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* [SPARK-13920][BUILD] MIMA checks should apply to @Experimental and ↵Dongjoon Hyun2016-03-151-2/+211
| | | | | | | | | | | | | | | | @DeveloperAPI APIs ## What changes were proposed in this pull request? We are able to change `Experimental` and `DeveloperAPI` API freely but also should monitor and manage those API carefully. This PR for [SPARK-13920](https://issues.apache.org/jira/browse/SPARK-13920) enables MiMa check and adds filters for them. ## How was this patch tested? Pass the Jenkins tests (including MiMa). Author: Dongjoon Hyun <dongjoon@apache.org> Closes #11751 from dongjoon-hyun/SPARK-13920.
* [SPARK-13576][BUILD] Don't create assembly for examples.Marcelo Vanzin2016-03-151-3/+38
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | As part of the goal to stop creating assemblies in Spark, this change modifies the mvn and sbt builds to not create an assembly for examples. Instead, dependencies are copied to the build directory (under target/scala-xx/jars), and in the final archive, into the "examples/jars" directory. To avoid having to deal too much with Windows batch files, I made examples run through the launcher library; the spark-submit launcher now has a special mode to run examples, which adds all the necessary jars to the spark-submit command line, and replaces the bash and batch scripts that were used to run examples. The scripts are now just a thin wrapper around spark-submit; another advantage is that now all spark-submit options are supported. There are a few glitches; in the mvn build, a lot of duplicated dependencies get copied, because they are promoted to "compile" scope due to extra dependencies in the examples module (such as HBase). In the sbt build, all dependencies are copied, because there doesn't seem to be an easy way to filter things. I plan to clean some of this up when the rest of the tasks are finished. When the main assembly is replaced with jars, we can remove duplicate jars from the examples directory during packaging. Tested by running SparkPi in: maven build, sbt build, dist created by make-distribution.sh. Finally: note that running the "assembly" target in sbt doesn't build the examples anymore. You need to run "package" for that. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #11452 from vanzin/SPARK-13576.
* [SPARK-13880][SPARK-13881][SQL] Rename DataFrame.scala Dataset.scala, and ↵Reynold Xin2016-03-151-0/+1
| | | | | | | | | | | | | | | remove LegacyFunctions ## What changes were proposed in this pull request? 1. Rename DataFrame.scala Dataset.scala, since the class is now named Dataset. 2. Remove LegacyFunctions. It was introduced in Spark 1.6 for backward compatibility, and can be removed in Spark 2.0. ## How was this patch tested? Should be covered by existing unit/integration tests. Author: Reynold Xin <rxin@databricks.com> Closes #11704 from rxin/SPARK-13880.
* [SPARK-13843][STREAMING] Remove streaming-flume, streaming-mqtt, ↵Shixiong Zhu2016-03-141-28/+9
| | | | | | | | | | | | | | | | | | | | | | | | | | streaming-zeromq, streaming-akka, streaming-twitter to Spark packages ## What changes were proposed in this pull request? Currently there are a few sub-projects, each for integrating with different external sources for Streaming. Now that we have better ability to include external libraries (spark packages) and with Spark 2.0 coming up, we can move the following projects out of Spark to https://github.com/spark-packages - streaming-flume - streaming-akka - streaming-mqtt - streaming-zeromq - streaming-twitter They are just some ancillary packages and considering the overhead of maintenance, running tests and PR failures, it's better to maintain them out of Spark. In addition, these projects can have their different release cycles and we can release them faster. I have already copied these projects to https://github.com/spark-packages ## How was this patch tested? Jenkins tests Author: Shixiong Zhu <shixiong@databricks.com> Closes #11672 from zsxwing/remove-external-pkg.
* [SPARK-13686][MLLIB][STREAMING] Add a constructor parameter `reqParam` to ↵Dongjoon Hyun2016-03-141-0/+3
| | | | | | | | | | | | | | | | | (Streaming)LinearRegressionWithSGD ## What changes were proposed in this pull request? `LinearRegressionWithSGD` and `StreamingLinearRegressionWithSGD` does not have `regParam` as their constructor arguments. They just depends on GradientDescent's default reqParam values. To be consistent with other algorithms, we had better add them. The same default value is used. ## How was this patch tested? Pass the existing unit test. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #11527 from dongjoon-hyun/SPARK-13686.
* [MINOR][DOCS] Fix more typos in comments/strings.Dongjoon Hyun2016-03-141-3/+3
| | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR fixes 135 typos over 107 files: * 121 typos in comments * 11 typos in testcase name * 3 typos in log messages ## How was this patch tested? Manual. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #11689 from dongjoon-hyun/fix_more_typos.
