Github user yanboliang commented on the issue:
https://github.com/apache/spark/pull/13481
Merged to master/2.0. Thanks!
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Github user clockfly commented on the issue:
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How about SparkSession.range? It returns a Dataset[Long], but the encoder's
schema (value: Long) is not matching logical plan's schema (id: Long).
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Github user kayousterhout commented on the issue:
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Did you consider instead doing this when a task fails (on line 761 in
TaskSetManager)? Instead of just checking if the number of failures is greater
than maxTaskFailures, you could add a
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Github user nezihyigitbasi commented on a diff in the pull request:
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--- Diff: core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala ---
@@ -444,6 +444,7 @@ object SparkSubmit {
Github user kayousterhout commented on the issue:
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@squito if it's not too painful, would you mind moving the visibility stuff
to a separate PR? (I suspect that PR can be merged almost immediately!).
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Github user kayousterhout commented on the issue:
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@rxin no, this is an old (an un-documented) feature that was added a while
ago as a band-aid until we did the more complete solution (which @squito is
planning to do soon, but not targeted
Github user cloud-fan commented on the issue:
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@liancheng yes, but is always used as a `DataFrame` and call untyped
operations on it.
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Github user amitsela commented on the issue:
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Done.
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Github user rxin commented on the issue:
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Merging in master/2.0. I'm not sure whether any of these cases are actually
perf sensitive though. If they are, they probably shouldn't be using Seq anyway.
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Github user marmbrus commented on the issue:
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Thanks, merged to master.
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Github user rxin commented on the issue:
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Let me just merge this to save some time debating. Merging in master/2.0.
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Github user zsxwing commented on the issue:
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> I'd more readily believe that a process uses UTF-8 regardless of the
platform encoding.
This is about stdout and stderr. I think most processes won't hard code
UTF-8 for them. Otherwise,
Github user shivaram commented on a diff in the pull request:
https://github.com/apache/spark/pull/12836#discussion_r66673292
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/object.scala
---
@@ -286,6 +290,9 @@ case class FlatMapGroupsInR(
Github user marmbrus commented on the issue:
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LGTM, can you update the description (it still says WIP).
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Github user rxin commented on the issue:
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Any reason you are not using the jdbc data source in Spark SQL? It seems
like it'd only make sense for jdbc to use the jdbc data source since it is
structured.
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Github user NarineK commented on a diff in the pull request:
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--- Diff:
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@@ -286,6 +290,9 @@ case class FlatMapGroupsInR(
Github user rxin commented on the issue:
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q: was blacklist merged in 2.0?
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Thanks, merging to master and 2.0.
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Merged into master and 2.0
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--- Diff:
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@@ -286,6 +290,9 @@ case class FlatMapGroupsInR(
Github user dongjoon-hyun commented on the issue:
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Thank you, @marmbrus !
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Merging to master and 2.0
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Github user shivaram commented on the issue:
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Thanks @wangmiao1981 - LGTM. Merging this to master and branch-2.0
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Github user shivaram commented on the issue:
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Thanks @liancheng for clarification and @NarineK for implementing the
override. I just had one minor comment.
@sun-rui Can you take one final look ? Since we have not still cut RC1, we
Github user shivaram commented on a diff in the pull request:
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@@ -286,6 +290,9 @@ case class FlatMapGroupsInR(
Github user marmbrus commented on the issue:
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Seems fine to me.
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Github user srowen commented on a diff in the pull request:
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--- Diff:
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@@ -20,18 +20,24 @@ package org.apache.spark.deploy.master
import
Github user srowen commented on the issue:
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Yes that was the original argument for not hard-coding UTF-8 here. I'd more
readily believe that a process uses UTF-8 regardless of the platform encoding.
But, making it configurable and defaulting
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--- Diff:
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@@ -226,4 +226,11 @@ abstract class Catalog {
*/
def
Github user sameeragarwal commented on a diff in the pull request:
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Github user yhuai commented on the issue:
https://github.com/apache/spark/pull/12313
@rdblue Thank you for updating the patch. I was out of town late last week
and was busy on spark summit early this week. Sorry for my late reply. Having
name-based resolution is very useful! Since
Github user tejasapatil commented on the issue:
https://github.com/apache/spark/pull/13563
@rxin @zsxwing Thanks for confirming. I will work on the change. Just to
clarify, I will use the configuration value for interactions with all the
streams (stderr, stdout and stdin).
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Github user liancheng commented on a diff in the pull request:
https://github.com/apache/spark/pull/13592#discussion_r3884
--- Diff: docs/sql-programming-guide.md ---
@@ -12,130 +12,121 @@ title: Spark SQL and DataFrames
Spark SQL is a Spark module for structured data
Github user liancheng commented on the issue:
https://github.com/apache/spark/pull/13605
Do we use `SQLContext.range` in any test/example code?
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Github user rxin commented on the issue:
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LGTM
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Github user rxin commented on the issue:
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To summarize:
For people coming from RDD land, they would assume read.text to return
Dataset[String], and it is easier to program for those guys.
That said, there are also arguments
Github user rxin commented on the issue:
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Got it - yea it'd make sense to make this configurable.
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Github user liancheng commented on a diff in the pull request:
https://github.com/apache/spark/pull/13592#discussion_r3638
--- Diff: docs/sql-programming-guide.md ---
@@ -184,20 +175,20 @@ showDF(df)
-## DataFrame Operations
+## Untyped Dataset
Github user rxin commented on the issue:
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@cloud-fan change the title/description to have only text?
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Github user marmbrus commented on the issue:
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I'm not sure I agree with all of the reasoning here. Here are my thoughts:
- `SQLContext` should probably not break any APIs (its only there for
compatibility anyway).
- In
Github user zsxwing commented on the issue:
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> Are there cases when we need non UTF-8 encoding?
It depends on the encoding of the external commands. Some commands may just
use the default system encoding. If we hard code UTF-8, we
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Github user cloud-fan commented on the issue:
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cc @rxin @liancheng @yhuai
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Github user srowen commented on the issue:
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The effect for source and readability is that of a cast; yes it is not a
call to asInstanceOf. I do not feel strongly though this would have been the
righter way to write this code.
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GitHub user cloud-fan opened a pull request:
https://github.com/apache/spark/pull/13605
[SPARK-15856][SQL] Revert API breaking changes made in SQLContext.range
## What changes were proposed in this pull request?
It's easy for users to call `range(...).as[Long]` to get typed
Github user rxin commented on the issue:
https://github.com/apache/spark/pull/13591
@srowen it wasn't really casting here. It's just an explicit type
definition.
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Github user asfgit closed the pull request at:
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Github user rxin commented on the issue:
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Are there cases when we need non UTF-8 encoding?
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Github user rxin commented on the issue:
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Can you break the text change from the range change? i.e. 2 prs.
I think @marmbrus doesn't agree with the text change so we should debate
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Github user tdas commented on the issue:
https://github.com/apache/spark/pull/13595
Yes. we are still reviewing the final API, so hold it for a bit. Thanks for
noticing the inconsistencies.
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Github user zsxwing commented on the issue:
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@lw-lin thanks for the PR. However, we have not yet finalized the terms...
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Github user liancheng commented on the issue:
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I'd prefer change `SparkSession.range`'s return type to `Dataset[Row]` for
better consistency, also there's an annoying nullability issue regarding to
`Dataset[java.lang.Long]` (boxed types are
Github user rxin commented on the issue:
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LGTM - I guess the main question now is whether we want to change
SparkSession.range's return type.
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