My Dataflow jobs fail with the following error:
INFO:root:2018-10-15T18:55:37.417Z: JOB_MESSAGE_ERROR: Workflow failed.
Causes: S17:fold2/Write/WriteImpl/WindowInto(WindowIntoFn)+write instances fold2/Write/WriteImpl/GroupByKey/Reify+write instances fold2/Write/WriteImpl/GroupByKey/Write failed.,
A work item was attempted 4 times without success.
Each time the worker eventually lost contact with the service. The work item was attempted on:
yuri-nine-gag-recommender-10151140-3kmq-harness-mdgd,
yuri-nine-gag-recommender-10151140-3kmq-harness-mdgd,
yuri-nine-gag-recommender-10151140-3kmq-harness-41dd,
yuri-nine-gag-recommender-10151140-3kmq-harness-mdgd
Digging into the logs shows only one error:
An exception was raised when trying to execute the workitem 6479210647275353150 :
Traceback (most recent call last): File "/usr/local/lib/python2.7/dist-packages/dataflow_worker/batchworker.py", line 642, in do_work work_executor.execute()
File "/usr/local/lib/python2.7/dist-packages/dataflow_worker/executor.py", line 158, in execute op.finish()
File "dataflow_worker/shuffle_operations.py", line 144, in dataflow_worker.shuffle_operations.ShuffleWriteOperation.finish def finish(self):
File "dataflow_worker/shuffle_operations.py", line 145, in dataflow_worker.shuffle_operations.ShuffleWriteOperation.finish with self.scoped_finish_state:
File "dataflow_worker/shuffle_operations.py", line 147, in dataflow_worker.shuffle_operations.ShuffleWriteOperation.finish self.writer.__exit__(None, None, None)
File "/usr/local/lib/python2.7/dist-packages/dataflow_worker/shuffle.py", line 599, in __exit__ self.writer.Close()
File "third_party/windmill/shuffle/python/shuffle_client.pyx", line 202, in shuffle_client.PyShuffleWriter.Close IOError: Shuffle close failed: FAILED_PRECONDITION: Precondition check failed.
Any ideas?
I finally figured out the problem by removing various pieces for code, printing tons of logs and running the job again. It turned out that I had a regular expression that blew up for one particular entry. Unfortunately, Dataflow logs were not helpful at all.
Related
I have a Dataflow job that fails repeatedly with the following log message:
022-03-27T01:39:21.871476411ZAn exception was raised when trying to execute the workitem 1257504293434498471 : Traceback (most recent call last): File "/usr/local/lib/python3.7/site-packages/dataflow_worker/batchworker.py", line 646, in do_work work_executor.execute() File "/usr/local/lib/python3.7/site-packages/dataflow_worker/executor.py", line 210, in execute op.finish() File "dataflow_worker/shuffle_operations.py", line 171, in dataflow_worker.shuffle_operations.ShuffleWriteOperation.finish File "dataflow_worker/shuffle_operations.py", line 172, in dataflow_worker.shuffle_operations.ShuffleWriteOperation.finish File "dataflow_worker/shuffle_operations.py", line 174, in dataflow_worker.shuffle_operations.ShuffleWriteOperation.finish File "/usr/local/lib/python3.7/site-packages/dataflow_worker/shuffle.py", line 593, in exit self.writer.Close() File "third_party/windmill/shuffle/python/shuffle_client.pyx", line 185, in shuffle_client.PyShuffleWriter.Close OSError: Shuffle close failed: b'FAILED_PRECONDITION: Precondition check failed. [type.googleapis.com/util.MessageSetPayload='[dist_proc.dax.internal.TrailProto] { trail_point { source_file_loc { filepath: "dist_proc/dax/shuffle/batch/chunking_shuffle_writer.cc" line: 146 } } trail_point { source_file_loc { filepath: "dist_proc/dax/shuffle/batch/chunking_shuffle_writer.cc" line: 102 } } }']'
I tried running the job a few times, and it fails in the same place each time. Other than that error and the set of DoFns that were running, I don't have many clues about where to look for problems.
I suspect it's my code that causing a problem. Would love advice on how to diagnose this.
Have you tried using runner v2?
I wrote a Python Dataflow job which managed to process 300 files, unfortunately, when I try to run it on 400 files it gets stuck in the Write phase forever.