* [SPARK-13834][BUILD] Update sbt and sbt plugins for 2.x.Dongjoon Hyun2016-03-134-9/+8
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? For 2.0.0, we had better make **sbt** and **sbt plugins** up-to-date. This PR checks the status of each plugins and bumps the followings. * sbt: 0.13.9 --> 0.13.11 * sbteclipse-plugin: 2.2.0 --> 4.0.0 * sbt-dependency-graph: 0.7.4 --> 0.8.2 * sbt-mima-plugin: 0.1.6 --> 0.1.9 * sbt-revolver: 0.7.2 --> 0.8.0 All other plugins are up-to-date. (Note that `sbt-avro` seems to be change from 0.3.2 to 1.0.1, but it's not published in the repository.) During upgrade, this PR also updated the following MiMa error. Note that the related excluding filter is already registered correctly. It seems due to the change of MiMa exception result. ``` // SPARK-12896 Send only accumulator updates to driver, not TaskMetrics ProblemFilters.exclude[IncompatibleMethTypeProblem]("org.apache.spark.Accumulable.this"), -ProblemFilters.exclude[IncompatibleMethTypeProblem]("org.apache.spark.Accumulator.this"), +ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.Accumulator.this"), ``` ## How was this patch tested? Pass the Jenkins build. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #11669 from dongjoon-hyun/update_mima.
* [SPARK-13817][BUILD][SQL] Re-enable MiMA and removes object DataFrameCheng Lian2016-03-111-0/+22
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? PR #11443 temporarily disabled MiMA check, this PR re-enables it. One extra change is that `object DataFrame` is also removed. The only purpose of introducing `object DataFrame` was to use it as an internal factory for creating `Dataset[Row]`. By replacing this internal factory with `Dataset.newDataFrame`, both `DataFrame` and `DataFrame$` are entirely removed from the API, so that we can simply put a `MissingClassProblem` filter in `MimaExcludes.scala` for most DataFrame API changes. ## How was this patch tested? Tested by MiMA check triggered by Jenkins. Author: Cheng Lian <lian@databricks.com> Closes #11656 from liancheng/re-enable-mima.
* [SPARK-13294][PROJECT INFRA] Remove MiMa's dependency on spark-class / Spark ↵Josh Rosen2016-03-101-9/+10
| | | | | | | | | | | | | | | assembly This patch removes the need to build a full Spark assembly before running the `dev/mima` script. - I modified the `tools` project to remove a direct dependency on Spark, so `sbt/sbt tools/fullClasspath` will now return the classpath for the `GenerateMIMAIgnore` class itself plus its own dependencies. - This required me to delete two classes full of dead code that we don't use anymore - `GenerateMIMAIgnore` now uses [ClassUtil](http://software.clapper.org/classutil/) to find all of the Spark classes rather than our homemade JAR traversal code. The problem in our own code was that it didn't handle folders of classes properly, which is necessary in order to generate excludes with an assembly-free Spark build. - `./dev/mima` no longer runs through `spark-class`, eliminating the need to reason about classpath ordering between `SPARK_CLASSPATH` and the assembly. Author: Josh Rosen <joshrosen@databricks.com> Closes #11178 from JoshRosen/remove-assembly-in-run-tests.
* [SPARK-13665][SQL] Separate the concerns of HadoopFsRelationMichael Armbrust2016-03-071-1/+5
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | `HadoopFsRelation` is used for reading most files into Spark SQL. However today this class mixes the concerns of file management, schema reconciliation, scan building, bucketing, partitioning, and writing data. As a result, many data sources are forced to reimplement the same functionality and the various layers have accumulated a fair bit of inefficiency. This PR is a first cut at separating this into several components / interfaces that are each described below. Additionally, all implementations inside of Spark (parquet, csv, json, text, orc, svmlib) have been ported to the new API `FileFormat`. External libraries, such as spark-avro will also need to be ported to work with Spark 2.0. ### HadoopFsRelation A simple `case class` that acts as a container for all of the metadata required to read from a datasource. All discovery, resolution and merging logic for schemas and partitions has been removed. This an internal representation that no longer needs to be exposed to developers. ```scala case class HadoopFsRelation( sqlContext: SQLContext, location: FileCatalog, partitionSchema: StructType, dataSchema: StructType, bucketSpec: Option[BucketSpec], fileFormat: FileFormat, options: Map[String, String]) extends BaseRelation ``` ### FileFormat The primary interface that will be implemented by each different format including external libraries. Implementors are responsible for reading a given format and converting it into `InternalRow` as well as writing out an `InternalRow`. A format can optionally return a schema that is inferred from a set of files. ```scala trait FileFormat { def inferSchema( sqlContext: SQLContext, options: Map[String, String], files: Seq[FileStatus]): Option[StructType] def prepareWrite( sqlContext: SQLContext, job: Job, options: Map[String, String], dataSchema: StructType): OutputWriterFactory def buildInternalScan( sqlContext: SQLContext, dataSchema: StructType, requiredColumns: Array[String], filters: Array[Filter], bucketSet: Option[BitSet], inputFiles: Array[FileStatus], broadcastedConf: Broadcast[SerializableConfiguration], options: Map[String, String]): RDD[InternalRow] } ``` The current interface is based on what was required to get all the tests passing again, but still mixes a couple of concerns (i.e. `bucketSet` is passed down to the scan instead of being resolved by the planner). Additionally, scans are still returning `RDD`s instead of iterators for single files. In a future PR, bucketing should be removed from this interface and the scan should be isolated to a single file. ### FileCatalog This interface is used to list the files that make up a given relation, as well as handle directory based partitioning. ```scala trait FileCatalog { def paths: Seq[Path] def partitionSpec(schema: Option[StructType]): PartitionSpec def allFiles(): Seq[FileStatus] def getStatus(path: Path): Array[FileStatus] def refresh(): Unit } ``` Currently there are two implementations: - `HDFSFileCatalog` - based on code from the old `HadoopFsRelation`. Infers partitioning by recursive listing and caches this data for performance - `HiveFileCatalog` - based on the above, but it uses the partition spec from the Hive Metastore. ### ResolvedDataSource Produces a logical plan given the following description of a Data Source (which can come from DataFrameReader or a metastore): - `paths: Seq[String] = Nil` - `userSpecifiedSchema: Option[StructType] = None` - `partitionColumns: Array[String] = Array.empty` - `bucketSpec: Option[BucketSpec] = None` - `provider: String` - `options: Map[String, String]` This class is responsible for deciding which of the Data Source APIs a given provider is using (including the non-file based ones). All reconciliation of partitions, buckets, schema from metastores or inference is done here. ### DataSourceAnalysis / DataSourceStrategy Responsible for analyzing and planning reading/writing of data using any of the Data Source APIs, including: - pruning the files from partitions that will be read based on filters. - appending partition columns* - applying additional filters when a data source can not evaluate them internally. - constructing an RDD that is bucketed correctly when required* - sanity checking schema match-up and other analysis when writing. *In the future we should do that following: - Break out file handling into its own Strategy as its sufficiently complex / isolated. - Push the appending of partition columns down in to `FileFormat` to avoid an extra copy / unvectorization. - Use a custom RDD for scans instead of `SQLNewNewHadoopRDD2` Author: Michael Armbrust <michael@databricks.com> Author: Wenchen Fan <wenchen@databricks.com> Closes #11509 from marmbrus/fileDataSource.
* [SPARK-12073][STREAMING] backpressure rate controller consumes events ↵Jason White2016-03-041-0/+4
| | | | | | | | | | | | | | | | | | | | | | preferentially from lagg… …ing partitions I'm pretty sure this is the reason we couldn't easily recover from an unbalanced Kafka partition under heavy load when using backpressure. `maxMessagesPerPartition` calculates an appropriate limit for the message rate from all partitions, and then divides by the number of partitions to determine how many messages to retrieve per partition. The problem with this approach is that when one partition is behind by millions of records (due to random Kafka issues), but the rate estimator calculates only 100k total messages can be retrieved, each partition (out of say 32) only retrieves max 100k/32=3125 messages. This PR (still needing a test) determines a per-partition desired message count by using the current lag for each partition to preferentially weight the total message limit among the partitions. In this situation, if each partition gets 1k messages, but 1 partition starts 1M behind, then the total number of messages to retrieve is (32 * 1k + 1M) = 1032000 messages, of which the one partition needs 1001000. So, it gets (1001000 / 1032000) = 97% of the 100k messages, and the other 31 partitions share the remaining 3%. Assuming all of 100k the messages are retrieved and processed within the batch window, the rate calculator will increase the number of messages to retrieve in the next batch, until it reaches a new stable point or the backlog is finished processed. We're going to try deploying this internally at Shopify to see if this resolves our issue. tdas koeninger holdenk Author: Jason White <jason.white@shopify.com> Closes #10089 from JasonMWhite/rate_controller_offsets.
* [MINOR] Fix typos in comments and testcase name of codeDongjoon Hyun2016-03-031-1/+1
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR fixes typos in comments and testcase name of code. ## How was this patch tested? manual. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #11481 from dongjoon-hyun/minor_fix_typos_in_code.
