[GitHub] spark issue #15681: [SPARK-18176][Streaming][Kafka] Kafka010 .createRDD() sc...

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[GitHub] spark issue #15681: [SPARK-18176][Streaming][Kafka] Kafka010 .createRDD() sc...

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[GitHub] spark issue #15681: [SPARK-18176][Streaming][Kafka] Kafka010 .createRDD() sc...

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[GitHub] spark issue #14937: [SPARK-8519][SPARK-11560] [ML] [MLlib] Optimize KMeans i...

Github user sethah commented on the issue: https://github.com/apache/spark/pull/14937 @yanboliang I ran some tests on a 3 node bare-metal cluster, 144 cores, 384 gb ram on some dense synthetic data. I installed OpenBLAS customized for the hardware on the nodes (I can confirm it's

[GitHub] spark issue #15686: [MINOR][DOC] Remove spaces following slashs

Github user HyukjinKwon commented on the issue: https://github.com/apache/spark/pull/15686 I believe the message indicates the same case with the PR 15673 but it seems spurious in this case. --- If your project is set up for it, you can reply to this email and have your reply appear

[GitHub] spark issue #15686: [MINOR][DOC] Remove spaces following slashs

Github user HyukjinKwon commented on the issue: https://github.com/apache/spark/pull/15686 @rxin, it seems spurious. The message seems meaning the failure when the commit is virtually not mergeable[1]. It seems it fails time to time for various reasons. For example, in some

[GitHub] spark issue #14937: [SPARK-8519][SPARK-11560] [ML] [MLlib] Optimize KMeans i...

Github user yanboliang commented on the issue: https://github.com/apache/spark/pull/14937 @sethah I think the test result can be reproduced against the current patch, however, there are two issues should be considered: * Make sure you installed optimized/native BLAS on your system

[GitHub] spark issue #15670: [SPARK-18161] [Python] Allow pickle to serialize >4 GB o...

Github user rxin commented on the issue: https://github.com/apache/spark/pull/15670 cc @davies --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the

[GitHub] spark issue #15685: [BUILD] Close stale Pull Requests.

Github user rxin commented on the issue: https://github.com/apache/spark/pull/15685 LGTM --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature

[GitHub] spark issue #15686: [MINOR][DOC] Remove spaces following slashs

Github user rxin commented on the issue: https://github.com/apache/spark/pull/15686 @HyukjinKwon why are the appveyor checks failing? --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this

[GitHub] spark issue #15663: [SPARK-18143][SQL]Ignore Structured Streaming event logs...

Github user rxin commented on the issue: https://github.com/apache/spark/pull/15663 cc @tdas / @marmbrus does this change lgtu? --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have

[GitHub] spark pull request #15659: [SPARK-1267][SPARK-18129] Allow PySpark to be pip...

Github user viirya commented on a diff in the pull request: https://github.com/apache/spark/pull/15659#discussion_r85686524 --- Diff: python/MANIFEST.in --- @@ -0,0 +1,23 @@ +#!/usr/bin/env python + +# +# Licensed to the Apache Software Foundation (ASF) under one or

[GitHub] spark pull request #15659: [SPARK-1267][SPARK-18129] Allow PySpark to be pip...

Github user viirya commented on a diff in the pull request: https://github.com/apache/spark/pull/15659#discussion_r85686116 --- Diff: dev/create-release/release-build.sh --- @@ -162,14 +162,35 @@ if [[ "$1" == "package" ]]; then export ZINC_PORT=$ZINC_PORT echo

[GitHub] spark pull request #15659: [SPARK-1267][SPARK-18129] Allow PySpark to be pip...

Github user viirya commented on a diff in the pull request: https://github.com/apache/spark/pull/15659#discussion_r85685534 --- Diff: docs/index.md --- @@ -14,7 +14,9 @@ It also supports a rich set of higher-level tools including [Spark SQL](sql-prog Get Spark from the

[GitHub] spark issue #15691: [SPARK-18175] [SQL] [WIP] Improve the test case coverage...

Github user SparkQA commented on the issue: https://github.com/apache/spark/pull/15691 **[Test build #67801 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/67801/consoleFull)** for PR 15691 at commit

[GitHub] spark pull request #15659: [SPARK-1267][SPARK-18129] Allow PySpark to be pip...

Github user viirya commented on a diff in the pull request: https://github.com/apache/spark/pull/15659#discussion_r85685141 --- Diff: dev/create-release/release-build.sh --- @@ -162,14 +162,35 @@ if [[ "$1" == "package" ]]; then export ZINC_PORT=$ZINC_PORT echo

[GitHub] spark issue #15667: [SPARK-18107][SQL] Insert overwrite statement runs much ...