The logs aren't really helpful, but I think that the issue comes from the writing logic of the code, initially, I only wanted 1 output file, so I wrote:
| 'Write' >> beam.io.WriteToText(
known_args.output,
file_name_suffix=".json",
num_shards=1,
shard_name_template=""
))
Then, I removed, num_shards=1 and shard_name_template="" and I was able to process more files but it'd still get stuck.
Extra Information
the files to process are small, less than a 1MB
also, when removing the num_shards and shard_name_template fields, I noticed that the data got output a temporary folder in the target path, but the job never finishes
I have the following DEADLINE_EXCEEDED exception and I tried solving it by increasing --num_workers to 6 and --disk_size_gb to 30 but it doesn't work.
Error message from worker: Traceback (most recent call last): File "/usr/local/lib/python3.7/site-packages/dataflow_worker/batchworker.py", line 638, in do_work work_executor.execute() File "/usr/local/lib/python3.7/site-packages/dataflow_worker/executor.py", line 179, in execute op.start() File "dataflow_worker/shuffle_operations.py", line 63, in dataflow_worker.shuffle_operations.GroupedShuffleReadOperation.start File "dataflow_worker/shuffle_operations.py", line 64, in dataflow_worker.shuffle_operations.GroupedShuffleReadOperation.start File "dataflow_worker/shuffle_operations.py", line 79, in dataflow_worker.shuffle_operations.GroupedShuffleReadOperation.start File "dataflow_worker/shuffle_operations.py", line 80, in dataflow_worker.shuffle_operations.GroupedShuffleReadOperation.start File "dataflow_worker/shuffle_operations.py", line 82, in dataflow_worker.shuffle_operations.GroupedShuffleReadOperation.start File "/usr/local/lib/python3.7/site-packages/dataflow_worker/shuffle.py", line 441, in __iter__ for entry in entries_iterator: File "/usr/local/lib/python3.7/site-packages/dataflow_worker/shuffle.py", line 282, in __next__ return next(self.iterator) File "/usr/local/lib/python3.7/site-packages/dataflow_worker/shuffle.py", line 240, in __iter__ chunk, next_position = self.reader.Read(start_position, end_position) File "third_party/windmill/shuffle/python/shuffle_client.pyx", line 133, in shuffle_client.PyShuffleReader.Read OSError: Shuffle read failed: b'DEADLINE_EXCEEDED: (g)RPC timed out when extract-fields-three-mont-10090801-dlaj-harness-fj4v talking to extract-fields-three-mont-10090801-dlaj-harness-1f7r:12346. Server unresponsive (ping error: Deadline Exceeded, {"created":"#1602260204.931126454","description":"Deadline Exceeded","file":"third_party/grpc/src/core/ext/filters/deadline/deadline_filter.cc","file_line":69,"grpc_status":4}). Typically one can self manage this issue, please read: https://cloud.google.com/dataflow/docs/guides/common-errors#tsg-rpc-timeout'
Can you please recommend ways to troubleshoot this type of issues?
After trying to pump resources, I managed to get it working by enabling the Dataflow shuffle service fixed the situation. Please see resource
Just add --experiments=shuffle_mode=service to your PipelineOptions.
I'm running a Dataflow job (Apache Beam 2.12.0) using python on the Google Cloud Platform. The pipeline is not terminating and keeps running.
The issue is the same to
https://issues.apache.org/jira/browse/BEAM-7266
It wasn't solved and says "open when met again". It also says that file writer is not closing.
There's only one error log:
Traceback (most recent call last):
File "/usr/local/lib/python2.7/dist-packages/dataflow_worker/batchworker.py", line 649, in do_work
work_executor.execute()
File "/usr/local/lib/python2.7/dist-packages/dataflow_worker/executor.py", line 178, in execute
op.finish()
File "dataflow_worker/native_operations.py", line 93, in dataflow_worker.native_operations.NativeWriteOperation.finish
def finish(self):
File "dataflow_worker/native_operations.py", line 94, in dataflow_worker.native_operations.NativeWriteOperation.finish
with self.scoped_finish_state:
File "dataflow_worker/native_operations.py", line 95, in dataflow_worker.native_operations.NativeWriteOperation.finish
self.writer.__exit__(None, None, None)
File "/usr/local/lib/python2.7/dist-packages/dataflow_worker/nativefileio.py", line 465, in __exit__
self.file.close()
File "/usr/local/lib/python2.7/dist-packages/apache_beam/io/filesystemio.py", line 202, in close
self._uploader.finish()
File "/usr/local/lib/python2.7/dist-packages/apache_beam/io/gcp/gcsio.py", line 606, in finish
raise self._upload_thread.last_error # pylint: disable=raising-bad-type
NotImplementedError: offset: 0, whence: 0, position: 51518, last: 0
I'm trying to run a Dask job on a YARN cluster. This jobs reads and writes to HDFS using the hdfs3 library.
