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LGTM. Merged into master. Thanks! I created a JIRA to remember add Python
code example to the user guide:
https://issues.apache.org/jira/browse/SPARK-3838 . Not a high pri
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retest this please
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@Ishiihara Could you try to merge master? Maybe the python doc conf changed.
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@mengxr will take care of that and other comments
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@Ishiihara Another file to update is `python/docs/pyspark.mllib.rst`. We
need a section for `pyspark.mllib.feature` module.
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--- Diff: python/pyspark/mllib/Word2Vec.py ---
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+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
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--- Diff: python/pyspark/mllib/Word2Vec.py ---
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--- End diff --
Please rename the file to `feature.py` to make `Word2Vec` l
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@mengxr Repartition is very slow when caching at Python side. It takes 9
minutes to do the repartition where as caching in Java only takes 5s.
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Could you add some tests?
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@mengxr PR updated to use new pickle SerDe.
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We need to modify the implementation to use the new SerDe mechanism.
Working on that now.
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Now that #2378 has been merged, is this unblocked?
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@davies Thanks for working on MLlib's SerDe! It definitely simplifies
future Python API implementations. We will wait #2378 .
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Github user davies commented on the pull request:
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@mengxr I'm looking into this, could we block this a few days until we find
out the scalable way to do serialization?
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Github user mengxr commented on the pull request:
https://github.com/apache/spark/pull/2356#issuecomment-55375085
@davies Could you take a look at this PR and see whether there is an easier
way for SerDe? Thanks!
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Github user SparkQA commented on the pull request:
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GitHub user Ishiihara opened a pull request:
https://github.com/apache/spark/pull/2356
[SPARK-3486][MLlib][PySpark] PySpark support for Word2Vec
@mengxr
Added PySpark support for Word2Vec
Change list
(1) PySpark support for Word2Vec
(2) SerDe support of string sequenc
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