* [SPARK-13526][SQL] Move SQLContext per-session states to new classAndrew Or2016-02-271-1/+6
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? This creates a `SessionState`, which groups a few fields that existed in `SQLContext`. Because `HiveContext` extends `SQLContext` we also need to make changes there. This is mainly a cleanup task that will soon pave the way for merging the two contexts. ## How was this patch tested? Existing unit tests; this patch introduces no change in behavior. Author: Andrew Or <andrew@databricks.com> Closes #11405 from andrewor14/refactor-session.
* [SPARK-13465] Add a task failure listener to TaskContextReynold Xin2016-02-261-1/+3
| | | | | | | | | | | | | ## What changes were proposed in this pull request? TaskContext supports task completion callback, which gets called regardless of task failures. However, there is no way for the listener to know if there is an error. This patch adds a new listener that gets called when a task fails. ## How was the this patch tested? New unit test case and integration test case covering the code path Author: Reynold Xin <rxin@databricks.com> Closes #11340 from rxin/SPARK-13465.
* [SPARK-13486][SQL] Move SQLConf into an internal packageReynold Xin2016-02-251-0/+6
| | | | | | | | | | | | ## What changes were proposed in this pull request? This patch moves SQLConf into org.apache.spark.sql.internal package to make it very explicit that it is internal. Soon I will also submit more API work that creates implementations of interfaces in this internal package. ## How was this patch tested? If it compiles, then the refactoring should work. Author: Reynold Xin <rxin@databricks.com> Closes #11363 from rxin/SPARK-13486.
* [SPARK-7729][UI] Executor which has been killed should also be displayed on ↵Lianhui Wang2016-02-231-0/+3
| | | | | | | | | | | | | | | Executor Tab andrewor14 squito Dead Executors should also be displayed on Executor Tab. as following: ![image](https://cloud.githubusercontent.com/assets/545478/11492707/ae55d7f6-982b-11e5-919a-b62cd84684b2.png) Author: Lianhui Wang <lianhuiwang09@gmail.com> This patch had conflicts when merged, resolved by Committer: Andrew Or <andrew@databricks.com> Closes #10058 from lianhuiwang/SPARK-7729.
* [SPARK-13220][CORE] deprecate yarn-client and yarn-cluster modejerryshao2016-02-231-2/+6
| | | | | | Author: jerryshao <sshao@hortonworks.com> Closes #11229 from jerryshao/SPARK-13220.
* [SPARK-13413] Remove SparkContext.metricsSystemReynold Xin2016-02-221-1/+5
| | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This patch removes SparkContext.metricsSystem. SparkContext.metricsSystem returns MetricsSystem, which is a private class. I think it was added by accident. In addition, I also removed an unused private[spark] method schedulerBackend setter. ## How was the this patch tested? N/A. Author: Reynold Xin <rxin@databricks.com> This patch had conflicts when merged, resolved by Committer: Josh Rosen <joshrosen@databricks.com> Closes #11282 from rxin/SPARK-13413.
* [SPARK-13426][CORE] Remove the support of SIMRjerryshao2016-02-221-0/+3
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR removes the support of SIMR, since SIMR is not actively used and maintained for a long time, also is not supported from `SparkSubmit`, so here propose to remove it. ## How was the this patch tested? This patch is tested locally by running unit tests. Author: jerryshao <sshao@hortonworks.com> Closes #11296 from jerryshao/SPARK-13426.
* [SPARK-13248][STREAMING] Remove deprecated Streaming APIs.Luciano Resende2016-02-211-0/+13
| | | | | | | | Remove deprecated Streaming APIs and adjust sample applications. Author: Luciano Resende <lresende@apache.org> Closes #11139 from lresende/streaming-deprecated-apis.
* [SPARK-13109][BUILD] Fix SBT publishLocal issuejerryshao2016-02-171-1/+2
| | | | | | | | | | Add local ivy repo to the SBT build file to fix this. Scaladoc compile error is fixed. Author: jerryshao <sshao@hortonworks.com> Closes #11001 from jerryshao/SPARK-13109.
* [SPARK-12995][GRAPHX] Remove deprecate APIs from PregelTakeshi YAMAMURO2016-02-151-0/+6
| | | | | | Author: Takeshi YAMAMURO <linguin.m.s@gmail.com> Closes #10918 from maropu/RemoveDeprecateInPregel.
* [SPARK-13278][CORE] Launcher fails to start with JDK 9 EAClaes Redestad2016-02-141-2/+4
| | | | | | | | See http://openjdk.java.net/jeps/223 for more information about the JDK 9 version string scheme. Author: Claes Redestad <claes.redestad@gmail.com> Closes #11160 from cl4es/master.
