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Agreed. This is a fundamental change to the way Spark handles task
scheduling, task parallelism, and dynamic resource allocation, etc., and it
impacts every scheduler backends. I'm closing this
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cc @srinathshankar @rxin @cloud-fan
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[SPARK-23327] [SQL] Update the description of three external API or
functions
## What changes were proposed in this pull request?
Update the description of three external API or functions
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--- Diff: docs/sql-programming-guide.md ---
@@ -1776,6 +1776,42 @@ working with timestamps in `pandas_udf`s to get the
best performance, see
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--- Diff: docs/sql-programming-guide.md ---
@@ -1776,6 +1776,42 @@ working with timestamps in `pandas_udf`s to get the
best performance, see
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It's a well-known irrelevant failure.
-
org.apache.spark.sql.kafka010.KafkaContinuousSourceStressForDontFailOnDataLossSuite.stress
test for failOnDataLoss=false
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Retest this please.
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Thanks! Merged to master/2.3
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retest this please
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Thanks! Merged to master/2.3
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--- Diff: docs/sql-programming-guide.md ---
@@ -1776,6 +1776,42 @@ working with timestamps in `pandas_udf`s to get the
best performance, see
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Thanks @yucai , It's a great improvement for many output files. The figure
below is our comparison:
**Before**:
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Just a minor comment, LGTM. Thanks!
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--- Diff:
core/src/main/java/org/apache/spark/util/collection/unsafe/sort/UnsafeSorterSpillReader.java
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@@ -77,7 +77,7 @@ public
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I would suggest to bring out a discussion or even a design on dev mail list
before doing such ground changing. This may affect not only dynamic allocation,
but also scheduler. It is better to
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Retest this please.
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Merging to master and 2.3
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LGTM
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[SPARK-23064][SS][DOCS] Stream-stream joins Documentation - follow up
## What changes were proposed in this pull request?
Further clarification of caveats in using stream-stream outer joins.
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--- Diff: python/pyspark/sql/utils.py ---
@@ -115,18 +115,30 @@ def toJArray(gateway, jtype, arr):
def require_minimum_pandas_version():
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--- Diff: python/pyspark/sql/tests.py ---
@@ -48,19 +48,26 @@
else:
import unittest
-_have_pandas = False
-_have_old_pandas
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