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--- Diff: python/pyspark/cloudpickle.py ---
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file.close()
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--- Diff: python/pyspark/cloudpickle.py ---
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file
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The name of
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from global modules.
"""
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Determines what kind of function
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--- Diff: python/pyspark/cloudpickle.py ---
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return getattr(types, name)
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[WIP][SPARK-23159][PYTHON] Update cloudpickle to match 0.4.2
## What changes were proposed in this pull request?
The version of cloudpickle in PySpark was close to version 0.4.0 with
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LGTM, pending jenkins. Thanks!
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Improved block merging logic for partitions
## What changes were proposed in this pull request?
Change DataSourceScanExec so that when grouping blocks together into
partitions, also
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@@ -63,7 +63,7 @@ case class InMemoryRelation(
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Hi, @conorbmurphy .
Could you add a test case for your contribution, too?
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Thanks! Merged to master/2.3
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Will do!
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Since the last change is just to change the test case name, I merge this PR.
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@sameeragarwal this PR should fix this flakiness.
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@conorbmurphy Could you create a JIRA and follow [the
instruction](https://spark.apache.org/contributing.html) to make a
contribution?
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[SPARK-23197][DStreams] Increased timeouts to resolve flakiness
## What changes were proposed in this pull request?
Increased timeout from 50 ms to 300 ms (50 ms was really too low).
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Changing JDBC relation to better process quotes
## What changes were proposed in this pull request?
The way JDBC writes currently work, they do not properly account for mixed
case
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[SPARK-23196] Unify continuous and microbatch V2 sinks
## What changes were proposed in this pull request?
Replace streaming V2 sinks with a unified StreamWriteSupport interface,
with
Github user dongjoon-hyun commented on the issue:
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Hi, @mengxr .
Could you resolve the JIRA, too?
- https://issues.apache.org/jira/browse/SPARK-22735
Thanks!
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LGTM. Merged into master and branch-2.3. Thanks!
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--- Diff: docs/ml-features.md ---
@@ -1283,6 +1283,56 @@ for more details on the API.
+## VectorSizeHint
+
+It can sometimes be
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--- Diff: docs/ml-features.md ---
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+It can sometimes be
Github user jiangxb1987 commented on the issue:
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This is a behavior change, may be useful under your cases, but we have to
make sure it doesn't cause any regressions in other scenarios. cc
@gengliangwang
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LGTM
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retest this please
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