为什么aws emr中缺少hive\u暂存文件

busg9geu  于 2021-06-28  发布在  Hive
关注(0)|答案(2)|浏览(360)

问题-
我正在aws emr中运行1个查询。它通过抛出异常而失败-

java.io.FileNotFoundException: File s3://xxx/yyy/internal_test_automation/2016/09/17/17156/data/feed/commerce_feed_redshift_dedup/.hive-staging_hive_2016-09-17_10-24-20_998_2833938482542362802-639 does not exist.

我在下面提到了这个问题的所有相关信息。请检查一下。
查询-

INSERT OVERWRITE TABLE base_performance_order_dedup_20160917
SELECT 

* 

 FROM 
(
select
commerce_feed_redshift_dedup.sku AS sku,
commerce_feed_redshift_dedup.revenue AS revenue,
commerce_feed_redshift_dedup.orders AS orders,
commerce_feed_redshift_dedup.units AS units,
commerce_feed_redshift_dedup.feed_date AS feed_date
from commerce_feed_redshift_dedup
) tb

例外情况-

ERROR Error while executing queries
java.sql.SQLException: Error while processing statement: FAILED: Execution Error, return code 2 from org.apache.hadoop.hive.ql.exec.tez.TezTask. Vertex failed, vertexName=Map 1, vertexId=vertex_1474097800415_0311_2_00, diagnostics=[Vertex vertex_1474097800415_0311_2_00 [Map 1] killed/failed due to:ROOT_INPUT_INIT_FAILURE, Vertex Input: commerce_feed_redshift_dedup initializer failed, vertex=vertex_1474097800415_0311_2_00 [Map 1], java.io.FileNotFoundException: File s3://xxx/yyy/internal_test_automation/2016/09/17/17156/data/feed/commerce_feed_redshift_dedup/.hive-staging_hive_2016-09-17_10-24-20_998_2833938482542362802-639 does not exist.
    at com.amazon.ws.emr.hadoop.fs.s3n.S3NativeFileSystem.listStatus(S3NativeFileSystem.java:987)
    at com.amazon.ws.emr.hadoop.fs.s3n.S3NativeFileSystem.listStatus(S3NativeFileSystem.java:929)
    at com.amazon.ws.emr.hadoop.fs.EmrFileSystem.listStatus(EmrFileSystem.java:339)
    at org.apache.hadoop.fs.FileSystem.listStatus(FileSystem.java:1530)
    at org.apache.hadoop.fs.FileSystem.listStatus(FileSystem.java:1537)
    at org.apache.hadoop.fs.FileSystem.listStatus(FileSystem.java:1556)
    at org.apache.hadoop.fs.FileSystem.listStatus(FileSystem.java:1601)
    at org.apache.hadoop.fs.FileSystem$4.(FileSystem.java:1778)
    at org.apache.hadoop.fs.FileSystem.listLocatedStatus(FileSystem.java:1777)
    at org.apache.hadoop.fs.FileSystem.listLocatedStatus(FileSystem.java:1755)
    at org.apache.hadoop.mapred.FileInputFormat.singleThreadedListStatus(FileInputFormat.java:239)
    at org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:201)
    at org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:281)
    at org.apache.hadoop.hive.ql.io.HiveInputFormat.addSplitsForGroup(HiveInputFormat.java:363)
    at org.apache.hadoop.hive.ql.io.HiveInputFormat.getSplits(HiveInputFormat.java:486)
    at org.apache.hadoop.hive.ql.exec.tez.HiveSplitGenerator.initialize(HiveSplitGenerator.java:200)
    at org.apache.tez.dag.app.dag.RootInputInitializerManager$InputInitializerCallable$1.run(RootInputInitializerManager.java:278)
    at org.apache.tez.dag.app.dag.RootInputInitializerManager$InputInitializerCallable$1.run(RootInputInitializerManager.java:269)
    at java.security.AccessController.doPrivileged(Native Method)
    at javax.security.auth.Subject.doAs(Subject.java:422)
    at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1657)
    at org.apache.tez.dag.app.dag.RootInputInitializerManager$InputInitializerCallable.call(RootInputInitializerManager.java:269)
    at org.apache.tez.dag.app.dag.RootInputInitializerManager$InputInitializerCallable.call(RootInputInitializerManager.java:253)
    at java.util.concurrent.FutureTask.run(FutureTask.java:266)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
    at java.lang.Thread.run(Thread.java:745)
]Vertex killed, vertexName=Reducer 2, vertexId=vertex_1474097800415_0311_2_01, diagnostics=[Vertex received Kill in INITED state., Vertex vertex_1474097800415_0311_2_01 [Reducer 2] killed/failed due to:OTHER_VERTEX_FAILURE]DAG did not succeed due to VERTEX_FAILURE. failedVertices:1 killedVertices:1
    at org.apache.hive.jdbc.HiveStatement.waitForOperationToComplete(HiveStatement.java:348)
    at org.apache.hive.jdbc.HiveStatement.execute(HiveStatement.java:251)
    at com.XXX.YYY.executors.HiveQueryExecutor.executeQueriesInternal(HiveQueryExecutor.java:234)
    at com.XXX.YYY.executors.HiveQueryExecutor.executeQueriesMetricsEnabled(HiveQueryExecutor.java:184)
    at com.XXX.YYY.azkaban.jobexecutors.impl.AzkabanHiveQueryExecutor.run(AzkabanHiveQueryExecutor.java:68)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:606)
    at azkaban.jobtype.JavaJobRunnerMain.runMethod(JavaJobRunnerMain.java:192)
    at azkaban.jobtype.JavaJobRunnerMain.(JavaJobRunnerMain.java:132)
    at azkaban.jobtype.JavaJobRunnerMain.main(JavaJobRunnerMain.java:76)

