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* [SPARK-12221] add cpu time to metricsjisookim2016-09-2330-21/+492
| | | | | | | | Currently task metrics don't support executor CPU time, so there's no way to calculate how much CPU time a stage/task took from History Server metrics. This PR enables reporting CPU time. Author: jisookim <jisookim0513@gmail.com> Closes #10212 from jisookim0513/add-cpu-time-metric.
* [SPARK-17643] Remove comparable requirement from OffsetMichael Armbrust2016-09-235-94/+9
| | | | | | | | For some sources, it is difficult to provide a global ordering based only on the data in the offset. Since we don't use comparison for correctness, lets remove it. Author: Michael Armbrust <michael@databricks.com> Closes #15207 from marmbrus/removeComparable.
* [SPARK-17210][SPARKR] sparkr.zip is not distributed to executors when ↵Jeff Zhang2016-09-232-0/+19
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | running sparkr in RStudio ## What changes were proposed in this pull request? Spark will add sparkr.zip to archive only when it is yarn mode (SparkSubmit.scala). ``` if (args.isR && clusterManager == YARN) { val sparkRPackagePath = RUtils.localSparkRPackagePath if (sparkRPackagePath.isEmpty) { printErrorAndExit("SPARK_HOME does not exist for R application in YARN mode.") } val sparkRPackageFile = new File(sparkRPackagePath.get, SPARKR_PACKAGE_ARCHIVE) if (!sparkRPackageFile.exists()) { printErrorAndExit(s"$SPARKR_PACKAGE_ARCHIVE does not exist for R application in YARN mode.") } val sparkRPackageURI = Utils.resolveURI(sparkRPackageFile.getAbsolutePath).toString // Distribute the SparkR package. // Assigns a symbol link name "sparkr" to the shipped package. args.archives = mergeFileLists(args.archives, sparkRPackageURI + "#sparkr") // Distribute the R package archive containing all the built R packages. if (!RUtils.rPackages.isEmpty) { val rPackageFile = RPackageUtils.zipRLibraries(new File(RUtils.rPackages.get), R_PACKAGE_ARCHIVE) if (!rPackageFile.exists()) { printErrorAndExit("Failed to zip all the built R packages.") } val rPackageURI = Utils.resolveURI(rPackageFile.getAbsolutePath).toString // Assigns a symbol link name "rpkg" to the shipped package. args.archives = mergeFileLists(args.archives, rPackageURI + "#rpkg") } } ``` So it is necessary to pass spark.master from R process to JVM. Otherwise sparkr.zip won't be distributed to executor. Besides that I also pass spark.yarn.keytab/spark.yarn.principal to spark side, because JVM process need them to access secured cluster. ## How was this patch tested? Verify it manually in R Studio using the following code. ``` Sys.setenv(SPARK_HOME="/Users/jzhang/github/spark") .libPaths(c(file.path(Sys.getenv(), "R", "lib"), .libPaths())) library(SparkR) sparkR.session(master="yarn-client", sparkConfig = list(spark.executor.instances="1")) df <- as.DataFrame(mtcars) head(df) ``` … Author: Jeff Zhang <zjffdu@apache.org> Closes #14784 from zjffdu/SPARK-17210.
* [SPARK-17499][SPARKR][ML][MLLIB] make the default params in sparkR spark.mlp ↵WeichenXu2016-09-233-7/+33
| | | | | | | | | | | | | | | | | | | | | | | | | | | consistent with MultilayerPerceptronClassifier ## What changes were proposed in this pull request? update `MultilayerPerceptronClassifierWrapper.fit` paramter type: `layers: Array[Int]` `seed: String` update several default params in sparkR `spark.mlp`: `tol` --> 1e-6 `stepSize` --> 0.03 `seed` --> NULL ( when seed == NULL, the scala-side wrapper regard it as a `null` value and the seed will use the default one ) r-side `seed` only support 32bit integer. remove `layers` default value, and move it in front of those parameters with default value. add `layers` parameter validation check. ## How was this patch tested? tests added. Author: WeichenXu <WeichenXu123@outlook.com> Closes #15051 from WeichenXu123/update_py_mlp_default.
* [SPARK-16861][PYSPARK][CORE] Refactor PySpark accumulator API on top of ↵Holden Karau2016-09-232-22/+25
| | | | | | | | | | | | | | | | Accumulator V2 ## What changes were proposed in this pull request? Move the internals of the PySpark accumulator API from the old deprecated API on top of the new accumulator API. ## How was this patch tested? The existing PySpark accumulator tests (both unit tests and doc tests at the start of accumulator.py). Author: Holden Karau <holden@us.ibm.com> Closes #14467 from holdenk/SPARK-16861-refactor-pyspark-accumulator-api.
* [BUILD] Closes some stale PRshyukjinkwon2016-09-230-0/+0
| | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR proposes to close some stale PRs and ones suggested to be closed by committer(s) Closes #12415 Closes #14765 Closes #15118 Closes #15184 Closes #15183 Closes #9440 Closes #15023 Closes #14643 Closes #14827 ## How was this patch tested? N/A Author: hyukjinkwon <gurwls223@gmail.com> Closes #15198 from HyukjinKwon/stale-prs.
