Author: niranda <niranda.perera@gmail.com>
Closes#5832 from nirandaperera/PersistanceEngine_abstract_class and squashes the following commits:
67b9d5a [niranda] changing persistence engine trait to an abstract class
Added word-boundary delimiters so that embedded text such as "-h" within command line options and values doesn't trigger the usage script and exit.
Author: Chris Biow <chris.biow@10gen.com>
Closes#5816 from cbiow/patch-1 and squashes the following commits:
36b3726 [Chris Biow] Limit help option regex
This is based on #3098 from debasish83.
1. BLAS' GEMM is used to compute inner products.
2. Reverted changes to MovieLensALS. SPARK-4231 should be addressed in a separate PR.
3. ~~Fixed a bug in topByKey~~
Closes#3098
debasish83 coderxiang
Author: Debasish Das <debasish.das@one.verizon.com>
Author: Xiangrui Meng <meng@databricks.com>
Closes#5829 from mengxr/SPARK-3066 and squashes the following commits:
22e6a87 [Xiangrui Meng] topByKey was correct. update its usage
389b381 [Xiangrui Meng] fix indentation
49953de [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into SPARK-3066
cb9799a [Xiangrui Meng] revert MovieLensALS
f864f5e [Xiangrui Meng] update test and fix a bug in topByKey
c5e0181 [Xiangrui Meng] use GEMM and topByKey
3a0c4eb [Debasish Das] updated with spark master
98fa424 [Debasish Das] updated with master
ee99571 [Debasish Das] addressed initial review comments;merged with master;added tests for batch predict APIs in matrix factorization
3f97c49 [Debasish Das] fixed spark coding style for imports
7163a5c [Debasish Das] Added API for batch user and product recommendation; MAP calculation for product recommendation per user using randomized split
d144f57 [Debasish Das] recommendAll API to MatrixFactorizationModel, uses topK finding using BoundedPriorityQueue similar to RDD.top
f38a1b5 [Debasish Das] use sampleByKey for per user sampling
10cbb37 [Debasish Das] provide ratio for topN product validation; generate MAP and prec@k metric for movielens dataset
9fa063e [Debasish Das] import scala.math.round
4bbae0f [Debasish Das] comments fixed as per scalastyle
cd3ab31 [Debasish Das] merged with AbstractParams serialization bug
9b3951f [Debasish Das] validate user/product on MovieLens dataset through user input and compute map measure along with rmse
This change modifies the event logging listener to write the logs for different application
attempts to different files. The attempt ID is set by the scheduler backend, so as long
as the backend returns that ID to SparkContext, things should work. Currently, the
YARN backend does that.
The history server was also modified to model multiple attempts per application. Each
attempt has its own UI and a separate row in the listing table, so that users can look at
all the attempts separately. The UI "adapts" itself to avoid showing attempt-specific info
when all the applications being shown have a single attempt.
Author: Marcelo Vanzin <vanzin@cloudera.com>
Author: twinkle sachdeva <twinkle@kite.ggn.in.guavus.com>
Author: twinkle.sachdeva <twinkle.sachdeva@guavus.com>
Author: twinkle sachdeva <twinkle.sachdeva@guavus.com>
Closes#5432 from vanzin/SPARK-4705 and squashes the following commits:
7e289fa [Marcelo Vanzin] Review feedback.
f66dcc5 [Marcelo Vanzin] Merge branch 'master' into SPARK-4705
bc885b7 [Marcelo Vanzin] Review feedback.
76a3651 [Marcelo Vanzin] Fix log cleaner, add test.
7c381ec [Marcelo Vanzin] Merge branch 'master' into SPARK-4705
1aa309d [Marcelo Vanzin] Improve sorting of app attempts.
2ad77e7 [Marcelo Vanzin] Missed a reference to the old property name.
9d59d92 [Marcelo Vanzin] Scalastyle...
d5a9c37 [Marcelo Vanzin] Update JsonProtocol test, make property name consistent.
ba34b69 [Marcelo Vanzin] Use Option[String] for attempt id.
f1cb9b3 [Marcelo Vanzin] Merge branch 'master' into SPARK-4705
c14ec19 [Marcelo Vanzin] Merge branch 'master' into SPARK-4705
9092d39 [Marcelo Vanzin] Merge branch 'master' into SPARK-4705
86de638 [Marcelo Vanzin] Merge branch 'master' into SPARK-4705
07446c6 [Marcelo Vanzin] Disable striping for app id / name when multiple attempts exist.
9092af5 [Marcelo Vanzin] Fix HistoryServer test.
3a14503 [Marcelo Vanzin] Argh scalastyle.
657ec18 [Marcelo Vanzin] Fix yarn history URL, app links.
c3e0a82 [Marcelo Vanzin] Move app name to app info, more UI fixes.
ce5ee5d [Marcelo Vanzin] Misc UI, test, style fixes.
cbe8bba [Marcelo Vanzin] Attempt ID in listener event should be an option.
88b1de8 [Marcelo Vanzin] Add a test for apps with multiple attempts.
3245aa2 [Marcelo Vanzin] Make app attempts part of the history server model.
5fd5c6f [Marcelo Vanzin] Fix my broken rebase.
318525a [twinkle.sachdeva] SPARK-4705: 1) moved from directory structure to single file, as per the master branch. 2) Added the attempt id inside the SparkListenerApplicationStart, to make the info available independent of directory structure. 3) Changes in History Server to render the UI as per the snaphot II
6b2e521 [twinkle sachdeva] SPARK-4705 Incorporating the review comments regarding formatting, will do the rest of the changes after this
4c1fc26 [twinkle sachdeva] SPARK-4705 Incorporating the review comments regarding formatting, will do the rest of the changes after this
0eb7722 [twinkle sachdeva] SPARK-4705: Doing cherry-pick of fix into master
I sometimes trouble-shoot and analyse the cause of long time spending job.
At the time, I find the stages which spends long time or fails, then I find the tasks which spends long time or fails, next I analyse the proportion of each phase in a task.
Another case, I find executors which spends long time for running a task and analyse the details of a task.
In such situation, I think it's helpful to visualize timeline for each application, job, task and the details of proportion of activity for each task.
I added 3 timeline features to existing Web UI.
[Application Timeline View]
This view shows following things.
* When each executor was added/removed and the reason why it's removed.
* When each job was started/finished.
* Status of each job.
[Stage Timeline View]
Similar to Application Timeline View, this view shows following things.
* When each executor was added/removed and the reason why it's removed.
* When each job was started/finished.
* Status of each stage.
[Task Assignment Timeline View]
This view shows following things.
* When each task started/finished
* How long each task spent and the proportion.
* Status of each task.
* Where each task ran on.
All the view above is zoomable by mouse wheel action and scrollable by drag action.
Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>
Closes#2342 from sarutak/timeline-viewer-feature and squashes the following commits:
11fe67d [Kousuke Saruta] Fixed conflict
79ac03d [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into timeline-viewer-feature
a91abd3 [Kousuke Saruta] Merge branch 'master' of https://github.com/apache/spark into timeline-viewer-feature
ef34a5b [Kousuke Saruta] Implement tooltip using bootstrap
b09d0c5 [Kousuke Saruta] Move `stroke` and `fill` attribute of rect elements to css
d3c63c8 [Kousuke Saruta] Fixed a little bit bugs
a36291b [Kousuke Saruta] Merge branch 'master' of https://github.com/apache/spark into timeline-viewer-feature
28714b6 [Kousuke Saruta] Fixed highlight issue
0dc4278 [Kousuke Saruta] Addressed most of Patrics's feedbacks
8110acf [Kousuke Saruta] Added scroll limit to Job timeline
974a64a [Kousuke Saruta] Removed unused function
ee7a7f0 [Kousuke Saruta] Refactored
6a91872 [Kousuke Saruta] Temporary commit
6693f34 [Kousuke Saruta] Added link to job/stage box in the timeline in order to move to corresponding row when we click
8f88222 [Kousuke Saruta] Added job/stage description
aeed4b1 [Kousuke Saruta] Removed stage timeline
fc1696c [Kousuke Saruta] Merge branch 'timeline-viewer-feature' of github.com:sarutak/spark into timeline-viewer-feature
999ccd4 [Kousuke Saruta] Improved scalability
0fc6a31 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into timeline-viewer-feature
19815ae [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into timeline-viewer-feature
68b7540 [Kousuke Saruta] Merge branch 'timeline-viewer-feature' of github.com:sarutak/spark into timeline-viewer-feature
52b5f0b [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into timeline-viewer-feature
dec85db [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into timeline-viewer-feature
fcdab7d [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into timeline-viewer-feature
dab7cc1 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into timeline-viewer-feature
09cce97 [Kousuke Saruta] Cleanuped
16f82cf [Kousuke Saruta] Cleanuped
9fb522e [Kousuke Saruta] Cleanuped
d05f2c2 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into timeline-viewer-feature
e85e9aa [Kousuke Saruta] Cleanup: Added TimelineViewUtils.scala
a76e569 [Kousuke Saruta] Removed unused setting in timeline-view.css
5ce1b21 [Kousuke Saruta] Added vis.min.js, vis.min.css and vis.map to .rat-exclude
082f709 [Kousuke Saruta] Added Timeline-View feature for Applications, Jobs and Stages
Adds
rank, recommendUsers and RecommendProducts to MatrixFactorizationModel in PySpark.
Author: MechCoder <manojkumarsivaraj334@gmail.com>
Closes#5807 from MechCoder/spark-6257 and squashes the following commits:
09629c6 [MechCoder] doc
953b326 [MechCoder] [SPARK-6257] MLlib API missing items in Recommendation
Read the port from RpcEnv to check the result so that it will success even if port conflicts
Author: zsxwing <zsxwing@gmail.com>
Closes#5822 from zsxwing/SPARK-7291 and squashes the following commits:
e521b84 [zsxwing] Fix a flaky test in AkkaRpcEnvSuite
andrewor14 pwendell I reenabled the test. Let's see if it's fixed. I did also notice that `--jars` started to fail after this was ignored though in the JIRA. like [here](https://amplab.cs.berkeley.edu/jenkins/job/Spark-Master-SBT/AMPLAB_JENKINS_BUILD_PROFILE=hadoop2.0,label=centos/2238/consoleFull), you see that --jars fails for the same exact reason.
Has any change been made to Spark Submit recently? Did the test setup on Jenkins change? If we look into flaky tests last month, you wouldn't find this test among them.
Author: Burak Yavuz <brkyvz@gmail.com>
Closes#5826 from brkyvz/restart-test and squashes the following commits:
f509f68 [Burak Yavuz] enabled fixed test
Refer to the JIRA for the design doc and some perf results.
I wanted to call out some of the more possibly controversial changes up front:
* Map outputs are only stored in serialized form when Kryo is in use. I'm still unsure whether Java-serialized objects can be relocated. At the very least, Java serialization writes out a stream header which causes problems with the current approach, so I decided to leave investigating this to future work.
* The shuffle now explicitly operates on key-value pairs instead of any object. Data is written to shuffle files in alternating keys and values instead of key-value tuples. `BlockObjectWriter.write` now accepts a key argument and a value argument instead of any object.
* The map output buffer can hold a max of Integer.MAX_VALUE bytes. Though this wouldn't be terribly difficult to change.
* When spilling occurs, the objects that still in memory at merge time end up serialized and deserialized an extra time.
Author: Sandy Ryza <sandy@cloudera.com>
Closes#4450 from sryza/sandy-spark-4550 and squashes the following commits:
8c70dd9 [Sandy Ryza] Fix serialization
9c16fe6 [Sandy Ryza] Fix a couple tests and move getAutoReset to KryoSerializerInstance
6c54e06 [Sandy Ryza] Fix scalastyle
d8462d8 [Sandy Ryza] SPARK-4550
This is the classes for creating off-heap block storage API. It also includes the migration for Tachyon. The diff seems to be big, but it mainly just rename tachyon to offheap. New implementation for hdfs will be submit for review in spark-6112.
Author: Zhan Zhang <zhazhan@gmail.com>
Closes#5430 from zhzhan/SPARK-6479 and squashes the following commits:
60acd84 [Zhan Zhang] minor change to kickoff the test
12f54c9 [Zhan Zhang] solve merge conflicts
a54132c [Zhan Zhang] solve review comments
ffb8e00 [Zhan Zhang] rebase to sparkcontext change
6e121e0 [Zhan Zhang] resolve review comments and restructure blockmanasger code
a7aed6c [Zhan Zhang] add Tachyon migration code
186de31 [Zhan Zhang] initial commit for off-heap block storage api
Adds the functions `rand` (Uniform Dist) and `randn` (Normal Dist.) as expressions to DataFrames.
