spark-instrumented-optimizer/core/pom.xml

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<?xml version="1.0" encoding="UTF-8"?>
<!--
~ Licensed to the Apache Software Foundation (ASF) under one or more
~ contributor license agreements. See the NOTICE file distributed with
~ this work for additional information regarding copyright ownership.
~ The ASF licenses this file to You under the Apache License, Version 2.0
~ (the "License"); you may not use this file except in compliance with
~ the License. You may obtain a copy of the License at
~
~ http://www.apache.org/licenses/LICENSE-2.0
~
~ Unless required by applicable law or agreed to in writing, software
~ distributed under the License is distributed on an "AS IS" BASIS,
~ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
~ See the License for the specific language governing permissions and
~ limitations under the License.
-->
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<parent>
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<groupId>org.apache.spark</groupId>
<artifactId>spark-parent</artifactId>
<version>1.2.0-SNAPSHOT</version>
<relativePath>../pom.xml</relativePath>
</parent>
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<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.10</artifactId>
[SPARK-1776] Have Spark's SBT build read dependencies from Maven. Patch introduces the new way of working also retaining the existing ways of doing things. For example build instruction for yarn in maven is `mvn -Pyarn -PHadoop2.2 clean package -DskipTests` in sbt it can become `MAVEN_PROFILES="yarn, hadoop-2.2" sbt/sbt clean assembly` Also supports `sbt/sbt -Pyarn -Phadoop-2.2 -Dhadoop.version=2.2.0 clean assembly` Author: Prashant Sharma <prashant.s@imaginea.com> Author: Patrick Wendell <pwendell@gmail.com> Closes #772 from ScrapCodes/sbt-maven and squashes the following commits: a8ac951 [Prashant Sharma] Updated sbt version. 62b09bb [Prashant Sharma] Improvements. fa6221d [Prashant Sharma] Excluding sql from mima 4b8875e [Prashant Sharma] Sbt assembly no longer builds tools by default. 72651ca [Prashant Sharma] Addresses code reivew comments. acab73d [Prashant Sharma] Revert "Small fix to run-examples script." ac4312c [Prashant Sharma] Revert "minor fix" 6af91ac [Prashant Sharma] Ported oldDeps back. + fixes issues with prev commit. 65cf06c [Prashant Sharma] Servelet API jars mess up with the other servlet jars on the class path. 446768e [Prashant Sharma] minor fix 89b9777 [Prashant Sharma] Merge conflicts d0a02f2 [Prashant Sharma] Bumped up pom versions, Since the build now depends on pom it is better updated there. + general cleanups. dccc8ac [Prashant Sharma] updated mima to check against 1.0 a49c61b [Prashant Sharma] Fix for tools jar a2f5ae1 [Prashant Sharma] Fixes a bug in dependencies. cf88758 [Prashant Sharma] cleanup 9439ea3 [Prashant Sharma] Small fix to run-examples script. 96cea1f [Prashant Sharma] SPARK-1776 Have Spark's SBT build read dependencies from Maven. 36efa62 [Patrick Wendell] Set project name in pom files and added eclipse/intellij plugins. 4973dbd [Patrick Wendell] Example build using pom reader.
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<properties>
<sbt.project.name>core</sbt.project.name>
[SPARK-1776] Have Spark's SBT build read dependencies from Maven. Patch introduces the new way of working also retaining the existing ways of doing things. For example build instruction for yarn in maven is `mvn -Pyarn -PHadoop2.2 clean package -DskipTests` in sbt it can become `MAVEN_PROFILES="yarn, hadoop-2.2" sbt/sbt clean assembly` Also supports `sbt/sbt -Pyarn -Phadoop-2.2 -Dhadoop.version=2.2.0 clean assembly` Author: Prashant Sharma <prashant.s@imaginea.com> Author: Patrick Wendell <pwendell@gmail.com> Closes #772 from ScrapCodes/sbt-maven and squashes the following commits: a8ac951 [Prashant Sharma] Updated sbt version. 62b09bb [Prashant Sharma] Improvements. fa6221d [Prashant Sharma] Excluding sql from mima 4b8875e [Prashant Sharma] Sbt assembly no longer builds tools by default. 72651ca [Prashant Sharma] Addresses code reivew comments. acab73d [Prashant Sharma] Revert "Small fix to run-examples script." ac4312c [Prashant Sharma] Revert "minor fix" 6af91ac [Prashant Sharma] Ported oldDeps back. + fixes issues with prev commit. 65cf06c [Prashant Sharma] Servelet API jars mess up with the other servlet jars on the class path. 446768e [Prashant Sharma] minor fix 89b9777 [Prashant Sharma] Merge conflicts d0a02f2 [Prashant Sharma] Bumped up pom versions, Since the build now depends on pom it is better updated there. + general cleanups. dccc8ac [Prashant Sharma] updated mima to check against 1.0 a49c61b [Prashant Sharma] Fix for tools jar a2f5ae1 [Prashant Sharma] Fixes a bug in dependencies. cf88758 [Prashant Sharma] cleanup 9439ea3 [Prashant Sharma] Small fix to run-examples script. 96cea1f [Prashant Sharma] SPARK-1776 Have Spark's SBT build read dependencies from Maven. 36efa62 [Patrick Wendell] Set project name in pom files and added eclipse/intellij plugins. 4973dbd [Patrick Wendell] Example build using pom reader.