* [SPARK-17640][SQL] Avoid using -1 as the default batchId for ↵Shixiong Zhu2016-09-222-30/+31
| | | | | | | | | | | | | | | | FileStreamSource.FileEntry ## What changes were proposed in this pull request? Avoid using -1 as the default batchId for FileStreamSource.FileEntry so that we can make sure not writing any FileEntry(..., batchId = -1) into the log. This also avoids people misusing it in future (#15203 is an example). ## How was this patch tested? Jenkins. Author: Shixiong Zhu <shixiong@databricks.com> Closes #15206 from zsxwing/cleanup.
* [SPARK-16719][ML] Random Forests should communicate fewer trees on each ↵Joseph K. Bradley2016-09-222-34/+46
| | | | | | | | | | | | | | | | | | | | | | | iteration ## What changes were proposed in this pull request? RandomForest currently sends the entire forest to each worker on each iteration. This is because (a) the node queue is FIFO and (b) the closure references the entire array of trees (topNodes). (a) causes RFs to handle splits in many trees, especially early on in learning. (b) sends all trees explicitly. This PR: (a) Change the RF node queue to be FILO (a stack), so that RFs tend to focus on 1 or a few trees before focusing on others. (b) Change topNodes to pass only the trees required on that iteration. ## How was this patch tested? Unit tests: * Existing tests for correctness of tree learning * Manually modifying code and running tests to verify that a small number of trees are communicated on each iteration * This last item is hard to test via unit tests given the current APIs. Author: Joseph K. Bradley <joseph@databricks.com> Closes #14359 from jkbradley/rfs-fewer-trees.
* [SPARK-17639][BUILD] Add jce.jar to buildclasspath when building.Marcelo Vanzin2016-09-223-8/+7
| | | | | | | | | This was missing, preventing code that uses javax.crypto to properly compile in Spark. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #15204 from vanzin/SPARK-17639.
* [SPARK-17635][SQL] Remove hardcode "agg_plan" in HashAggregateExecYucai Yu2016-09-221-1/+1
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? "agg_plan" are hardcoded in HashAggregateExec, which have potential issue, so removing them. ## How was this patch tested? existing tests. Author: Yucai Yu <yucai.yu@intel.com> Closes #15199 from yucai/agg_plan.
* [SPARK-17569][SPARK-17569][TEST] Make the unit test added for work againBurak Yavuz2016-09-221-1/+1
| | | | | | | | | | | | | | | ## What changes were proposed in this pull request? A [PR](https://github.com/apache/spark/commit/a6aade0042d9c065669f46d2dac40ec6ce361e63) was merged concurrently that made the unit test for PR #15122 not test anything anymore. This PR fixes the test. ## How was this patch tested? Changed line https://github.com/apache/spark/blob/0d634875026ccf1eaf984996e9460d7673561f80/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/FileStreamSource.scala#L137 from `false` to `true` and made sure the unit test failed. Author: Burak Yavuz <brkyvz@gmail.com> Closes #15203 from brkyvz/fix-test.
* [SPARK-16240][ML] ML persistence backward compatibility for LDAGayathri Murali2016-09-222-18/+72
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Allow Spark 2.x to load instances of LDA, LocalLDAModel, and DistributedLDAModel saved from Spark 1.6. ## How was this patch tested? I tested this manually, saving the 3 types from 1.6 and loading them into master (2.x). In the future, we can add generic tests for testing backwards compatibility across all ML models in SPARK-15573. Author: Joseph K. Bradley <joseph@databricks.com> Closes #15034 from jkbradley/lda-backwards.
* [SPARK-17616][SQL] Support a single distinct aggregate combined with a ↵Herman van Hovell2016-09-223-9/+111
| | | | | | | | | | | | | | | | | | | | | | non-partial aggregate ## What changes were proposed in this pull request? We currently cannot execute an aggregate that contains a single distinct aggregate function and an one or more non-partially plannable aggregate functions, for example: ```sql select grp, collect_list(col1), count(distinct col2) from tbl_a group by 1 ``` This is a regression from Spark 1.6. This is caused by the fact that the single distinct aggregation code path assumes that all aggregates can be planned in two phases (is partially aggregatable). This PR works around this issue by triggering the `RewriteDistinctAggregates` in such cases (this is similar to the approach taken in 1.6). ## How was this patch tested? Created `RewriteDistinctAggregatesSuite` which checks if the aggregates with distinct aggregate functions get rewritten into two `Aggregates` and an `Expand`. Added a regression test to `DataFrameAggregateSuite`. Author: Herman van Hovell <hvanhovell@databricks.com> Closes #15187 from hvanhovell/SPARK-17616.
* [SPARK-17638][STREAMING] Stop JVM StreamingContext when the Python process ↵Shixiong Zhu2016-09-223-2/+35
| | | | | | | | | | | | | | | | is dead ## What changes were proposed in this pull request? When the Python process is dead, the JVM StreamingContext is still running. Hence we will see a lot of Py4jException before the JVM process exits. It's better to stop the JVM StreamingContext to avoid those annoying logs. ## How was this patch tested? Jenkins Author: Shixiong Zhu <shixiong@databricks.com> Closes #15201 from zsxwing/stop-jvm-ssc.
