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* [SPARK-13681][SPARK-14458][SPARK-14566][SQL] Add back once removed ↵Cheng Lian2016-04-197-8/+403
| | | | | | | | | | | | | | | | | | | | | | | | | | | | CommitFailureTestRelationSuite and SimpleTextHadoopFsRelationSuite ## What changes were proposed in this pull request? These test suites were removed while refactoring `HadoopFsRelation` related API. This PR brings them back. This PR also fixes two regressions: - SPARK-14458, which causes runtime error when saving partitioned tables using `FileFormat` data sources that are not able to infer their own schemata. This bug wasn't detected by any built-in data sources because all of them happen to have schema inference feature. - SPARK-14566, which happens to be covered by SPARK-14458 and causes wrong query result or runtime error when - appending a Dataset `ds` to a persisted partitioned data source relation `t`, and - partition columns in `ds` don't all appear after data columns ## How was this patch tested? `CommitFailureTestRelationSuite` uses a testing relation that always fails when committing write tasks to test write job cleanup. `SimpleTextHadoopFsRelationSuite` uses a testing relation to test general `HadoopFsRelation` and `FileFormat` interfaces. The two regressions are both covered by existing test cases. Author: Cheng Lian <lian@databricks.com> Closes #12179 from liancheng/spark-13681-commit-failure-test.
* [SPARK-14577][SQL] Add spark.sql.codegen.maxCaseBranches config optionDongjoon Hyun2016-04-196-35/+180
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? We currently disable codegen for `CaseWhen` if the number of branches is greater than 20 (in CaseWhen.MAX_NUM_CASES_FOR_CODEGEN). It would be better if this value is a non-public config defined in SQLConf. ## How was this patch tested? Pass the Jenkins tests (including a new testcase `Support spark.sql.codegen.maxCaseBranches option`) Author: Dongjoon Hyun <dongjoon@apache.org> Closes #12353 from dongjoon-hyun/SPARK-14577.
* [SPARK-14398][SQL] Audit non-reserved keyword list in ANTLR4 parserbomeng2016-04-191-0/+1
| | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? I have compared non-reserved list in Antlr3 and Antlr4 one by one as well as all the existing keywords defined in Antlr4, added the missing keywords to the non-reserved keywords list. If we need to support more syntax, we can add more keywords by then. Any recommendation for the above is welcome. ## How was this patch tested? I manually checked the keywords one by one. Please let me know if there is a better way to test. Another thought: I suggest to put all the keywords definition and non-reserved list in order, that will be much easier to check in the future. Author: bomeng <bmeng@us.ibm.com> Closes #12191 from bomeng/SPARK-14398.
* [SPARK-14595][SQL] add input metrics for FileScanRDDWenchen Fan2016-04-181-7/+53
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? This is roughly based on the input metrics logic in `SqlNewHadoopRDD` ## How was this patch tested? Not sure how to write a test, I manually verified it in Spark UI. Author: Wenchen Fan <wenchen@databricks.com> Closes #12352 from cloud-fan/metrics.
* [SPARK-14722][SQL] Rename upstreams() -> inputRDDs() in WholeStageCodegenSameer Agarwal2016-04-1811-37/+37
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Per rxin's suggestions, this patch renames `upstreams()` to `inputRDDs()` in `WholeStageCodegen` for better implied semantics ## How was this patch tested? N/A Author: Sameer Agarwal <sameer@databricks.com> Closes #12486 from sameeragarwal/codegen-cleanup.
* [SPARK-14718][SQL] Avoid mutating ExprCode in doGenCodeSameer Agarwal2016-04-1832-440/+362
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? The `doGenCode` method currently takes in an `ExprCode`, mutates it and returns the java code to evaluate the given expression. It should instead just return a new `ExprCode` to avoid passing around mutable objects during code generation. ## How was this patch tested? Existing Tests Author: Sameer Agarwal <sameer@databricks.com> Closes #12483 from sameeragarwal/new-exprcode-2.
* [SPARK-14719] WriteAheadLogBasedBlockHandler should ignore BlockManager put ↵Josh Rosen2016-04-182-31/+40
| | | | | | | | | | | | | | | | | | | errors WriteAheadLogBasedBlockHandler will currently throw exceptions if its BlockManager `put()` calls fail, even though those calls are only performed as a performance optimization. Instead, it should log and ignore exceptions during that `put()`. This is a longstanding issue that was masked by an incorrect test case. I think that we haven't noticed this in production because 1. most people probably use a `MEMORY_AND_DISK` storage level, and 2. typically, individual blocks may be small enough relative to the total storage memory such that they're able to evict blocks from previous batches, so `put()` failures here may be rare in practice. This patch fixes the faulty test and fixes the bug. /cc tdas Author: Josh Rosen <joshrosen@databricks.com> Closes #12484 from JoshRosen/received-block-hadndler-fix.
