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Github user jose-torres commented on the issue:
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I'm not sure isDataAvailable makes sense in the context of continuous
processing; it seems fundamentally tied to the microbatch execution model. I
think the best option is to just leave it and
Github user gaborgsomogyi commented on a diff in the pull request:
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--- Diff:
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@@ -0,0 +1,111 @@
+/*
+ *
Github user koeninger commented on a diff in the pull request:
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GitHub user rdblue opened a pull request:
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SPARK-23972: Update Parquet to 1.10.0.
## What changes were proposed in this pull request?
This updates Parquet to 1.10.0 and updates the vectorized path for buffer
management changes.
Github user gatorsmile commented on the issue:
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Could you share the performance number?
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@liyinan926 Sounds good
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Is this PR still needed?
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Github user holdenk commented on the issue:
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So we need to update for the changed MimaExcludes, I think its ok to
include this in the model directly if no one objects in the next week or so?
Sklearn has this directly in the model return as
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Github user kiszk commented on a diff in the pull request:
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@@ -87,6 +87,62 @@ case class MapKeys(child:
Github user DylanGuedes commented on the issue:
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Ok so It works fine in spark-shell but in pyspark I got this error:
```shell
File "/home/dguedes/Workspace/spark/python/pyspark/sql/functions.py", line
2155, in pyspark.sql.functions.zip
Github user mgaido91 commented on the issue:
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@DylanGuedes the first suggestion I can give you is: do not use spark-shell
for testing, but write UT and run them with a debugger. Then, you can
breakpoint to check the generated code (or you can
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Github user gatorsmile commented on the issue:
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Thanks! Merged to master.
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.stringConf
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retest this please
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Upstream benchmarks for buffer management changes are here:
https://github.com/apache/parquet-mr/pull/390#issuecomment-338505426
That doesn't show the GC benefit for smaller buffer
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Github user jose-torres commented on the issue:
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I guess we might not even need to make an API change, just document that
these flags only mean anything for microbatch execution. In any case that's a
separate discussion.
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Anything else do we need to do to merge in this change?
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@cloud-fan or @gatorsmile, could you review this?
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Awesome, looking forward to the update.
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--- Diff: python/pyspark/streaming/kafka.py ---
@@ -104,7 +104,7 @@ def createDirectStream(ssc, topics, kafkaParams,
fromOffsets=None,
Github user mccheah commented on the issue:
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> We don't have a solid story for checkpointing streaming computation right
now, and even if we did, you'll certainly lose all progress from batch jobs.
Should probably clarify re:
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retest this please
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--- Diff: python/pyspark/ml/clustering.py ---
@@ -322,7 +323,11 @@ def computeCost(self, dataset):
"""
Return the K-means cost
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Github user mccheah commented on the issue:
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Looks like there's a lot of conflicts from the refactor that was just
merged.
In general though I don't think this buys us too much. The problem is that
when the driver fails, you'll lose
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@@ -152,22 +154,28 @@ class DataFrameRangeSuite extends QueryTest with
Github user foxish commented on the issue:
https://github.com/apache/spark/pull/21032
@madanadit @liyinan926, can we do a short doc with all the types of volumes
and config options and run that through the rest of the community?
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Github user madanadit commented on the issue:
https://github.com/apache/spark/pull/21032
@liyinan926 @foxish I've started a doc
[here](https://docs.google.com/document/d/15-mk7UnOYNTXoF6EKaVlelWYc9DTrTXrYoodwDuAwY4/edit?usp=sharing).
Feel free to edit and circulate to interested
GitHub user huaxingao opened a pull request:
https://github.com/apache/spark/pull/21069
[SPARK-23920][SQL]add array_remove to remove all elements that equal
element from array
## What changes were proposed in this pull request?
add array_remove to remove all elements that
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/21068
Merged build finished. Test FAILed.
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