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</properties>
<packaging>jar</packaging>
<name>Spark Project Core</name>
<url>http://spark.apache.org/</url>
<dependencies>
<dependency>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-client</artifactId>
<exclusions>
<exclusion>
<groupId>javax.servlet</groupId>
<artifactId>servlet-api</artifactId>
</exclusion>
</exclusions>
</dependency>
[SPARK-3453] Netty-based BlockTransferService, extracted from Spark core This PR encapsulates #2330, which is itself a continuation of #2240. The first goal of this PR is to provide an alternate, simpler implementation of the ConnectionManager which is based on Netty. In addition to this goal, however, we want to resolve [SPARK-3796](https://issues.apache.org/jira/browse/SPARK-3796), which calls for a standalone shuffle service which can be integrated into the YARN NodeManager, Standalone Worker, or on its own. This PR makes the first step in this direction by ensuring that the actual Netty service is as small as possible and extracted from Spark core. Given this, we should be able to construct this standalone jar which can be included in other JVMs without incurring significant dependency or runtime issues. The actual work to ensure that such a standalone shuffle service would work in Spark will be left for a future PR, however. In order to minimize dependencies and allow for the service to be long-running (possibly much longer-running than Spark, and possibly having to support multiple version of Spark simultaneously), the entire service has been ported to Java, where we have full control over the binary compatibility of the components and do not depend on the Scala runtime or version. These issues: have been addressed by folding in #2330: SPARK-3453: Refactor Netty module to use BlockTransferService interface SPARK-3018: Release all buffers upon task completion/failure SPARK-3002: Create a connection pool and reuse clients across different threads SPARK-3017: Integration tests and unit tests for connection failures SPARK-3049: Make sure client doesn't block when server/connection has error(s) SPARK-3502: SO_RCVBUF and SO_SNDBUF should be bootstrap childOption, not option SPARK-3503: Disable thread local cache in PooledByteBufAllocator TODO before mergeable: - [x] Implement uploadBlock() - [x] Unit tests for RPC side of code - [x] Performance testing (see comments [here](https://github.com/apache/spark/pull/2753#issuecomment-59475022)) - [x] Turn OFF by default (currently on for unit testing) Author: Reynold Xin <rxin@apache.org> Author: Aaron Davidson <aaron@databricks.com> Author: cocoatomo <cocoatomo77@gmail.com> Author: Patrick Wendell <pwendell@gmail.com> Author: Prashant Sharma <prashant.s@imaginea.com> Author: Davies Liu <davies.liu@gmail.com> Author: Anand Avati <avati@redhat.com> Closes #2753 from aarondav/netty and squashes the following commits: cadfd28 [Aaron Davidson] Turn netty off by default d7be11b [Aaron Davidson] Turn netty on by default 4a204b8 [Aaron Davidson] Fail block fetches if client connection fails 2b0d1c0 [Aaron Davidson] 100ch 0c5bca2 [Aaron Davidson] Merge branch 'master' of https://github.com/apache/spark into netty 14e37f7 [Aaron Davidson] Address Reynold's comments 8dfcceb [Aaron Davidson] Merge branch 'master' of https://github.com/apache/spark into netty 322dfc1 [Aaron Davidson] Address Reynold's comments, including major rename e5675a4 [Aaron Davidson] Fail outstanding RPCs as well ccd4959 [Aaron Davidson] Don't throw exception if client immediately fails 9da0bc1 [Aaron Davidson] Add RPC unit tests d236dfd [Aaron Davidson] Remove no-op serializer :) 7b7a26c [Aaron Davidson] Fix Nio compile issue dd420fd [Aaron Davidson] Merge branch 'master' of https://github.com/apache/spark into netty-test 939f276 [Aaron Davidson] Attempt to make comm. bidirectional aa58f67 [cocoatomo] [SPARK-3909][PySpark][Doc] A corrupted format in Sphinx documents and building warnings 8dc1ded [cocoatomo] [SPARK-3867][PySpark] ./python/run-tests failed when it run with Python 2.6 and unittest2 is not installed 5b5dbe6 [Prashant Sharma] [SPARK-2924] Required by scala 2.11, only one fun/ctor amongst overriden alternatives, can have default argument(s). 2c5d9dc [Patrick Wendell] HOTFIX: Fix build issue with Akka 2.3.4 upgrade. 020691e [Davies Liu] [SPARK-3886] [PySpark] use AutoBatchedSerializer by default ae4083a [Anand Avati] [SPARK-2805] Upgrade Akka to 2.3.4 29c6dcf [Aaron Davidson] [SPARK-3453] Netty-based BlockTransferService, extracted from Spark core f7e7568 [Reynold Xin] Fixed spark.shuffle.io.receiveBuffer setting. 5d98ce3 [Reynold Xin] Flip buffer. f6c220d [Reynold Xin] Merge with latest master. 407e59a [Reynold Xin] Fix style violation. a0518c7 [Reynold Xin] Implemented block uploads. 4b18db2 [Reynold Xin] Copy the buffer in fetchBlockSync. bec4ea2 [Reynold Xin] Removed OIO and added num threads settings. 1bdd7ee [Reynold Xin] Fixed tests. d68f328 [Reynold Xin] Logging close() in case close() fails. f63fb4c [Reynold Xin] Add more debug message. 6afc435 [Reynold Xin] Added logging. c066309 [Reynold Xin] Implement java.io.Closeable interface. 519d64d [Reynold Xin] Mark private package visibility and MimaExcludes. f0a16e9 [Reynold Xin] Fixed test hanging. 14323a5 [Reynold Xin] Removed BlockManager.getLocalShuffleFromDisk. b2f3281 [Reynold Xin] Added connection pooling. d23ed7b [Reynold Xin] Incorporated feedback from Norman: - use same pool for boss and worker - remove ioratio - disable caching of byte buf allocator - childoption sendbuf/receivebuf - fire exception through pipeline 9e0cb87 [Reynold Xin] Fixed BlockClientHandlerSuite 5cd33d7 [Reynold Xin] Fixed style violation. cb589ec [Reynold Xin] Added more test cases covering cleanup when fault happens in ShuffleBlockFetcherIteratorSuite 1be4e8e [Reynold Xin] Shorten NioManagedBuffer and NettyManagedBuffer class names. 108c9ed [Reynold Xin] Forgot to add TestSerializer to the commit list. b5c8d1f [Reynold Xin] Fixed ShuffleBlockFetcherIteratorSuite. 064747b [Reynold Xin] Reference count buffers and clean them up properly. 2b44cf1 [Reynold Xin] Added more documentation. 1760d32 [Reynold Xin] Use Epoll.isAvailable in BlockServer as well. 165eab1 [Reynold Xin] [SPARK-3453] Refactor Netty module to use BlockTransferService.
