JobTracker - 高内存和本机线程使用
JobTracker - High memory and native thread usage
我们是 运行 GCE 上的 hadoop，具有 HDFS 默认文件系统，数据 input/output from/to GCS。
Hadoop 版本：1.2.1
连接器版本：com.google.cloud.bigdataoss:gcs-connector:1.3.0-hadoop1
观察到的行为：JT会堆积等待状态的线程，导致OOM：
2015-02-06 14:15:51,206 ERROR org.apache.hadoop.mapred.JobTracker: Job initialization failed:
java.lang.OutOfMemoryError: unable to create new native thread
at java.lang.Thread.start0(Native Method)
at java.lang.Thread.start(Thread.java:714)
at java.util.concurrent.ThreadPoolExecutor.addWorker(ThreadPoolExecutor.java:949)
at java.util.concurrent.ThreadPoolExecutor.execute(ThreadPoolExecutor.java:1371)
at com.google.cloud.hadoop.util.AbstractGoogleAsyncWriteChannel.initialize(AbstractGoogleAsyncWriteChannel.java:318)
at com.google.cloud.hadoop.gcsio.GoogleCloudStorageImpl.create(GoogleCloudStorageImpl.java:275)
at com.google.cloud.hadoop.gcsio.CacheSupplementedGoogleCloudStorage.create(CacheSupplementedGoogleCloudStorage.java:145)
at com.google.cloud.hadoop.gcsio.GoogleCloudStorageFileSystem.createInternal(GoogleCloudStorageFileSystem.java:184)
at com.google.cloud.hadoop.gcsio.GoogleCloudStorageFileSystem.create(GoogleCloudStorageFileSystem.java:168)
at com.google.cloud.hadoop.fs.gcs.GoogleHadoopOutputStream.<init>(GoogleHadoopOutputStream.java:77)
at com.google.cloud.hadoop.fs.gcs.GoogleHadoopFileSystemBase.create(GoogleHadoopFileSystemBase.java:655)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:564)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:545)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:452)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:444)
at org.apache.hadoop.mapred.JobHistory$JobInfo.logSubmitted(JobHistory.java:1860)
at org.apache.hadoop.mapred.JobInProgress.run(JobInProgress.java:709)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:415)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1190)
at org.apache.hadoop.mapred.JobInProgress.initTasks(JobInProgress.java:706)
at org.apache.hadoop.mapred.JobTracker.initJob(Jobenter code hereTracker.java:3890)
at org.apache.hadoop.mapred.EagerTaskInitializationListener$InitJob.run(EagerTaskInitializationListener.java:79)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
查看 JT 日志后，我发现了这些警告：
2015-02-06 14:30:17,442 WARN org.apache.hadoop.hdfs.DFSClient: Failed recovery attempt #0 from primary datanode xx.xxx.xxx.xxx:50010
java.io.IOException: Call to /xx.xxx.xxx.xxx:50020 failed on local exception: java.io.IOException: Couldn't set up IO streams
at org.apache.hadoop.ipc.Client.wrapException(Client.java:1150)
at org.apache.hadoop.ipc.Client.call(Client.java:1118)
at org.apache.hadoop.ipc.RPC$Invoker.invoke(RPC.java:229)
at com.sun.proxy.$Proxy10.getProtocolVersion(Unknown Source)
at org.apache.hadoop.ipc.RPC.checkVersion(RPC.java:422)
at org.apache.hadoop.ipc.RPC.getProxy(RPC.java:414)
at org.apache.hadoop.ipc.RPC.getProxy(RPC.java:392)
at org.apache.hadoop.hdfs.DFSClient.createClientDatanodeProtocolProxy(DFSClient.java:201)
at org.apache.hadoop.hdfs.DFSClient$DFSOutputStream.processDatanodeError(DFSClient.java:3317)
at org.apache.hadoop.hdfs.DFSClient$DFSOutputStream.access00(DFSClient.java:2783)
at org.apache.hadoop.hdfs.DFSClient$DFSOutputStream$DataStreamer.run(DFSClient.java:2987)
Caused by: java.io.IOException: Couldn't set up IO streams