* [SPARK-13296][SQL] Move UserDefinedFunction into sql.expressions.Reynold Xin2016-02-131-1/+7
| | | | | | | | | | | | | | | | This pull request has the following changes: 1. Moved UserDefinedFunction into expressions package. This is more consistent with how we structure the packages for window functions and UDAFs. 2. Moved UserDefinedPythonFunction into execution.python package, so we don't have a random private class in the top level sql package. 3. Move everything in execution/python.scala into the newly created execution.python package. Most of the diffs are just straight copy-paste. Author: Reynold Xin <rxin@databricks.com> Closes #11181 from rxin/SPARK-13296.
* [SPARK-7889][WEBUI] HistoryServer updates UI for incomplete appsSteve Loughran2016-02-111-0/+3
| | | | | | | | | | | When the HistoryServer is showing an incomplete app, it needs to check if there is a newer version of the app available. It does this by checking if a version of the app has been loaded with a larger *filesize*. If so, it detaches the current UI, attaches the new one, and redirects back to the same URL to show the new UI. https://issues.apache.org/jira/browse/SPARK-7889 Author: Steve Loughran <stevel@hortonworks.com> Author: Imran Rashid <irashid@cloudera.com> Closes #11118 from squito/SPARK-7889-alternate.
* [SPARK-13277][BUILD] Follow-up ANTLR warnings are treated as build errorsHerman van Hovell2016-02-111-3/+6
| | | | | | | | | | It is possible to create faulty but legal ANTLR grammars. ANTLR will produce warnings but also a valid compileable parser. This PR makes sure we treat such warnings as build errors. cc rxin / viirya Author: Herman van Hovell <hvanhovell@questtec.nl> Closes #11174 from hvanhovell/ANTLR-warnings-as-errors.
* [SPARK-12950] [SQL] Improve lookup of BytesToBytesMap in aggregateDavies Liu2016-02-091-0/+1
| | | | | | | | | | | | This PR improve the lookup of BytesToBytesMap by: 1. Generate code for calculate the hash code of grouping keys. 2. Do not use MemoryLocation, fetch the baseObject and offset for key and value directly (remove the indirection). Author: Davies Liu <davies@databricks.com> Closes #11010 from davies/gen_map.
* [SPARK-10620][SPARK-13054] Minor addendum to #10835Andrew Or2016-02-081-1/+2
| | | | | | | | Additional changes to #10835, mainly related to style and visibility. This patch also adds back a few deprecated methods for backward compatibility. Author: Andrew Or <andrew@databricks.com> Closes #10958 from andrewor14/task-metrics-to-accums-followups.
* [SPARK-12689][SQL] Migrate DDL parsing to the newly absorbed parserLiang-Chi Hsieh2016-01-301-0/+5
| | | | | | | | | | | | JIRA: https://issues.apache.org/jira/browse/SPARK-12689 DDLParser processes three commands: createTable, describeTable and refreshTable. This patch migrates the three commands to newly absorbed parser. Author: Liang-Chi Hsieh <viirya@gmail.com> Author: Liang-Chi Hsieh <viirya@appier.com> Closes #10723 from viirya/migrate-ddl-describe.
* [SPARK-6363][BUILD] Make Scala 2.11 the default Scala versionJosh Rosen2016-01-303-7/+13
| | | | | | | | | | | | This patch changes Spark's build to make Scala 2.11 the default Scala version. To be clear, this does not mean that Spark will stop supporting Scala 2.10: users will still be able to compile Spark for Scala 2.10 by following the instructions on the "Building Spark" page; however, it does mean that Scala 2.11 will be the default Scala version used by our CI builds (including pull request builds). The Scala 2.11 compiler is faster than 2.10, so I think we'll be able to look forward to a slight speedup in our CI builds (it looks like it's about 2X faster for the Maven compile-only builds, for instance). After this patch is merged, I'll update Jenkins to add new compile-only jobs to ensure that Scala 2.10 compilation doesn't break. Author: Josh Rosen <joshrosen@databricks.com> Closes #10608 from JoshRosen/SPARK-6363.