cc mengxr rxin
Author: Burak Yavuz <brkyvz@gmail.com>
Closes#5819 from brkyvz/df-rng and squashes the following commits:
50d69d4 [Burak Yavuz] add seed for test that failed
4234c3a [Burak Yavuz] fix Rand expression
13cad5c [Burak Yavuz] couple fixes
7d53953 [Burak Yavuz] waiting for hive tests
b453716 [Burak Yavuz] move radn with seed down
03637f0 [Burak Yavuz] fix broken hive func
c5909eb [Burak Yavuz] deleted old implementation of Rand
6d43895 [Burak Yavuz] implemented random generators
Fixed the following flaky test
```Scala
[info] StreamingListenerSuite:
[info] - batch info reporting (782 milliseconds)
[info] - receiver info reporting *** FAILED *** (3 seconds, 911 milliseconds)
[info] The code passed to eventually never returned normally. Attempted 10 times over 3.4735783689999997 seconds. Last failure message: 0 did not equal 1. (StreamingListenerSuite.scala:104)
[info] org.scalatest.exceptions.TestFailedDueToTimeoutException:
[info] at org.scalatest.concurrent.Eventually$class.tryTryAgain$1(Eventually.scala:420)
[info] at org.scalatest.concurrent.Eventually$class.eventually(Eventually.scala:438)
[info] at org.scalatest.concurrent.Eventually$.eventually(Eventually.scala:478)
[info] at org.scalatest.concurrent.Eventually$class.eventually(Eventually.scala:307)
[info] at org.scalatest.concurrent.Eventually$.eventually(Eventually.scala:478)
[info] at org.apache.spark.streaming.StreamingListenerSuite$$anonfun$2.apply$mcV$sp(StreamingListenerSuite.scala:104)
[info] at org.apache.spark.streaming.StreamingListenerSuite$$anonfun$2.apply(StreamingListenerSuite.scala:94)
[info] at org.apache.spark.streaming.StreamingListenerSuite$$anonfun$2.apply(StreamingListenerSuite.scala:94)
[info] at org.scalatest.Transformer$$anonfun$apply$1.apply$mcV$sp(Transformer.scala:22)
[info] at org.scalatest.OutcomeOf$class.outcomeOf(OutcomeOf.scala:85)
[info] at org.scalatest.OutcomeOf$.outcomeOf(OutcomeOf.scala:104)
[info] at org.scalatest.Transformer.apply(Transformer.scala:22)
[info] at org.scalatest.Transformer.apply(Transformer.scala:20)
[info] at org.scalatest.FunSuiteLike$$anon$1.apply(FunSuiteLike.scala:166)
[info] at org.scalatest.Suite$class.withFixture(Suite.scala:1122)
[info] at org.scalatest.FunSuite.withFixture(FunSuite.scala:1555)
[info] at org.scalatest.FunSuiteLike$class.invokeWithFixture$1(FunSuiteLike.scala:163)
[info] at org.scalatest.FunSuiteLike$$anonfun$runTest$1.apply(FunSuiteLike.scala:175)
[info] at org.scalatest.FunSuiteLike$$anonfun$runTest$1.apply(FunSuiteLike.scala:175)
[info] at org.scalatest.SuperEngine.runTestImpl(Engine.scala:306)
[info] at org.scalatest.FunSuiteLike$class.runTest(FunSuiteLike.scala:175)
[info] at org.apache.spark.streaming.StreamingListenerSuite.org$scalatest$BeforeAndAfter$$super$runTest(StreamingListenerSuite.scala:34)
[info] at org.scalatest.BeforeAndAfter$class.runTest(BeforeAndAfter.scala:200)
[info] at org.apache.spark.streaming.StreamingListenerSuite.runTest(StreamingListenerSuite.scala:34)
[info] at org.scalatest.FunSuiteLike$$anonfun$runTests$1.apply(FunSuiteLike.scala:208)
[info] at org.scalatest.FunSuiteLike$$anonfun$runTests$1.apply(FunSuiteLike.scala:208)
[info] at org.scalatest.SuperEngine$$anonfun$traverseSubNodes$1$1.apply(Engine.scala:413)
[info] at org.scalatest.SuperEngine$$anonfun$traverseSubNodes$1$1.apply(Engine.scala:401)
[info] at scala.collection.immutable.List.foreach(List.scala:318)
[info] at org.scalatest.SuperEngine.traverseSubNodes$1(Engine.scala:401)
[info] at org.scalatest.SuperEngine.org$scalatest$SuperEngine$$runTestsInBranch(Engine.scala:396)
[info] at org.scalatest.SuperEngine.runTestsImpl(Engine.scala:483)
[info] at org.scalatest.FunSuiteLike$class.runTests(FunSuiteLike.scala:208)
[info] at org.scalatest.FunSuite.runTests(FunSuite.scala:1555)
[info] at org.scalatest.Suite$class.run(Suite.scala:1424)
[info] at org.scalatest.FunSuite.org$scalatest$FunSuiteLike$$super$run(FunSuite.scala:1555)
[info] at org.scalatest.FunSuiteLike$$anonfun$run$1.apply(FunSuiteLike.scala:212)
[info] at org.scalatest.FunSuiteLike$$anonfun$run$1.apply(FunSuiteLike.scala:212)
[info] at org.scalatest.SuperEngine.runImpl(Engine.scala:545)
[info] at org.scalatest.FunSuiteLike$class.run(FunSuiteLike.scala:212)
[info] at org.apache.spark.streaming.StreamingListenerSuite.org$scalatest$BeforeAndAfter$$super$run(StreamingListenerSuite.scala:34)
[info] at org.scalatest.BeforeAndAfter$class.run(BeforeAndAfter.scala:241)
[info] at org.apache.spark.streaming.StreamingListenerSuite.run(StreamingListenerSuite.scala:34)
[info] at org.scalatest.tools.Framework.org$scalatest$tools$Framework$$runSuite(Framework.scala:462)
[info] at org.scalatest.tools.Framework$ScalaTestTask.execute(Framework.scala:671)
[info] at sbt.ForkMain$Run$2.call(ForkMain.java:294)
[info] at sbt.ForkMain$Run$2.call(ForkMain.java:284)
[info] at java.util.concurrent.FutureTask.run(FutureTask.java:262)
[info] at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
[info] at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
[info] at java.lang.Thread.run(Thread.java:745)
[info] Cause: org.scalatest.exceptions.TestFailedException: 0 did not equal 1
[info] at org.scalatest.MatchersHelper$.newTestFailedException(MatchersHelper.scala:160)
[info] at org.scalatest.Matchers$ShouldMethodHelper$.shouldMatcher(Matchers.scala:6231)
[info] at org.scalatest.Matchers$AnyShouldWrapper.should(Matchers.scala:6277)
[info] at org.apache.spark.streaming.StreamingListenerSuite$$anonfun$2$$anonfun$apply$mcV$sp$1.apply$mcV$sp(StreamingListenerSuite.scala:105)
[info] at org.apache.spark.streaming.StreamingListenerSuite$$anonfun$2$$anonfun$apply$mcV$sp$1.apply(StreamingListenerSuite.scala:104)
[info] at org.apache.spark.streaming.StreamingListenerSuite$$anonfun$2$$anonfun$apply$mcV$sp$1.apply(StreamingListenerSuite.scala:104)
[info] at org.scalatest.concurrent.Eventually$class.makeAValiantAttempt$1(Eventually.scala:394)
[info] at org.scalatest.concurrent.Eventually$class.tryTryAgain$1(Eventually.scala:408)
[info] at org.scalatest.concurrent.Eventually$class.eventually(Eventually.scala:438)
[info] at org.scalatest.concurrent.Eventually$.eventually(Eventually.scala:478)
[info] at org.scalatest.concurrent.Eventually$class.eventually(Eventually.scala:307)
[info] at org.scalatest.concurrent.Eventually$.eventually(Eventually.scala:478)
[info] at org.apache.spark.streaming.StreamingListenerSuite$$anonfun$2.apply$mcV$sp(StreamingListenerSuite.scala:104)
[info] at org.apache.spark.streaming.StreamingListenerSuite$$anonfun$2.apply(StreamingListenerSuite.scala:94)
[info] at org.apache.spark.streaming.StreamingListenerSuite$$anonfun$2.apply(StreamingListenerSuite.scala:94)
[info] at org.scalatest.Transformer$$anonfun$apply$1.apply$mcV$sp(Transformer.scala:22)
[info] at org.scalatest.OutcomeOf$class.outcomeOf(OutcomeOf.scala:85)