at org.apache.hadoop.ipc.Client$Connection.setupIOstreams(Client.java:642)
at org.apache.hadoop.ipc.Client$Connection.access00(Client.java:205)
at org.apache.hadoop.ipc.Client.getConnection(Client.java:1249)
at org.apache.hadoop.ipc.Client.call(Client.java:1093)
... 9 more
Caused by: java.lang.OutOfMemoryError: unable to create new native thread
at java.lang.Thread.start0(Native Method)
at java.lang.Thread.start(Thread.java:714)
at org.apache.hadoop.ipc.Client$Connection.setupIOstreams(Client.java:635)
... 12 more
这似乎与此处的 hadoop 错误报告器相似：https://issues.apache.org/jira/browse/MAPREDUCE-5606
我通过禁用将作业日志保存到输出路径尝试了建议的解决方案，它以丢失日志为代价解决了问题:)
我还在 JT 上 运行 jstack，它显示了数百个 WAITING 或 TIMED_WAITING 线程：
pool-52-thread-1" prio=10 tid=0x00007feaec581000 nid=0x524f in Object.wait() [0x00007fead39b3000]
java.lang.Thread.State: TIMED_WAITING (on object monitor)
at java.lang.Object.wait(Native Method)
- waiting on <0x000000074d86ba60> (a java.io.PipedInputStream)
at java.io.PipedInputStream.read(PipedInputStream.java:327)
- locked <0x000000074d86ba60> (a java.io.PipedInputStream)
at java.io.PipedInputStream.read(PipedInputStream.java:378)
- locked <0x000000074d86ba60> (a java.io.PipedInputStream)
at com.google.api.client.util.ByteStreams.read(ByteStreams.java:181)
at com.google.api.client.googleapis.media.MediaHttpUploader.setContentAndHeadersOnCurrentReque
st(MediaHttpUploader.java:629)
at com.google.api.client.googleapis.media.MediaHttpUploader.resumableUpload(MediaHttpUploader.
java:409)
at com.google.api.client.googleapis.media.MediaHttpUploader.upload(MediaHttpUploader.java:336)
at com.google.api.client.googleapis.services.AbstractGoogleClientRequest.executeUnparsed(Abstr
actGoogleClientRequest.java:419)
at com.google.api.client.googleapis.services.AbstractGoogleClientRequest.executeUnparsed(Abstr
actGoogleClientRequest.java:343)
at com.google.api.client.googleapis.services.AbstractGoogleClientRequest.execute(AbstractGoogl
eClientRequest.java:460)
at com.google.cloud.hadoop.util.AbstractGoogleAsyncWriteChannel$UploadOperation.run(AbstractGo
ogleAsyncWriteChannel.java:354)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
Locked ownable synchronizers:
- <0x000000074d864918> (a java.util.concurrent.ThreadPoolExecutor$Worker)
JT 似乎很难通过 GCS 连接器与 GCS 保持通信。
请指教，
谢谢
目前，Hadoop 的 GCS 连接器中的每个打开 FSDataOutputStream 都会消耗一个线程，直到它关闭，因为一个单独的线程需要 运行 "resumable" HttpRequests 而用户的 OutputStream 间歇性地写入字节。在大多数情况下（例如在单个 Hadoop 任务中），只有一个长寿命的输出流，可能还有一些短寿命的用于写入小 metadata/marker 文件等
一般来说，您 运行 遇到的 OOM 可能有两个原因：
- 您有很多工作在排队；每个提交的作业都持有一个未关闭的 OutputStream，因此消耗一个 "waiting" 线程。但是，既然你提到你只需要排队 ~10 个工作，这不应该是根本原因。
- 某些原因导致 "leak" 最初在 logSubmitted and added to fileManager. Typically, terminal events (like logFinished will correctly close() all the PrintWriters before removing them from the map via
markCompleted, but in theory they may be bugs here or there which can cause one of the OutputStreams to leak without being close()'d. For example, while I haven't had a chance to verify this assertion, it seems that IOException trying to do something like logMetaInfo will "removeWriter" without closing it 中创建的 PrintWriter 对象。
我已经验证至少在正常情况下，OutputStream 似乎正确关闭，并且我的示例 JobTracker 在成功 运行 大量作业后显示干净的 jstack。
TL;DR：关于为什么某些资源可能会泄漏并最终阻止创建必要的线程，有一些工作理论。同时，您应该考虑将 hadoop.job.history.user.location 更改为某个 HDFS 位置，作为在没有将作业日志放置在 GCS 上的情况下保留作业日志的一种方式。