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<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-network-common_2.10</artifactId>
[SPARK-3453] Netty-based BlockTransferService, extracted from Spark core This PR encapsulates #2330, which is itself a continuation of #2240. The first goal of this PR is to provide an alternate, simpler implementation of the ConnectionManager which is based on Netty. In addition to this goal, however, we want to resolve [SPARK-3796](https://issues.apache.org/jira/browse/SPARK-3796), which calls for a standalone shuffle service which can be integrated into the YARN NodeManager, Standalone Worker, or on its own. This PR makes the first step in this direction by ensuring that the actual Netty service is as small as possible and extracted from Spark core. Given this, we should be able to construct this standalone jar which can be included in other JVMs without incurring significant dependency or runtime issues. The actual work to ensure that such a standalone shuffle service would work in Spark will be left for a future PR, however. In order to minimize dependencies and allow for the service to be long-running (possibly much longer-running than Spark, and possibly having to support multiple version of Spark simultaneously), the entire service has been ported to Java, where we have full control over the binary compatibility of the components and do not depend on the Scala runtime or version. These issues: have been addressed by folding in #2330: SPARK-3453: Refactor Netty module to use BlockTransferService interface SPARK-3018: Release all buffers upon task completion/failure SPARK-3002: Create a connection pool and reuse clients across different threads SPARK-3017: Integration tests and unit tests for connection failures SPARK-3049: Make sure client doesn't block when server/connection has error(s) SPARK-3502: SO_RCVBUF and SO_SNDBUF should be bootstrap childOption, not option SPARK-3503: Disable thread local cache in PooledByteBufAllocator TODO before mergeable: - [x] Implement uploadBlock() - [x] Unit tests for RPC side of code - [x] Performance testing (see comments [here](https://github.com/apache/spark/pull/2753#issuecomment-59475022)) - [x] Turn OFF by default (currently on for unit testing) Author: Reynold Xin <rxin@apache.org> Author: Aaron Davidson <aaron@databricks.com> Author: cocoatomo <cocoatomo77@gmail.com> Author: Patrick Wendell <pwendell@gmail.com> Author: Prashant Sharma <prashant.s@imaginea.com> Author: Davies Liu <davies.liu@gmail.com> Author: Anand Avati <avati@redhat.com> Closes #2753 from aarondav/netty and squashes the following commits: cadfd28 [Aaron Davidson] Turn netty off by default d7be11b [Aaron Davidson] Turn netty on by default 4a204b8 [Aaron Davidson] Fail block fetches if client connection fails 2b0d1c0 [Aaron Davidson] 100ch 0c5bca2 [Aaron Davidson] Merge branch 'master' of https://github.com/apache/spark into netty 14e37f7 [Aaron Davidson] Address Reynold's comments 8dfcceb [Aaron Davidson] Merge branch 'master' of https://github.com/apache/spark into netty 322dfc1 [Aaron Davidson] Address Reynold's comments, including major rename e5675a4 [Aaron Davidson] Fail outstanding RPCs as well ccd4959 [Aaron Davidson] Don't throw exception if client immediately fails 9da0bc1 [Aaron Davidson] Add RPC unit tests d236dfd [Aaron Davidson] Remove no-op serializer :) 7b7a26c [Aaron Davidson] Fix Nio compile issue dd420fd [Aaron Davidson] Merge branch 'master' of https://github.com/apache/spark into netty-test 939f276 [Aaron Davidson] Attempt to make comm. bidirectional aa58f67 [cocoatomo] [SPARK-3909][PySpark][Doc] A corrupted format in Sphinx documents and building warnings 8dc1ded [cocoatomo] [SPARK-3867][PySpark] ./python/run-tests failed when it run with Python 2.6 and unittest2 is not installed 5b5dbe6 [Prashant Sharma] [SPARK-2924] Required by scala 2.11, only one fun/ctor amongst overriden alternatives, can have default argument(s). 2c5d9dc [Patrick Wendell] HOTFIX: Fix build issue with Akka 2.3.4 upgrade. 020691e [Davies Liu] [SPARK-3886] [PySpark] use AutoBatchedSerializer by default ae4083a [Anand Avati] [SPARK-2805] Upgrade Akka to 2.3.4 29c6dcf [Aaron Davidson] [SPARK-3453] Netty-based BlockTransferService, extracted from Spark core f7e7568 [Reynold Xin] Fixed spark.shuffle.io.receiveBuffer setting. 5d98ce3 [Reynold Xin] Flip buffer. f6c220d [Reynold Xin] Merge with latest master. 407e59a [Reynold Xin] Fix style violation. a0518c7 [Reynold Xin] Implemented block uploads. 4b18db2 [Reynold Xin] Copy the buffer in fetchBlockSync. bec4ea2 [Reynold Xin] Removed OIO and added num threads settings. 1bdd7ee [Reynold Xin] Fixed tests. d68f328 [Reynold Xin] Logging close() in case close() fails. f63fb4c [Reynold Xin] Add more debug message. 6afc435 [Reynold Xin] Added logging. c066309 [Reynold Xin] Implement java.io.Closeable interface. 519d64d [Reynold Xin] Mark private package visibility and MimaExcludes. f0a16e9 [Reynold Xin] Fixed test hanging. 14323a5 [Reynold Xin] Removed BlockManager.getLocalShuffleFromDisk. b2f3281 [Reynold Xin] Added connection pooling. d23ed7b [Reynold Xin] Incorporated feedback from Norman: - use same pool for boss and worker - remove ioratio - disable caching of byte buf allocator - childoption sendbuf/receivebuf - fire exception through pipeline 9e0cb87 [Reynold Xin] Fixed BlockClientHandlerSuite 5cd33d7 [Reynold Xin] Fixed style violation. cb589ec [Reynold Xin] Added more test cases covering cleanup when fault happens in ShuffleBlockFetcherIteratorSuite 1be4e8e [Reynold Xin] Shorten NioManagedBuffer and NettyManagedBuffer class names. 108c9ed [Reynold Xin] Forgot to add TestSerializer to the commit list. b5c8d1f [Reynold Xin] Fixed ShuffleBlockFetcherIteratorSuite. 064747b [Reynold Xin] Reference count buffers and clean them up properly. 2b44cf1 [Reynold Xin] Added more documentation. 1760d32 [Reynold Xin] Use Epoll.isAvailable in BlockServer as well. 165eab1 [Reynold Xin] [SPARK-3453] Refactor Netty module to use BlockTransferService.