配置单元配置属性,我在执行上述查询之前设置的-

set hivevar:hive.mapjoin.smalltable.filesize=2000000000
set hivevar:mapreduce.map.speculative=false
set hivevar:mapreduce.output.fileoutputformat.compress=true
set hivevar:hive.exec.compress.output=true
set hivevar:mapreduce.task.timeout=6000000
set hivevar:hive.optimize.bucketmapjoin.sortedmerge=true
set hivevar:io.compression.codecs=org.apache.hadoop.io.compress.GzipCodec
set hivevar:hive.input.format=org.apache.hadoop.hive.ql.io.BucketizedHiveInputFormat
set hivevar:hive.auto.convert.sortmerge.join.noconditionaltask=false
set hivevar:FEED_DATE=20160917
set hivevar:hive.optimize.bucketmapjoin=true
set hivevar:hive.exec.compress.intermediate=true
set hivevar:hive.enforce.bucketmapjoin=true
set hivevar:mapred.output.compress=true
set hivevar:mapreduce.map.output.compress=true
set hivevar:hive.auto.convert.sortmerge.join=false
set hivevar:hive.auto.convert.join=false
set hivevar:mapreduce.reduce.speculative=false
set hivevar:PD_KEY=vijay-test-mail@XXX.pagerduty.com
set hivevar:mapred.output.compression.codec=org.apache.hadoop.io.compress.GzipCodec
set hive.mapjoin.smalltable.filesize=2000000000
set mapreduce.map.speculative=false
set mapreduce.output.fileoutputformat.compress=true
set hive.exec.compress.output=true
set mapreduce.task.timeout=6000000
set hive.optimize.bucketmapjoin.sortedmerge=true
set io.compression.codecs=org.apache.hadoop.io.compress.GzipCodec
set hive.input.format=org.apache.hadoop.hive.ql.io.BucketizedHiveInputFormat
set hive.auto.convert.sortmerge.join.noconditionaltask=false
set FEED_DATE=20160917
set hive.optimize.bucketmapjoin=true
set hive.exec.compress.intermediate=true
set hive.enforce.bucketmapjoin=true 
set mapred.output.compress=true 
set mapreduce.map.output.compress=true 
set hive.auto.convert.sortmerge.join=false 
set hive.auto.convert.join=false 
set mapreduce.reduce.speculative=false 
set PD_KEY=vijay-test-mail@XXX.pagerduty.com 
set mapred.output.compression.codec=org.apache.hadoop.io.compress.GzipCodec