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[GitHub] spark issue #15667: [SPARK-18107][SQL] Insert overwrite statement runs much ...

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[GitHub] spark issue #15667: [SPARK-18107][SQL] Insert overwrite statement runs much ...

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[GitHub] spark issue #15671: [SPARK-14567][ML]Add instrumentation logs to MLlib train...

Github user zhengruifeng commented on the issue: https://github.com/apache/spark/pull/15671 @jkbradley @yanboliang Could you please make a reivew? --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not

[GitHub] spark issue #15659: [SPARK-1267][SPARK-18129] Allow PySpark to be pip instal...

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[GitHub] spark issue #15659: [SPARK-1267][SPARK-18129] Allow PySpark to be pip instal...

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[GitHub] spark issue #15659: [SPARK-1267][SPARK-18129] Allow PySpark to be pip instal...

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[GitHub] spark issue #15667: [SPARK-18107][SQL] Insert overwrite statement runs much ...

Github user viirya commented on the issue: https://github.com/apache/spark/pull/15667 @snodawn Thanks. I expect it should perform as good as you tested. But there are few tests failed I fix in newer patch. --- If your project is set up for it, you can reply to this email and have

[GitHub] spark issue #15667: [SPARK-18107][SQL] Insert overwrite statement runs much ...

Github user snodawn commented on the issue: https://github.com/apache/spark/pull/15667 Ok, I see. I haven't tested the newest code, I would try it later. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project

[GitHub] spark issue #15667: [SPARK-18107][SQL] Insert overwrite statement runs much ...

Github user viirya commented on the issue: https://github.com/apache/spark/pull/15667 @snodawn You just said the new patch runs better. Do you use the latest patch I just updated in about 1 hr ago? Thanks. --- If your project is set up for it, you can reply to this email and have

[GitHub] spark issue #15667: [SPARK-18107][SQL] Insert overwrite statement runs much ...

Github user viirya commented on the issue: https://github.com/apache/spark/pull/15667 @snodawn Current fixing does not do anything for dynamic partition. So we can expect this. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as

[GitHub] spark issue #15667: [SPARK-18107][SQL] Insert overwrite statement runs much ...

Github user snodawn commented on the issue: https://github.com/apache/spark/pull/15667 The execution logs in spark show me that, it does the same thing as what it does before I add the patch, which may be the reason why it runs so slow when running dynamic insert overwrite statement.

[GitHub] spark issue #15691: [SPARK-18175] [SQL] [WIP] Improve the test case coverage...

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[GitHub] spark issue #15691: [SPARK-18175] [SQL] [WIP] Improve the test case coverage...

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[GitHub] spark issue #15667: [SPARK-18107][SQL] Insert overwrite statement runs much ...

Github user viirya commented on the issue: https://github.com/apache/spark/pull/15667 @snodawn I just updated this with a new commit. Do you use this new patch to test? Yeah, current fixing doesn't consider dynamic partition. I would like to see if we can improve static

[GitHub] spark issue #15691: [SPARK-18175] [SQL] [WIP] Improve the test case coverage...

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[GitHub] spark issue #15667: [SPARK-18107][SQL] Insert overwrite statement runs much ...

Github user snodawn commented on the issue: https://github.com/apache/spark/pull/15667 @viirya I have tested the new patch, which performs better than expected. Before patching, it costs about 500~600 seconds, but now it just cost me about 16 seconds to run the same statement. But it

[GitHub] spark issue #15691: [SPARK-18175] [SQL] [WIP] Improve the test case coverage...

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[GitHub] spark issue #15691: [SPARK-18175] [SQL] [WIP] Improve the test case coverage...

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[GitHub] spark issue #15691: [SPARK-18175] [SQL] [WIP] Improve the test case coverage...

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[GitHub] spark issue #15681: [SPARK-18176][Streaming][Kafka] Kafka010 .createRDD() sc...

Github user lw-lin commented on the issue: https://github.com/apache/spark/pull/15681 @koeninger well received and thanks! JIRA opened and unrelated changes removed. Let's see what Jenkins would say. --- If your project is set up for it, you can reply to this email and have

[GitHub] spark issue #15681: [SPARK-18176][Streaming][Kafka] Kafka010 .createRDD() sc...

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[GitHub] spark issue #15690: [SPARK-18174] [SQL] [DO-NOT-MERGE] Avoid Implicit Type C...