我们是 运行 GCE 上的 hadoop，具有 HDFS 默认文件系统，数据 input/output from/to GCS。
Hadoop 版本：1.2.1 连接器版本：com.google.cloud.bigdataoss:gcs-connector:1.3.0-hadoop1
观察到的行为：JT会堆积等待状态的线程，导致OOM：
2015-02-06 14:15:51,206 ERROR org.apache.hadoop.mapred.JobTracker: Job initialization failed:
java.lang.OutOfMemoryError: unable to create new native thread
at java.lang.Thread.start0(Native Method)
at java.lang.Thread.start(Thread.java:714)
at java.util.concurrent.ThreadPoolExecutor.addWorker(ThreadPoolExecutor.java:949)
at java.util.concurrent.ThreadPoolExecutor.execute(ThreadPoolExecutor.java:1371)
at com.google.cloud.hadoop.util.AbstractGoogleAsyncWriteChannel.initialize(AbstractGoogleAsyncWriteChannel.java:318)
at com.google.cloud.hadoop.gcsio.GoogleCloudStorageImpl.create(GoogleCloudStorageImpl.java:275)
at com.google.cloud.hadoop.gcsio.CacheSupplementedGoogleCloudStorage.create(CacheSupplementedGoogleCloudStorage.java:145)
at com.google.cloud.hadoop.gcsio.GoogleCloudStorageFileSystem.createInternal(GoogleCloudStorageFileSystem.java:184)
at com.google.cloud.hadoop.gcsio.GoogleCloudStorageFileSystem.create(GoogleCloudStorageFileSystem.java:168)
at com.google.cloud.hadoop.fs.gcs.GoogleHadoopOutputStream.<init>(GoogleHadoopOutputStream.java:77)
at com.google.cloud.hadoop.fs.gcs.GoogleHadoopFileSystemBase.create(GoogleHadoopFileSystemBase.java:655)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:564)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:545)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:452)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:444)
at org.apache.hadoop.mapred.JobHistory$JobInfo.logSubmitted(JobHistory.java:1860)
at org.apache.hadoop.mapred.JobInProgress.run(JobInProgress.java:709)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:415)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1190)
at org.apache.hadoop.mapred.JobInProgress.initTasks(JobInProgress.java:706)
at org.apache.hadoop.mapred.JobTracker.initJob(Jobenter code hereTracker.java:3890)
at org.apache.hadoop.mapred.EagerTaskInitializationListener$InitJob.run(EagerTaskInitializationListener.java:79)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
查看 JT 日志后，我发现了这些警告：
2015-02-06 14:30:17,442 WARN org.apache.hadoop.hdfs.DFSClient: Failed recovery attempt #0 from primary datanode xx.xxx.xxx.xxx:50010
java.io.IOException: Call to /xx.xxx.xxx.xxx:50020 failed on local exception: java.io.IOException: Couldn't set up IO streams
at org.apache.hadoop.ipc.Client.wrapException(Client.java:1150)
at org.apache.hadoop.ipc.Client.call(Client.java:1118)
at org.apache.hadoop.ipc.RPC$Invoker.invoke(RPC.java:229)
at com.sun.proxy.$Proxy10.getProtocolVersion(Unknown Source)
at org.apache.hadoop.ipc.RPC.checkVersion(RPC.java:422)
at org.apache.hadoop.ipc.RPC.getProxy(RPC.java:414)
at org.apache.hadoop.ipc.RPC.getProxy(RPC.java:392)
at org.apache.hadoop.hdfs.DFSClient.createClientDatanodeProtocolProxy(DFSClient.java:201)
at org.apache.hadoop.hdfs.DFSClient$DFSOutputStream.processDatanodeError(DFSClient.java:3317)
at org.apache.hadoop.hdfs.DFSClient$DFSOutputStream.access00(DFSClient.java:2783)
at org.apache.hadoop.hdfs.DFSClient$DFSOutputStream$DataStreamer.run(DFSClient.java:2987)
Caused by: java.io.IOException: Couldn't set up IO streams
