Glad you were able to figure it out! Agree the error message was suboptimal. Was there any indication in the logs that the hadoop file system attempted to load but failed?
On Wed, May 29, 2019 at 4:41 AM 青雉（祁明良） <[email protected]> wrote: > > Thanks guys, I got it. It was because Flink taskmanager docker missing > HADOOP_CONF_DIR environment. > Maybe we could improve the error message in the future:) > > Best, > Mingliang > > On 29 May 2019, at 3:12 AM, Lukasz Cwik <[email protected]> wrote: > > Are you losing the META-INF/ ServiceLoader entries related to binding the > FileSystem via the FileSystemRegistrar when building the uber jar[1]? > It does look like the Flink JobServer driver is registering the file > systems[2]. > > 1: > https://github.com/apache/beam/blob/95297dd82bd2fd3986900093cc1797c806c859e6/sdks/java/core/src/main/java/org/apache/beam/sdk/io/FileSystemRegistrar.java#L33 > 2: > https://github.com/apache/beam/blob/ee96f66e14866f9642e9c67bf2ef231be7e7d55b/runners/flink/src/main/java/org/apache/beam/runners/flink/FlinkJobServerDriver.java#L63 > > On Tue, May 28, 2019 at 11:39 AM 青雉（祁明良） <[email protected]> wrote: >> >> Yes, I did (2). Since the job server successfully >> created the artifact directory, I think I did it correctly. And somehow this >> dependency is not submitted to task manager. >> Maybe I can also try out (1), but to add additional jar to flink classpath >> sounds not a perfect solution. >> >> 获取 Outlook for iOS >> >> >> >> On Wed, May 29, 2019 at 1:01 AM +0800, "Maximilian Michels" >> <[email protected]> wrote: >> >>> Hi Mingliang, >>> >>> Oh I see. You will also have to add the Jars to the TaskManager then. >>> >>> You have these options: >>> >>> 1. Include them directly in the TaskManager classpath >>> 2. Include them as dependencies to the JobServer, which will cause them >>> to be attached to Flink's JobGraph. >>> >>> Do I understand correctly that you already did (2)? >>> >>> Cheers, >>> Max >>> >>> On 28.05.19 18:33, 青雉（祁明良） wrote: >>> > Yes Max, I did add these Hadoop jars. The error >>> > message from task manager was about missing HDFS file system class from >>> > beam-sdks-java-io-hadoop-file-system module, which I also shadowed into >>> > job server. >>> > I see the artifact directory is successfully created at HDFS by job >>> > server, but fails at task manager when reading. >>> > >>> > Best, >>> > Mingliang >>> > >>> > 获取 Outlook for iOS >>> > >>> > >>> > >>> > On Tue, May 28, 2019 at 11:47 PM +0800, "Maximilian Michels" >>> > > wrote: >>> > >>> > Recent versions of Flink do not bundle Hadoop anymore, but they are >>> > still "Hadoop compatible". You just need to include the Hadoop jars in >>> > the classpath. >>> > >>> > Beams's Hadoop does not bundle Hadoop either, it just provides Beam >>> > file >>> > system abstractions which are similar to Flink "Hadoop compatibility". >>> > >>> > You probably want to add this to the job server: >>> > shadow library.java.hadoop_client >>> > shadow library.java.hadoop_common >>> > >>> > Cheers, >>> > Max >>> > >>> > On 28.05.19 15:41, 青雉（祁明良） wrote: >>> > > Thanks Robert, I had one, “qmlmoon” >>> > > >>> > > Looks like I had the jobserver working now, I just add a shadow >>> > > dependency of /beam-sdks-java-io-hadoop-file-system/ to >>> > > /beam-runners-flink_2.11-job-server/ and rebuild the job server, but >>> > > Flink taskmanger also complains about the same issue during job >>> > running. >>> > > >>> > > So how is Flink taskmanager finding this HDFS filesystem dependency? >>> > > ------- >>> > > 2019-05-28 13:15:57,695 INFO >>> > > >>> > org.apache.beam.runners.fnexecution.artifact.BeamFileSystemArtifactRetrievalService >>> > > - GetManifest for >>> > > >>> > hdfs://myhdfs/algo-emr/k8s_flink/beam/job_87fa794e-9cd7-4c20-b95c-086f11abfaa4/MANIFEST >>> > > 2019-05-28 13:15:57,696 INFO >>> > > >>> > org.apache.beam.runners.fnexecution.artifact.BeamFileSystemArtifactRetrievalService >>> > > - Loading manifest for retrieval token >>> > > >>> > hdfs://myhdfs/algo-emr/k8s_flink/beam/job_87fa794e-9cd7-4c20-b95c-086f11abfaa4/MANIFEST >>> > > 2019-05-28 13:15:57,698 INFO >>> > > >>> > org.apache.beam.runners.fnexecution.artifact.BeamFileSystemArtifactRetrievalService >>> > > - GetManifest for >>> > > >>> > hdfs://myhdfs/algo-emr/k8s_flink/beam/job_87fa794e-9cd7-4c20-b95c-086f11abfaa4/MANIFEST >>> > > failed >>> > > >>> > org.apache.beam.vendor.guava.v20_0.com.google.common.util.concurrent.UncheckedExecutionException: >>> > > java.lang.IllegalArgumentException: No filesystem found for scheme >>> > hdfs >>> > > at >>> > > >>> > org.apache.beam.vendor.guava.v20_0.com.google.common.cache.LocalCache$Segment.get(LocalCache.java:2214) >>> > > at >>> > > >>> > org.apache.beam.vendor.guava.v20_0.com.google.common.cache.LocalCache.get(LocalCache.java:4053) >>> > > at >>> > > >>> > org.apache.beam.vendor.guava.v20_0.com.google.common.cache.LocalCache.getOrLoad(LocalCache.java:4057) >>> > > at >>> > > >>> > org.apache.beam.vendor.guava.v20_0.com.google.common.cache.LocalCache$LocalLoadingCache.get(LocalCache.java:4986) >>> > > at >>> > > >>> > org.apache.beam.runners.fnexecution.artifact.BeamFileSystemArtifactRetrievalService.getManifest(BeamFileSystemArtifactRetrievalService.java:80) >>> > > at >>> > > >>> > org.apache.beam.model.jobmanagement.v1.ArtifactRetrievalServiceGrpc$MethodHandlers.invoke(ArtifactRetrievalServiceGrpc.java:298) >>> > > at >>> > > >>> > org.apache.beam.vendor.grpc.v1p13p1.io.grpc.stub.ServerCalls$UnaryServerCallHandler$UnaryServerCallListener.onHalfClose(ServerCalls.java:171) >>> > > at >>> > > >>> > org.apache.beam.vendor.grpc.v1p13p1.io.grpc.PartialForwardingServerCallListener.onHalfClose(PartialForwardingServerCallListener.java:35) >>> > > at >>> > > >>> > org.apache.beam.vendor.grpc.v1p13p1.io.grpc.ForwardingServerCallListener.onHalfClose(ForwardingServerCallListener.java:23) >>> > > at >>> > > >>> > org.apache.beam.vendor.grpc.v1p13p1.io.grpc.ForwardingServerCallListener$SimpleForwardingServerCallListener.onHalfClose(ForwardingServerCallListener.java:40) >>> > > at >>> > > >>> > org.apache.beam.vendor.grpc.v1p13p1.io.grpc.Contexts$ContextualizedServerCallListener.onHalfClose(Contexts.java:86) >>> > > at >>> > > >>> > org.apache.beam.vendor.grpc.v1p13p1.io.grpc.internal.ServerCallImpl$ServerStreamListenerImpl.halfClosed(ServerCallImpl.java:283) >>> > > at >>> > > >>> > org.apache.beam.vendor.grpc.v1p13p1.io.grpc.internal.ServerImpl$JumpToApplicationThreadServerStreamListener$1HalfClosed.runInContext(ServerImpl.java:707) >>> > > at >>> > > >>> > org.apache.beam.vendor.grpc.v1p13p1.io.grpc.internal.ContextRunnable.run(ContextRunnable.java:37) >>> > > at >>> > > >>> > org.apache.beam.vendor.grpc.v1p13p1.io.grpc.internal.SerializingExecutor.run(SerializingExecutor.java:123) >>> > > at >>> > > >>> > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) >>> > > at >>> > > >>> > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) >>> > > at java.lang.Thread.run(Thread.java:748) >>> > > >>> > > >>> > >> On 28 May 2019, at 9:31 PM, Robert Bradshaw > > wrote: >> >> The >>> > easiest would probably be to create a project >>> > that depends on both >> the job server and the hadoop filesystem and >>> > then build that as a fat >> jar. > > > 本邮件及其附件含有小红书公司 >>> > 的保密信息，仅限于发送给以上收件人或群组。禁 > 止任何其他人以任何形 >>> > 式使用（包括但不限于全部或部分地泄露、复制、或散发） > 本邮件中的信 >>> > 息。如果您错收了本邮件，请您立即电话或邮件通知发件人并删除本 > 邮 >>> > 件！ > This communication may contain privileged or other >>> > confidential > information of Red. 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