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https://issues.apache.org/jira/browse/BEAM-1787?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15937806#comment-15937806
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Mike Lambert edited comment on BEAM-1787 at 3/23/17 6:22 AM:
-------------------------------------------------------------
Nope, there is just a print statement at step 3. Using the datastore_wordcount
example:
{noformat}
lines = p | 'read from datastore' >> ReadFromDatastore(
project, query, user_options.namespace)
# Count the occurrences of each word.
counts = (lines
| 'split' >> (beam.ParDo(WordExtractingDoFn())
.with_output_types(unicode))
| 'pair_with_one' >> beam.Map(lambda x: (x, 1))
| 'group' >> beam.GroupByKey()
| 'count' >> beam.Map(lambda (word, ones): (word, sum(ones))))
{noformat}
If I put logging statements inside WordExtractingDoFn, they are not printed
until the very end of the script execution, and are printed all at once.
was (Author: mlambert):
Nope, there is just a print statement at step 3. Using the datastore_wordcount
example:
{code:none}
lines = p | 'read from datastore' >> ReadFromDatastore(
project, query, user_options.namespace)
# Count the occurrences of each word.
counts = (lines
| 'split' >> (beam.ParDo(WordExtractingDoFn())
.with_output_types(unicode))
| 'pair_with_one' >> beam.Map(lambda x: (x, 1))
| 'group' >> beam.GroupByKey()
| 'count' >> beam.Map(lambda (word, ones): (word, sum(ones))))
{code:none}
If I put logging statements inside WordExtractingDoFn, they are not printed
until the very end of the script execution, and are printed all at once.
> Python DirectRunner silently blocks reading full query from Google Datastore
> ----------------------------------------------------------------------------
>
> Key: BEAM-1787
> URL: https://issues.apache.org/jira/browse/BEAM-1787
> Project: Beam
> Issue Type: Bug
> Components: sdk-py
> Reporter: Mike Lambert
> Assignee: Ahmet Altay
> Priority: Minor
> Labels: datastore, python
>
> When I run a query (even with many splits) against the production datastore
> (such as in the datastore_wordcount demo), it operates as follows:
> 1. split the query into a bunch of split queries
> 2. run each split query, collecting the results
> 3. then pass the results to the following stage / ParDo
> However, 2 is run to completion with DirectRunner before starting 3. So a
> large dataset must be fully downloaded before it attempts to run any of the
> following stages.
> While it may make sense and local parallelism/pipelining might be
> impossible....there is no output or status messages. And debugging why my
> code appeared to hang before processing results, took forever to dig through
> code and instrument-log-debug all the beam code to figure out what was going
> on.
> See https://github.com/GoogleCloudPlatform/DataflowPythonSDK/issues/36 for
> more details
> This happens with github head 0.7.0-dev (there was no "version" tag for this
> above).
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