[info] at org.scalatest.OutcomeOf$.outcomeOf(OutcomeOf.scala:104)
[info] at org.scalatest.Transformer.apply(Transformer.scala:22)
[info] at org.scalatest.Transformer.apply(Transformer.scala:20)
[info] at org.scalatest.FunSuiteLike$$anon$1.apply(FunSuiteLike.scala:166)
[info] at org.scalatest.Suite$class.withFixture(Suite.scala:1122)
[info] at org.scalatest.FunSuite.withFixture(FunSuite.scala:1555)
[info] at org.scalatest.FunSuiteLike$class.invokeWithFixture$1(FunSuiteLike.scala:163)
[info] at org.scalatest.FunSuiteLike$$anonfun$runTest$1.apply(FunSuiteLike.scala:175)
[info] at org.scalatest.FunSuiteLike$$anonfun$runTest$1.apply(FunSuiteLike.scala:175)
[info] at org.scalatest.SuperEngine.runTestImpl(Engine.scala:306)
[info] at org.scalatest.FunSuiteLike$class.runTest(FunSuiteLike.scala:175)
[info] at org.apache.spark.streaming.StreamingListenerSuite.org$scalatest$BeforeAndAfter$$super$runTest(StreamingListenerSuite.scala:34)
[info] at org.scalatest.BeforeAndAfter$class.runTest(BeforeAndAfter.scala:200)
[info] at org.apache.spark.streaming.StreamingListenerSuite.runTest(StreamingListenerSuite.scala:34)
[info] at org.scalatest.FunSuiteLike$$anonfun$runTests$1.apply(FunSuiteLike.scala:208)
[info] at org.scalatest.FunSuiteLike$$anonfun$runTests$1.apply(FunSuiteLike.scala:208)
[info] at org.scalatest.SuperEngine$$anonfun$traverseSubNodes$1$1.apply(Engine.scala:413)
[info] at org.scalatest.SuperEngine$$anonfun$traverseSubNodes$1$1.apply(Engine.scala:401)
[info] at scala.collection.immutable.List.foreach(List.scala:318)
[info] at org.scalatest.SuperEngine.traverseSubNodes$1(Engine.scala:401)
[info] at org.scalatest.SuperEngine.org$scalatest$SuperEngine$$runTestsInBranch(Engine.scala:396)
[info] at org.scalatest.SuperEngine.runTestsImpl(Engine.scala:483)
[info] at org.scalatest.FunSuiteLike$class.runTests(FunSuiteLike.scala:208)
[info] at org.scalatest.FunSuite.runTests(FunSuite.scala:1555)
[info] at org.scalatest.Suite$class.run(Suite.scala:1424)
[info] at org.scalatest.FunSuite.org$scalatest$FunSuiteLike$$super$run(FunSuite.scala:1555)
[info] at org.scalatest.FunSuiteLike$$anonfun$run$1.apply(FunSuiteLike.scala:212)
[info] at org.scalatest.FunSuiteLike$$anonfun$run$1.apply(FunSuiteLike.scala:212)
[info] at org.scalatest.SuperEngine.runImpl(Engine.scala:545)
[info] at org.scalatest.FunSuiteLike$class.run(FunSuiteLike.scala:212)
[info] at org.apache.spark.streaming.StreamingListenerSuite.org$scalatest$BeforeAndAfter$$super$run(StreamingListenerSuite.scala:34)
[info] at org.scalatest.BeforeAndAfter$class.run(BeforeAndAfter.scala:241)
[info] at org.apache.spark.streaming.StreamingListenerSuite.run(StreamingListenerSuite.scala:34)
[info] at org.scalatest.tools.Framework.org$scalatest$tools$Framework$$runSuite(Framework.scala:462)
[info] at org.scalatest.tools.Framework$ScalaTestTask.execute(Framework.scala:671)
[info] at sbt.ForkMain$Run$2.call(ForkMain.java:294)
[info] at sbt.ForkMain$Run$2.call(ForkMain.java:284)
[info] at java.util.concurrent.FutureTask.run(FutureTask.java:262)
[info] at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
[info] at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
[info] at java.lang.Thread.run(Thread.java:745)
```
The original codes didn't have a memory barrier in the `eventually` closure, which might fail the test, because JVM doesn't guarantee the memory consistency between different threads without a memory barrier.
This PR used `ConcurrentLinkedQueue` to set up the memory barrier.
Author: zsxwing <zsxwing@gmail.com>
Closes#5812 from zsxwing/SPARK-7282 and squashes the following commits:
59115ef [zsxwing] Use SynchronizedBuffer
014dd2b [zsxwing] Fix the race conditions in StreamingListenerSuite
Run following sql get error
`SELECT r.*
FROM testData l join testData2 r on (l.key = r.a)`
Author: scwf <wangfei1@huawei.com>
Closes#5690 from scwf/tablestar and squashes the following commits:
3b2e2b6 [scwf] support table.star
This PR aims to make the SQL Parser Pluggable, and user can register it's own parser via Spark SQL CLI.
```
# add the jar into the classpath
$hchengmydesktop:spark>bin/spark-sql --jars sql99.jar
-- switch to "hiveql" dialect
spark-sql>SET spark.sql.dialect=hiveql;
spark-sql>SELECT * FROM src LIMIT 1;
-- switch to "sql" dialect
spark-sql>SET spark.sql.dialect=sql;
spark-sql>SELECT * FROM src LIMIT 1;
-- switch to a custom dialect
spark-sql>SET spark.sql.dialect=com.xxx.xxx.SQL99Dialect;
spark-sql>SELECT * FROM src LIMIT 1;
-- register the non-exist SQL dialect
spark-sql> SET spark.sql.dialect=NotExistedClass;
spark-sql> SELECT * FROM src LIMIT 1;
-- Exception will be thrown and switch to default sql dialect ("sql" for SQLContext and "hiveql" for HiveContext)
```
Author: Cheng Hao <hao.cheng@intel.com>
Closes#4015 from chenghao-intel/sqlparser and squashes the following commits:
493775c [Cheng Hao] update the code as feedback
81a731f [Cheng Hao] remove the unecessary comment
aab0b0b [Cheng Hao] polish the code a little bit
49b9d81 [Cheng Hao] shrink the comment for rebasing
Fixed `java.sql.SQLException: No suitable driver found` when loading DataFrame into Spark SQL if the driver is supplied with `--jars` argument.
The problem is in `java.sql.DriverManager` class that can't access drivers loaded by Spark ClassLoader.
Wrappers that forward requests are created for these drivers.
Also, it's not necessary any more to include JDBC drivers in `--driver-class-path` in local mode, specifying in `--jars` argument is sufficient.
Author: Vyacheslav Baranov <slavik.baranov@gmail.com>
Closes#5782 from SlavikBaranov/SPARK-6913 and squashes the following commits:
510c43f [Vyacheslav Baranov] [SPARK-6913] Fixed review comments
b2a727c [Vyacheslav Baranov] [SPARK-6913] Fixed thread race on driver registration
c8294ae [Vyacheslav Baranov] [SPARK-6913] Fixed "No suitable driver found" when using using JDBC driver added with SparkContext.addJar
Now in spark sql optimizer we only push down right side filter for left semi join, actually we can push down left side filter because left semi join is doing filter on left table essentially.
Author: wangfei <wangfei1@huawei.com>
Author: scwf <wangfei1@huawei.com>
Closes#5677 from scwf/leftsemi and squashes the following commits:
483d205 [wangfei] update with master to fix compile issue
82df0e1 [wangfei] Merge branch 'master' of https://github.com/apache/spark into leftsemi
d68a053 [wangfei] added apply
8f48a3d [scwf] added test
ebadaa9 [wangfei] left filter push down for left semi join
Using newPredicate in NestedLoopJoin instead of InterpretedPredicate to make it can make use of code generation
Author: scwf <wangfei1@huawei.com>
Closes#5665 from scwf/NLP and squashes the following commits:
d19dd31 [scwf] improvement
a887c02 [scwf] improve for NLP boundCondition
Takes a column name/s and returns a new DataFrame that drops a column/s.