* [SPARK-10873] Support column sort and search for History Server.zhuol2016-01-291-0/+4
| | | | | | | | | | | | | | | | | | | | | | | | [SPARK-10873] Support column sort and search for History Server using jQuery DataTable and REST API. Before this commit, the history server was generated hard-coded html and can not support search, also, the sorting was disabled if there is any application that has more than one attempt. Supporting search and sort (over all applications rather than the 20 entries in the current page) in any case will greatly improve user experience. 1. Create the historypage-template.html for displaying application information in datables. 2. historypage.js uses jQuery to access the data from /api/v1/applications REST API, and use DataTable to display each application's information. For application that has more than one attempt, the RowsGroup is used to merge such entries while at the same time supporting sort and search. 3. "duration" and "lastUpdated" rest API are added to application's "attempts". 4. External javascirpt and css files for datatables, RowsGroup and jquery plugins are added with licenses clarified. Snapshots for how it looks like now: History page view: ![historypage](https://cloud.githubusercontent.com/assets/11683054/12184383/89bad774-b55a-11e5-84e4-b0276172976f.png) Search: ![search](https://cloud.githubusercontent.com/assets/11683054/12184385/8d3b94b0-b55a-11e5-869a-cc0ef0a4242a.png) Sort by started time: ![sort-by-started-time](https://cloud.githubusercontent.com/assets/11683054/12184387/8f757c3c-b55a-11e5-98c8-577936366566.png) Author: zhuol <zhuol@yahoo-inc.com> Closes #10648 from zhuoliu/10873.
* [SPARK-12895][SPARK-12896] Migrate TaskMetrics to accumulatorsAndrew Or2016-01-271-0/+9
| | | | | | | | | | | | | | | | The high level idea is that instead of having the executors send both accumulator updates and TaskMetrics, we should have them send only accumulator updates. This eliminates the need to maintain both code paths since one can be implemented in terms of the other. This effort is split into two parts: **SPARK-12895: Implement TaskMetrics using accumulators.** TaskMetrics is basically just a bunch of accumulable fields. This patch makes TaskMetrics a syntactic wrapper around a collection of accumulators so we don't need to send TaskMetrics from the executors to the driver. **SPARK-12896: Send only accumulator updates to the driver.** Now that TaskMetrics are expressed in terms of accumulators, we can capture all TaskMetrics values if we just send accumulator updates from the executors to the driver. This completes the parent issue SPARK-10620. While an effort has been made to preserve as much of the public API as possible, there were a few known breaking DeveloperApi changes that would be very awkward to maintain. I will gather the full list shortly and post it here. Note: This was once part of #10717. This patch is split out into its own patch from there to make it easier for others to review. Other smaller pieces of already been merged into master. Author: Andrew Or <andrew@databricks.com> Closes #10835 from andrewor14/task-metrics-use-accums.
* [SPARK-11622][MLLIB] Make LibSVMRelation extends HadoopFsRelation and…Jeff Zhang2016-01-261-0/+4
| | | | | | | | | | | | … Add LibSVMOutputWriter The behavior of LibSVMRelation is not changed except adding LibSVMOutputWriter * Partition is still not supported * Multiple input paths is not supported Author: Jeff Zhang <zjffdu@apache.org> Closes #9595 from zjffdu/SPARK-11622.
* [SPARK-3369][CORE][STREAMING] Java mapPartitions Iterator->Iterable is ↵Sean Owen2016-01-261-0/+31
| | | | | | | | | | | | inconsistent with Scala's Iterator->Iterator Fix Java function API methods for flatMap and mapPartitions to require producing only an Iterator, not Iterable. Also fix DStream.flatMap to require a function producing TraversableOnce only, not Traversable. CC rxin pwendell for API change; tdas since it also touches streaming. Author: Sean Owen <sowen@cloudera.com> Closes #10413 from srowen/SPARK-3369.
* [SPARK-12149][WEB UI] Executor UI improvement suggestions - Color UIAlex Bozarth2016-01-251-0/+6
| | | | | | | | | | | | | Added color coding to the Executors page for Active Tasks, Failed Tasks, Completed Tasks and Task Time. Active Tasks is shaded blue with it's range based on percentage of total cores used. Failed Tasks is shaded red ranging over the first 10% of total tasks failed Completed Tasks is shaded green ranging over 10% of total tasks including failed and active tasks, but only when there are active or failed tasks on that executor. Task Time is shaded red when GC Time goes over 10% of total time with it's range directly corresponding to the percent of total time. Author: Alex Bozarth <ajbozart@us.ibm.com> Closes #10154 from ajbozarth/spark12149.
* [SPARK-12933][SQL] Initial implementation of Count-Min sketchCheng Lian2016-01-231-12/+27
| | | | | | | | | | | | | | | | | | | This PR adds an initial implementation of count min sketch, contained in a new module spark-sketch under `common/sketch`. The implementation is based on the [`CountMinSketch` class in stream-lib][1]. As required by the [design doc][2], spark-sketch should have no external dependency. Two classes, `Murmur3_x86_32` and `Platform` are copied to spark-sketch from spark-unsafe for hashing facilities. They'll also be used in the upcoming bloom filter implementation. The following features will be added in future follow-up PRs: - Serialization support - DataFrame API integration [1]: https://github.com/addthis/stream-lib/blob/aac6b4d23a8686b000f80baa447e0922ecac3bcb/src/main/java/com/clearspring/analytics/stream/frequency/CountMinSketch.java [2]: https://issues.apache.org/jira/secure/attachment/12782378/BloomFilterandCount-MinSketchinSpark2.0.pdf Author: Cheng Lian <lian@databricks.com> Closes #10851 from liancheng/count-min-sketch.