at org.apache.hadoop.ipc.Client$Connection.setupIOstreams(Client.java:642)
at org.apache.hadoop.ipc.Client$Connection.access00(Client.java:205)
at org.apache.hadoop.ipc.Client.getConnection(Client.java:1249)
at org.apache.hadoop.ipc.Client.call(Client.java:1093)
... 9 more
Caused by: java.lang.OutOfMemoryError: unable to create new native thread
at java.lang.Thread.start0(Native Method)
at java.lang.Thread.start(Thread.java:714)
at org.apache.hadoop.ipc.Client$Connection.setupIOstreams(Client.java:635)
... 12 more
这似乎与此处的 hadoop 错误报告器相似：https://issues.apache.org/jira/browse/MAPREDUCE-5606
我通过禁用将作业日志保存到输出路径尝试了建议的解决方案，它以丢失日志为代价解决了问题:)
我还在 JT 上 运行 jstack，它显示了数百个 WAITING 或 TIMED_WAITING 线程：
pool-52-thread-1" prio=10 tid=0x00007feaec581000 nid=0x524f in Object.wait() [0x00007fead39b3000]
java.lang.Thread.State: TIMED_WAITING (on object monitor)
at java.lang.Object.wait(Native Method)
- waiting on <0x000000074d86ba60> (a java.io.PipedInputStream)
at java.io.PipedInputStream.read(PipedInputStream.java:327)
- locked <0x000000074d86ba60> (a java.io.PipedInputStream)
at java.io.PipedInputStream.read(PipedInputStream.java:378)
- locked <0x000000074d86ba60> (a java.io.PipedInputStream)
at com.google.api.client.util.ByteStreams.read(ByteStreams.java:181)
at com.google.api.client.googleapis.media.MediaHttpUploader.setContentAndHeadersOnCurrentReque
st(MediaHttpUploader.java:629)
at com.google.api.client.googleapis.media.MediaHttpUploader.resumableUpload(MediaHttpUploader.
java:409)
at com.google.api.client.googleapis.media.MediaHttpUploader.upload(MediaHttpUploader.java:336)
at com.google.api.client.googleapis.services.AbstractGoogleClientRequest.executeUnparsed(Abstr
actGoogleClientRequest.java:419)
at com.google.api.client.googleapis.services.AbstractGoogleClientRequest.executeUnparsed(Abstr
actGoogleClientRequest.java:343)
at com.google.api.client.googleapis.services.AbstractGoogleClientRequest.execute(AbstractGoogl
eClientRequest.java:460)
at com.google.cloud.hadoop.util.AbstractGoogleAsyncWriteChannel$UploadOperation.run(AbstractGo
ogleAsyncWriteChannel.java:354)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
Locked ownable synchronizers:
- <0x000000074d864918> (a java.util.concurrent.ThreadPoolExecutor$Worker)
JT 似乎很难通过 GCS 连接器与 GCS 保持通信。
请指教，
谢谢
目前，Hadoop 的 GCS 连接器中的每个打开 FSDataOutputStream 都会消耗一个线程，直到它关闭，因为一个单独的线程需要 运行 "resumable" HttpRequests 而用户的 OutputStream 间歇性地写入字节。在大多数情况下（例如在单个 Hadoop 任务中），只有一个长寿命的输出流，可能还有一些短寿命的用于写入小 metadata/marker 文件等
一般来说，您 运行 遇到的 OOM 可能有两个原因：
- 您有很多工作在排队；每个提交的作业都持有一个未关闭的 OutputStream，因此消耗一个 "waiting" 线程。但是，既然你提到你只需要排队 ~10 个工作，这不应该是根本原因。
- 某些原因导致 "leak" 最初在 logSubmitted and added to fileManager. Typically, terminal events (like logFinished will correctly close() all the PrintWriters before removing them from the map via
markCompleted, but in theory they may be bugs here or there which can cause one of the OutputStreams to leak without being close()'d. For example, while I haven't had a chance to verify this assertion, it seems that IOException trying to do something like logMetaInfo will "removeWriter" without closing it 中创建的 PrintWriter 对象。
我已经验证至少在正常情况下，OutputStream 似乎正确关闭，并且我的示例 JobTracker 在成功 运行 大量作业后显示干净的 jstack。
TL;DR：关于为什么某些资源可能会泄漏并最终阻止创建必要的线程，有一些工作理论。同时，您应该考虑将 hadoop.job.history.user.location 更改为某个 HDFS 位置，作为在没有将作业日志放置在 GCS 上的情况下保留作业日志的一种方式。