Author: rakeshchalasani <vnit.rakesh@gmail.com>
Closes#5818 from rakeshchalasani/SPARK-7280 and squashes the following commits:
ce2ec09 [rakeshchalasani] Minor edit
45c06f1 [rakeshchalasani] Change withColumnRename and format changes
f68945a [rakeshchalasani] Minor fix
0b9104d [rakeshchalasani] Drop one column at a time
289afd2 [rakeshchalasani] [SPARK-7280][SQL] Add "drop" column/s on a data frame
Finding frequent items with possibly false positives, using the algorithm described in `http://www.cs.umd.edu/~samir/498/karp.pdf`.
public API under:
```
df.stat.freqItems(cols: Array[String], support: Double = 0.001): DataFrame
```
The output is a local DataFrame having the input column names with `-freqItems` appended to it. This is a single pass algorithm that may return false positives, but no false negatives.
cc mengxr rxin
Let's get the implementations in, I can add python API in a follow up PR.
Author: Burak Yavuz <brkyvz@gmail.com>
Closes#5799 from brkyvz/freq-items and squashes the following commits:
a6ec82c [Burak Yavuz] addressed comments v?
39b1bba [Burak Yavuz] removed toSeq
0915e23 [Burak Yavuz] addressed comments v2.1
3a5c177 [Burak Yavuz] addressed comments v2.0
482e741 [Burak Yavuz] removed old import
38e784d [Burak Yavuz] addressed comments v1.0
8279d4d [Burak Yavuz] added default value for support
3d82168 [Burak Yavuz] made base implementation
Author: DB Tsai <dbt@netflix.com>
Closes#5809 from dbtsai/format and squashes the following commits:
6904eed [DB Tsai] triger jenkins
9146e19 [DB Tsai] initial commit
Now that 1.3 has been released, we should enable MiMa checks for the `sql` subproject.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#5727 from JoshRosen/enable-more-mima-checks and squashes the following commits:
3ad302b [Josh Rosen] Merge remote-tracking branch 'origin/master' into enable-more-mima-checks
0c48e4d [Josh Rosen] Merge remote-tracking branch 'origin/master' into enable-more-mima-checks
e276cee [Josh Rosen] Fix SQL MiMa checks via excludes and private[sql]
44d0d01 [Josh Rosen] Add back 'launcher' exclude
1aae027 [Josh Rosen] Enable MiMa checks for launcher and sql projects.
This patch suppresses compiler warnings due to our use of `sun.misc.Unsafe` (introduced in #5725). These warnings can only be suppressed via the `-XDignore.symbol.file` javac flag; the `SuppressWarnings` annotation won't work for these.
In order to restrict uses of this compiler flag to the `unsafe` module, I placed a facade in front of `Unsafe` so that other modules won't call it directly. This facade also will also help us to avoid accidental usage of deprecated Unsafe methods or methods that aren't supported in Java 6.
I also removed an unnecessary use of `Unsafe.setMemory`, which isn't present in certain versions of Java 6, and excluded the new `unsafe` module from Javadoc.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#5814 from JoshRosen/unsafe-compiler-warnings-fixes and squashes the following commits:
9e8c483 [Josh Rosen] Exclude new unsafe module from Javadoc
ba75ecf [Josh Rosen] Only apply -XDignore.symbol.file flag in unsafe project.
7403345 [Josh Rosen] Put facade in front of Unsafe.
50230c0 [Josh Rosen] Remove usage of Unsafe.setMemory
96d41c9 [Josh Rosen] Use -XDignore.symbol.file to suppress warnings about sun.misc.Unsafe usage
JIRA: https://issues.apache.org/jira/browse/SPARK-7196
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#5777 from viirya/jdbc_precision and squashes the following commits:
f40f5e6 [Liang-Chi Hsieh] Support precision and scale for NUMERIC type.
49acbf9 [Liang-Chi Hsieh] Add unit test.
a509e19 [Liang-Chi Hsieh] Support precision and scale of decimal type for JDBC.
Added ml.recommendation, ml.regression to SparkBuild
CC: mengxr
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#5758 from jkbradley/SPARK-7207 and squashes the following commits:
a28158a [Joseph K. Bradley] Added ml.recommendation, ml.regression to SparkBuild
Current Spark apps running on Secure YARN/HDFS would not be able to write data
to HDFS after 7 days, since delegation tokens cannot be renewed beyond that. This
means Spark Streaming apps will not be able to run on Secure YARN.
This commit adds basic functionality to fix this issue. In this patch:
- new parameters are added - principal and keytab, which can be used to login to a KDC
- the client logs in, and then get tokens to start the AM
- the keytab is copied to the staging directory
- the AM waits for 60% of the time till expiry of the tokens and then logs in using the keytab
- each time after 60% of the time, new tokens are created and sent to the executors
Currently, to avoid complicating the architecture, we set the keytab and principal in the
SparkHadoopUtil singleton, and schedule a login. Once the login is completed, a callback is scheduled.
This is being posted for feedback, so I can gather feedback on the general implementation.
There are currently a bunch of things to do:
- [x] logging
- [x] testing - I plan to manually test this soon. If you have ideas of how to add unit tests, comment.
- [x] add code to ensure that if these params are set in non-YARN cluster mode, we complain
- [x] documentation
- [x] Have the executors request for credentials from the AM, so that retries are possible.
Author: Hari Shreedharan <hshreedharan@apache.org>
Closes#4688 from harishreedharan/kerberos-longrunning and squashes the following commits:
36eb8a9 [Hari Shreedharan] Change the renewal interval config param. Fix a bunch of comments.
611923a [Hari Shreedharan] Make sure the namenodes are listed correctly for creating tokens.
09fe224 [Hari Shreedharan] Use token.renew to get token's renewal interval rather than using hdfs-site.xml
6963bbc [Hari Shreedharan] Schedule renewal in AM before starting user class. Else, a restarted AM cannot access HDFS if the user class tries to.
072659e [Hari Shreedharan] Fix build failure caused by thread factory getting moved to ThreadUtils.
f041dd3 [Hari Shreedharan] Merge branch 'master' into kerberos-longrunning
42eead4 [Hari Shreedharan] Remove RPC part. Refactor and move methods around, use renewal interval rather than max lifetime to create new tokens.
ebb36f5 [Hari Shreedharan] Merge branch 'master' into kerberos-longrunning
bc083e3 [Hari Shreedharan] Overload RegisteredExecutor to send tokens. Minor doc updates.
7b19643 [Hari Shreedharan] Merge branch 'master' into kerberos-longrunning
8a4f268 [Hari Shreedharan] Added docs in the security guide. Changed some code to ensure that the renewer objects are created only if required.
e800c8b [Hari Shreedharan] Restore original RegisteredExecutor message, and send new tokens via NewTokens message.
0e9507e [Hari Shreedharan] Merge branch 'master' into kerberos-longrunning
7f1bc58 [Hari Shreedharan] Minor fixes, cleanup.
bcd11f9 [Hari Shreedharan] Refactor AM and Executor token update code into separate classes, also send tokens via akka on executor startup.
f74303c [Hari Shreedharan] Move the new logic into specialized classes. Add cleanup for old credentials files.
2f9975c [Hari Shreedharan] Ensure new tokens are written out immediately on AM restart. Also, pikc up the latest suffix from HDFS if the AM is restarted.
61b2b27 [Hari Shreedharan] Account for AM restarts by making sure lastSuffix is read from the files on HDFS.