* [SPARK-7997][CORE] Remove Akka from Spark Core and StreamingShixiong Zhu2016-01-221-1/+3
| | | | | | | | | | | | - Remove Akka dependency from core. Note: the streaming-akka project still uses Akka. - Remove HttpFileServer - Remove Akka configs from SparkConf and SSLOptions - Rename `spark.akka.frameSize` to `spark.rpc.message.maxSize`. I think it's still worth to keep this config because using `DirectTaskResult` or `IndirectTaskResult` depends on it. - Update comments and docs Author: Shixiong Zhu <shixiong@databricks.com> Closes #10854 from zsxwing/remove-akka.
* [SPARK-7799][SPARK-12786][STREAMING] Add "streaming-akka" projectShixiong Zhu2016-01-202-4/+15
| | | | | | | | | | | | | Include the following changes: 1. Add "streaming-akka" project and org.apache.spark.streaming.akka.AkkaUtils for creating an actorStream 2. Remove "StreamingContext.actorStream" and "JavaStreamingContext.actorStream" 3. Update the ActorWordCount example and add the JavaActorWordCount example 4. Make "streaming-zeromq" depend on "streaming-akka" and update the codes accordingly Author: Shixiong Zhu <shixiong@databricks.com> Closes #10744 from zsxwing/streaming-akka-2.
* [SPARK-12847][CORE][STREAMING] Remove StreamingListenerBus and post all ↵Shixiong Zhu2016-01-201-0/+4
| | | | | | | | | | | | | | | Streaming events to the same thread as Spark events Including the following changes: 1. Add StreamingListenerForwardingBus to WrappedStreamingListenerEvent process events in `onOtherEvent` to StreamingListener 2. Remove StreamingListenerBus 3. Merge AsynchronousListenerBus and LiveListenerBus to the same class LiveListenerBus 4. Add `logEvent` method to SparkListenerEvent so that EventLoggingListener can use it to ignore WrappedStreamingListenerEvents Author: Shixiong Zhu <shixiong@databricks.com> Closes #10779 from zsxwing/streaming-listener.
* [BUILD] Runner for spark packagesMichael Armbrust2016-01-191-0/+15
| | | | | | | | | | | | | | This is a convenience method added to the SBT build for developers, though if people think its useful we could consider adding a official script that runs using the assembly instead of compiling on demand. It simply compiles spark (without requiring an assembly), and invokes Spark Submit to download / run the package. Example Usage: ``` $ build/sbt > sparkPackage com.databricks:spark-sql-perf_2.10:0.2.4 com.databricks.spark.sql.perf.RunBenchmark --help ``` Author: Michael Armbrust <michael@databricks.com> Closes #10834 from marmbrus/sparkPackageRunner.
* [SPARK-12855][SQL] Remove parser dialect developer APIReynold Xin2016-01-181-1/+3
| | | | | | | | This pull request removes the public developer parser API for external parsers. Given everything a parser depends on (e.g. logical plans and expressions) are internal and not stable, external parsers will break with every release of Spark. It is a bad idea to create the illusion that Spark actually supports pluggable parsers. In addition, this also reduces incentives for 3rd party projects to contribute parse improvements back to Spark. Author: Reynold Xin <rxin@databricks.com> Closes #10801 from rxin/SPARK-12855.
* [SPARK-12667] Remove block manager's internal "external block store" APIReynold Xin2016-01-151-1/+5
| | | | | | | | | | This pull request removes the external block store API. This is rarely used, and the file system interface is actually a better, more standard way to interact with external storage systems. There are some other things to remove also, as pointed out by JoshRosen. We will do those as follow-up pull requests. Author: Reynold Xin <rxin@databricks.com> Closes #10752 from rxin/remove-offheap.
* [SPARK-12692][BUILD][STREAMING] Scala style: Fix the style violation (Space ↵Kousuke Saruta2016-01-111-0/+12
| | | | | | | | | | | before "," or ":") Fix the style violation (space before , and :). This PR is a followup for #10643. Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp> Closes #10685 from sarutak/SPARK-12692-followup-streaming.