* [SPARK-17613] S3A base paths with no '/' at the end return empty DataFramesBurak Yavuz2016-09-222-2/+53
| | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Consider you have a bucket as `s3a://some-bucket` and under it you have files: ``` s3a://some-bucket/file1.parquet s3a://some-bucket/file2.parquet ``` Getting the parent path of `s3a://some-bucket/file1.parquet` yields `s3a://some-bucket/` and the ListingFileCatalog uses this as the key in the hash map. When catalog.allFiles is called, we use `s3a://some-bucket` (no slash at the end) to get the list of files, and we're left with an empty list! This PR fixes this by adding a `/` at the end of the `URI` iff the given `Path` doesn't have a parent, i.e. is the root. This is a no-op if the path already had a `/` at the end, and is handled through the Hadoop Path, path merging semantics. ## How was this patch tested? Unit test in `FileCatalogSuite`. Author: Burak Yavuz <brkyvz@gmail.com> Closes #15169 from brkyvz/SPARK-17613.
* Skip building R vignettes if Spark is not builtShivaram Venkataraman2016-09-221-3/+22
| | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? When we build the docs separately we don't have the JAR files from the Spark build in the same tree. As the SparkR vignettes need to launch a SparkContext to be built, we skip building them if JAR files don't exist ## How was this patch tested? To test this we can run the following: ``` build/mvn -DskipTests -Psparkr clean ./R/create-docs.sh ``` You should see a line `Skipping R vignettes as Spark JARs not found` at the end Author: Shivaram Venkataraman <shivaram@cs.berkeley.edu> Closes #15200 from shivaram/sparkr-vignette-skip.
* [SPARK-17365][CORE] Remove/Kill multiple executors together to reduce RPC ↵Dhruve Ashar2016-09-2211-55/+239
| | | | | | | | | | | | | | | call time. ## What changes were proposed in this pull request? We are killing multiple executors together instead of iterating over expensive RPC calls to kill single executor. ## How was this patch tested? Executed sample spark job to observe executors being killed/removed with dynamic allocation enabled. Author: Dhruve Ashar <dashar@yahoo-inc.com> Author: Dhruve Ashar <dhruveashar@gmail.com> Closes #15152 from dhruve/impr/SPARK-17365.
* [SQL][MINOR] correct the comment of SortBasedAggregationIterator.safeProjWenchen Fan2016-09-221-2/+9
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? This comment went stale long time ago, this PR fixes it according to my understanding. ## How was this patch tested? N/A Author: Wenchen Fan <wenchen@databricks.com> Closes #15095 from cloud-fan/update-comment.
* [SPARK-17281][ML][MLLIB] Add treeAggregateDepth parameter for ↵WeichenXu2016-09-222-10/+25
| | | | | | | | | | | | | | | | AFTSurvivalRegression ## What changes were proposed in this pull request? Add treeAggregateDepth parameter for AFTSurvivalRegression to keep consistent with LiR/LoR. ## How was this patch tested? Existing tests. Author: WeichenXu <WeichenXu123@outlook.com> Closes #14851 from WeichenXu123/add_treeAggregate_param_for_survival_regression.
* [SPARK-17421][DOCS] Documenting the current treatment of MAVEN_OPTS.frreiss2016-09-221-6/+14
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Modified the documentation to clarify that `build/mvn` and `pom.xml` always add Java 7-specific parameters to `MAVEN_OPTS`, and that developers can safely ignore warnings about `-XX:MaxPermSize` that may result from compiling or running tests with Java 8. ## How was this patch tested? Rebuilt HTML documentation, made sure that building-spark.html displays correctly in a browser. Author: frreiss <frreiss@us.ibm.com> Closes #15005 from frreiss/fred-17421a.
* [SPARK-17625][SQL] set expectedOutputAttributes when converting ↵Zhenhua Wang2016-09-222-4/+20
| | | | | | | | | | | | | | | | SimpleCatalogRelation to LogicalRelation ## What changes were proposed in this pull request? We should set expectedOutputAttributes when converting SimpleCatalogRelation to LogicalRelation, otherwise the outputs of LogicalRelation are different from outputs of SimpleCatalogRelation - they have different exprId's. ## How was this patch tested? add a test case Author: Zhenhua Wang <wzh_zju@163.com> Closes #15182 from wzhfy/expectedAttributes.
* [SPARK-17492][SQL] Fix Reading Cataloged Data Sources without Extending ↵gatorsmile2016-09-224-24/+102
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | SchemaRelationProvider ### What changes were proposed in this pull request? For data sources without extending `SchemaRelationProvider`, we expect users to not specify schemas when they creating tables. If the schema is input from users, an exception is issued. Since Spark 2.1, for any data source, to avoid infer the schema every time, we store the schema in the metastore catalog. Thus, when reading a cataloged data source table, the schema could be read from metastore catalog. In this case, we also got an exception. For example, ```Scala sql( s""" |CREATE TABLE relationProvierWithSchema |USING org.apache.spark.sql.sources.SimpleScanSource |OPTIONS ( | From '1', | To '10' |) """.stripMargin) spark.table(tableName).show() ``` ``` org.apache.spark.sql.sources.SimpleScanSource does not allow user-specified schemas.; ``` This PR is to fix the above issue. When building a data source, we introduce a flag `isSchemaFromUsers` to indicate whether the schema is really input from users. If true, we issue an exception. Otherwise, we will call the `createRelation` of `RelationProvider` to generate the `BaseRelation`, in which it contains the actual schema. ### How was this patch tested? Added a few cases. Author: gatorsmile <gatorsmile@gmail.com> Closes #15046 from gatorsmile/tempViewCases.