62c45ce [Hari Shreedharan] Relogin from keytab periodically.
fa233bd [Hari Shreedharan] Adding logging, fixing minor formatting and ordering issues.
42813b4 [Hari Shreedharan] Remove utils.sh, which was re-added due to merge with master.
0de27ee [Hari Shreedharan] Merge branch 'master' into kerberos-longrunning
55522e3 [Hari Shreedharan] Fix failure caused by Preconditions ambiguity.
9ef5f1b [Hari Shreedharan] Added explanation of how the credentials refresh works, some other minor fixes.
f4fd711 [Hari Shreedharan] Fix SparkConf usage.
2debcea [Hari Shreedharan] Change the file structure for credentials files. I will push a followup patch which adds a cleanup mechanism for old credentials files. The credentials files are small and few enough for it to cause issues on HDFS.
af6d5f0 [Hari Shreedharan] Cleaning up files where changes weren't required.
f0f54cb [Hari Shreedharan] Be more defensive when updating the credentials file.
f6954da [Hari Shreedharan] Got rid of Akka communication to renew, instead the executors check a known file's modification time to read the credentials.
5c11c3e [Hari Shreedharan] Move tests to YarnSparkHadoopUtil to fix compile issues.
b4cb917 [Hari Shreedharan] Send keytab to AM via DistributedCache rather than directly via HDFS
0985b4e [Hari Shreedharan] Write tokens to HDFS and read them back when required, rather than sending them over the wire.
d79b2b9 [Hari Shreedharan] Make sure correct credentials are passed to FileSystem#addDelegationTokens()
8c6928a [Hari Shreedharan] Fix issue caused by direct creation of Actor object.
fb27f46 [Hari Shreedharan] Make sure principal and keytab are set before CoarseGrainedSchedulerBackend is started. Also schedule re-logins in CoarseGrainedSchedulerBackend#start()
41efde0 [Hari Shreedharan] Merge branch 'master' into kerberos-longrunning
d282d7a [Hari Shreedharan] Fix ClientSuite to set YARN mode, so that the correct class is used in tests.
bcfc374 [Hari Shreedharan] Fix Hadoop-1 build by adding no-op methods in SparkHadoopUtil, with impl in YarnSparkHadoopUtil.
f8fe694 [Hari Shreedharan] Handle None if keytab-login is not scheduled.
2b0d745 [Hari Shreedharan] [SPARK-5342][YARN] Allow long running Spark apps to run on secure YARN/HDFS.
ccba5bc [Hari Shreedharan] WIP: More changes wrt kerberos
77914dd [Hari Shreedharan] WIP: Add kerberos principal and keytab to YARN client.
This patch contains an `IvyTestUtils` file, which dynamically generates jars and pom files to test the `--packages` feature without having to rely on the internet, and Maven Central.
cc pwendell I know that there existed Util functions to create Jars and stuff already, but they didn't really serve my purposes as they appended random prefixes that was breaking things.
I also added the local repository tests. Notice that they work without passing the `repo` to `resolveMavenCoordinates`.
Author: Burak Yavuz <brkyvz@gmail.com>
Closes#5790 from brkyvz/maven-utils and squashes the following commits:
3ec79b7 [Burak Yavuz] addressed comments v0.2
a39151b [Burak Yavuz] address comments v0.1
172dfef [Burak Yavuz] use Ivy format
7476d06 [Burak Yavuz] added mock repository generator
See PDF attached to the JIRA issue 1406.
The contribution is my original work and I license the work to the project under the project's open source license.
Author: Vincenzo Selvaggio <vselvaggio@hotmail.it>
Author: Xiangrui Meng <meng@databricks.com>
Author: selvinsource <vselvaggio@hotmail.it>
Closes#3062 from selvinsource/mllib_pmml_model_export_SPARK-1406 and squashes the following commits:
852aac6 [Vincenzo Selvaggio] [SPARK-1406] Update JPMML version to 1.1.15 in LICENSE file
085cf42 [Vincenzo Selvaggio] [SPARK-1406] Added Double Min and Max Fixed scala style
30165c4 [Vincenzo Selvaggio] [SPARK-1406] Fixed extreme cases for logit
7a5e0ec [Vincenzo Selvaggio] [SPARK-1406] Binary classification for SVM and Logistic Regression
cfcb596 [Vincenzo Selvaggio] [SPARK-1406] Throw IllegalArgumentException when exporting a multinomial logistic regression
25dce33 [Vincenzo Selvaggio] [SPARK-1406] Update code to latest pmml model
dea98ca [Vincenzo Selvaggio] [SPARK-1406] Exclude transitive dependency for pmml model
66b7c12 [Vincenzo Selvaggio] [SPARK-1406] Updated pmml model lib to 1.1.15, latest Java 6 compatible
a0a55f7 [Vincenzo Selvaggio] Merge pull request #2 from mengxr/SPARK-1406
3c22f79 [Xiangrui Meng] more code style
e2313df [Vincenzo Selvaggio] Merge pull request #1 from mengxr/SPARK-1406
472d757 [Xiangrui Meng] fix code style
1676e15 [Vincenzo Selvaggio] fixed scala issue
e2ffae8 [Vincenzo Selvaggio] fixed scala style
b8823b0 [Vincenzo Selvaggio] Merge remote-tracking branch 'upstream/master' into mllib_pmml_model_export_SPARK-1406
b25bbf7 [Vincenzo Selvaggio] [SPARK-1406] Added export of pmml to distributed file system using the spark context
7a949d0 [Vincenzo Selvaggio] [SPARK-1406] Fixed scala style
f46c75c [Vincenzo Selvaggio] [SPARK-1406] Added PMMLExportable to supported models
7b33b4e [Vincenzo Selvaggio] [SPARK-1406] Added a PMMLExportable interface Restructured code in a new package mllib.pmml Supported models implements the new PMMLExportable interface: LogisticRegression, SVM, KMeansModel, LinearRegression, RidgeRegression, Lasso
d559ec5 [Vincenzo Selvaggio] Merge remote-tracking branch 'upstream/master' into mllib_pmml_model_export_SPARK-1406
8fe12bb [Vincenzo Selvaggio] [SPARK-1406] Adjusted logistic regression export description and target categories
03bc3a5 [Vincenzo Selvaggio] added logistic regression
da2ec11 [Vincenzo Selvaggio] [SPARK-1406] added linear SVM PMML export
82f2131 [Vincenzo Selvaggio] Merge remote-tracking branch 'upstream/master' into mllib_pmml_model_export_SPARK-1406
19adf29 [Vincenzo Selvaggio] [SPARK-1406] Fixed scala style
1faf985 [Vincenzo Selvaggio] [SPARK-1406] Added target field to the regression model for completeness Adjusted unit test to deal with this change
3ae8ae5 [Vincenzo Selvaggio] [SPARK-1406] Adjusted imported order according to the guidelines
c67ce81 [Vincenzo Selvaggio] Merge remote-tracking branch 'upstream/master' into mllib_pmml_model_export_SPARK-1406
78515ec [Vincenzo Selvaggio] [SPARK-1406] added pmml export for LinearRegressionModel, RidgeRegressionModel and LassoModel
e29dfb9 [Vincenzo Selvaggio] removed version, by default is set to 4.2 (latest from jpmml) removed copyright
ae8b993 [Vincenzo Selvaggio] updated some commented tests to use the new ModelExporter object reordered the imports
df8a89e [Vincenzo Selvaggio] added pmml version to pmml model changed the copyright to spark
a1b4dc3 [Vincenzo Selvaggio] updated imports
834ca44 [Vincenzo Selvaggio] reordered the import accordingly to the guidelines
349a76b [Vincenzo Selvaggio] new helper object to serialize the models to pmml format
c3ef9b8 [Vincenzo Selvaggio] set it to private
6357b98 [Vincenzo Selvaggio] set it to private
e1eb251 [Vincenzo Selvaggio] removed serialization part, this will be part of the ModelExporter helper object
aba5ee1 [Vincenzo Selvaggio] fixed cluster export
cd6c07c [Vincenzo Selvaggio] fixed scala style to run tests
f75b988 [Vincenzo Selvaggio] Merge remote-tracking branch 'origin/master' into mllib_pmml_model_export_SPARK-1406
07a29bf [selvinsource] Update LICENSE
8841439 [Vincenzo Selvaggio] adjust scala style in order to compile
1433b11 [Vincenzo Selvaggio] complete suite tests
8e71b8d [Vincenzo Selvaggio] kmeans pmml export implementation
9bc494f [Vincenzo Selvaggio] added scala suite tests added saveLocalFile to ModelExport trait
226e184 [Vincenzo Selvaggio] added javadoc and export model type in case there is a need to support other types of export (not just PMML)
a0e3679 [Vincenzo Selvaggio] export and pmml export traits kmeans test implementation
Author: DB Tsai <dbt@netflix.com>
Closes#5794 from dbtsai/clean and squashes the following commits:
ad639dd [DB Tsai] Indentation
834d527 [DB Tsai] Some code clean up.