/etc/hive/conf/hive-site.xml

<configuration>

<!-- Hive Configuration can either be stored in this file or in the hadoop configuration files  -->
<!-- that are implied by Hadoop setup variables.                                                -->
<!-- Aside from Hadoop setup variables - this file is provided as a convenience so that Hive    -->
<!-- users do not have to edit hadoop configuration files (that may be managed as a centralized -->
<!-- resource).                                                                                 -->

<!-- Hive Execution Parameters -->

<property>
  <name>hbase.zookeeper.quorum</name>
  <value>ip-172-30-2-16.us-west-2.compute.internal</value>
  <description>http://wiki.apache.org/hadoop/Hive/HBaseIntegration</description>
</property>

<property>
  <name>hive.execution.engine</name>
  <value>tez</value>
</property>

  <property>
    <name>fs.defaultFS</name>
    <value>hdfs://ip-172-30-2-16.us-west-2.compute.internal:8020</value>
  </property>

  <property>
    <name>hive.metastore.uris</name>
    <value>thrift://ip-172-30-2-16.us-west-2.compute.internal:9083</value>
    <description>JDBC connect string for a JDBC metastore</description>
  </property>

  <property>
    <name>javax.jdo.option.ConnectionURL</name>
    <value>jdbc:mysql://ip-172-30-2-16.us-west-2.compute.internal:3306/hive?createDatabaseIfNotExist=true</value>
    <description>username to use against metastore database</description>
  </property>

  <property>
    <name>javax.jdo.option.ConnectionDriverName</name>
    <value>org.mariadb.jdbc.Driver</value>
    <description>username to use against metastore database</description>
  </property>

  <property>
    <name>javax.jdo.option.ConnectionUserName</name>
    <value>hive</value>
    <description>username to use against metastore database</description>
  </property>

  <property>
    <name>javax.jdo.option.ConnectionPassword</name>
    <value>mrN949zY9P2riCeY</value>
    <description>password to use against metastore database</description>
  </property>

  <property>
    <name>datanucleus.fixedDatastore</name>
    <value>true</value>
  </property>

  <property>
    <name>mapred.reduce.tasks</name>
    <value>-1</value>
  </property>

  <property>
    <name>mapred.max.split.size</name>
    <value>256000000</value>
  </property>

  <property>
    <name>hive.metastore.connect.retries</name>
    <value>15</value>
  </property>

  <property>
    <name>hive.optimize.sort.dynamic.partition</name>
    <value>true</value>
  </property>

  <property>
    <name>hive.async.log.enabled</name>
    <value>false</value>
  </property>

</configuration>

/etc/tez/conf/tez-site.xml文件

<configuration>
    <property>
    <name>tez.lib.uris</name>
    <value>hdfs:///apps/tez/tez.tar.gz</value>
  </property>

  <property>
    <name>tez.use.cluster.hadoop-libs</name>
    <value>true</value>
  </property>

  <property>
    <name>tez.am.grouping.max-size</name>
    <value>134217728</value>
  </property>

  <property>
    <name>tez.runtime.intermediate-output.should-compress</name>
    <value>true</value>
  </property>

  <property>
    <name>tez.runtime.intermediate-input.is-compressed</name>
    <value>true</value>
  </property>

  <property>
    <name>tez.runtime.intermediate-output.compress.codec</name>
    <value>org.apache.hadoop.io.compress.LzoCodec</value>
  </property>

  <property>
    <name>tez.runtime.intermediate-input.compress.codec</name>
    <value>org.apache.hadoop.io.compress.LzoCodec</value>
  </property>

  <property>
    <name>tez.history.logging.service.class</name>
    <value>org.apache.tez.dag.history.logging.ats.ATSHistoryLoggingService</value>
  </property>