* [SPARK-14667] Remove HashShuffleManagerReynold Xin2016-04-1818-582/+19
| | | | | | | | | | | | ## What changes were proposed in this pull request? The sort shuffle manager has been the default since Spark 1.2. It is time to remove the old hash shuffle manager. ## How was this patch tested? Removed some tests related to the old manager. Author: Reynold Xin <rxin@databricks.com> Closes #12423 from rxin/SPARK-14667.
* [SPARK-13227] Risky apply() in OpenHashMapCodingCat2016-04-181-0/+3
| | | | | | | | | | | | | | | | | | https://issues.apache.org/jira/browse/SPARK-13227 It might confuse the future developers when they use OpenHashMap.apply() with a numeric value type. null.asInstance[Int], null.asInstance[Long], null.asInstace[Float] and null.asInstance[Double] will return 0/0.0/0L, which might confuse the developer if the value set contains 0/0.0/0L with an existing key The current patch only adds the comments describing the issue, with the respect to apply the minimum changes to the code base The more direct, yet more aggressive, approach is use Option as the return type andrewor14 JoshRosen any thoughts about how to avoid the potential issue? Author: CodingCat <zhunansjtu@gmail.com> Closes #11107 from CodingCat/SPARK-13227.
* [SPARK-14711][BUILD] Examples jar not a part of distribution.Mark Grover2016-04-181-0/+7
| | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Move the spark-examples.jar from being in examples/target to examples/target/scala-2.11/jars ## How was this patch tested? Built distribution to make sure examples jar was being included in the tarball. Ran run-example to make sure examples were run. Author: Mark Grover <mark@apache.org> Closes #12476 from markgrover/spark-14711.
* [SPARK-14714][ML][PYTHON] Fixed issues with non-kwarg typeConverter arg for ↵Joseph K. Bradley2016-04-183-13/+19
| | | | | | | | | | | | | | | | | | | | | | | | | Param constructor ## What changes were proposed in this pull request? PySpark Param constructors need to pass the TypeConverter argument by name, partly to make sure it is not mistaken for the expectedType arg and partly because we will remove the expectedType arg in 2.1. In several places, this is not being done correctly. This PR changes all usages in pyspark/ml/ to keyword args. ## How was this patch tested? Existing unit tests. I will not test type conversion for every Param unless we really think it necessary. Also, if you start the PySpark shell and import classes (e.g., pyspark.ml.feature.StandardScaler), then you no longer get this warning: ``` /Users/josephkb/spark/python/pyspark/ml/param/__init__.py:58: UserWarning: expectedType is deprecated and will be removed in 2.1. Use typeConverter instead, as a keyword argument. "Use typeConverter instead, as a keyword argument.") ``` That warning came from the typeConverter argument being passes as the expectedType arg by mistake. Author: Joseph K. Bradley <joseph@databricks.com> Closes #12480 from jkbradley/typeconverter-fix.
* [SPARK-14515][DOC] Add python example for ChiSqSelectorZheng RuiFeng2016-04-182-0/+52
| | | | | | | | | | | | ## What changes were proposed in this pull request? Add the missing python example for ChiSqSelector ## How was this patch tested? manual tests Author: Zheng RuiFeng <ruifengz@foxmail.com> Closes #12283 from zhengruifeng/chi2_pe.
* [SPARK-14628][CORE][FOLLLOW-UP] Always tracking read/write metricsWenchen Fan2016-04-1840-391/+2590
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR is a follow up for https://github.com/apache/spark/pull/12417, now we always track input/output/shuffle metrics in spark JSON protocol and status API. Most of the line changes are because of re-generating the gold answer for `HistoryServerSuite`, and we add a lot of 0 values for read/write metrics. ## How was this patch tested? existing tests. Author: Wenchen Fan <wenchen@databricks.com> Closes #12462 from cloud-fan/follow.