small fixes regarding comments in PR #5761
cc rxin
Author: Burak Yavuz <brkyvz@gmail.com>
Closes#5795 from brkyvz/split-followup and squashes the following commits:
369c522 [Burak Yavuz] changed wording a little
1ea456f [Burak Yavuz] Addressed follow up comments
Author: 云峤 <chensong.cs@alibaba-inc.com>
Closes#5778 from kaka1992/fix_codegenon_datetype_mismatch and squashes the following commits:
1ad4cff [云峤] SPARK-7234 fix dateType mismatch
This is an initial commit for SPARK-6862. Once SPARK-6796 is merged, I will add the links to StreamingPage so that the user can jump to BatchPage.
Screenshots:
Author: zsxwing <zsxwing@gmail.com>
Closes#5473 from zsxwing/SPARK-6862 and squashes the following commits:
0727d35 [zsxwing] Change BatchUIData to a case class
b380cfb [zsxwing] Add createJobStart to eliminate duplicate codes
9a3083d [zsxwing] Rename XxxDatas -> XxxData
087ba98 [zsxwing] Refactor BatchInfo to store only necessary fields
cb62e4f [zsxwing] Use Seq[(OutputOpId, SparkJobId)] to store the id relations
72f8e7e [zsxwing] Add unit tests for BatchPage
1282b10 [zsxwing] Handle some corner cases and add tests for StreamingJobProgressListener
77a69ae [zsxwing] Refactor codes as per TD's comments
35ffd80 [zsxwing] Merge branch 'master' into SPARK-6862
15bdf9b [zsxwing] Add batch links and unit tests
4bf66b6 [zsxwing] Merge branch 'master' into SPARK-6862
7168807 [zsxwing] Limit the max width of the error message and fix nits in the UI
0b226f9 [zsxwing] Change 'Last Error' to 'Error'
fc98a43 [zsxwing] Put clearing local properties to finally and remove redundant private[streaming]
0c7b2eb [zsxwing] Add BatchPage to display details of a batch
Main change: Added isValid field to Param. Modified all usages to use isValid when relevant. Added helper methods in ParamValidate.
Also overrode Params.validate() in:
* CrossValidator + model
* Pipeline + model
I made a few updates for the elastic net patch:
* I changed "tol" to "convergenceTol"
* I added some documentation
This PR is Scala + Java only. Python will be in a follow-up PR.
CC: mengxr
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#5740 from jkbradley/enforce-validate and squashes the following commits:
ad9c6c1 [Joseph K. Bradley] re-generated sharedParams after merging with current master
76415e8 [Joseph K. Bradley] reverted convergenceTol to tol
af62f4b [Joseph K. Bradley] Removed changes to SparkBuild, python linalg. Fixed test failures. Renamed ParamValidate to ParamValidators. Removed explicit type from ParamValidators calls where possible.
bb2665a [Joseph K. Bradley] merged with elastic net pr
ecda302 [Joseph K. Bradley] fix rat tests, plus add a little doc
6895dfc [Joseph K. Bradley] small cleanups
069ac6d [Joseph K. Bradley] many cleanups
928fb84 [Joseph K. Bradley] Maybe done
a910ac7 [Joseph K. Bradley] still workin
6d60e2e [Joseph K. Bradley] Still workin
b987319 [Joseph K. Bradley] Partly done with adding checks, but blocking on adding checking functionality to Param
dbc9fb2 [Joseph K. Bradley] merged with master. enforcing Params.validate
Changed VectorIndexer so it does not carry non-ML metadata from the input to the output column. Removed ml.util.TestingUtils since VectorIndexer was the only use.
CC: mengxr
Author: Joseph K. Bradley <joseph@databricks.com>
Closes#5789 from jkbradley/vector-indexer-metadata and squashes the following commits:
b28e159 [Joseph K. Bradley] Changed VectorIndexer so it does not carry non-ML metadata from the input to the output column. Removed ml.util.TestingUtils since VectorIndexer was the only use.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#5772 from chenghao-intel/specific_row and squashes the following commits:
2cd064d [Cheng Hao] scala style issue
60347a2 [Cheng Hao] SpecificMutableRow should take integer type as internal representation for DateType
See JIRA: https://issues.apache.org/jira/browse/SPARK-7155
SparkContext's newAPIHadoopFile() does not support comma-separated list of files. For example, the following:
```scala
sc.newAPIHadoopFile("/root/file1.txt,/root/file2.txt", classOf[TextInputFormat], classOf[LongWritable], classOf[Text])
```
will throw
```
org.apache.hadoop.mapreduce.lib.input.InvalidInputException: Input path does not exist: file:/root/file1.txt,/root/file2.txt
```
However, the other API hadoopFile() is able to process comma-separated list of files correctly. In addition, since sc.textFile() uses hadoopFile(), it is also able to process comma-separated list of files correctly.
That means the behaviors of hadoopFile() and newAPIHadoopFile() are not aligned.
This pull request fix this issue and allows newAPIHadoopFile() to support comma-separated list of files as input.
A unit test has also been added in SparkContextSuite.scala. It creates two temporary text files as the input and tested against sc.textFile(), sc.hadoopFile(), and sc.newAPIHadoopFile().
Note: The contribution is my original work and that I license the work to the project under the project's open source license.
Author: yongtang <yongtang@users.noreply.github.com>
Closes#5708 from yongtang/SPARK-7155 and squashes the following commits:
654c80c [yongtang] [SPARK-7155] [CORE] Remove unneeded temp file deletion in unit test as parent dir is already temporary.
26faa6a [yongtang] [SPARK-7155] [CORE] Support comma-separated list of files as input for newAPIHadoopFile, wholeTextFiles, and binaryFiles. Use setInputPaths for consistency.