When I run it on a cluster without a Kerberos security layer, it runs fine.
But, on a cluster with a Kerberos security layer, I had to implement the solution here to avoid Kerberos related errors. Running the same job, led to the following error:
File "/fsstreamdevl/f6_development/acoustics/acoustics_analysis_dask/acoustics_analytics/task_runner/task_runner.py", line 123, in run
dask.compute(tasks)
File "/anaconda_env/projects/f6acoustics/dev/dask_yarn_test/lib/python3.7/site-packages/dask/base.py", line 446, in compute
results = schedule(dsk, keys, **kwargs)
File "/anaconda_env/projects/f6acoustics/dev/dask_yarn_test/lib/python3.7/site-packages/distributed/client.py", line 2568, in get
results = self.gather(packed, asynchronous=asynchronous, direct=direct)
File "/anaconda_env/projects/f6acoustics/dev/dask_yarn_test/lib/python3.7/site-packages/distributed/client.py", line 1822, in gather
asynchronous=asynchronous,
File "/anaconda_env/projects/f6acoustics/dev/dask_yarn_test/lib/python3.7/site-packages/distributed/client.py", line 753, in sync
return sync(self.loop, func, *args, **kwargs)
File "/anaconda_env/projects/f6acoustics/dev/dask_yarn_test/lib/python3.7/site-packages/distributed/utils.py", line 331, in sync
six.reraise(*error[0])
File "/anaconda_env/projects/f6acoustics/dev/dask_yarn_test/lib/python3.7/site-packages/six.py", line 693, in reraise
raise value
File "/anaconda_env/projects/f6acoustics/dev/dask_yarn_test/lib/python3.7/site-packages/distributed/utils.py", line 316, in f
result[0] = yield future
File "/anaconda_env/projects/f6acoustics/dev/dask_yarn_test/lib/python3.7/site-packages/tornado/gen.py", line 735, in run
value = future.result()
File "/anaconda_env/projects/f6acoustics/dev/dask_yarn_test/lib/python3.7/site-packages/tornado/gen.py", line 742, in run
yielded = self.gen.throw(*exc_info) # type: ignore
File "/anaconda_env/projects/f6acoustics/dev/dask_yarn_test/lib/python3.7/site-packages/distributed/client.py", line 1653, in _gather
six.reraise(type(exception), exception, traceback)
File "/anaconda_env/projects/f6acoustics/dev/dask_yarn_test/lib/python3.7/site-packages/six.py", line 693, in reraise
raise value
distributed.scheduler.KilledWorker: ('__call__-6af7aa29-2a09-45f3-a5e2-207c06562672', <Worker 'tcp://10.194.211.132:11927', memory: 0, processing: 1>)
Strangely enough, running the same solution on the former cluster without a Kerberos security layer, I get the same error.
Looking at the YARN application logs, I see the following traceback, but cannot tell what it means.