* [SPARK-14713][TESTS] Fix the flaky test NettyBlockTransferServiceSuiteShixiong Zhu2016-04-181-8/+17
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? When there are multiple tests running, "NettyBlockTransferServiceSuite.can bind to a specific port twice and the second increments" may fail. E.g., assume there are 2 tests running. Here are the execution order to reproduce the test failure. | Execution Order | Test 1 | Test 2 | | ------------- | ------------- | ------------- | | 1 | service0 binds to 17634 | | | 2 | | service0 binds to 17635 (17634 is occupied) | | 3 | service1 binds to 17636 | | | 4 | pass test | | | 5 | service0.close (release 17634) | | | 6 | | service1 binds to 17634 | | 7 | | `service1.port should be (service0.port + 1)` fails (17634 != 17635 + 1) | Here is an example in Jenkins: https://amplab.cs.berkeley.edu/jenkins/view/Spark%20QA%20Test/job/spark-master-test-maven-hadoop-2.2/786/testReport/junit/org.apache.spark.network.netty/NettyBlockTransferServiceSuite/can_bind_to_a_specific_port_twice_and_the_second_increments/ This PR makes two changes: - Use a random port between 17634 and 27634 to reduce the possibility of port conflicts. - Make `service1` use `service0.port` to bind to avoid the above race condition. ## How was this patch tested? Jenkins unit tests. Author: Shixiong Zhu <shixiong@databricks.com> Closes #12477 from zsxwing/SPARK-14713.
* [SPARK-14504][SQL] Enable Oracle docker testsLuciano Resende2016-04-183-12/+15
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Enable Oracle docker tests ## How was this patch tested? Existing tests Author: Luciano Resende <lresende@apache.org> Closes #12270 from lresende/oracle.
* [SPARK-14674][SQL] Move HiveContext.hiveconf to HiveSessionStateAndrew Or2016-04-1818-71/+59
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This is just cleanup. This allows us to remove HiveContext later without inflating the diff too much. This PR fixes the conflicts of https://github.com/apache/spark/pull/12431. It also removes the `def hiveConf` from `HiveSqlParser`. So, we will pass the HiveConf associated with a session explicitly instead of relying on Hive's `SessionState` to pass `HiveConf`. ## How was this patch tested? Existing tests. Closes #12431 Author: Andrew Or <andrew@databricks.com> Author: Yin Huai <yhuai@databricks.com> Closes #12449 from yhuai/hiveconf.
* [SPARK-14710][SQL] Rename gen/genCode to genCode/doGenCode to better reflect ↵Sameer Agarwal2016-04-1844-298/+305
| | | | | | | | | | | | | | | | the semantics ## What changes were proposed in this pull request? Per rxin's suggestions, this patch renames `s/gen/genCode` and `s/genCode/doGenCode` to better reflect the semantics of these 2 function calls. ## How was this patch tested? N/A (refactoring only) Author: Sameer Agarwal <sameer@databricks.com> Closes #12475 from sameeragarwal/gencode.
* [MINOR] Revert removing explicit typing (changed in some examples and ↵hyukjinkwon2016-04-183-3/+3
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | StatFunctions) ## What changes were proposed in this pull request? This PR reverts some changes in https://github.com/apache/spark/pull/12413. (please see the discussion in that PR). from ```scala words.foreachRDD { (rdd, time) => ... ``` to ```scala words.foreachRDD { (rdd: RDD[String], time: Time) => ... ``` Also, this was discussed in dev-mailing list, [here](http://apache-spark-developers-list.1001551.n3.nabble.com/Question-about-Scala-style-explicit-typing-within-transformation-functions-and-anonymous-val-td17173.html) ## How was this patch tested? This was tested with `sbt scalastyle`. Author: hyukjinkwon <gurwls223@gmail.com> Closes #12452 from HyukjinKwon/revert-explicit-typing.
* [SPARK-14299][EXAMPLES] Remove duplications for scala.examples.mlXusen Yin2016-04-184-192/+17
| | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? https://issues.apache.org/jira/browse/SPARK-14299 Delete duplications in scala/examples/ml. TrainValidationSplitExample.scala --> ModelSelectionViaTrainValidationSplitExample CrossValidatorExample.scala --> ModelSelectionViaCrossValidationExample ## How was this patch tested? Existing tests passed. (If this patch involves UI changes, please attach a screenshot; otherwise, remove this) Author: Xusen Yin <yinxusen@gmail.com> Closes #12366 from yinxusen/SPARK-14299-2.
