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Github user suchithjn225 commented on the issue:
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Done.
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GitHub user wangyum opened a pull request:
https://github.com/apache/spark/pull/20430
[SPARK-23263][SQL] Create table stored as parquet should update table size
if automatic update table size is enabled
â¦update table size is enabled
## What changes were proposed in this
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/20361#discussion_r164634591
--- Diff:
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---
@@ -115,13 +116,15 @@
Github user cloud-fan commented on a diff in the pull request:
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--- Diff:
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---
@@ -49,8 +49,9 @@
* After
Github user cloud-fan commented on a diff in the pull request:
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--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/internal/SQLConf.scala ---
@@ -400,6 +406,12 @@ object SQLConf {
.booleanConf
Github user cloud-fan commented on a diff in the pull request:
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--- Diff:
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@@ -377,6 +377,12 @@ object SQLConf {
.booleanConf
Github user jerryshao commented on the issue:
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I agree with @squito , unless there's a bug in it, it is risky and
unnecessary to change the logic in this critical path.
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Github user cloud-fan commented on the issue:
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LGTM, merging to master/2.3!
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Github user yaooqinn commented on the issue:
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thanks guys for reviewing. yes, this is just a minor improvement which I
guess code here seem not very logical when I was trying to do some
optimizations for my customer's heavy shuffle case. If
Github user cloud-fan commented on a diff in the pull request:
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--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/DataSourceV2Relation.scala
---
@@ -17,15 +17,149 @@
package
Github user jiangxb1987 commented on the issue:
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cc @sameeragarwal @mridulm @cloud-fan
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Github user squito commented on the issue:
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thanks for taking a look at this @yaooqinn . To clarify -- there is no bug
you are trying to fix here, is there? Its just an optimization? From a quick
glance I think the change seems correct ...
Github user cloud-fan commented on the issue:
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> I thought it was a good thing to push a single node down at a time and
not depend on order.
The order must be taken care. For example, we can't push down a limit
through Filter, unless
Github user cloud-fan commented on the issue:
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> This is a new API...
Are you saying you wanna add a new method in `DataFreameReader` that is
different than `load`? In Scala, parameter name is part of the method
signature, so for
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Github user heary-cao commented on the issue:
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@hvanhovell ,thank you for review it.
I tested the code for this PR change,
**in FileSourceScanExec->doExecute code:**
```
if (needsUnsafeRowConversion) {
Github user jerryshao commented on the issue:
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Since this is a behavior change compared to 2.2/2.3, so I will only merge
to master branch. Thanks @pmackles !
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Github user cloud-fan commented on the issue:
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I'm kind of convinced but maybe it's because I wrote this `ReadTask`. Let's
get feedback from more people, cc @RussellSpitzer @VincentPoncet @HyukjinKwon
@wzhfy @dongjoon-hyun @j-baker
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Github user cloud-fan commented on the issue:
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+1 on `GROUPED AGG` too, we may add new UDF type when we support partial
aggregate.
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@@ -254,6 +255,7 @@ private class LiveExecutor(val executorId: String,
_addTime:
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--- Diff:
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* session.
*/
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+1 on `GROUPED AGG` to me too, just to be clear.
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+1 on `GROUPED AGG` as well
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--- Diff:
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* session.
*/
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* session.
*/
Github user HyukjinKwon commented on the issue:
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LGTM except two nits and one question.
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--- Diff:
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package org.apache.spark.sql.sources.v2;
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package org.apache.spark.sql.sources.v2;
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Github user gatorsmile commented on the issue:
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LGTM
Thanks! Merged to master/2.3
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Github user viirya commented on the issue:
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First two changes looks good. The last one, maybe `PANDAS GROUP AGG UDF` ->
`GROUPED AGG PANDAS UDF`?
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retest this please
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Ah, OK. fixing the error message is fine as a separate improvement.
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Thanks.
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>IIUC there was a issue in launching Thrift Server on YARN cluster mode,
and I'm not sure whether it has been fixed (maybe @jerryshao can kindly check
that?)
Sorry I cannot remember the
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Github user sameeragarwal commented on the issue:
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Thanks @mridulm, all great points!
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Ouch... Yea, we have to think out a way to make it deterministic under hash
collisions.
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Github user kiszk commented on a diff in the pull request:
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package org.apache.spark.sql.sources.v2;
Github user HyukjinKwon commented on the issue:
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Yup, fortunately(?) we are free to rename `SQL_PANDAS_GROUP_AGG_UDF` within
2.4.0 currently but I believe here is a good place to decide based on what I
got so far. The proposal seems fine to
Github user mridulm commented on the issue:
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@jiangxb1987 You are correct when the sizes of the map's are same.
But if the map sizes are different, the resulting order can be different -
which can happen when requests for additional memory
Github user jiangxb1987 commented on the issue:
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Hey I searched the `ExternalAppendOnlyMap` and here are the findings:
The `ExternalAppendOnlyMap` claims it keeps the sorted content, but it
actually uses a `HashComparator` that compare the
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Yup, I double checked that ahead by manual port. I think that failure might
be related with environment which I think is the same I met. If we run the
comments as written in the travis, seems
Github user BryanCutler commented on the issue:
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I ran cloudpickle_tests locally and verified that the tests pass with the 2
backported fixes applied. I did get an unrelated test failure but that
happened even before added the fixes and
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--- Diff: python/pyspark/cloudpickle.py ---
@@ -318,6 +329,24 @@ def save_function(self, obj, name=None):
Determines what kind of function
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--- Diff: python/pyspark/cloudpickle.py ---
@@ -608,37 +626,22 @@ def save_global(self, obj, name=None,
pack=struct.pack):
The name of
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Github user icexelloss commented on the issue:
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* `PANDAS SCALAR UDF` -> `SCALAR PANDAS UDF`
This doesn't really change the API so +1
* `PANDAS GROUP MAP UDF` -> `GROUPED MAP PANDAS UDF`
The API changes from
Github user attilapiros commented on the issue:
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@ajbozarth Ok. For tomorrow I can update both the label and the screenshots.
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Github user ajbozarth commented on the issue:
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@jiangxb1987 I agree that this is a behavior change, but it's a behavior
change back to how it was before we switched the page from scala to js. This
LGTM
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Github user ajbozarth commented on the issue:
https://github.com/apache/spark/pull/20408
I agree that despite being wordy `Active (Blacklisted in Stages: [...])`
looks best, could you update it and post screenshots to confirm?
And if @squito says the code looks good I trust
Github user gatorsmile commented on the issue:
https://github.com/apache/spark/pull/19575
@icexelloss Thanks for your reply. Welcome your comment in my PR
https://github.com/apache/spark/pull/20428
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