* [SPARK-17425][SQL] Override sameResult in HiveTableScanExec to make ↵Yadong Qi2016-09-221-0/+15
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ReuseExchange work in text format table ## What changes were proposed in this pull request? The PR will override the `sameResult` in `HiveTableScanExec` to make `ReuseExchange` work in text format table. ## How was this patch tested? # SQL ```sql SELECT * FROM src t1 JOIN src t2 ON t1.key = t2.key JOIN src t3 ON t1.key = t3.key; ``` # Before ``` == Physical Plan == *BroadcastHashJoin [key#30], [key#34], Inner, BuildRight :- *BroadcastHashJoin [key#30], [key#32], Inner, BuildRight : :- *Filter isnotnull(key#30) : : +- HiveTableScan [key#30, value#31], MetastoreRelation default, src : +- BroadcastExchange HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint))) : +- *Filter isnotnull(key#32) : +- HiveTableScan [key#32, value#33], MetastoreRelation default, src +- BroadcastExchange HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint))) +- *Filter isnotnull(key#34) +- HiveTableScan [key#34, value#35], MetastoreRelation default, src ``` # After ``` == Physical Plan == *BroadcastHashJoin [key#2], [key#6], Inner, BuildRight :- *BroadcastHashJoin [key#2], [key#4], Inner, BuildRight : :- *Filter isnotnull(key#2) : : +- HiveTableScan [key#2, value#3], MetastoreRelation default, src : +- BroadcastExchange HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint))) : +- *Filter isnotnull(key#4) : +- HiveTableScan [key#4, value#5], MetastoreRelation default, src +- ReusedExchange [key#6, value#7], BroadcastExchange HashedRelationBroadcastMode(List(cast(input[0, int, false] as bigint))) ``` cc: davies cloud-fan Author: Yadong Qi <qiyadong2010@gmail.com> Closes #14988 from watermen/SPARK-17425.
* [SPARK-17609][SQL] SessionCatalog.tableExists should not check temp viewWenchen Fan2016-09-229-115/+81
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? After #15054 , there is no place in Spark SQL that need `SessionCatalog.tableExists` to check temp views, so this PR makes `SessionCatalog.tableExists` only check permanent table/view and removes some hacks. This PR also improves the `getTempViewOrPermanentTableMetadata` that is introduced in #15054 , to make the code simpler. ## How was this patch tested? existing tests Author: Wenchen Fan <wenchen@databricks.com> Closes #15160 from cloud-fan/exists.
* [SPARK-17494][SQL] changePrecision() on compact decimal should respect ↵Davies Liu2016-09-212-4/+39
| | | | | | | | | | | | | | | | | | rounding mode ## What changes were proposed in this pull request? Floor()/Ceil() of decimal is implemented using changePrecision() by passing a rounding mode, but the rounding mode is not respected when the decimal is in compact mode (could fit within a Long). This Update the changePrecision() to respect rounding mode, which could be ROUND_FLOOR, ROUND_CEIL, ROUND_HALF_UP, ROUND_HALF_EVEN. ## How was this patch tested? Added regression tests. Author: Davies Liu <davies@databricks.com> Closes #15154 from davies/decimal_round.
* [SPARK-17627] Mark Streaming Providers ExperimentalMichael Armbrust2016-09-211-0/+4
| | | | | | | | All of structured streaming is experimental in its first release. We missed the annotation on two of the APIs. Author: Michael Armbrust <michael@databricks.com> Closes #15188 from marmbrus/experimentalApi.
* [SPARK-17315][FOLLOW-UP][SPARKR][ML] Fix print of Kolmogorov-Smirnov test ↵Yanbo Liang2016-09-212-21/+11
| | | | | | | | | | | | | | | | | | | | | | | | | | | | summary ## What changes were proposed in this pull request? #14881 added Kolmogorov-Smirnov Test wrapper to SparkR. I found that ```print.summary.KSTest``` was implemented inappropriately and result in no effect. Running the following code for KSTest: ```Scala data <- data.frame(test = c(0.1, 0.15, 0.2, 0.3, 0.25, -1, -0.5)) df <- createDataFrame(data) testResult <- spark.kstest(df, "test", "norm") summary(testResult) ``` Before this PR: ![image](https://cloud.githubusercontent.com/assets/1962026/18615016/b9a2823a-7d4f-11e6-934b-128beade355e.png) After this PR: ![image](https://cloud.githubusercontent.com/assets/1962026/18615014/aafe2798-7d4f-11e6-8b99-c705bb9fe8f2.png) The new implementation is similar with [```print.summary.GeneralizedLinearRegressionModel```](https://github.com/apache/spark/blob/master/R/pkg/R/mllib.R#L284) of SparkR and [```print.summary.glm```](https://svn.r-project.org/R/trunk/src/library/stats/R/glm.R) of native R. BTW, I removed the comparison of ```print.summary.KSTest``` in unit test, since it's only wrappers of the summary output which has been checked. Another reason is that these comparison will output summary information to the test console, it will make the test output in a mess. ## How was this patch tested? Existing test. Author: Yanbo Liang <ybliang8@gmail.com> Closes #15139 from yanboliang/spark-17315.