* [SPARK-14440][PYSPARK] Remove pipeline specific reader and writerXusen Yin2016-04-181-46/+7
| | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? https://issues.apache.org/jira/browse/SPARK-14440 Remove * PipelineMLWriter * PipelineMLReader * PipelineModelMLWriter * PipelineModelMLReader and modify comments. ## How was this patch tested? test with unit test. Author: Xusen Yin <yinxusen@gmail.com> Closes #12216 from yinxusen/SPARK-14440.
* [SPARK-14647][SQL] Group SQLContext/HiveContext state into SharedStateAndrew Or2016-04-188-122/+175
| | | | | | | | | | | | | ## What changes were proposed in this pull request? This patch adds a SharedState that groups state shared across multiple SQLContexts. This is analogous to the SessionState added in SPARK-13526 that groups session-specific state. This cleanup makes the constructors of the contexts simpler and ultimately allows us to remove HiveContext in the near future. ## How was this patch tested? Existing tests. Author: Yin Huai <yhuai@databricks.com> Closes #12463 from yhuai/sharedState.
* [HOTFIX] Fix Scala 2.10 compilation break.Reynold Xin2016-04-181-2/+2
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* [SPARK-14564][ML][MLLIB][PYSPARK] Python Word2Vec missing setWindowSize methodJason Lee2016-04-185-8/+45
| | | | | | | | | | | | ## What changes were proposed in this pull request? Added windowSize getter/setter to ML/MLlib ## How was this patch tested? Added test cases in tests.py under both ML and MLlib Author: Jason Lee <cjlee@us.ibm.com> Closes #12428 from jasoncl/SPARK-14564.
* [SPARK-14580][SPARK-14655][SQL] Hive IfCoercion should preserve predicate.Dongjoon Hyun2016-04-185-7/+70
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Currently, `HiveTypeCoercion.IfCoercion` removes all predicates whose return-type are null. However, some UDFs need evaluations because they are designed to throw exceptions. This PR fixes that to preserve the predicates. Also, `assert_true` is implemented as Spark SQL function. **Before** ``` scala> sql("select if(assert_true(false),2,3)").head res2: org.apache.spark.sql.Row = [3] ``` **After** ``` scala> sql("select if(assert_true(false),2,3)").head ... ASSERT_TRUE ... ``` **Hive** ``` hive> select if(assert_true(false),2,3); OK Failed with exception java.io.IOException:org.apache.hadoop.hive.ql.metadata.HiveException: ASSERT_TRUE(): assertion failed. ``` ## How was this patch tested? Pass the Jenkins tests (including a new testcase in `HivePlanTest`) Author: Dongjoon Hyun <dongjoon@apache.org> Closes #12340 from dongjoon-hyun/SPARK-14580.
* [SPARK-14306][ML][PYSPARK] PySpark ml.classification OneVsRest support ↵Xusen Yin2016-04-183-23/+151
| | | | | | | | | | | | | | | | | | export/import ## What changes were proposed in this pull request? https://issues.apache.org/jira/browse/SPARK-14306 Add PySpark OneVsRest save/load supports. ## How was this patch tested? Test with Python unit test. Author: Xusen Yin <yinxusen@gmail.com> Closes #12439 from yinxusen/SPARK-14306-0415.
* [SPARK-14473][SQL] Define analysis rules to catch operations not supported ↵Tathagata Das2016-04-1816-12/+685
| | | | | | | | | | | | | | | | | | | | | | | | in streaming ## What changes were proposed in this pull request? There are many operations that are currently not supported in the streaming execution. For example: - joining two streams - unioning a stream and a batch source - sorting - window functions (not time windows) - distinct aggregates Furthermore, executing a query with a stream source as a batch query should also fail. This patch add an additional step after analysis in the QueryExecution which will check that all the operations in the analyzed logical plan is supported or not. ## How was this patch tested? unit tests. Author: Tathagata Das <tathagata.das1565@gmail.com> Closes #12246 from tdas/SPARK-14473.
* [SPARK-14614] [SQL] Add `bround` functionDongjoon Hyun2016-04-187-27/+113
| | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR aims to add `bound` function (aka Banker's round) by extending current `round` implementation. [Hive supports `bround` since 1.3.0.](https://cwiki.apache.org/confluence/display/Hive/LanguageManual+UDF) **Hive (1.3 ~ 2.0)** ``` hive> select round(2.5), bround(2.5); OK 3.0 2.0 ``` **After this PR** ```scala scala> sql("select round(2.5), bround(2.5)").head res0: org.apache.spark.sql.Row = [3,2] ``` ## How was this patch tested? Pass the Jenkins tests (with extended tests). Author: Dongjoon Hyun <dongjoon@apache.org> Closes #12376 from dongjoon-hyun/SPARK-14614.