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<version>${project.version}</version>
</dependency>
<dependency>
<groupId>net.java.dev.jets3t</groupId>
<artifactId>jets3t</artifactId>
</dependency>
<dependency>
<groupId>org.apache.curator</groupId>
<artifactId>curator-recipes</artifactId>
</dependency>
<dependency>
<groupId>org.eclipse.jetty</groupId>
<artifactId>jetty-plus</artifactId>
</dependency>
<dependency>
<groupId>org.eclipse.jetty</groupId>
<artifactId>jetty-security</artifactId>
</dependency>
<dependency>
<groupId>org.eclipse.jetty</groupId>
<artifactId>jetty-util</artifactId>
</dependency>
<dependency>
<groupId>org.eclipse.jetty</groupId>
<artifactId>jetty-server</artifactId>
</dependency>
[SPARK-2848] Shade Guava in uber-jars. For further discussion, please check the JIRA entry. This change moves Guava classes to a different package so that they don't conflict with the user-provided Guava (or the Hadoop-provided one). Since one class (Optional) was exposed through Spark's public API, that class was forked from Guava at the current dependency version (14.0.1) so that it can be kept going forward (until the API is cleaned). Note this change has a few implications: - *all* classes in the final jars will reference the relocated classes. If Hadoop classes are included (i.e. "-Phadoop-provided" is not activated), those will also reference the Guava 14 classes (instead of the Guava 11 classes from the Hadoop classpath). - if the Guava version in Spark is ever changed, the new Guava will still reference the forked Optional class; this may or may not be a problem, but in the long term it's better to think about removing Optional from the public API. For the end user, there are two visible implications: - Guava is not provided as a transitive dependency anymore (since it's "provided" in Spark) - At runtime, unless they provide their own, they'll either have no Guava or Hadoop's version of Guava (11), depending on how they set up their classpath. Note that this patch does not change the sbt deliverables; those will still contain guava in its original package, and provide guava as a compile-time dependency. This assumes that maven is the canonical build, and sbt-built artifacts are not (officially) published. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #1813 from vanzin/SPARK-2848 and squashes the following commits: 9bdffb0 [Marcelo Vanzin] Undo sbt build changes. 819b445 [Marcelo Vanzin] Review feedback. 05e0a3d [Marcelo Vanzin] Merge branch 'master' into SPARK-2848 fef4370 [Marcelo Vanzin] Unfork Optional.java. d3ea8e1 [Marcelo Vanzin] Exclude asm classes from final jar. 637189b [Marcelo Vanzin] Add hacky filter to prefer Spark's copy of Optional. 2fec990 [Marcelo Vanzin] Shade Guava in the sbt build. 616998e [Marcelo Vanzin] Shade Guava in the maven build, fork Guava's Optional.java.
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<!--
Promote Guava to "compile" so that maven-shade-plugin picks it up (for packaging the Optional
class exposed in the Java API). The plugin will then remove this dependency from the published
pom, so that Guava does not pollute the client's compilation classpath.
-->
<dependency>
<groupId>com.google.guava</groupId>
<artifactId>guava</artifactId>
[SPARK-2848] Shade Guava in uber-jars. For further discussion, please check the JIRA entry. This change moves Guava classes to a different package so that they don't conflict with the user-provided Guava (or the Hadoop-provided one). Since one class (Optional) was exposed through Spark's public API, that class was forked from Guava at the current dependency version (14.0.1) so that it can be kept going forward (until the API is cleaned). Note this change has a few implications: - *all* classes in the final jars will reference the relocated classes. If Hadoop classes are included (i.e. "-Phadoop-provided" is not activated), those will also reference the Guava 14 classes (instead of the Guava 11 classes from the Hadoop classpath). - if the Guava version in Spark is ever changed, the new Guava will still reference the forked Optional class; this may or may not be a problem, but in the long term it's better to think about removing Optional from the public API. For the end user, there are two visible implications: - Guava is not provided as a transitive dependency anymore (since it's "provided" in Spark) - At runtime, unless they provide their own, they'll either have no Guava or Hadoop's version of Guava (11), depending on how they set up their classpath. Note that this patch does not change the sbt deliverables; those will still contain guava in its original package, and provide guava as a compile-time dependency. This assumes that maven is the canonical build, and sbt-built artifacts are not (officially) published. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #1813 from vanzin/SPARK-2848 and squashes the following commits: 9bdffb0 [Marcelo Vanzin] Undo sbt build changes. 819b445 [Marcelo Vanzin] Review feedback. 05e0a3d [Marcelo Vanzin] Merge branch 'master' into SPARK-2848 fef4370 [Marcelo Vanzin] Unfork Optional.java. d3ea8e1 [Marcelo Vanzin] Exclude asm classes from final jar. 637189b [Marcelo Vanzin] Add hacky filter to prefer Spark's copy of Optional. 2fec990 [Marcelo Vanzin] Shade Guava in the sbt build. 616998e [Marcelo Vanzin] Shade Guava in the maven build, fork Guava's Optional.java.