* [SPARK-17577][SPARKR][CORE] SparkR support add files to Spark job and get by ↵Yanbo Liang2016-09-214-3/+67
| | | | | | | | | | | | | | | executors ## What changes were proposed in this pull request? Scala/Python users can add files to Spark job by submit options ```--files``` or ```SparkContext.addFile()```. Meanwhile, users can get the added file by ```SparkFiles.get(filename)```. We should also support this function for SparkR users, since they also have the requirements for some shared dependency files. For example, SparkR users can download third party R packages to driver firstly, add these files to the Spark job as dependency by this API and then each executor can install these packages by ```install.packages```. ## How was this patch tested? Add unit test. Author: Yanbo Liang <ybliang8@gmail.com> Closes #15131 from yanboliang/spark-17577.
* [SPARK-17569] Make StructuredStreaming FileStreamSource batch generation fasterBurak Yavuz2016-09-213-4/+62
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? While getting the batch for a `FileStreamSource` in StructuredStreaming, we know which files we must take specifically. We already have verified that they exist, and have committed them to a metadata log. When creating the FileSourceRelation however for an incremental execution, the code checks the existence of every single file once again! When you have 100,000s of files in a folder, creating the first batch takes 2 hours+ when working with S3! This PR disables that check ## How was this patch tested? Added a unit test to `FileStreamSource`. Author: Burak Yavuz <brkyvz@gmail.com> Closes #15122 from brkyvz/SPARK-17569.
* [SPARK-17512][CORE] Avoid formatting to python path for yarn and mesos ↵jerryshao2016-09-212-3/+29
| | | | | | | | | | | | | | | | cluster mode ## What changes were proposed in this pull request? Yarn and mesos cluster mode support remote python path (HDFS/S3 scheme) by their own mechanism, it is not necessary to check and format the python when running on these modes. This is a potential regression compared to 1.6, so here propose to fix it. ## How was this patch tested? Unit test to verify SparkSubmit arguments, also with local cluster verification. Because of lack of `MiniDFSCluster` support in Spark unit test, there's no integration test added. Author: jerryshao <sshao@hortonworks.com> Closes #15137 from jerryshao/SPARK-17512.
* [SPARK-17623][CORE] Clarify type of TaskEndReason with a failed task.Imran Rashid2016-09-217-19/+13
| | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? In TaskResultGetter, enqueueFailedTask currently deserializes the result as a TaskEndReason. But the type is actually more specific, its a TaskFailedReason. This just leads to more blind casting later on – it would be more clear if the msg was cast to the right type immediately, so method parameter types could be tightened. ## How was this patch tested? Existing unit tests via jenkins. Note that the code was already performing a blind-cast to a TaskFailedReason before in any case, just in a different spot, so there shouldn't be any behavior change. Author: Imran Rashid <irashid@cloudera.com> Closes #15181 from squito/SPARK-17623.
* [SPARK-4563][CORE] Allow driver to advertise a different network address.Marcelo Vanzin2016-09-2121-40/+133
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | The goal of this feature is to allow the Spark driver to run in an isolated environment, such as a docker container, and be able to use the host's port forwarding mechanism to be able to accept connections from the outside world. The change is restricted to the driver: there is no support for achieving the same thing on executors (or the YARN AM for that matter). Those still need full access to the outside world so that, for example, connections can be made to an executor's block manager. The core of the change is simple: add a new configuration that tells what's the address the driver should bind to, which can be different than the address it advertises to executors (spark.driver.host). Everything else is plumbing the new configuration where it's needed. To use the feature, the host starting the container needs to set up the driver's port range to fall into a range that is being forwarded; this required the block manager port to need a special configuration just for the driver, which falls back to the existing spark.blockManager.port when not set. This way, users can modify the driver settings without affecting the executors; it would theoretically be nice to also have different retry counts for driver and executors, but given that docker (at least) allows forwarding port ranges, we can probably live without that for now. Because of the nature of the feature it's kinda hard to add unit tests; I just added a simple one to make sure the configuration works. This was tested with a docker image running spark-shell with the following command: docker blah blah blah \ -p 38000-38100:38000-38100 \ [image] \ spark-shell \ --num-executors 3 \ --conf spark.shuffle.service.enabled=false \ --conf spark.dynamicAllocation.enabled=false \ --conf spark.driver.host=[host's address] \ --conf spark.driver.port=38000 \ --conf spark.driver.blockManager.port=38020 \ --conf spark.ui.port=38040 Running on YARN; verified the driver works, executors start up and listen on ephemeral ports (instead of using the driver's config), and that caching and shuffling (without the shuffle service) works. Clicked through the UI to make sure all pages (including executor thread dumps) worked. Also tested apps without docker, and ran unit tests. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #15120 from vanzin/SPARK-4563.
* [SPARK-11918][ML] Better error from WLS for cases like singular inputSean Owen2016-09-212-4/+35
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Update error handling for Cholesky decomposition to provide a little more info when input is singular. ## How was this patch tested? New test case; jenkins tests. Author: Sean Owen <sowen@cloudera.com> Closes #15177 from srowen/SPARK-11918.