* [SPARK-14423][YARN] Avoid same name files added to distributed cache againjerryshao2016-04-182-4/+42
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? In the current implementation of assembly-free spark deployment, jars under `assembly/target/scala-xxx/jars` will be uploaded to distributed cache by default, there's a chance these jars' name will be conflicted with name of jars specified in `--jars`, this will introduce exception when starting application: ``` client token: N/A diagnostics: Application application_1459907402325_0004 failed 2 times due to AM Container for appattempt_1459907402325_0004_000002 exited with exitCode: -1000 For more detailed output, check application tracking page:http://hw12100.local:8088/proxy/application_1459907402325_0004/Then, click on links to logs of each attempt. Diagnostics: Resource hdfs://localhost:8020/user/sshao/.sparkStaging/application_1459907402325_0004/avro-mapred-1.7.7-hadoop2.jar changed on src filesystem (expected 1459909780508, was 1459909782590 java.io.IOException: Resource hdfs://localhost:8020/user/sshao/.sparkStaging/application_1459907402325_0004/avro-mapred-1.7.7-hadoop2.jar changed on src filesystem (expected 1459909780508, was 1459909782590 at org.apache.hadoop.yarn.util.FSDownload.copy(FSDownload.java:253) at org.apache.hadoop.yarn.util.FSDownload.access$000(FSDownload.java:61) at org.apache.hadoop.yarn.util.FSDownload$2.run(FSDownload.java:359) at org.apache.hadoop.yarn.util.FSDownload$2.run(FSDownload.java:357) at java.security.AccessController.doPrivileged(Native Method) at javax.security.auth.Subject.doAs(Subject.java:422) at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1628) at org.apache.hadoop.yarn.util.FSDownload.call(FSDownload.java:356) at org.apache.hadoop.yarn.util.FSDownload.call(FSDownload.java:60) at java.util.concurrent.FutureTask.run(FutureTask.java:266) at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511) at java.util.concurrent.FutureTask.run(FutureTask.java:266) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) at java.lang.Thread.run(Thread.java:745) ``` So here by checking the name of file to avoid same name files uploaded again. ## How was this patch tested? Unit test and manual integrated test is done locally. Author: jerryshao <sshao@hortonworks.com> Closes #12203 from jerryshao/SPARK-14423.
* [SPARK-14696][SQL] Add implicit encoders for boxed primitive typesReynold Xin2016-04-182-0/+27
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? We currently only have implicit encoders for scala primitive types. We should also add implicit encoders for boxed primitives. Otherwise, the following code would not have an encoder: ```scala sqlContext.range(1000).map { i => i } ``` ## How was this patch tested? Added a unit test case for this. Author: Reynold Xin <rxin@databricks.com> Closes #12466 from rxin/SPARK-14696.
* [SPARK-13363][SQL] support Aggregator in RelationalGroupedDatasetWenchen Fan2016-04-182-2/+18
| | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? set the input encoder for `TypedColumn` in `RelationalGroupedDataset.agg`. ## How was this patch tested? new tests in `DatasetAggregatorSuite` close https://github.com/apache/spark/pull/11269 This PR brings https://github.com/apache/spark/pull/12359 up to date and fix the compile. Author: Wenchen Fan <wenchen@databricks.com> Closes #12451 from cloud-fan/agg.
* Revert "[SPARK-14647][SQL] Group SQLContext/HiveContext state into SharedState"Andrew Or2016-04-178-175/+122
| | | | This reverts commit 5cefecc95a5b8418713516802c416cfde5a94a2d.
* [SPARK-14632] randomSplit method fails on dataframes with maps in schemaSubhobrata Dey2016-04-171-1/+3
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? The patch fixes the issue with the randomSplit method which is not able to split dataframes which has maps in schema. The bug was introduced in spark 1.6.1. ## How was this patch tested? Tested with unit tests. (If this patch involves UI changes, please attach a screenshot; otherwise, remove this) Author: Subhobrata Dey <sbcd90@gmail.com> Closes #12438 from sbcd90/randomSplitIssue.
