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https://issues.apache.org/jira/browse/BEAM-7608?focusedWorklogId=278439&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-278439
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ASF GitHub Bot logged work on BEAM-7608:
----------------------------------------
Author: ASF GitHub Bot
Created on: 17/Jul/19 19:53
Start Date: 17/Jul/19 19:53
Worklog Time Spent: 10m
Work Description: udim commented on issue #8921: [BEAM-7608] Honor
DATASTORE_EMULATOR_HOST env var
URL: https://github.com/apache/beam/pull/8921#issuecomment-512544084
run python postcommit
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Issue Time Tracking
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Worklog Id: (was: 278439)
Time Spent: 1h (was: 50m)
> v1new ReadFromDatastore skips entities
> --------------------------------------
>
> Key: BEAM-7608
> URL: https://issues.apache.org/jira/browse/BEAM-7608
> Project: Beam
> Issue Type: Bug
> Components: io-python-gcp
> Affects Versions: 2.13.0
> Environment: MacOS 10.14.5, Python 2.7
> Reporter: Jacob Gur
> Assignee: Udi Meiri
> Priority: Critical
> Time Spent: 1h
> Remaining Estimate: 0h
>
> A simple map over a datastore kind in local emulator using the new
> v1new.datastoreio.ReadFromDatastore skip entities.
> The kind has 1516 entities, and when I map over it using the old
> ReadFromDatastore transform, it maps all of them, i.e., I can map to id and
> write to text file.
> But the new transform only maps 365 entities. There is no error. The tail of
> the standard output is:
> {code:java}
> INFO:root:Latest stats timestamp for kind face_apilog is 2019-06-18
> 08:15:21+00:00
> INFO:root:Estimated size bytes for query: 116188
> INFO:root:Splitting the query into 12 splits
> INFO:root:Running
> (((GetEntities/Reshuffle/ReshufflePerKey/GroupByKey/Read)(ref_AppliedPTransform_GetEntities/Reshuffle/ReshufflePerKey/FlatMap(restore_timestamps)_14))((ref_AppliedPTransform_GetEntities/Reshuffle/RemoveRandomKeys_15)(ref_AppliedPTransform_GetEntities/Read_16)))((ref_AppliedPTransform_MapToId_17)((ref_AppliedPTransform_WriteToFile/Write/WriteImpl/WriteBundles_24)((ref_AppliedPTransform_WriteToFile/Write/WriteImpl/Pair_25)((ref_AppliedPTransform_WriteToFile/Write/WriteImpl/WindowInto(WindowIntoFn)_26)(WriteToFile/Write/WriteImpl/GroupByKey/Write)))))
> INFO:root:Running
> (WriteToFile/Write/WriteImpl/GroupByKey/Read)((ref_AppliedPTransform_WriteToFile/Write/WriteImpl/Extract_31)(ref_PCollection_PCollection_20/Write))
> INFO:root:Running
> (ref_PCollection_PCollection_12/Read)((ref_AppliedPTransform_WriteToFile/Write/WriteImpl/PreFinalize_32)(ref_PCollection_PCollection_21/Write))
> INFO:root:Running
> (ref_PCollection_PCollection_12/Read)+(ref_AppliedPTransform_WriteToFile/Write/WriteImpl/FinalizeWrite_33)
> INFO:root:Starting finalize_write threads with num_shards: 1 (skipped: 0),
> batches: 1, num_threads: 1
> INFO:root:Renamed 1 shards in 0.12 seconds.{code}
>
> The code for the job on the new transform is:
>
>
> {code:java}
> from __future__ import absolute_import
> import logging
> import os
> import sys
> import apache_beam as beam
> from apache_beam.io.gcp.datastore.v1new.datastoreio import ReadFromDatastore
> from apache_beam.io.gcp.datastore.v1new.types import Query
> # TODO: should be set outside of python process
> os.environ['DATASTORE_EMULATOR_HOST'] = 'localhost:8085'
> def map_to_id(element):
> face_log_id = element.to_client_entity().id
> return face_log_id
> def run(argv=None):
> p = beam.Pipeline(argv=argv)
> project = 'dev'
> (p
> | 'GetEntities' >> ReadFromDatastore(Query(kind='face_apilog',
> project=project))
> | 'MapToId' >> beam.Map(map_to_id)
> | 'WriteToFile' >> beam.io.WriteToText('result')
> )
> p.run().wait_until_finish()
> if __name__ == '__main__':
> logging.getLogger().setLevel(logging.INFO)
> run(sys.argv){code}
>
> For comparison, the code for the job on the old transform is:
>
> {code:java}
> from __future__ import absolute_import
> import logging
> import os
> import sys
> import apache_beam as beam
> from apache_beam.io.gcp.datastore.v1.datastoreio import ReadFromDatastore
> from google.cloud.proto.datastore.v1 import query_pb2
> # TODO: should be set outside of python process
> os.environ['DATASTORE_EMULATOR_HOST'] = 'localhost:8085'
> def map_to_id(element):
> face_log_id = element.key.path[-1].id
> return face_log_id
> def run(argv=None):
> p = beam.Pipeline(argv=argv)
> project = 'dev'
> query = query_pb2.Query()
> query.kind.add().name = 'face_apilog'
> (p
> | 'GetEntities' >> ReadFromDatastore(project=project, query=query)
> # TODO: ParDo???
> | 'MapToId' >> beam.Map(map_to_id)
> | 'WriteToFile' >> beam.io.WriteToText('result')
> )
> p.run().wait_until_finish()
> if __name__ == '__main__':
> logging.getLogger().setLevel(logging.INFO)
> run(sys.argv){code}
>
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