Github user rxin commented on the issue: https://github.com/apache/spark/pull/15690 Why not have a strict mode flag? On Sunday, October 30, 2016, Xiao Li wrote: > Closed #15690 . > > —

[GitHub] spark issue #15681: [Minor][Streaming][Kafka] Kafka010 .createRDD() scala AP...

Github user koeninger commented on the issue: https://github.com/apache/spark/pull/15681 Public API changes even on an experimental module aren't a minor thing, open a Jira. It's also better not to lump unrelated changes together. --- If your project is set up for it, you

[GitHub] spark issue #15667: [SPARK-18107][SQL] Insert overwrite statement runs much ...

Github user SparkQA commented on the issue: https://github.com/apache/spark/pull/15667 **[Test build #67799 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/67799/consoleFull)** for PR 15667 at commit

[GitHub] spark issue #14640: [SPARK-17055] [MLLIB] add groupKFold to CrossValidator

Github user VinceShieh commented on the issue: https://github.com/apache/spark/pull/14640 @rdelassus Agree. There are a number of folding methods, so some code refractoring should be done if more folding methods are to be supported in the future. But for now, I guess we will just

[GitHub] spark issue #15605: [WIP] [SPARK-18067] [SQL] SortMergeJoin adds shuffle if ...

Github user tejasapatil commented on the issue: https://github.com/apache/spark/pull/15605 Most of the tests are failing because `ShuffleExchange` currently does not handle `PartitioningCollection`. That can be fixed but as I looked at this more, I found a flaw in the current

[GitHub] spark issue #15668: [SPARK-18137][SQL]Fix RewriteDistinctAggregates Unresolv...

Github user windpiger commented on the issue: https://github.com/apache/spark/pull/15668 @hvanhovell @cloud-fan Do you mean that just change distinctAggChildren/regularAggChildren to represent the unfoldable expressions, and then the followings code could be unchanged? ...

[GitHub] spark issue #15681: [Minor][Streaming][Kafka] Kafka010 .createRDD() scala AP...

Github user lw-lin commented on the issue: https://github.com/apache/spark/pull/15681 @koeninger could you also take a look at this, thanks! --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have

[GitHub] spark pull request #15659: [SPARK-1267][SPARK-18129] Allow PySpark to be pip...

Github user viirya commented on a diff in the pull request: https://github.com/apache/spark/pull/15659#discussion_r85676793 --- Diff: python/setup.py --- @@ -0,0 +1,170 @@ +#!/usr/bin/env python + +# +# Licensed to the Apache Software Foundation (ASF) under one or

[GitHub] spark issue #15659: [SPARK-1267][SPARK-18129] Allow PySpark to be pip instal...

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[GitHub] spark issue #15691: [SPARK-18175] [SQL] [WIP] Improve the test case coverage...

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[GitHub] spark issue #15690: [SPARK-18174] [SQL] [DO-NOT-MERGE] Avoid Implicit Type C...

Github user gatorsmile commented on the issue: https://github.com/apache/spark/pull/15690 Thank you for your inputs! @tejasapatil We should not break the existing behaviors. Thus, I close this PR. Thanks! --- If your project is set up for it, you can reply to this email and

[GitHub] spark pull request #15690: [SPARK-18174] [SQL] [DO-NOT-MERGE] Avoid Implicit...

Github user gatorsmile closed the pull request at: https://github.com/apache/spark/pull/15690 --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature

[GitHub] spark issue #15691: [SPARK-18175] [SQL] [WIP] Improve the test case coverage...

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[GitHub] spark issue #15690: [SPARK-18174] [SQL] [DO-NOT-MERGE] Avoid Implicit Type C...

Github user tejasapatil commented on the issue: https://github.com/apache/spark/pull/15690 >> have you hit the behavior differences between Hive and Spark SQL caused by the implicit type casting? So far I have not seen correctness issue due to casting. I can imagine casting

[GitHub] spark pull request #15691: [SPARK-18175] [SQL] [WIP] Improve the test case c...

GitHub user gatorsmile opened a pull request: https://github.com/apache/spark/pull/15691 [SPARK-18175] [SQL] [WIP] Improve the test case coverage of implicit type casting ### What changes were proposed in this pull request? So far, we have limited test case coverage about

[GitHub] spark pull request #15659: [SPARK-1267][SPARK-18129] Allow PySpark to be pip...

Github user holdenk commented on a diff in the pull request: https://github.com/apache/spark/pull/15659#discussion_r85675496 --- Diff: python/setup.py --- @@ -0,0 +1,170 @@ +#!/usr/bin/env python + +# +# Licensed to the Apache Software Foundation (ASF) under one or

[GitHub] spark issue #15677: [SPARK-17963][SQL][Documentation] Add examples (extend) ...