73e1f16 [yongtang] [SPARK-7155] [CORE] Allow newAPIHadoopFile to support comma-separated list of files as input.
see [SPARK-7181](https://issues.apache.org/jira/browse/SPARK-7181).
Author: Qiping Li <liqiping1991@gmail.com>
Closes#5737 from chouqin/externalsorter and squashes the following commits:
2924b93 [Qiping Li] fix inifite loop in Externalsorter's mergeWithAggregation
This is built on top of kaka1992 's PR #5711 using Logical plans.
Author: Burak Yavuz <brkyvz@gmail.com>
Closes#5761 from brkyvz/random-sample and squashes the following commits:
a1fb0aa [Burak Yavuz] remove unrelated file
69669c3 [Burak Yavuz] fix broken test
1ddb3da [Burak Yavuz] copy base
6000328 [Burak Yavuz] added python api and fixed test
3c11d1b [Burak Yavuz] fixed broken test
f400ade [Burak Yavuz] fix build errors
2384266 [Burak Yavuz] addressed comments v0.1
e98ebac [Burak Yavuz] [SPARK-7156][SQL] support RandomSplit in DataFrames
See JIRA issue [here](https://issues.apache.org/jira/browse/SPARK-6529).
There are some notes:
1. I add `learningRate` in sharedParams since it is a common parameter for ML algorithms.
2. We will not support transform of finding synonyms from a `Vector`, which will support in further JIRA issues.
3. Word2Vec is different with other ML models that its training set and transformed set are different. Its training set is an `RDD[Iterable[String]]` which represents documents, but the transformed set we want is an `RDD[String]` that represents unique words. So you have to switch your `inputCol` in these two stages.
Author: Xusen Yin <yinxusen@gmail.com>
Closes#5596 from yinxusen/SPARK-6529 and squashes the following commits:
ee2b37a [Xusen Yin] merge with former HEAD
4945462 [Xusen Yin] merge with #5626
3bc2cbd [Xusen Yin] change foldLeft to for loop and use blas
5dd4ee7 [Xusen Yin] fix scala style
743e0d5 [Xusen Yin] fix comments and code style
04c48e9 [Xusen Yin] ensure the functionality
a190f2c [Xusen Yin] fix code style and refine the transform function of word2vec
02848fa [Xusen Yin] refine comments
34a55c0 [Xusen Yin] fix errors
109d124 [Xusen Yin] add test suite and pass it
04dde06 [Xusen Yin] add shared params
c594095 [Xusen Yin] add word2vec transformer
23d77fa [Xusen Yin] merge with #5626
e8cfaf7 [Xusen Yin] fix conflict with master
66e7bd3 [Xusen Yin] change foldLeft to for loop and use blas
566ec20 [Xusen Yin] fix scala style
b54399f [Xusen Yin] fix comments and code style
1211e86 [Xusen Yin] ensure the functionality
6b97ec8 [Xusen Yin] fix code style and refine the transform function of word2vec
7cde18f [Xusen Yin] rm sharedParams
618abd0 [Xusen Yin] refine comments
e29680a [Xusen Yin] fix errors
fe3afe9 [Xusen Yin] add test suite and pass it
02767fb [Xusen Yin] add shared params
6a514f1 [Xusen Yin] add word2vec transformer
Added detailed mathematical derivation of how scaling and LeastSquaresAggregator work. Refactored the code so the model is compressed based on the storage. We may try compression based on the prediction time.
Also, I found that diffSum will be always zero mathematically, so no corrections are required.
Author: DB Tsai <dbt@netflix.com>
Closes#5767 from dbtsai/lir-doc and squashes the following commits:
5e346c9 [DB Tsai] refactoring
fc9f582 [DB Tsai] doc
58456d8 [DB Tsai] address feedback
69757b8 [DB Tsai] actually diffSum is mathematically zero! No correction is needed.
5929e49 [DB Tsai] typo
63f7d1e [DB Tsai] Added compression to the model based on storage
203a295 [DB Tsai] Add more documentation to LinearRegression in new ML framework.
When a job is submitted with a job group and that job group is inherited from a parent thread, there are multiple bugs that may prevent this job from being cancelable via `SparkContext.cancelJobGroup()`:
- When filtering jobs based on their job group properties, DAGScheduler calls `get()` instead of `getProperty()`, which does not respect inheritance, so it will skip over jobs whose job group properties were inherited.
- `Properties` objects are mutable, but we do not make defensive copies / snapshots, so modifications of the parent thread's job group will cause running jobs' groups to change; this also breaks cancelation.
Both of these issues are easy to fix: use `getProperty()` and perform defensive copying.
Author: Josh Rosen <joshrosen@databricks.com>
Closes#5288 from JoshRosen/localProperties-mutability-race and squashes the following commits:
9e29654 [Josh Rosen] Fix style issue
5d90750 [Josh Rosen] Merge remote-tracking branch 'origin/master' into localProperties-mutability-race
3f7b9e8 [Josh Rosen] Add JIRA reference; move clone into DAGScheduler
707e417 [Josh Rosen] Clone local properties to prevent mutations from breaking job cancellation.
b376114 [Josh Rosen] Fix bug that prevented jobs with inherited job group properties from being cancelled.
Original PR #5428 got reverted due to issues between MutableBoolean and Hadoop 1.0.4 (see JIRA). This replaces MutableBoolean with AtomicBoolean.
srowen pwendell
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#5773 from tdas/SPARK-6752 and squashes the following commits:
a0c0ead [Tathagata Das] Fix for hadoop 1.0.4
70ae85b [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into SPARK-6752
94db63c [Tathagata Das] Fix long line.
524f519 [Tathagata Das] Many changes based on PR comments.
eabd092 [Tathagata Das] Added Function0, Java API and unit tests for StreamingContext.getOrCreate
36a7823 [Tathagata Das] Minor changes.
204814e [Tathagata Das] Added StreamingContext.getOrCreate with existing SparkContext
Users may want the WAL data to be written to non-HDFS data storage systems. To allow that, we have to make the WAL pluggable. The following design doc outlines the plan.
https://docs.google.com/a/databricks.com/document/d/1A2XaOLRFzvIZSi18i_luNw5Rmm9j2j4AigktXxIYxmY/edit?usp=sharing
Things to add.
* Unit tests for WriteAheadLogUtils
Author: Tathagata Das <tathagata.das1565@gmail.com>
Closes#5645 from tdas/wal-pluggable and squashes the following commits:
2c431fd [Tathagata Das] Minor fixes.
c2bc7384 [Tathagata Das] More changes based on PR comments.
569a416 [Tathagata Das] fixed long line
bde26b1 [Tathagata Das] Renamed segment to record handle everywhere
b65e155 [Tathagata Das] More changes based on PR comments.
d7cd15b [Tathagata Das] Fixed test
1a32a4b [Tathagata Das] Fixed test
e0d19fb [Tathagata Das] Fixed defaults
9310cbf [Tathagata Das] style fix.
86abcb1 [Tathagata Das] Refactored WriteAheadLogUtils, and consolidated all WAL related configuration into it.
84ce469 [Tathagata Das] Added unit test and fixed compilation error.
bce5e75 [Tathagata Das] Fixed long lines.
837c4f5 [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into wal-pluggable
754fbf8 [Tathagata Das] Added license and docs.
09bc6fe [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into wal-pluggable
7dd2d4b [Tathagata Das] Added pluggable WriteAheadLog interface, and refactored all code along with it
