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cc @JeremyNixon also
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--- Diff: python/pyspark/sql/readwriter.py ---
@@ -500,6 +500,41 @@ def partitionBy(self, *cols):
self._jwrite = self._jwrite.partitionBy(_to_seq(
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thanks, merging to master and 2.0!
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Github user MLnick commented on the issue:
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@WeichenXu123 I believe #13729 already took care of the actual
serialization issue. Out of interest have you tested this impl here for a
difference in shuffle data read/write?
However, #1410
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Github user MLnick commented on the issue:
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@debasish83 thanks, would like to get your comments especially around
`transform` semantics. I will be doing performance testing on this and post
numbers soon.
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fair enough, I think it's worth adding a negative test just to see what
we're dealing with.
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Github user MLnick commented on the issue:
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I tend to agree the default should be a new random seed, and it is more
consistent with other libs. But @jkbradley seemed to explicitly want things to
default to reproducible behavior in
[SPARK-7678
GitHub user zjffdu reopened a pull request:
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[SPARK-13081][PYSPARK][SPARK_SUBMIT]. Allow set pythonExec of driver and
executor through confâ¦
## What changes were proposed in this pull request?
Before this PR, user have to export e
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Github user hvanhovell commented on the issue:
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@eyalfa I am a bit hesitant to add yet another almost pointless
`LogicalPlan` node to Catalyst, and certainly not one that is functionally
exactly the same as a `Union`. This would require us to
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@hvanhovell don't you think that if you're already taking a stab at it,
it's better to introduce something like UnresolvedInlineTable with its own
resolution logic and type coercion, once it's resol
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Can one of the admins verify this patch?
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GitHub user szczeles opened a pull request:
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[SPARK-16950] [PySpark] fromOffsets parameter support in
KafkaUtils.createDirectStream for python3
## What changes were proposed in this pull request?
Ability to use KafkaUtils.createDire
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@eyalfa It is currently going to complain about Unions (if type coercion
fails).
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> cc @skonto. This somewhat relates to your work on
https://issues.apache.org/jira/browse/SPARK-13401, but it seems to be disjoint.
The link is not correct i guess you meant
https://issues.a
Github user skonto commented on the issue:
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You need to add UI screenshots for the changes in the description
(https://github.com/apache/spark/blob/master/.github/PULL_REQUEST_TEMPLATE).
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@hvanhovell in case of validation error, how will the error message look
like? will it mention inline-tables in any way, or is it just going to complain
about Union's requirements?
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--- Diff: docs/running-on-mesos.md ---
@@ -467,7 +467,19 @@ See the [configuration page](configuration.html) for
information on Spark config
Set the
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cc @cloud-fan @eyalfa
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[SPARK-16947][SQL] Improve type coercion for inline tables.
## What changes were proposed in this pull request?
Inline tables were added in to Spark SQL in 2.0, e.g.: `select * from
values (
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cc @rxin
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[SPARK-16588][SQL][FOLLOWUP] Rename approxCountDistinct, toDegrees and
toRadians according to FunctionRegistry as well.
## What changes were proposed in this pull request?
It seems `ap
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I will have a look shortly
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Merging to master. Thanks for working on this!
Ping me as soon as you open a JIRA for null aware anti joins.
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GitHub user rajeshbalamohan opened a pull request:
https://github.com/apache/spark/pull/14537
[SPARK-16948][SQL] Querying empty partitioned orc tables throws excepâ¦
## What changes were proposed in this pull request?
Querying empty partitioned ORC tables from spark-sql throws e
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/14426
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Github user srowen commented on the issue:
https://github.com/apache/spark/pull/14532
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Github user asfgit closed the pull request at:
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Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/14509
To the original issue here, `inferSchema` is CSV-specific option. I guess
we don't need this option for other sources because,
- we need anyway to read the same amount of data for JSON (
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/14509
1. I think this issue is related with the question,
https://issues.apache.org/jira/browse/SPARK-15458. It seems we want to disable
the inference and promote to give schema explicitly in this cas
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Github user SparkQA commented on the issue:
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Github user f7753 closed the pull request at:
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Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/14530#discussion_r73835552
--- Diff:
core/src/main/scala/org/apache/spark/storage/StorageStatusListener.scala ---
@@ -77,6 +77,18 @@ class StorageStatusListener(conf: SparkConf) extends
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