  <property>
    <name>tez.tez-ui.history-url.base</name>
    <value>http://ip-172-30-2-16.us-west-2.compute.internal:8080/tez-ui/</value>
  </property>
</configuration>

问题-
哪个进程删除了这个文件?对于配置单元,此文件只应存在(此外,此文件不是由应用程序代码创建的。)
当我多次运行失败的查询时,它通过了。为什么会有暧昧的行为?
因为,我刚刚升级了hiveexec,hivejdbc版本到2.1.0。因此,似乎某些配置单元配置属性设置错误或缺少某些属性。你能帮我找到错误设置/丢失的配置单元属性吗?
注意-我将hive exec版本从0.13.0升级到了2.1.0。在以前的版本中,所有查询都可以正常工作。
更新-1
当我启动另一个集群时,它运行得很好。我在同一个etl上测试了3次。
当我在newcluster上再次执行相同的操作时,它显示了相同的异常。无法理解,为什么会出现这种歧义。
帮助我理解这种模糊性。
我对付Hive很幼稚。所以,对这个概念的理解要少一些。
更新-2-
集群公共dns下的hfs日志name:50070 - 2016-09-20 11:31:55,155 WARN org.apache.hadoop.hdfs.server.blockmanagement.BlockPlacementPolicy (IPC Server handler 11 on 8020): Failed to place enough replicas, still in need of 1 to reach 1 (unavailableStorages=[], storagePolicy=BlockStoragePolicy{HOT:7, storageTypes=[DISK], creationFallbacks=[], replicationFallbacks=[ARCHIVE]}, newBlock=true) For more information, please enable DEBUG log level on org.apache.hadoop.hdfs.server.blockmanagement.BlockPlacementPolicy 2016-09-20 11:31:55,155 WARN org.apache.hadoop.hdfs.protocol.BlockStoragePolicy (IPC Server handler 11 on 8020): Failed to place enough replicas: expected size is 1 but only 0 storage types can be selected (replication=1, selected=[], unavailable=[DISK], removed=[DISK], policy=BlockStoragePolicy{HOT:7, storageTypes=[DISK], creationFallbacks=[], replicationFallbacks=[ARCHIVE]}) 2016-09-20 11:31:55,155 WARN org.apache.hadoop.hdfs.server.blockmanagement.BlockPlacementPolicy (IPC Server handler 11 on 8020): Failed to place enough replicas, still in need of 1 to reach 1 (unavailableStorages=[DISK], storagePolicy=BlockStoragePolicy{HOT:7, storageTypes=[DISK], creationFallbacks=[], replicationFallbacks=[ARCHIVE]}, newBlock=true) All required storage types are unavailable: unavailableStorages=[DISK], storagePolicy=BlockStoragePolicy{HOT:7, storageTypes=[DISK], creationFallbacks=[], replicationFallbacks=[ARCHIVE]} 2016-09-20 11:31:55,155 INFO org.apache.hadoop.ipc.Server (IPC Server handler 11 on 8020): IPC Server handler 11 on 8020, call org.apache.hadoop.hdfs.protocol.ClientProtocol.addBlock from 172.30.2.207:56462 Call#7497 Retry#0 java.io.IOException: File /user/hive/warehouse/bc_kmart_3813.db/dp_internal_temp_full_load_offer_flexibility_20160920/.hive-staging_hive_2016-09-20_11-17-51_558_1222354063413369813-58/_task_tmp.-ext-10000/_tmp.000079_0 could only be replicated to 0 nodes instead of minReplication (=1). There are 1 datanode(s) running and no node(s) are excluded in this operation. at org.apache.hadoop.hdfs.server.blockmanagement.BlockManager.chooseTarget4NewBlock(BlockManager.java:1547) at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.getNewBlockTargets(FSNamesystem.java:3107) at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.getAdditionalBlock(FSNamesystem.java:3031) at org.apache.hadoop.hdfs.server.namenode.NameNodeRpcServer.addBlock(NameNodeRpcServer.java:724) at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolServerSideTranslatorPB.addBlock(ClientNamenodeProtocolServerSideTranslatorPB.java:492) at org.apache.hadoop.hdfs.protocol.proto.ClientNamenodeProtocolProtos$ClientNamenodeProtocol$2.callBlockingMethod(ClientNamenodeProtocolProtos.java) at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:616) at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:969) at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2049) at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2045) at java.security.AccessController.doPrivileged(Native Method) at javax.security.auth.Subject.doAs(Subject.java:422) at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1657) at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2043) 当我搜索这个例外的时候。我找到了这一页-https://wiki.apache.org/hadoop/couldonlybereplicatedto
在我的群集中,有一个数据节点有32 gb的磁盘空间。