* Mark ExternalClusterManager as private[spark].Reynold Xin2016-04-161-4/+1
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* [SPARK-13904][SCHEDULER] Add support for pluggable cluster managerHemant Bhanawat2016-04-167-8/+193
| | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This commit adds support for pluggable cluster manager. And also allows a cluster manager to clean up tasks without taking the parent process down. To plug a new external cluster manager, ExternalClusterManager trait should be implemented. It returns task scheduler and backend scheduler that will be used by SparkContext to schedule tasks. An external cluster manager is registered using the java.util.ServiceLoader mechanism (This mechanism is also being used to register data sources like parquet, json, jdbc etc.). This allows auto-loading implementations of ExternalClusterManager interface. Currently, when a driver fails, executors exit using system.exit. This does not bode well for cluster managers that would like to reuse the parent process of an executor. Hence, 1. Moving system.exit to a function that can be overriden in subclasses of CoarseGrainedExecutorBackend. 2. Added functionality of killing all the running tasks in an executor. ## How was this patch tested? ExternalClusterManagerSuite.scala was added to test this patch. Author: Hemant Bhanawat <hemant@snappydata.io> Closes #11723 from hbhanawat/pluggableScheduler.
* [SPARK-14672][SQL] Move HiveContext analyze logic to AnalyzeTableAndrew Or2016-04-162-78/+81
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Move the implementation of `hiveContext.analyze` to the command of `AnalyzeTable`. ## How was this patch tested? Existing tests. Closes #12429 Author: Yin Huai <yhuai@databricks.com> Author: Andrew Or <andrew@databricks.com> Closes #12448 from yhuai/analyzeTable.
* [SPARK-14647][SQL] Group SQLContext/HiveContext state into SharedStateAndrew Or2016-04-168-122/+175
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This patch adds a SharedState that groups state shared across multiple SQLContexts. This is analogous to the SessionState added in SPARK-13526 that groups session-specific state. This cleanup makes the constructors of the contexts simpler and ultimately allows us to remove HiveContext in the near future. ## How was this patch tested? Existing tests. Closes #12405 Author: Andrew Or <andrew@databricks.com> Author: Yin Huai <yhuai@databricks.com> Closes #12447 from yhuai/sharedState.
* [SPARK-14683][DOCUMENTATION] Configure external links in ScalaDoc杨博 (Yang Bo)2016-04-161-0/+2
| | | | | | | | | | Right now Spark's Scaladoc does not link to Scala standard library and other dependencies. This would bother Spark starters because they may be not experienced Scala programmers. This patch fixes these links in ScalaDoc. Author: 杨博 (Yang Bo) <pop.atry@gmail.com> Closes #12444 from Atry/patch-1.
* [SPARK-14677][SQL] follow up: make max iter num config internalReynold Xin2016-04-161-0/+1
| | | | | | | | | | | | ## What changes were proposed in this pull request? This is a follow-up to make the max iteration number an internal config. ## How was this patch tested? N/A Author: Reynold Xin <rxin@databricks.com> Closes #12441 from rxin/maxIterConfInternal.
* [SPARK-14605][ML][PYTHON] Changed Python to use unicode UIDs for spark.ml ↵Joseph K. Bradley2016-04-164-4/+8
| | | | | | | | | | | | | | | | | | Identifiable ## What changes were proposed in this pull request? Python spark.ml Identifiable classes use UIDs of type str, but they should use unicode (in Python 2.x) to match Java. This could be a problem if someone created a class in Java with odd unicode characters, saved it, and loaded it in Python. This PR: Use unicode everywhere in Python. ## How was this patch tested? Updated persistence unit test to check uid type Author: Joseph K. Bradley <joseph@databricks.com> Closes #12368 from jkbradley/python-uid-unicode.
* [MINOR] Remove inappropriate type notation and extra anonymous closure ↵hyukjinkwon2016-04-1619-64/+54
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | within functional transformations ## What changes were proposed in this pull request? This PR removes - Inappropriate type notations For example, from ```scala words.foreachRDD { (rdd: RDD[String], time: Time) => ... ``` to ```scala words.foreachRDD { (rdd, time) => ... ``` - Extra anonymous closure within functional transformations. For example, ```scala .map(item => { ... }) ``` which can be just simply as below: ```scala .map { item => ... } ``` and corrects some obvious style nits. ## How was this patch tested? This was tested after adding rules in `scalastyle-config.xml`, which ended up with not finding all perfectly. The rules applied were below: - For the first correction, ```xml <check customId="NoExtraClosure" level="error" class="org.scalastyle.file.RegexChecker" enabled="true"> <parameters><parameter name="regex">(?m)\.[a-zA-Z_][a-zA-Z0-9]*\(\s*[^,]+s*=>\s*\{[^\}]+\}\s*\)</parameter></parameters> </check> ``` ```xml <check customId="NoExtraClosure" level="error" class="org.scalastyle.file.RegexChecker" enabled="true"> <parameters><parameter name="regex">\.[a-zA-Z_][a-zA-Z0-9]*\s*[\{|\(]([^\n>,]+=>)?\s*\{([^()]|(?R))*\}^[,]</parameter></parameters> </check> ``` - For the second correction ```xml <check customId="TypeNotation" level="error" class="org.scalastyle.file.RegexChecker" enabled="true"> <parameters><parameter name="regex">\.[a-zA-Z_][a-zA-Z0-9]*\s*[\{|\(]\s*\([^):]*:R))*\}^[,]</parameter></parameters> </check> ``` **Those rules were not added** Author: hyukjinkwon <gurwls223@gmail.com> Closes #12413 from HyukjinKwon/SPARK-style.