* [SPARK-4628][BUILD] Add a resolver to MiMaBuild.scala for mqttv3(1.0.1).Kousuke Saruta2016-01-101-1/+6
| | | | | | | | | | | #10659 removed the repository `https://repo.eclipse.org/content/repositories/paho-releases` but it's needed by MiMa because `spark-streaming-mqtt(1.6.0)` depends on `mqttv3(1.0.1)` and it is provided by the removed repository and maven-central provide only `mqttv3(1.0.2)` for now. Otherwise, if `mqttv3(1.0.1)` is absent from the local repository, dev/mima should fail. JoshRosen Do you have any other better idea? Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp> Closes #10688 from sarutak/SPARK-4628-followup.
* [SPARK-4628][BUILD] Remove all non-Maven-Central repositories from buildJosh Rosen2016-01-082-7/+6
| | | | | | | | | | | | | | | | | | | | | | This patch removes all non-Maven-central repositories from Spark's build, thereby avoiding any risk of future build-breaks due to us accidentally depending on an artifact which is not present in an immutable public Maven repository. I tested this by running ``` build/mvn \ -Phive \ -Phive-thriftserver \ -Pkinesis-asl \ -Pspark-ganglia-lgpl \ -Pyarn \ dependency:go-offline ``` inside of a fresh Ubuntu Docker container with no Ivy or Maven caches (I did a similar test for SBT). Author: Josh Rosen <joshrosen@databricks.com> Closes #10659 from JoshRosen/SPARK-4628.
* [SPARK-4819] Remove Guava's "Optional" from public APISean Owen2016-01-081-1/+10
| | | | | | | | | | Replace Guava `Optional` with (an API clone of) Java 8 `java.util.Optional` (edit: and a clone of Guava `Optional`) See also https://github.com/apache/spark/pull/10512 Author: Sean Owen <sowen@cloudera.com> Closes #10513 from srowen/SPARK-4819.
* [SPARK-12591][STREAMING] Register OpenHashMapBasedStateMap for KryoShixiong Zhu2016-01-071-0/+4
| | | | | | | | The default serializer in Kryo is FieldSerializer and it ignores transient fields and never calls `writeObject` or `readObject`. So we should register OpenHashMapBasedStateMap using `DefaultSerializer` to make it work with Kryo. Author: Shixiong Zhu <shixiong@databricks.com> Closes #10609 from zsxwing/SPARK-12591.
* [SPARK-12510][STREAMING] Refactor ActorReceiver to support JavaShixiong Zhu2016-01-071-0/+3
| | | | | | | | | | | | | This PR includes the following changes: 1. Rename `ActorReceiver` to `ActorReceiverSupervisor` 2. Remove `ActorHelper` 3. Add a new `ActorReceiver` for Scala and `JavaActorReceiver` for Java 4. Add `JavaActorWordCount` example Author: Shixiong Zhu <shixiong@databricks.com> Closes #10457 from zsxwing/java-actor-stream.
* [SPARK-12573][SPARK-12574][SQL] Move SQL Parser from Hive to CatalystHerman van Hovell2016-01-061-48/+56
| | | | | | | | | | | | | | | | | This PR moves a major part of the new SQL parser to Catalyst. This is a prelude to start using this parser for all of our SQL parsing. The following key changes have been made: The ANTLR Parser & Supporting classes have been moved to the Catalyst project. They are now part of the ```org.apache.spark.sql.catalyst.parser``` package. These classes contained quite a bit of code that was originally from the Hive project, I have added aknowledgements whenever this applied. All Hive dependencies have been factored out. I have also taken this chance to clean-up the ```ASTNode``` class, and to improve the error handling. The HiveQl object that provides the functionality to convert an AST into a LogicalPlan has been refactored into three different classes, one for every SQL sub-project: - ```CatalystQl```: This implements Query and Expression parsing functionality. - ```SparkQl```: This is a subclass of CatalystQL and provides SQL/Core only functionality such as Explain and Describe. - ```HiveQl```: This is a subclass of ```SparkQl``` and this adds Hive-only functionality to the parser such as Analyze, Drop, Views, CTAS & Transforms. This class still depends on Hive. cc rxin Author: Herman van Hovell <hvanhovell@questtec.nl> Closes #10583 from hvanhovell/SPARK-12575.
* [SPARK-12665][CORE][GRAPHX] Remove Vector, VectorSuite and ↵Kousuke Saruta2016-01-061-0/+7
| | | | | | | | | | GraphKryoRegistrator which are deprecated and no longer used Whole code of Vector.scala, VectorSuite.scala and GraphKryoRegistrator.scala are no longer used so it's time to remove them in Spark 2.0. Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp> Closes #10613 from sarutak/SPARK-12665.
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