* [SPARK-17418] Prevent kinesis-asl-assembly artifacts from being publishedJosh Rosen2016-09-211-0/+15
| | | | | | | | | | This patch updates the `kinesis-asl-assembly` build to prevent that module from being published as part of Maven releases and snapshot builds. The `kinesis-asl-assembly` includes classes from the Kinesis Client Library (KCL) and Kinesis Producer Library (KPL), both of which are licensed under the Amazon Software License and are therefore prohibited from being distributed in Apache releases. Author: Josh Rosen <joshrosen@databricks.com> Closes #15167 from JoshRosen/stop-publishing-kinesis-assembly.
* [SPARK-17590][SQL] Analyze CTE definitions at once and allow CTE subquery to ↵Liang-Chi Hsieh2016-09-214-5/+29
| | | | | | | | | | | | | | | | | | define CTE ## What changes were proposed in this pull request? We substitute logical plan with CTE definitions in the analyzer rule CTESubstitution. A CTE definition can be used in the logical plan for multiple times, and its analyzed logical plan should be the same. We should not analyze CTE definitions multiple times when they are reused in the query. By analyzing CTE definitions before substitution, we can support defining CTE in subquery. ## How was this patch tested? Jenkins tests. Author: Liang-Chi Hsieh <simonh@tw.ibm.com> Closes #15146 from viirya/cte-analysis-once.
* [CORE][MINOR] Add minor code change to TaskState and Taskerenavsarogullari2016-09-212-2/+2
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? - TaskState and ExecutorState expose isFailed and isFinished functions. It can be useful to add test coverage for different states. Currently, Other enums do not expose any functions so this PR aims just these two enums. - `private` access modifier is added for Finished Task States Set - A minor doc change is added. ## How was this patch tested? New Unit tests are added and run locally. Author: erenavsarogullari <erenavsarogullari@gmail.com> Closes #15143 from erenavsarogullari/SPARK-17584.
* [SPARK-17583][SQL] Remove uesless rowSeparator variable and set ↵hyukjinkwon2016-09-2112-17/+13
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | auto-expanding buffer as default for maxCharsPerColumn option in CSV ## What changes were proposed in this pull request? This PR includes the changes below: 1. Upgrade Univocity library from 2.1.1 to 2.2.1 This includes some performance improvement and also enabling auto-extending buffer in `maxCharsPerColumn` option in CSV. Please refer the [release notes](https://github.com/uniVocity/univocity-parsers/releases). 2. Remove useless `rowSeparator` variable existing in `CSVOptions` We have this unused variable in [CSVOptions.scala#L127](https://github.com/apache/spark/blob/29952ed096fd2a0a19079933ff691671d6f00835/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVOptions.scala#L127) but it seems possibly causing confusion that it actually does not care of `\r\n`. For example, we have an issue open about this, [SPARK-17227](https://issues.apache.org/jira/browse/SPARK-17227), describing this variable. This variable is virtually not being used because we rely on `LineRecordReader` in Hadoop which deals with only both `\n` and `\r\n`. 3. Set the default value of `maxCharsPerColumn` to auto-expending. We are setting 1000000 for the length of each column. It'd be more sensible we allow auto-expending rather than fixed length by default. To make sure, using `-1` is being described in the release note, [2.2.0](https://github.com/uniVocity/univocity-parsers/releases/tag/v2.2.0). ## How was this patch tested? N/A Author: hyukjinkwon <gurwls223@gmail.com> Closes #15138 from HyukjinKwon/SPARK-17583.
* [SPARK-17219][ML] Add NaN value handling in BucketizerVinceShieh2016-09-217-12/+85
| | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR fixes an issue when Bucketizer is called to handle a dataset containing NaN value. Sometimes, null value might also be useful to users, so in these cases, Bucketizer should reserve one extra bucket for NaN values, instead of throwing an illegal exception. Before: ``` Bucketizer.transform on NaN value threw an illegal exception. ``` After: ``` NaN values will be grouped in an extra bucket. ``` ## How was this patch tested? New test cases added in `BucketizerSuite`. Signed-off-by: VinceShieh <vincent.xieintel.com> Author: VinceShieh <vincent.xie@intel.com> Closes #14858 from VinceShieh/spark-17219.
* [SPARK-17017][MLLIB][ML] add a chiSquare Selector based on False Positive ↵Peng, Meng2016-09-217-41/+262
| | | | | | | | | | | | | | | | | Rate (FPR) test ## What changes were proposed in this pull request? Univariate feature selection works by selecting the best features based on univariate statistical tests. False Positive Rate (FPR) is a popular univariate statistical test for feature selection. We add a chiSquare Selector based on False Positive Rate (FPR) test in this PR, like it is implemented in scikit-learn. http://scikit-learn.org/stable/modules/feature_selection.html#univariate-feature-selection ## How was this patch tested? Add Scala ut Author: Peng, Meng <peng.meng@intel.com> Closes #14597 from mpjlu/fprChiSquare.