* Revert "[SPARK-13363][SQL] support Aggregator in RelationalGroupedDataset"Reynold Xin2016-04-162-18/+2
| | | | This reverts commit 12854464c4fa30c4df3b5b17bd8914d048dbf4a9.
* [SPARK-13363][SQL] support Aggregator in RelationalGroupedDatasetWenchen Fan2016-04-162-2/+18
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? set the input encoder for `TypedColumn` in `RelationalGroupedDataset.agg`. ## How was this patch tested? new tests in `DatasetAggregatorSuite` close https://github.com/apache/spark/pull/11269 Author: Wenchen Fan <wenchen@databricks.com> Closes #12359 from cloud-fan/agg.
* [SPARK-14677][SQL] Make the max number of iterations configurable for CatalystReynold Xin2016-04-159-64/+62
| | | | | | | | | | | | ## What changes were proposed in this pull request? We currently hard code the max number of optimizer/analyzer iterations to 100. This patch makes it configurable. While I'm at it, I also added the SessionCatalog to the optimizer, so we can use information there in optimization. ## How was this patch tested? Updated unit tests to reflect the change. Author: Reynold Xin <rxin@databricks.com> Closes #12434 from rxin/SPARK-14677.
* [SPARK-14668][SQL] Move CurrentDatabase to CatalystYin Huai2016-04-157-24/+47
| | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR moves `CurrentDatabase` from sql/hive package to sql/catalyst. It also adds the function description, which looks like the following. ``` scala> sqlContext.sql("describe function extended current_database").collect.foreach(println) [Function: current_database] [Class: org.apache.spark.sql.execution.command.CurrentDatabase] [Usage: current_database() - Returns the current database.] [Extended Usage: > SELECT current_database()] ``` ## How was this patch tested? Existing tests Author: Yin Huai <yhuai@databricks.com> Closes #12424 from yhuai/SPARK-14668.
* [SPARK-14620][SQL] Use/benchmark a better hash in VectorizedHashMapSameer Agarwal2016-04-152-28/+66
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR uses a better hashing algorithm while probing the AggregateHashMap: ```java long h = 0 h = (h ^ (0x9e3779b9)) + key_1 + (h << 6) + (h >>> 2); h = (h ^ (0x9e3779b9)) + key_2 + (h << 6) + (h >>> 2); h = (h ^ (0x9e3779b9)) + key_3 + (h << 6) + (h >>> 2); ... h = (h ^ (0x9e3779b9)) + key_n + (h << 6) + (h >>> 2); return h ``` Depends on: https://github.com/apache/spark/pull/12345 ## How was this patch tested? Java HotSpot(TM) 64-Bit Server VM 1.8.0_73-b02 on Mac OS X 10.11.4 Intel(R) Core(TM) i7-4960HQ CPU 2.60GHz Aggregate w keys: Best/Avg Time(ms) Rate(M/s) Per Row(ns) Relative ------------------------------------------------------------------------------------------- codegen = F 2417 / 2457 8.7 115.2 1.0X codegen = T hashmap = F 1554 / 1581 13.5 74.1 1.6X codegen = T hashmap = T 877 / 929 23.9 41.8 2.8X Author: Sameer Agarwal <sameer@databricks.com> Closes #12379 from sameeragarwal/hash.