Github user gatorsmile commented on the issue: https://github.com/apache/spark/pull/15677 I did not say the other changes are wrong. The only concern is argument types. Like what I said above, if we remove the newly added argument types, I am fine to merge this as a document

[GitHub] spark issue #15677: [SPARK-17963][SQL][Documentation] Add examples (extend) ...

Github user HyukjinKwon commented on the issue: https://github.com/apache/spark/pull/15677 My answer to that is https://github.com/apache/spark/pull/15677#issuecomment-257137604. It seems the discussion goes in a loop. --- If your project is set up for it, you can reply to this

[GitHub] spark issue #15685: [BUILD] Close stale Pull Requests.

Github user HyukjinKwon commented on the issue: https://github.com/apache/spark/pull/15685 Hi @srowen, I have a couple of things you may consider adding. 9008 14699 --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as

[GitHub] spark issue #15689: [SPARK-9487] [TESTS] [WIP]Use the same num. worker threa...

Github user skanjila commented on the issue: https://github.com/apache/spark/pull/15689 One step at a time, first lets get the unit tests all working with local[4] in python and scala, I just added a bunch of new commits in unit tests in ml package, once I get the green light I will

[GitHub] spark issue #15677: [SPARK-17963][SQL][Documentation] Add examples (extend) ...

Github user gatorsmile commented on the issue: https://github.com/apache/spark/pull/15677 Sorry, I am confusing the merging standards. Why can we accept merging something incorrect? Just like `reverse`, to the external users, the argument type of `str` is not `a string

[GitHub] spark issue #15686: [MINOR][DOC] Remove spaces following slashs

Github user HyukjinKwon commented on the issue: https://github.com/apache/spark/pull/15686 Build started: [SparkR] `ALL`

[GitHub] spark issue #15689: [SPARK-9487] [TESTS] [WIP]Use the same num. worker threa...

Github user HyukjinKwon commented on the issue: https://github.com/apache/spark/pull/15689 (Yes, I guess we should fix many tests too. As far as I remember, many tests are dependent on the default partition number if I remember correctly.) --- If your project is set up for it, you

[GitHub] spark issue #15677: [SPARK-17963][SQL][Documentation] Add examples (extend) ...

Github user HyukjinKwon commented on the issue: https://github.com/apache/spark/pull/15677 I guess we can improve them in followups if a change does not make something worse. This introduces a general format to follow too. Can I just follow the majority if this can't be

[GitHub] spark issue #15677: [SPARK-17963][SQL][Documentation] Add examples (extend) ...

Github user HyukjinKwon commented on the issue: https://github.com/apache/spark/pull/15677 > However, the complex type we should block. We also need to fix it in the code. It does not support complex types already but only `AtomicType`[1]. ``` spark-sql> SELECT

[GitHub] spark issue #15675: [SPARK-18144][SQL] logging StreamingQueryListener$QueryS...

Github user CodingCat commented on the issue: https://github.com/apache/spark/pull/15675 @zsxwing mind looking at it again? --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature

[GitHub] spark issue #15538: [SPARK-17993][SQL] Fix Parquet log output redirection

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[GitHub] spark issue #15538: [SPARK-17993][SQL] Fix Parquet log output redirection

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[GitHub] spark issue #15538: [SPARK-17993][SQL] Fix Parquet log output redirection

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[GitHub] spark issue #15538: [SPARK-17993][SQL] Fix Parquet log output redirection

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[GitHub] spark issue #15538: [SPARK-17993][SQL] Fix Parquet log output redirection

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[GitHub] spark issue #15538: [SPARK-17993][SQL] Fix Parquet log output redirection

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[GitHub] spark issue #15640: [SPARK-18106][SQL] ANALYZE TABLE should raise a ParseExc...

Github user dongjoon-hyun commented on the issue: https://github.com/apache/spark/pull/15640 Thank you, @hvanhovell ! Also, Thank you, @srinathshankar . --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project

[GitHub] spark issue #15690: [SPARK-18174] [SQL] Avoid Implicit Type Cast in Argument...

Github user gatorsmile commented on the issue: https://github.com/apache/spark/pull/15690 Found another side effect caused by implicit casting. When we having `CAST` in the filter conditions, we are unable to push down these filters into the data sources. Performance could be very

[GitHub] spark pull request #15638: [SPARK-18110][PYTHON][ML] add missing parameter i...

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[GitHub] spark issue #15638: [SPARK-18110][PYTHON][ML] add missing parameter in Pytho...

