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[SPARK-26205][SQL] Optimize In for bytes, shorts, ints
## What changes were proposed in this pull request?
This PR optimizes `In` expressions for byte, short, integer types. It is a
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> The only question I have is does this cause more memory usage on the
driver because it has a reference to that broadcast value or is something else
already holding on to it?
yeah good
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retest this please
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--- Diff: python/pyspark/tests/test_broadcast.py ---
@@ -67,6 +67,20 @@ def test_broadcast_with_encryption(self):
def
Github user tgravescs commented on the issue:
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Yeah certainly seems like a good idea. The only question I have is does
this cause more memory usage on the driver because it has a reference to that
broadcast value or is something else already
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@@ -169,13 +169,18 @@ private[csv] class
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Thank you so much, @cloud-fan !
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Closing this pull request in favor of #23169
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@MaxGekk and @hvanhovell, this is an alternative solution for #23076. It
limits overall plan length when generating the full string in memory, but not
if a specific writer is passed in.
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[SPARK-24423][FOLLOW-UP][SQL] Fix error example
## What changes were proposed in this pull request?
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maybe a dumb question -- couldn't you just add
```python
self._value = value
```
[inside `__init__()` when on the
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[SPARK-26103][SQL] Limit the length of debug strings for query plans
## What changes were proposed in this pull request?
The PR puts in a limit on the size of a debug string generated
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@felixcheung Could you please review?
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@@ -222,29 +223,20 @@ private[spark] class AppStatusStore(
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[SPARK-26207][doc]add PowerIterationClustering (PIC) doc in 2.4 branch
## What changes were proposed in this pull request?
Add PIC doc in 2.4
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> So it's reasonble for users to expect that, if they set hadoop config via
the SQL SET command, it should override the one in spark-defaults.conf.
I agree with that. But the previous
Github user vanzin commented on a diff in the pull request:
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--- Diff: python/pyspark/worker.py ---
@@ -22,7 +22,12 @@
import os
import sys
import time
-import resource
+# 'resource' is a Unix
Github user ankuriitg commented on the issue:
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The change looks good to me. I understand that this change uses memory
efficiently but I am wondering whether it causes any performance degradation
compared to memory mapping. If yes, can we
Github user srowen commented on the issue:
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Looks like that kind of fallback logic was there for compatibility with
Spark 1.x and 2.0; see some comments about 'backwards compatibility' in for
example
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Some tests didn't pass on new changes till I set time zone explicitly. The
tests use the same functions for checking correctness as the code that is
supposed to test. I think need more
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@@ -54,27 +53,17 @@ case class
Github user MaxGekk commented on the issue:
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I have to correct timestamp/date pattern in a few test to follow ISO 8601
(see [Patterns for Formatting and
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> Are there any other behavior changes with the new code, besides being
able to parse microseconds?
The main one is new parser doesn't have the fallback to
`DateTimeUtils.stringToTime` if
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cc @squito
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ok to test
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[SPARK-26024][FOLLOWUP][MINOR] Follow-up to remove extra blank lines in R
function descriptions
## What changes were proposed in this pull request?
Follow-up to remove extra blank lines in
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#' using \code{spark.sql.shuffle.partitions} as
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The code looks good at a glance. So the flag lets people select the old
behavior; that keeps it pretty safe. Are there any other behavior changes with
the new code, besides being able to parse
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GitHub user redsanket opened a pull request:
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[SPARK-26201] Fix python broadcast with encryption
## What changes were proposed in this pull request?
Python with rpc and disk encryption enabled along with a python broadcast
variable and
Github user MaxGekk commented on the issue:
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@srowen @HyukjinKwon @viirya @mgaido91 May I ask you to look at the PR. The
changes are related to another PR which you have reviewed already.
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