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<scope>compile</scope>
</dependency>
<dependency>
<groupId>org.apache.commons</groupId>
<artifactId>commons-lang3</artifactId>
</dependency>
SPARK-1939 Refactor takeSample method in RDD to use ScaSRS Modified the takeSample method in RDD to use the ScaSRS sampling technique to improve performance. Added a private method that computes sampling rate > sample_size/total to ensure sufficient sample size with success rate >= 0.9999. Added a unit test for the private method to validate choice of sampling rate. Author: Doris Xin <doris.s.xin@gmail.com> Author: dorx <doris.s.xin@gmail.com> Author: Xiangrui Meng <meng@databricks.com> Closes #916 from dorx/takeSample and squashes the following commits: 5b061ae [Doris Xin] merge master 444e750 [Doris Xin] edge cases 3de882b [dorx] Merge pull request #2 from mengxr/SPARK-1939 82dde31 [Xiangrui Meng] update pyspark's takeSample 48d954d [Doris Xin] remove unused imports from RDDSuite fb1452f [Doris Xin] allowing num to be greater than count in all cases 1481b01 [Doris Xin] washing test tubes and making coffee dc699f3 [Doris Xin] give back imports removed by accident in rdd.py 64e445b [Doris Xin] logwarnning as soon as it enters the while loop 55518ed [Doris Xin] added TODO for logging in rdd.py eff89e2 [Doris Xin] addressed reviewer comments. ecab508 [Doris Xin] "fixed checkstyle violation 0a9b3e3 [Doris Xin] "reviewer comment addressed" f80f270 [Doris Xin] Merge branch 'master' into takeSample ae3ad04 [Doris Xin] fixed edge cases to prevent overflow 065ebcd [Doris Xin] Merge branch 'master' into takeSample 9bdd36e [Doris Xin] Check sample size and move computeFraction e3fd6a6 [Doris Xin] Merge branch 'master' into takeSample 7cab53a [Doris Xin] fixed import bug in rdd.py ffea61a [Doris Xin] SPARK-1939: Refactor takeSample method in RDD 1441977 [Doris Xin] SPARK-1939 Refactor takeSample method in RDD to use ScaSRS
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<dependency>
<groupId>org.apache.commons</groupId>
<artifactId>commons-math3</artifactId>
</dependency>
<dependency>
<groupId>com.google.code.findbugs</groupId>
<artifactId>jsr305</artifactId>
</dependency>
<dependency>
<groupId>org.slf4j</groupId>
<artifactId>slf4j-api</artifactId>
</dependency>
<dependency>
<groupId>org.slf4j</groupId>
<artifactId>jul-to-slf4j</artifactId>
</dependency>
<dependency>
<groupId>org.slf4j</groupId>
<artifactId>jcl-over-slf4j</artifactId>
</dependency>
<dependency>
<groupId>log4j</groupId>
<artifactId>log4j</artifactId>
</dependency>
<dependency>
<groupId>org.slf4j</groupId>
<artifactId>slf4j-log4j12</artifactId>
</dependency>
<dependency>
<groupId>com.ning</groupId>
<artifactId>compress-lzf</artifactId>
</dependency>
<dependency>
<groupId>org.xerial.snappy</groupId>
<artifactId>snappy-java</artifactId>
</dependency>
<dependency>
<groupId>net.jpountz.lz4</groupId>
<artifactId>lz4</artifactId>
</dependency>
<dependency>
<groupId>com.twitter</groupId>
<artifactId>chill_${scala.binary.version}</artifactId>
</dependency>
<dependency>
<groupId>com.twitter</groupId>
<artifactId>chill-java</artifactId>
</dependency>
[SPARK-4019] [SPARK-3740] Fix MapStatus compression bug that could lead to empty results or Snappy errors This commit fixes a bug in MapStatus that could cause jobs to wrongly return empty results if those jobs contained stages with more than 2000 partitions where most of those partitions were empty. For jobs with > 2000 partitions, MapStatus uses HighlyCompressedMapStatus, which only stores the average size of blocks. If the average block size is zero, then this will cause all blocks to be reported as empty, causing BlockFetcherIterator to mistakenly skip them. For example, this would return an empty result: sc.makeRDD(0 until 10, 1000).repartition(2001).collect() This can also lead to deserialization errors (e.g. Snappy decoding errors) for jobs with > 2000 partitions where the average block size is non-zero but there is at least one empty block. In this case, the BlockFetcher attempts to fetch empty blocks and fails when trying to deserialize them. The root problem here is that MapStatus has a (previously undocumented) correctness property that was violated by HighlyCompressedMapStatus: If a block is non-empty, then getSizeForBlock must be non-zero. I fixed this by modifying HighlyCompressedMapStatus to store the average size of _non-empty_ blocks and to use a compressed bitmap to track which blocks are empty. I also removed a test which was broken as originally written: it attempted to check that HighlyCompressedMapStatus's size estimation error was < 10%, but this was broken because HighlyCompressedMapStatus is only used for map statuses with > 2000 partitions, but the test only created 50. Author: Josh Rosen <joshrosen@databricks.com> Closes #2866 from JoshRosen/spark-4019 and squashes the following commits: fc8b490 [Josh Rosen] Roll back hashset change, which didn't improve performance. 5faa0a4 [Josh Rosen] Incorporate review feedback c8b8cae [Josh Rosen] Two performance fixes: 3b892dd [Josh Rosen] Address Reynold's review comments ba2e71c [Josh Rosen] Add missing newline 609407d [Josh Rosen] Use Roaring Bitmap to track non-empty blocks. c23897a [Josh Rosen] Use sets when comparing collect() results 91276a3 [Josh Rosen] [SPARK-4019] Fix MapStatus compression bug that could lead to empty results.