* [SPARK-14628][CORE] Simplify task metrics by always tracking read/write metricsReynold Xin2016-04-1534-610/+330
| | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Part of the reason why TaskMetrics and its callers are complicated are due to the optional metrics we collect, including input, output, shuffle read, and shuffle write. I think we can always track them and just assign 0 as the initial values. It is usually very obvious whether a task is supposed to read any data or not. By always tracking them, we can remove a lot of map, foreach, flatMap, getOrElse(0L) calls throughout Spark. This patch also changes a few behaviors. 1. Removed the distinction of data read/write methods (e.g. Hadoop, Memory, Network, etc). 2. Accumulate all data reads and writes, rather than only the first method. (Fixes SPARK-5225) ## How was this patch tested? existing tests. This is bases on https://github.com/apache/spark/pull/12388, with more test fixes. Author: Reynold Xin <rxin@databricks.com> Author: Wenchen Fan <wenchen@databricks.com> Closes #12417 from cloud-fan/metrics-refactor.
* [SPARK-7861][ML] PySpark OneVsRestXusen Yin2016-04-152-7/+249
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? https://issues.apache.org/jira/browse/SPARK-7861 Add PySpark OneVsRest. I implement it with Python since it's a meta-pipeline. ## How was this patch tested? Test with doctest. Author: Xusen Yin <yinxusen@gmail.com> Closes #12124 from yinxusen/SPARK-14306-7861.
* [SPARK-14104][PYSPARK][ML] All Python param setters should use the `_set` methodsethah2016-04-1512-91/+110
| | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Param setters in python previously accessed the _paramMap directly to update values. The `_set` method now implements type checking, so it should be used to update all parameters. This PR eliminates all direct accesses to `_paramMap` besides the one in the `_set` method to ensure type checking happens. Additional changes: * [SPARK-13068](https://github.com/apache/spark/pull/11663) missed adding type converters in evaluation.py so those are done here * An incorrect `toBoolean` type converter was used for StringIndexer `handleInvalid` param in previous PR. This is fixed here. ## How was this patch tested? Existing unit tests verify that parameters are still set properly. No new functionality is actually added in this PR. Author: sethah <seth.hendrickson16@gmail.com> Closes #11939 from sethah/SPARK-14104.
* [SPARK-14665][ML][PYTHON] Fixed bug with StopWordsRemover default stopwordsJoseph K. Bradley2016-04-152-1/+4
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? The default stopwords were a Java object. They are no longer. ## How was this patch tested? Unit test which failed before the fix Author: Joseph K. Bradley <joseph@databricks.com> Closes #12422 from jkbradley/pyspark-stopwords.
* [SPARK-13925][ML][SPARKR] Expose R-like summary statistics in SparkR::glm ↵Yanbo Liang2016-04-154-10/+143
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | for more family and link functions ## What changes were proposed in this pull request? Expose R-like summary statistics in SparkR::glm for more family and link functions. Note: Not all values in R [summary.glm](http://stat.ethz.ch/R-manual/R-patched/library/stats/html/summary.glm.html) are exposed, we only provide the most commonly used statistics in this PR. More statistics can be added in the followup work. ## How was this patch tested? Unit tests. SparkR Output: ``` Deviance Residuals: (Note: These are approximate quantiles with relative error <= 0.01) Min 1Q Median 3Q Max -0.95096 -0.16585 -0.00232 0.17410 0.72918 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1.6765 0.23536 7.1231 4.4561e-11 Sepal_Length 0.34988 0.046301 7.5566 4.1873e-12 Species_versicolor -0.98339 0.072075 -13.644 0 Species_virginica -1.0075 0.093306 -10.798 0 (Dispersion parameter for gaussian family taken to be 0.08351462) Null deviance: 28.307 on 149 degrees of freedom Residual deviance: 12.193 on 146 degrees of freedom AIC: 59.22 Number of Fisher Scoring iterations: 1 ``` R output: ``` Deviance Residuals: Min 1Q Median 3Q Max -0.95096 -0.16522 0.00171 0.18416 0.72918 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1.67650 0.23536 7.123 4.46e-11 *** Sepal.Length 0.34988 0.04630 7.557 4.19e-12 *** Speciesversicolor -0.98339 0.07207 -13.644 < 2e-16 *** Speciesvirginica -1.00751 0.09331 -10.798 < 2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 (Dispersion parameter for gaussian family taken to be 0.08351462) Null deviance: 28.307 on 149 degrees of freedom Residual deviance: 12.193 on 146 degrees of freedom AIC: 59.217 Number of Fisher Scoring iterations: 2 ``` cc mengxr Author: Yanbo Liang <ybliang8@gmail.com> Closes #12393 from yanboliang/spark-13925.
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