distributed.nanny - INFO - Closing Nanny at 'tcp://10.194.211.133:17659'
Traceback (most recent call last):
File "/opt/hadoop/data/05/hadoop/yarn/local/usercache/hdfsf6/appcache/application_1560931326013_171773/container_e47_1560931326013_171773_01_000003/environment/lib/python3.7/multiprocessing/queues.py", line 242, in _feed
send_bytes(obj)
File "/opt/hadoop/data/05/hadoop/yarn/local/usercache/hdfsf6/appcache/application_1560931326013_171773/container_e47_1560931326013_171773_01_000003/environment/lib/python3.7/multiprocessing/connection.py", line 200, in send_bytes
self._send_bytes(m[offset:offset + size])
File "/opt/hadoop/data/05/hadoop/yarn/local/usercache/hdfsf6/appcache/application_1560931326013_171773/container_e47_1560931326013_171773_01_000003/environment/lib/python3.7/multiprocessing/connection.py", line 404, in _send_bytes
self._send(header + buf)
File "/opt/hadoop/data/05/hadoop/yarn/local/usercache/hdfsf6/appcache/application_1560931326013_171773/container_e47_1560931326013_171773_01_000003/environment/lib/python3.7/multiprocessing/connection.py", line 368, in _send
n = write(self._handle, buf)
BrokenPipeError: [Errno 32] Broken pipe
End of LogType:dask.worker.log
I do not see any explicit messages in the logs about low memory. Would anyone know how to diagnose this issue?
hdfs3 is not actively maintained any more. You have two main choices for interacting with HDFS:
pyarrow's hdfs driver (via libhdfs jni library), which requires you to have java and hadoop requirements correctly set up and available to the session calling it
webhdfs such as in fsspec, which does not need java libraries, and can interact with kerberos if HTTP authentication is allowed on your system.
I have an issue whereby all clients cannot connect to openERP server 6.0.4 using port 8070.
It happened sometimes in a while (4-6 months). I wonder whats the problem, I checked the network traffic, processor, memory of the server, nothing wrong at all But it just happened few times.
When I checked on server logs, the error are same each time I met this issue, as below :
[2013-04-23 12:33:53,258][Server] ERROR:web-services:netrpc: cannot
deliver exception message to client Traceback (most recent call last):
File "/opt/openerp/server/bin/service/netrpc_server.py", line 89, in
run
ts.mysend(e, exception=True, traceback=tb_s) File "/opt/openerp/server/bin/tiny_socket.py", line 64, in mysend
self.sock.sendall('%8d%s%s' % (len(msg), exception and "1" or "0", msg)) File "/usr/lib/python2.7/socket.py", line 224, in meth
return getattr(self._sock,name)(*args) error: [Errno 32] Broken pipe
[2013-04-23 13:45:56,273][Server] ERROR:http:Could not run do_POST
Traceback (most recent call last): File
"/opt/openerp/server/bin/service/websrv_lib.py", line 299, in
_handle_one_foreign
method() File "/usr/lib/python2.7/SimpleXMLRPCServer.py", line 519, in do_POST
self.send_response(200) File "/usr/lib/python2.7/BaseHTTPServer.py", line 396, in send_response
(self.protocol_version, code, message)) File "/usr/lib/python2.7/socket.py", line 324, in write
self.flush() File "/usr/lib/python2.7/socket.py", line 303, in flush
self._sock.sendall(view[write_offset:write_offset+buffer_size]) error: [Errno 104] Connection reset by peer [2013-04-23
13:45:56,647][Server] ERROR:http:code 500, message Internal error
[2013-04-23 13:45:56,650][Server] ERROR:init:Server error in request
from ('192.168.0.132', 1880): Traceback (most recent call last):
File "/opt/openerp/server/bin/service/websrv_lib.py", line 528, in
_handle_request2
self.process_request(request, client_address) File "/usr/lib/python2.7/SocketServer.py", line 310, in process_request
self.finish_request(request, client_address) File "/usr/lib/python2.7/SocketServer.py", line 323, in finish_request
self.RequestHandlerClass(request, client_address, self) File "/opt/openerp/server/bin/service/websrv_lib.py", line 246, in init
SocketServer.StreamRequestHandler.init(self,request,client_address,server)
File "/usr/lib/python2.7/SocketServer.py", line 641, in init
self.finish() File "/usr/lib/python2.7/SocketServer.py", line 694, in finish
self.wfile.flush() File "/usr/lib/python2.7/socket.py", line 303, in flush
self._sock.sendall(view[write_offset:write_offset+buffer_size]) error: [Errno 32] Broken pipe
can anyone help me on this?
Broken-pipe error is a typical socket related error. It maybe if connect to slow from internet to server.
I suggest to use apache proxy to make available local server to internet. Mapping local server LOCALHOST:8069 to www.wxample.net:9000 using VirtualHost setting in apache. It may work for you.
For more information, Have a look at this link:
https://bugs.launchpad.net/openerp-web/+bug/927793
It may be helpful for you.