2014-10-23 19:39:32 -04:00
<dependency>
<groupId>org.roaringbitmap</groupId>
<artifactId>RoaringBitmap</artifactId>
</dependency>
<dependency>
<groupId>commons-net</groupId>
<artifactId>commons-net</artifactId>
</dependency>
<dependency>
<groupId>${akka.group}</groupId>
<artifactId>akka-remote_${scala.binary.version}</artifactId>
</dependency>
<dependency>
<groupId>${akka.group}</groupId>
<artifactId>akka-slf4j_${scala.binary.version}</artifactId>
</dependency>
<dependency>
<groupId>${akka.group}</groupId>
<artifactId>akka-testkit_${scala.binary.version}</artifactId>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.scala-lang</groupId>
<artifactId>scala-library</artifactId>
</dependency>
<dependency>
<groupId>org.json4s</groupId>
<artifactId>json4s-jackson_${scala.binary.version}</artifactId>
<version>3.2.10</version>
</dependency>
<dependency>
<groupId>org.apache.mesos</groupId>
<artifactId>mesos</artifactId>
<classifier>${mesos.classifier}</classifier>
</dependency>
<dependency>
<groupId>io.netty</groupId>
<artifactId>netty-all</artifactId>
</dependency>
<dependency>
<groupId>com.clearspring.analytics</groupId>
<artifactId>stream</artifactId>
</dependency>
<dependency>
<groupId>com.codahale.metrics</groupId>
<artifactId>metrics-core</artifactId>
</dependency>
<dependency>
<groupId>com.codahale.metrics</groupId>
<artifactId>metrics-jvm</artifactId>
</dependency>
<dependency>
<groupId>com.codahale.metrics</groupId>
<artifactId>metrics-json</artifactId>
</dependency>
<dependency>
<groupId>com.codahale.metrics</groupId>
<artifactId>metrics-graphite</artifactId>
</dependency>
<dependency>
<groupId>org.apache.derby</groupId>
<artifactId>derby</artifactId>
<scope>test</scope>
</dependency>
SPARK-1305: Support persisting RDD's directly to Tachyon Move the PR#468 of apache-incubator-spark to the apache-spark "Adding an option to persist Spark RDD blocks into Tachyon." Author: Haoyuan Li <haoyuan@cs.berkeley.edu> Author: RongGu <gurongwalker@gmail.com> Closes #158 from RongGu/master and squashes the following commits: 72b7768 [Haoyuan Li] merge master 9f7fa1b [Haoyuan Li] fix code style ae7834b [Haoyuan Li] minor cleanup a8b3ec6 [Haoyuan Li] merge master branch e0f4891 [Haoyuan Li] better check offheap. 55b5918 [RongGu] address matei's comment on the replication of offHeap storagelevel 7cd4600 [RongGu] remove some logic code for tachyonstore's replication 51149e7 [RongGu] address aaron's comment on returning value of the remove() function in tachyonstore 8adfcfa [RongGu] address arron's comment on inTachyonSize 120e48a [RongGu] changed the root-level dir name in Tachyon 5cc041c [Haoyuan Li] address aaron's comments 9b97935 [Haoyuan Li] address aaron's comments d9a6438 [Haoyuan Li] fix for pspark 77d2703 [Haoyuan Li] change python api.git status 3dcace4 [Haoyuan Li] address matei's comments 91fa09d [Haoyuan Li] address patrick's comments 589eafe [Haoyuan Li] use TRY_CACHE instead of MUST_CACHE 64348b2 [Haoyuan Li] update conf docs. ed73e19 [Haoyuan Li] Merge branch 'master' of github.com:RongGu/spark-1 619a9a8 [RongGu] set number of directories in TachyonStore back to 64; added a TODO tag for duplicated code from the DiskStore be79d77 [RongGu] find a way to clean up some unnecessay metods and classed to make the code simpler 49cc724 [Haoyuan Li] update docs with off_headp option 4572f9f [RongGu] reserving the old apply function API of StorageLevel 04301d3 [RongGu] rename StorageLevel.TACHYON to Storage.OFF_HEAP c9aeabf [RongGu] rename the StorgeLevel.TACHYON as StorageLevel.OFF_HEAP 76805aa [RongGu] unifies the config properties name prefix; add the configs into docs/configuration.md e700d9c [RongGu] add the SparkTachyonHdfsLR example and some comments fd84156 [RongGu] use randomUUID to generate sparkapp directory name on tachyon;minor code style fix 939e467 [Haoyuan Li] 0.4.1-thrift from maven central 86a2eab [Haoyuan Li] tachyon 0.4.1-thrift is in the staging repo. but jenkins failed to download it. temporarily revert it back to 0.4.1 16c5798 [RongGu] make the dependency on tachyon as tachyon-0.4.1-thrift eacb2e8 [RongGu] Merge branch 'master' of https://github.com/RongGu/spark-1 bbeb4de [RongGu] fix the JsonProtocolSuite test failure problem 6adb58f [RongGu] Merge branch 'master' of https://github.com/RongGu/spark-1 d827250 [RongGu] fix JsonProtocolSuie test failure 716e93b [Haoyuan Li] revert the version ca14469 [Haoyuan Li] bump tachyon version to 0.4.1-thrift 2825a13 [RongGu] up-merging to the current master branch of the apache spark 6a22c1a [Haoyuan Li] fix scalastyle 8968b67 [Haoyuan Li] exclude more libraries from tachyon dependency to be the same as referencing tachyon-client. 