* [SPARK-17599] Prevent ListingFileCatalog from failing if path doesn't existBurak Yavuz2016-09-212-2/+21
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? The `ListingFileCatalog` lists files given a set of resolved paths. If a folder is deleted at any time between the paths were resolved and the file catalog can check for the folder, the Spark job fails. This may abruptly stop long running StructuredStreaming jobs for example. Folders may be deleted by users or automatically by retention policies. These cases should not prevent jobs from successfully completing. ## How was this patch tested? Unit test in `FileCatalogSuite` Author: Burak Yavuz <brkyvz@gmail.com> Closes #15153 from brkyvz/SPARK-17599.
* [SPARK-17617][SQL] Remainder(%) expression.eval returns incorrect result on ↵Sean Zhong2016-09-212-1/+16
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | double value ## What changes were proposed in this pull request? Remainder(%) expression's `eval()` returns incorrect result when the dividend is a big double. The reason is that Remainder converts the double dividend to decimal to do "%", and that lose precision. This bug only affects the `eval()` that is used by constant folding, the codegen path is not impacted. ### Before change ``` scala> -5083676433652386516D % 10 res2: Double = -6.0 scala> spark.sql("select -5083676433652386516D % 10 as a").show +---+ | a| +---+ |0.0| +---+ ``` ### After change ``` scala> spark.sql("select -5083676433652386516D % 10 as a").show +----+ | a| +----+ |-6.0| +----+ ``` ## How was this patch tested? Unit test. Author: Sean Zhong <seanzhong@databricks.com> Closes #15171 from clockfly/SPARK-17617.
* [SPARK-17595][MLLIB] Use a bounded priority queue to find synonyms in ↵William Benton2016-09-211-3/+10
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Word2VecModel ## What changes were proposed in this pull request? The code in `Word2VecModel.findSynonyms` to choose the vocabulary elements with the highest similarity to the query vector currently sorts the collection of similarities for every vocabulary element. This involves making multiple copies of the collection of similarities while doing a (relatively) expensive sort. It would be more efficient to find the best matches by maintaining a bounded priority queue and populating it with a single pass over the vocabulary, and that is exactly what this patch does. ## How was this patch tested? This patch adds no user-visible functionality and its correctness should be exercised by existing tests. To ensure that this approach is actually faster, I made a microbenchmark for `findSynonyms`: ``` object W2VTiming { import org.apache.spark.{SparkContext, SparkConf} import org.apache.spark.mllib.feature.Word2VecModel def run(modelPath: String, scOpt: Option[SparkContext] = None) { val sc = scOpt.getOrElse(new SparkContext(new SparkConf(true).setMaster("local[*]").setAppName("test"))) val model = Word2VecModel.load(sc, modelPath) val keys = model.getVectors.keys val start = System.currentTimeMillis for(key <- keys) { model.findSynonyms(key, 5) model.findSynonyms(key, 10) model.findSynonyms(key, 25) model.findSynonyms(key, 50) } val finish = System.currentTimeMillis println("run completed in " + (finish - start) + "ms") } } ``` I ran this test on a model generated from the complete works of Jane Austen and found that the new approach was over 3x faster than the old approach. (If the `num` argument to `findSynonyms` is very close to the vocabulary size, the new approach will have less of an advantage over the old one.) Author: William Benton <willb@redhat.com> Closes #15150 from willb/SPARK-17595.
* [SPARK-17585][PYSPARK][CORE] PySpark SparkContext.addFile supports adding ↵Yanbo Liang2016-09-215-7/+34
| | | | | | | | | | | | | | files recursively ## What changes were proposed in this pull request? Users would like to add a directory as dependency in some cases, they can use ```SparkContext.addFile``` with argument ```recursive=true``` to recursively add all files under the directory by using Scala. But Python users can only add file not directory, we should also make it supported. ## How was this patch tested? Unit test. Author: Yanbo Liang <ybliang8@gmail.com> Closes #15140 from yanboliang/spark-17585.
* [CORE][DOC] Fix errors in commentswm624@hotmail.com2016-09-212-2/+2
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? While reading source code of CORE and SQL core, I found some minor errors in comments such as extra space, missing blank line and grammar error. I fixed these minor errors and might find more during my source code study. ## How was this patch tested? Manually build Author: wm624@hotmail.com <wm624@hotmail.com> Closes #15151 from wangmiao1981/mem.
* [SPARK-15698][SQL][STREAMING][FOLLW-UP] Fix FileStream source and sink log ↵jerryshao2016-09-203-11/+13
| | | | | | | | | | | | | | | | | | get configuration issue ## What changes were proposed in this pull request? This issue was introduced in the previous commit of SPARK-15698. Mistakenly change the way to get configuration back to original one, so here with the follow up PR to revert them up. ## How was this patch tested? N/A Ping zsxwing , please review again, sorry to bring the inconvenience. Thanks a lot. Author: jerryshao <sshao@hortonworks.com> Closes #15173 from jerryshao/SPARK-15698-follow.