/etc/hive/conf/hive-default.xml.template-

<property>
    <name>hive.exec.stagingdir</name>
    <value>.hive-staging</value>
    <description>Directory name that will be created inside table locations in order to support HDFS encryption. This is replaces ${hive.exec.scratchdir} for query results with the exception of read-only tables. In all cases ${hive.exec.scratchdir} is still used for other temporary files, such as job plans.</description>
  </property>

问题-
根据logs,hive staging folder是在cluster machine中创建的,如/var/log/hadoop hdfs/hadoop-hdfs-datanode-ip-172-30-2-189.log,那么为什么它也在s3中创建相同的文件夹呢?
更新-3-
有些异常属于-leaseexpiredexception类型- 2016-09-21 08:53:17,995 INFO org.apache.hadoop.ipc.Server (IPC Server handler 13 on 8020): IPC Server handler 13 on 8020, call org.apache.hadoop.hdfs.protocol.ClientProtocol.complete from 172.30.2.189:42958 Call#726 Retry#0: org.apache.hadoop.hdfs.server.namenode.LeaseExpiredException: No lease on /tmp/hive/hadoop/_tez_session_dir/6ebd2d18-f5b9-4176-ab8f-d6c78124b636/.tez/application_1474442135017_0022/recovery/1/summary (inode 20326): File does not exist. Holder DFSClient_NONMAPREDUCE_1375788009_1 does not have any open files.

2ic8powd

2ic8powd1#

根本原因是当hadoop仍在尝试写入文件时,该文件被从不同的会话中删除。

w1e3prcc

w1e3prcc2#

我解决了这个问题。让我详细解释一下。
即将到来的例外-
leaveExpiredException-从hdfs端。
filenotfoundexception-从配置单元端(当tez执行引擎执行dag时)
问题场景-
我们刚刚将hive版本从0.13.0升级到2.1.0。而且,以前的版本一切正常。零运行时异常。
解决问题的不同想法-
第一个想法是,由于nn智能,两个线程在同一块上工作。但根据以下设置
set mapreduce.map.投机性=false设置mapreduce.reduce.投机性=false
那是不可能的。
然后,我将以下设置的计数从1000增加到100000-
设置hive.exec.max.dynamic.partitions=100000;设置hive.exec.max.dynamic.partitions.pernode=100000;
那也没用。
第三个想法是,肯定是在同一个过程中,mapper-1被另一个mapper/reducer删除了。但是,我们在hveserver2中没有发现任何这样的日志,tez日志。
最后,根本原因在于应用层代码本身。在hive-exec-2.1.0版本中,他们引入了新的配置属性
“hive.exec.stagingdir”:“.hive staging”
上述财产的说明-
将在表位置内创建的目录名,以支持hdfs加密。这将替换${hive.exec.scratchdir}作为查询结果,只读表除外。在所有情况下,${hive.exec.scratchdir}仍然用于其他临时文件,例如作业计划。
因此,如果在应用层代码(etl)中存在任何并发作业,并且在同一个表上执行操作(rename/delete/move),则可能会导致此问题。
而且,在我们的例子中,两个并发作业在同一个表上执行“插入覆盖”,这导致删除1个Map器的元数据文件,这就是导致此问题的原因。
分辨率-
将元数据文件位置移到表外(表位于s3中)。
禁用hdfs加密(如stagingdir属性的描述中所述)
更改为应用程序层代码以避免并发问题。

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