77be7e8 [RongGu] address mateiz's comment about the temp folder name problem. The implementation followed mateiz's advice. 1dcadf9 [Haoyuan Li] typo bf278fa [Haoyuan Li] fix python tests e82909c [Haoyuan Li] minor cleanup 776a56c [Haoyuan Li] address patrick's and ali's comments from the previous PR 8859371 [Haoyuan Li] various minor fixes and clean up e3ddbba [Haoyuan Li] add doc to use Tachyon cache mode. fcaeab2 [Haoyuan Li] address Aaron's comment e554b1e [Haoyuan Li] add python code 47304b3 [Haoyuan Li] make tachyonStore in BlockMananger lazy val; add more comments StorageLevels. dc8ef24 [Haoyuan Li] add old storelevel constructor e01a271 [Haoyuan Li] update tachyon 0.4.1 8011a96 [RongGu] fix a brought-in mistake in StorageLevel 70ca182 [RongGu] a bit change in comment 556978b [RongGu] fix the scalastyle errors 791189b [RongGu] "Adding an option to persist Spark RDD blocks into Tachyon." move the PR#468 of apache-incubator-spark to the apache-spark
2014-04-04 23:36:24 -04:00
<dependency>
<groupId>org.tachyonproject</groupId>
<artifactId>tachyon-client</artifactId>
<version>0.5.0</version>
SPARK-1305: Support persisting RDD's directly to Tachyon Move the PR#468 of apache-incubator-spark to the apache-spark "Adding an option to persist Spark RDD blocks into Tachyon." Author: Haoyuan Li <haoyuan@cs.berkeley.edu> Author: RongGu <gurongwalker@gmail.com> Closes #158 from RongGu/master and squashes the following commits: 72b7768 [Haoyuan Li] merge master 9f7fa1b [Haoyuan Li] fix code style ae7834b [Haoyuan Li] minor cleanup a8b3ec6 [Haoyuan Li] merge master branch e0f4891 [Haoyuan Li] better check offheap. 55b5918 [RongGu] address matei's comment on the replication of offHeap storagelevel 7cd4600 [RongGu] remove some logic code for tachyonstore's replication 51149e7 [RongGu] address aaron's comment on returning value of the remove() function in tachyonstore 8adfcfa [RongGu] address arron's comment on inTachyonSize 120e48a [RongGu] changed the root-level dir name in Tachyon 5cc041c [Haoyuan Li] address aaron's comments 9b97935 [Haoyuan Li] address aaron's comments d9a6438 [Haoyuan Li] fix for pspark 77d2703 [Haoyuan Li] change python api.git status 3dcace4 [Haoyuan Li] address matei's comments 91fa09d [Haoyuan Li] address patrick's comments 589eafe [Haoyuan Li] use TRY_CACHE instead of MUST_CACHE 64348b2 [Haoyuan Li] update conf docs. ed73e19 [Haoyuan Li] Merge branch 'master' of github.com:RongGu/spark-1 619a9a8 [RongGu] set number of directories in TachyonStore back to 64; added a TODO tag for duplicated code from the DiskStore be79d77 [RongGu] find a way to clean up some unnecessay metods and classed to make the code simpler 49cc724 [Haoyuan Li] update docs with off_headp option 4572f9f [RongGu] reserving the old apply function API of StorageLevel 04301d3 [RongGu] rename StorageLevel.TACHYON to Storage.OFF_HEAP c9aeabf [RongGu] rename the StorgeLevel.TACHYON as StorageLevel.OFF_HEAP 76805aa [RongGu] unifies the config properties name prefix; add the configs into docs/configuration.md e700d9c [RongGu] add the SparkTachyonHdfsLR example and some comments fd84156 [RongGu] use randomUUID to generate sparkapp directory name on tachyon;minor code style fix 939e467 [Haoyuan Li] 0.4.1-thrift from maven central 86a2eab [Haoyuan Li] tachyon 0.4.1-thrift is in the staging repo. but jenkins failed to download it. temporarily revert it back to 0.4.1 16c5798 [RongGu] make the dependency on tachyon as tachyon-0.4.1-thrift eacb2e8 [RongGu] Merge branch 'master' of https://github.com/RongGu/spark-1 bbeb4de [RongGu] fix the JsonProtocolSuite test failure problem 6adb58f [RongGu] Merge branch 'master' of https://github.com/RongGu/spark-1 d827250 [RongGu] fix JsonProtocolSuie test failure 716e93b [Haoyuan Li] revert the version ca14469 [Haoyuan Li] bump tachyon version to 0.4.1-thrift 2825a13 [RongGu] up-merging to the current master branch of the apache spark 6a22c1a [Haoyuan Li] fix scalastyle 8968b67 [Haoyuan Li] exclude more libraries from tachyon dependency to be the same as referencing tachyon-client. 77be7e8 [RongGu] address mateiz's comment about the temp folder name problem. The implementation followed mateiz's advice. 1dcadf9 [Haoyuan Li] typo bf278fa [Haoyuan Li] fix python tests e82909c [Haoyuan Li] minor cleanup 776a56c [Haoyuan Li] address patrick's and ali's comments from the previous PR 8859371 [Haoyuan Li] various minor fixes and clean up e3ddbba [Haoyuan Li] add doc to use Tachyon cache mode. fcaeab2 [Haoyuan Li] address Aaron's comment e554b1e [Haoyuan Li] add python code 47304b3 [Haoyuan Li] make tachyonStore in BlockMananger lazy val; add more comments StorageLevels. dc8ef24 [Haoyuan Li] add old storelevel constructor e01a271 [Haoyuan Li] update tachyon 0.4.1 8011a96 [RongGu] fix a brought-in mistake in StorageLevel 70ca182 [RongGu] a bit change in comment 556978b [RongGu] fix the scalastyle errors 791189b [RongGu] "Adding an option to persist Spark RDD blocks into Tachyon." move the PR#468 of apache-incubator-spark to the apache-spark
