GCP存储中的文件名重复

时间:2019-03-14 21:26:03

标签: java google-cloud-platform google-cloud-storage google-cloud-dataflow

我正在将文件流式传输到GCP存储(存储桶)。这样做会导致经常发生错误(每天大约2百万次),该错误声称我的文件名策略必须生成一个唯一的名称。我尝试了多种方法来保证唯一名称,例如使用currentTimeMillis,currentThread,加密文件名等。它们在以相同频率返回之前,每天都会出现几个小时的时间来消除错误。我没有遇到文件丢失的情况,但是我也没有进行广泛的搜索。这是我的作家:

pipeline.apply("Read PubSub Events", PubsubIO.readMessagesWithAttributes().fromSubscription(options.getInputSubscription())) 
                    .apply(options.getWindowDuration() + " Window",
                                Window.<PubsubMessage>into(FixedWindows.of(parseDuration(options.getWindowDuration())))
                                    .triggering(AfterWatermark.pastEndOfWindow())
                                    .discardingFiredPanes()
                                    .withAllowedLateness(parseDuration("24h")))
                    .apply(new GenericFunctions.extractMsg())
                    .apply(FileIO.<String, String>writeDynamic()
                            .by(new datePartition(options.getOutputFilenamePrefix()))
                            .via(TextIO.sink())
                            .withNumShards(options.getNumShards())
                            .to(options.getOutputDirectory())
                            .withNaming(type -> FileIO.Write.defaultNaming(type, ".txt"))
                            .withDestinationCoder(StringUtf8Coder.of())); 

如果需要,我可以详细说明我们使用的所有非Google方法。这是StackDriver返回的错误的现象:

exception:  "java.lang.RuntimeException: org.apache.beam.sdk.util.UserCodeException: java.lang.IllegalArgumentException: Filename policy must generate unique filenames, but generated the same name gs://myBucket/myProject/2019/01/21/13h/myProject-2123065519-2019-01-21T12:58:00.000Z-2019-01-21T13:00:00.000Z-00000-of-00001.txt for file results FileResult{tempFilename=gs://myBucket/myProject/.temp-beam-2019-01-17_20-30-37-1/2e2c99ef-6508-4f10-ada4-e5c108b1d884, shard=0, window=[2019-01-21T12:58:00.000Z..2019-01-21T13:00:00.000Z), paneInfo=PaneInfo{isFirst=true, isLast=true, timing=ON_TIME, index=0, onTimeIndex=0}} and FileResult{tempFilename=gs://myBucket/myProject/.temp-beam-2019-01-17_20-30-37-1/2112c27f-8e0c-4831-b3fe-fbefe9ed560e, shard=0, window=[2019-01-21T12:58:00.000Z..2019-01-21T13:00:00.000Z), paneInfo=PaneInfo{isFirst=true, isLast=true, timing=ON_TIME, index=0, onTimeIndex=0}}
    at org.apache.beam.runners.dataflow.worker.GroupAlsoByWindowsParDoFn$1.output(GroupAlsoByWindowsParDoFn.java:185)
    at org.apache.beam.runners.dataflow.worker.GroupAlsoByWindowFnRunner$1.outputWindowedValue(GroupAlsoByWindowFnRunner.java:102)
    at org.apache.beam.runners.dataflow.worker.StreamingGroupAlsoByWindowReshuffleFn.processElement(StreamingGroupAlsoByWindowReshuffleFn.java:58)
    at org.apache.beam.runners.dataflow.worker.StreamingGroupAlsoByWindowReshuffleFn.processElement(StreamingGroupAlsoByWindowReshuffleFn.java:40)
    at org.apache.beam.runners.dataflow.worker.GroupAlsoByWindowFnRunner.invokeProcessElement(GroupAlsoByWindowFnRunner.java:115)
    at org.apache.beam.runners.dataflow.worker.GroupAlsoByWindowFnRunner.processElement(GroupAlsoByWindowFnRunner.java:73)
    at org.apache.beam.runners.dataflow.worker.GroupAlsoByWindowsParDoFn.processElement(GroupAlsoByWindowsParDoFn.java:135)
    at org.apache.beam.runners.dataflow.worker.util.common.worker.ParDoOperation.process(ParDoOperation.java:45)
    at org.apache.beam.runners.dataflow.worker.util.common.worker.OutputReceiver.process(OutputReceiver.java:50)
    at org.apache.beam.runners.dataflow.worker.util.common.worker.ReadOperation.runReadLoop(ReadOperation.java:202)
    at org.apache.beam.runners.dataflow.worker.util.common.worker.ReadOperation.start(ReadOperation.java:160)
    at org.apache.beam.runners.dataflow.worker.util.common.worker.MapTaskExecutor.execute(MapTaskExecutor.java:77)
    at org.apache.beam.runners.dataflow.worker.StreamingDataflowWorker.process(StreamingDataflowWorker.java:1226)
    at org.apache.beam.runners.dataflow.worker.StreamingDataflowWorker.access$1000(StreamingDataflowWorker.java:141)
    at org.apache.beam.runners.dataflow.worker.StreamingDataflowWorker$6.run(StreamingDataflowWorker.java:965)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
    at java.lang.Thread.run(Thread.java:745)
Caused by: org.apache.beam.sdk.util.UserCodeException: java.lang.IllegalArgumentException: Filename policy must generate unique filenames, but generated the same name gs://myBucket/myProject/2019/01/21/13h/myProject-2123065519-2019-01-21T12:58:00.000Z-2019-01-21T13:00:00.000Z-00000-of-00001.txt for file results FileResult{tempFilename=gs://myBucket/myProject/.temp-beam-2019-01-17_20-30-37-1/2e2c99ef-6508-4f10-ada4-e5c108b1d884, shard=0, window=[2019-01-21T12:58:00.000Z..2019-01-21T13:00:00.000Z), paneInfo=PaneInfo{isFirst=true, isLast=true, timing=ON_TIME, index=0, onTimeIndex=0}} and FileResult{tempFilename=gs://myBucket/myProject/.temp-beam-2019-01-17_20-30-37-1/2112c27f-8e0c-4831-b3fe-fbefe9ed560e, shard=0, window=[2019-01-21T12:58:00.000Z..2019-01-21T13:00:00.000Z), paneInfo=PaneInfo{isFirst=true, isLast=true, timing=ON_TIME, index=0, onTimeIndex=0}}
    at org.apache.beam.sdk.util.UserCodeException.wrap(UserCodeException.java:34)
    at org.apache.beam.sdk.io.WriteFiles$FinalizeTempFileBundles$FinalizeFn$DoFnInvoker.invokeProcessElement(Unknown Source)
    at org.apache.beam.runners.core.SimpleDoFnRunner.invokeProcessElement(SimpleDoFnRunner.java:275)
    at org.apache.beam.runners.core.SimpleDoFnRunner.processElement(SimpleDoFnRunner.java:240)
    at org.apache.beam.runners.dataflow.worker.SimpleParDoFn.processElement(SimpleParDoFn.java:326)