* [MINOR][BUILD] Fix CheckStyle ErrorWeiqing Yang2016-09-207-17/+23
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR is to fix the code style errors before 2.0.1 release. ## How was this patch tested? Manual. Before: ``` ./dev/lint-java Using `mvn` from path: /usr/local/bin/mvn Checkstyle checks failed at following occurrences: [ERROR] src/main/java/org/apache/spark/network/client/TransportClient.java:[153] (sizes) LineLength: Line is longer than 100 characters (found 107). [ERROR] src/main/java/org/apache/spark/network/client/TransportClient.java:[196] (sizes) LineLength: Line is longer than 100 characters (found 108). [ERROR] src/main/java/org/apache/spark/network/client/TransportClient.java:[239] (sizes) LineLength: Line is longer than 100 characters (found 115). [ERROR] src/main/java/org/apache/spark/network/server/TransportRequestHandler.java:[119] (sizes) LineLength: Line is longer than 100 characters (found 107). [ERROR] src/main/java/org/apache/spark/network/server/TransportRequestHandler.java:[129] (sizes) LineLength: Line is longer than 100 characters (found 104). [ERROR] src/main/java/org/apache/spark/network/util/LevelDBProvider.java:[124,11] (modifier) ModifierOrder: 'static' modifier out of order with the JLS suggestions. [ERROR] src/main/java/org/apache/spark/network/util/TransportConf.java:[26] (regexp) RegexpSingleline: No trailing whitespace allowed. [ERROR] src/main/java/org/apache/spark/util/collection/unsafe/sort/PrefixComparators.java:[33] (sizes) LineLength: Line is longer than 100 characters (found 110). [ERROR] src/main/java/org/apache/spark/util/collection/unsafe/sort/PrefixComparators.java:[38] (sizes) LineLength: Line is longer than 100 characters (found 110). [ERROR] src/main/java/org/apache/spark/util/collection/unsafe/sort/PrefixComparators.java:[43] (sizes) LineLength: Line is longer than 100 characters (found 106). [ERROR] src/main/java/org/apache/spark/util/collection/unsafe/sort/PrefixComparators.java:[48] (sizes) LineLength: Line is longer than 100 characters (found 110). [ERROR] src/main/java/org/apache/spark/util/collection/unsafe/sort/UnsafeInMemorySorter.java:[0] (misc) NewlineAtEndOfFile: File does not end with a newline. [ERROR] src/main/java/org/apache/spark/util/collection/unsafe/sort/UnsafeSorterSpillReader.java:[67] (sizes) LineLength: Line is longer than 100 characters (found 106). [ERROR] src/main/java/org/apache/spark/network/yarn/YarnShuffleService.java:[200] (regexp) RegexpSingleline: No trailing whitespace allowed. [ERROR] src/main/java/org/apache/spark/network/yarn/YarnShuffleService.java:[309] (regexp) RegexpSingleline: No trailing whitespace allowed. [ERROR] src/main/java/org/apache/spark/network/yarn/YarnShuffleService.java:[332] (regexp) RegexpSingleline: No trailing whitespace allowed. [ERROR] src/main/java/org/apache/spark/network/yarn/YarnShuffleService.java:[348] (regexp) RegexpSingleline: No trailing whitespace allowed. ``` After: ``` ./dev/lint-java Using `mvn` from path: /usr/local/bin/mvn Checkstyle checks passed. ``` Author: Weiqing Yang <yangweiqing001@gmail.com> Closes #15170 from Sherry302/fixjavastyle.
* [SPARK-17513][SQL] Make StreamExecution garbage-collect its metadatapetermaxlee2016-09-203-0/+32
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR modifies StreamExecution such that it discards metadata for batches that have already been fully processed. I used the purge method that was added as part of SPARK-17235. This is a resubmission of 15126, which was based on work by frreiss in #15067, but fixed the test case along with some typos. ## How was this patch tested? A new test case in StreamingQuerySuite. The test case would fail without the changes in this pull request. Author: petermaxlee <petermaxlee@gmail.com> Closes #15166 from petermaxlee/SPARK-17513-2.
* [SPARK-17611][YARN][TEST] Make shuffle service test really test auth.Marcelo Vanzin2016-09-202-27/+33
| | | | | | | | | | | Currently, the code is just swallowing exceptions, and not really checking whether the auth information was being recorded properly. Fix both problems, and also avoid tests inadvertently affecting other tests by modifying the shared config variable (by making it not shared). Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #15161 from vanzin/SPARK-17611.
* [SPARK-17549][SQL] Revert "[] Only collect table size stat in driver for ↵Yin Huai2016-09-202-20/+18
| | | | | | | | | | cached relation." This reverts commit 39e2bad6a866d27c3ca594d15e574a1da3ee84cc because of the problem mentioned at https://issues.apache.org/jira/browse/SPARK-17549?focusedCommentId=15505060&page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#comment-15505060 Author: Yin Huai <yhuai@databricks.com> Closes #15157 from yhuai/revert-SPARK-17549.
* [SPARK-15698][SQL][STREAMING] Add the ability to remove the old MetadataLog ↵jerryshao2016-09-209-222/+550
| | | | | | | | | | | | | | | | in FileStreamSource ## What changes were proposed in this pull request? Current `metadataLog` in `FileStreamSource` will add a checkpoint file in each batch but do not have the ability to remove/compact, which will lead to large number of small files when running for a long time. So here propose to compact the old logs into one file. This method is quite similar to `FileStreamSinkLog` but simpler. ## How was this patch tested? Unit test added. Author: jerryshao <sshao@hortonworks.com> Closes #13513 from jerryshao/SPARK-15698.
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