Github user felixcheung commented on the issue: https://github.com/apache/spark/pull/15638 merged to master. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes

[GitHub] spark pull request #15607: [SPARK-16137][SPARKR] randomForest for R

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[GitHub] spark issue #15607: [SPARK-16137][SPARKR] randomForest for R

Github user felixcheung commented on the issue: https://github.com/apache/spark/pull/15607 merged to master. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes

[GitHub] spark pull request #15471: [SPARK-17919] Make timeout to RBackend configurab...

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[GitHub] spark issue #15471: [SPARK-17919] Make timeout to RBackend configurable in S...

Github user felixcheung commented on the issue: https://github.com/apache/spark/pull/15471 merged to master. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes

[GitHub] spark issue #15471: [SPARK-17919] Make timeout to RBackend configurable in S...

Github user felixcheung commented on the issue: https://github.com/apache/spark/pull/15471 LGTM. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the

[GitHub] spark issue #15690: [SPARK-18174] [SQL] Avoid Implicit Type Cast in Argument...

Github user gatorsmile commented on the issue: https://github.com/apache/spark/pull/15690 @HyukjinKwon This PR is to collect the feedbacks from the others about implicit casting. Now, it seems like we should follow the general design principle. If we just put the target type as the

[GitHub] spark issue #15690: [SPARK-18174] [SQL] Avoid Implicit Type Cast in Argument...

Github user gatorsmile commented on the issue: https://github.com/apache/spark/pull/15690 @tejasapatil I see your point. Implicit casting is powerful. Actually, different languages have different preferences. I checked the related change history of Spark SQL. I think we prefer to

[GitHub] spark issue #15690: [SPARK-18174] [SQL] Avoid Implicit Type Cast in Argument...

Github user HyukjinKwon commented on the issue: https://github.com/apache/spark/pull/15690 cc @hvanhovell too. I guess we talked about the similar issue in another PR. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If

[GitHub] spark issue #15690: [SPARK-18174] [SQL] Avoid Implicit Type Cast in Argument...

Github user HyukjinKwon commented on the issue: https://github.com/apache/spark/pull/15690 This is a rapid change that breaks the compatibility in existing codes. I guess we should check other databases as well in this case. --- If your project is set up for it, you can reply to

[GitHub] spark pull request #15640: [SPARK-18106][SQL] ANALYZE TABLE should raise a P...

Github user asfgit closed the pull request at: https://github.com/apache/spark/pull/15640 --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is

[GitHub] spark issue #15640: [SPARK-18106][SQL] ANALYZE TABLE should raise a ParseExc...

Github user hvanhovell commented on the issue: https://github.com/apache/spark/pull/15640 LGTM - merging to master. Thanks! --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature

[GitHub] spark issue #15538: [SPARK-17993][SQL] Fix Parquet log output redirection

Github user mallman commented on the issue: https://github.com/apache/spark/pull/15538 Getting this redirection to work on remote executors was quite involved. The additional complexities derive from the following: 1. Java doesn't call the default (or any) constructor in

[GitHub] spark issue #15538: [SPARK-17993][SQL] Fix Parquet log output redirection

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[GitHub] spark issue #15640: [SPARK-18106][SQL] ANALYZE TABLE should raise a ParseExc...

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[GitHub] spark issue #15640: [SPARK-18106][SQL] ANALYZE TABLE should raise a ParseExc...

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[GitHub] spark issue #15640: [SPARK-18106][SQL] ANALYZE TABLE should raise a ParseExc...

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[GitHub] spark issue #15688: [SPARK-18173][SQL] data source tables should support tru...

Github user ericl commented on the issue: https://github.com/apache/spark/pull/15688 This lgtm --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the

[GitHub] spark issue #15538: [SPARK-17993][SQL] Fix Parquet log output redirection

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[GitHub] spark issue #15690: [SPARK-18174] [SQL] Avoid Implicit Type Cast in Argument...

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[GitHub] spark issue #15690: [SPARK-18174] [SQL] Avoid Implicit Type Cast in Argument...

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[GitHub] spark issue #15690: [SPARK-18174] [SQL] Avoid Implicit Type Cast in Argument...

Github user tejasapatil commented on the issue: https://github.com/apache/spark/pull/15690 If we want to go with the model of being super strict about users doing proper cast, shouldn't all UDFs / functions avoid doing implicit cast ? Else it will be confusing for users as sometimes

[GitHub] spark issue #15689: initial set of changes for local[4] in core

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[GitHub] spark issue #15689: initial set of changes for local[4] in core

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[GitHub] spark issue #15689: initial set of changes for local[4] in core

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[GitHub] spark issue #15689: initial set of changes for local[4] in core

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