    at org.apache.beam.runners.dataflow.worker.util.common.worker.ParDoOperation.process(ParDoOperation.java:45)
    at org.apache.beam.runners.dataflow.worker.util.common.worker.OutputReceiver.process(OutputReceiver.java:50)
    at org.apache.beam.runners.dataflow.worker.SimpleParDoFn$1.output(SimpleParDoFn.java:273)
    at org.apache.beam.runners.core.SimpleDoFnRunner.outputWindowedValue(SimpleDoFnRunner.java:309)
    at org.apache.beam.runners.core.SimpleDoFnRunner.access$700(SimpleDoFnRunner.java:77)
    at org.apache.beam.runners.core.SimpleDoFnRunner$DoFnProcessContext.output(SimpleDoFnRunner.java:621)
    at org.apache.beam.sdk.transforms.DoFnOutputReceivers$WindowedContextOutputReceiver.output(DoFnOutputReceivers.java:71)
    at org.apache.beam.sdk.transforms.MapElements$1.processElement(MapElements.java:128)
    at org.apache.beam.sdk.transforms.MapElements$1$DoFnInvoker.invokeProcessElement(Unknown Source)
    at org.apache.beam.runners.core.SimpleDoFnRunner.invokeProcessElement(SimpleDoFnRunner.java:275)
    at org.apache.beam.runners.core.SimpleDoFnRunner.processElement(SimpleDoFnRunner.java:240)
    at org.apache.beam.runners.dataflow.worker.SimpleParDoFn.processElement(SimpleParDoFn.java:326)
    at org.apache.beam.runners.dataflow.worker.util.common.worker.ParDoOperation.process(ParDoOperation.java:45)
    at org.apache.beam.runners.dataflow.worker.util.common.worker.OutputReceiver.process(OutputReceiver.java:50)
    at org.apache.beam.runners.dataflow.worker.SimpleParDoFn$1.output(SimpleParDoFn.java:273)
    at org.apache.beam.runners.core.SimpleDoFnRunner.outputWindowedValue(SimpleDoFnRunner.java:309)
    at org.apache.beam.runners.core.SimpleDoFnRunner.access$700(SimpleDoFnRunner.java:77)
    at org.apache.beam.runners.core.SimpleDoFnRunner$DoFnProcessContext.output(SimpleDoFnRunner.java:621)
    at org.apache.beam.runners.core.SimpleDoFnRunner$DoFnProcessContext.output(SimpleDoFnRunner.java:609)
    at org.apache.beam.runners.dataflow.ReshuffleOverrideFactory$ReshuffleWithOnlyTrigger$1.processElement(ReshuffleOverrideFactory.java:85)
    at org.apache.beam.runners.dataflow.ReshuffleOverrideFactory$ReshuffleWithOnlyTrigger$1$DoFnInvoker.invokeProcessElement(Unknown Source)
    at org.apache.beam.runners.core.SimpleDoFnRunner.invokeProcessElement(SimpleDoFnRunner.java:275)
    at org.apache.beam.runners.core.SimpleDoFnRunner.processElement(SimpleDoFnRunner.java:240)
    at org.apache.beam.runners.dataflow.worker.SimpleParDoFn.processElement(SimpleParDoFn.java:326)
    at org.apache.beam.runners.dataflow.worker.util.common.worker.ParDoOperation.process(ParDoOperation.java:45)
    at org.apache.beam.runners.dataflow.worker.util.common.worker.OutputReceiver.process(OutputReceiver.java:50)
    at org.apache.beam.runners.dataflow.worker.GroupAlsoByWindowsParDoFn$1.output(GroupAlsoByWindowsParDoFn.java:183)
    ... 17 more
Caused by: java.lang.IllegalArgumentException: Filename policy must generate unique filenames, but generated the same name gs://myBucket/myProject/2019/01/21/13h/myProject-2123065519-2019-01-21T12:58:00.000Z-2019-01-21T13:00:00.000Z-00000-of-00001.txt for file results FileResult{tempFilename=gs://myBucket/myProject/.temp-beam-2019-01-17_20-30-37-1/2e2c99ef-6508-4f10-ada4-e5c108b1d884, shard=0, window=[2019-01-21T12:58:00.000Z..2019-01-21T13:00:00.000Z), paneInfo=PaneInfo{isFirst=true, isLast=true, timing=ON_TIME, index=0, onTimeIndex=0}} and FileResult{tempFilename=gs://myBucket/myProject/.temp-beam-2019-01-17_20-30-37-1/2112c27f-8e0c-4831-b3fe-fbefe9ed560e, shard=0, window=[2019-01-21T12:58:00.000Z..2019-01-21T13:00:00.000Z), paneInfo=PaneInfo{isFirst=true, isLast=true, timing=ON_TIME, index=0, onTimeIndex=0}}
    at org.apache.beam.repackaged.beam_sdks_java_core.com.google.common.base.Preconditions.checkArgument(Preconditions.java:399)
    at org.apache.beam.sdk.io.FileBasedSink$WriteOperation.finalizeDestination(FileBasedSink.java:656)
    at org.apache.beam.sdk.io.WriteFiles.finalizeAllDestinations(WriteFiles.java:819)
    at org.apache.beam.sdk.io.WriteFiles.access$1600(WriteFiles.java:112)
    at org.apache.beam.sdk.io.WriteFiles$FinalizeTempFileBundles$FinalizeFn.process(WriteFiles.java:796)
"   

1 个答案:

答案 0 :(得分:3)

我将使用为此创建的方法。例如,UUID.randomUUID().toString()生成可用于唯一命名文件的4型UUID。