AngersZh commented on a change in pull request #25028: [SPARK-28227][SQL]
Support TRANSFORM with aggregation.
URL: https://github.com/apache/spark/pull/25028#discussion_r339891398
##
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/parser/AstBuilder.scala
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cloud-fan commented on issue #25962: [SPARK-29285][Shuffle] Temporary shuffle
files should be able to handle disk failures
URL: https://github.com/apache/spark/pull/25962#issuecomment-547252507
This makes sense to me. Temp files are not only used by shuffle, but also
external sorter,
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Add a mode to pin Python thread into JVM's
URL: https://github.com/apache/spark/pull/24898#discussion_r339890564
##
File path: python/pyspark/tests/test_pin_thread.py
##
@@ -0,0 +1,156 @@
+#
alfozan commented on a change in pull request #25028: [SPARK-28227][SQL]
Support TRANSFORM with aggregation.
URL: https://github.com/apache/spark/pull/25028#discussion_r339890074
##
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/parser/AstBuilder.scala
HyukjinKwon commented on issue #26243: Prepare Spark release v3.0.0-preview-rc1
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should be good to go.
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alfozan commented on a change in pull request #25028: [SPARK-28227][SQL]
Support TRANSFORM with aggregation.
URL: https://github.com/apache/spark/pull/25028#discussion_r339890074
##
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/parser/AstBuilder.scala
alfozan commented on issue #25028: [SPARK-28227][SQL] Support TRANSFORM with
aggregation.
URL: https://github.com/apache/spark/pull/25028#issuecomment-547250946
Follow up - I think It's even better to always use a manual aliasing
function and not just for a subset of expressions:
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AngersZh commented on issue #25028: [SPARK-28227][SQL] Support TRANSFORM
with aggregation.
URL: https://github.com/apache/spark/pull/25028#issuecomment-547248832
> Regarding the issue in [#25028
(comment)](https://github.com/apache/spark/pull/25028#issuecomment-547230458)
>
>
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URL: https://github.com/apache/spark/pull/26261#issuecomment-547247193
retest this please
This is an
alfozan commented on issue #25028: [SPARK-28227][SQL] Support TRANSFORM with
aggregation.
URL: https://github.com/apache/spark/pull/25028#issuecomment-547246714
Regarding the issue in
https://github.com/apache/spark/pull/25028#issuecomment-547230458
Instead of
```
val
zhengruifeng commented on issue #26124: [SPARK-29224][ML]Implement
Factorization Machines as a ml-pipeline component
URL: https://github.com/apache/spark/pull/26124#issuecomment-547246258
In practice I am using FM/FFM, and IMHO SSP or ASYNC solvers (like
Difacto/PS-lite) seems more
cloud-fan closed pull request #26287: [SPARK-28158][SQL][FOLLOWUP]
HiveUserDefinedTypeSuite: don't use RandomDataGenerator to create row for UDT
backed by ArrayType
URL: https://github.com/apache/spark/pull/26287
This is
cloud-fan commented on issue #26287: [SPARK-28158][SQL][FOLLOWUP]
HiveUserDefinedTypeSuite: don't use RandomDataGenerator to create row for UDT
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URL: https://github.com/apache/spark/pull/26287#issuecomment-547245580
thanks, merging to master!
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beliefer commented on a change in pull request #26282: [SPARK-29619] Add
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JkSelf commented on issue #26289: [SPARK-28560][SQL][followup] support the
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URL: https://github.com/apache/spark/pull/26289#issuecomment-547244817
@cloud-fan Please help me review. Thanks.
HyukjinKwon commented on a change in pull request #24898: [SPARK-22340][PYTHON]
Add a mode to pin Python thread into JVM's
URL: https://github.com/apache/spark/pull/24898#discussion_r339884667
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JkSelf opened a new pull request #26289: [SPARK-28560][SQL][followup] support
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URL: https://github.com/apache/spark/pull/26289
### What changes were proposed in this pull request?
zhengruifeng commented on a change in pull request #26124:
[SPARK-29224][ML]Implement Factorization Machines as a ml-pipeline component
URL: https://github.com/apache/spark/pull/26124#discussion_r339881152
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zhengruifeng commented on a change in pull request #26124:
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URL: https://github.com/apache/spark/pull/26124#discussion_r339883747
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zhengruifeng commented on a change in pull request #26124:
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Add a mode to pin Python thread into JVM's
URL: https://github.com/apache/spark/pull/24898#discussion_r339882917
##
File path: python/pyspark/context.py
##
@@ -1010,13 +1010,42 @@ def
yaooqinn commented on issue #25962: [SPARK-29285][Shuffle] Temporary shuffle
files should be able to handle disk failures
URL: https://github.com/apache/spark/pull/25962#issuecomment-547242547
@cloud-fan @squito sorry for the irrelevant answer. Yes, the final files
are not handled here
yaooqinn edited a comment on issue #25962: [SPARK-29285][Shuffle] Temporary
shuffle files should be able to handle disk failures
URL: https://github.com/apache/spark/pull/25962#issuecomment-547242547
@cloud-fan @squito sorry for the irrelevant answer. Yes, the final files
are not handled
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viirya edited a comment on issue #26159: [SPARK-29506][SQL] Use
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@rezasafi thanks for referring that. Is it specified to enabling
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@rezasafi thanks for referring that. Is it specified to enabling
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@yaooqinn I think @squito was asking about the final file, which has a fixed
name. How do you
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### What changes were proposed in this pull request?
This PR proposes to allow `array_contains` to take column
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HiveUserDefinedTypeSuite: don't use RandomDataGenerator to create row for UDT
backed by ArrayType
URL: https://github.com/apache/spark/pull/26287#issuecomment-547238759
Merged build finished. Test PASSed.
SparkQA removed a comment on issue #26287: [SPARK-28158][SQL][FOLLOWUP]
HiveUserDefinedTypeSuite: don't use RandomDataGenerator to create row for UDT
backed by ArrayType
URL: https://github.com/apache/spark/pull/26287#issuecomment-547213116
**[Test build #112810 has
AmplabJenkins commented on issue #26287: [SPARK-28158][SQL][FOLLOWUP]
HiveUserDefinedTypeSuite: don't use RandomDataGenerator to create row for UDT
backed by ArrayType
URL: https://github.com/apache/spark/pull/26287#issuecomment-547238766
Test PASSed.
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SparkQA commented on issue #26287: [SPARK-28158][SQL][FOLLOWUP]
HiveUserDefinedTypeSuite: don't use RandomDataGenerator to create row for UDT
backed by ArrayType
URL: https://github.com/apache/spark/pull/26287#issuecomment-547238532
**[Test build #112810 has
ConeyLiu commented on issue #25470: [SPARK-28751][Core][WIP] Improve java
serializer deserialization performance
URL: https://github.com/apache/spark/pull/25470#issuecomment-547238238
I have tested it locally, the performance is almost equally:
Test case:
```scala
object
beliefer commented on a change in pull request #26282: [SPARK-29619] Add
meaningful log and retry for start python worker process
URL: https://github.com/apache/spark/pull/26282#discussion_r339878728
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