yarn.nodemanager.log-dirs</name>
<value>/swap/hadoop/yarn/log,/data/hadoop/yarn/log</value>
</property>

在配置中去掉swap分区目录，重启yarn即可：

<property>
<name>yarn.nodemanager.local-dirs</name>
<value>/data/hadoop/yarn/local</value>
</property>

<property>
<name>yarn.nodemanager.log-dirs</name>
<value>/data/hadoop/yarn/log</value>
</property>