2014-04-04 23:36:24 -04:00
<exclusions>
<exclusion>
<groupId>org.apache.hadoop</groupId>
<artifactId>hadoop-client</artifactId>
</exclusion>
<exclusion>
<groupId>org.apache.curator</groupId>
<artifactId>curator-recipes</artifactId>
</exclusion>
<exclusion>
<groupId>org.eclipse.jetty</groupId>
<artifactId>jetty-jsp</artifactId>
</exclusion>
<exclusion>
<groupId>org.eclipse.jetty</groupId>
<artifactId>jetty-webapp</artifactId>
</exclusion>
<exclusion>
<groupId>org.eclipse.jetty</groupId>
<artifactId>jetty-server</artifactId>
</exclusion>
<exclusion>
<groupId>org.eclipse.jetty</groupId>
<artifactId>jetty-servlet</artifactId>
</exclusion>
<exclusion>
<groupId>junit</groupId>
<artifactId>junit</artifactId>
</exclusion>
<exclusion>
<groupId>org.powermock</groupId>
<artifactId>powermock-module-junit4</artifactId>
</exclusion>
<exclusion>
<groupId>org.powermock</groupId>
<artifactId>powermock-api-mockito</artifactId>
</exclusion>
<exclusion>
<groupId>org.apache.curator</groupId>
<artifactId>curator-test</artifactId>
</exclusion>
</exclusions>
</dependency>
<dependency>
<groupId>org.seleniumhq.selenium</groupId>
<artifactId>selenium-java</artifactId>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.scalatest</groupId>
<artifactId>scalatest_${scala.binary.version}</artifactId>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.mockito</groupId>
<artifactId>mockito-all</artifactId>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.scalacheck</groupId>
<artifactId>scalacheck_${scala.binary.version}</artifactId>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.easymock</groupId>
<artifactId>easymockclassextension</artifactId>
<scope>test</scope>
</dependency>
<dependency>
<groupId>asm</groupId>
<artifactId>asm</artifactId>
<scope>test</scope>
</dependency>
<dependency>
<groupId>junit</groupId>
<artifactId>junit</artifactId>
<scope>test</scope>
</dependency>
<dependency>
<groupId>com.novocode</groupId>
<artifactId>junit-interface</artifactId>
<scope>test</scope>
</dependency>
SPARK-1374: PySpark API for SparkSQL An initial API that exposes SparkSQL functionality in PySpark. A PythonRDD composed of dictionaries, with string keys and primitive values (boolean, float, int, long, string) can be converted into a SchemaRDD that supports sql queries. ``` from pyspark.context import SQLContext sqlCtx = SQLContext(sc) rdd = sc.parallelize([{"field1" : 1, "field2" : "row1"}, {"field1" : 2, "field2": "row2"}, {"field1" : 3, "field2": "row3"}]) srdd = sqlCtx.applySchema(rdd) sqlCtx.registerRDDAsTable(srdd, "table1") srdd2 = sqlCtx.sql("SELECT field1 AS f1, field2 as f2 from table1") srdd2.collect() ``` The last line yields ```[{"f1" : 1, "f2" : "row1"}, {"f1" : 2, "f2": "row2"}, {"f1" : 3, "f2": "row3"}]``` Author: Ahir Reddy <ahirreddy@gmail.com> Author: Michael Armbrust <michael@databricks.com> Closes #363 from ahirreddy/pysql and squashes the following commits: 0294497 [Ahir Reddy] Updated log4j properties to supress Hive Warns 307d6e0 [Ahir Reddy] Style fix 6f7b8f6 [Ahir Reddy] Temporary fix MIMA checker. Since we now assemble Spark jar with Hive, we don't want to check the interfaces of all of our hive dependencies 3ef074a [Ahir Reddy] Updated documentation because classes moved to sql.py 29245bf [Ahir Reddy] Cache underlying SchemaRDD instead of generating and caching PythonRDD f2312c7 [Ahir Reddy] Moved everything into sql.py a19afe4 [Ahir Reddy] Doc fixes 6d658ba [Ahir Reddy] Remove the metastore directory created by the HiveContext tests in SparkSQL 521ff6d [Ahir Reddy] Trying to get spark to build with hive ab95eba [Ahir Reddy] Set SPARK_HIVE=true on jenkins ded03e7 [Ahir Reddy] Added doc test for HiveContext 22de1d4 [Ahir Reddy] Fixed maven pyrolite dependency e4da06c [Ahir Reddy] Display message if hive is not built into spark 227a0be [Michael Armbrust] Update API links. Fix Hive example. 58e2aa9 [Michael Armbrust] Build Docs for pyspark SQL Api. Minor fixes. 4285340 [Michael Armbrust] Fix building of Hive API Docs. 38a92b0 [Michael Armbrust] Add note to future non-python developers about python docs. 337b201 [Ahir Reddy] Changed com.clearspring.analytics stream version from 2.4.0 to 2.5.1 to match SBT build, and added pyrolite to maven build 40491c9 [Ahir Reddy] PR Changes + Method Visibility 1836944 [Michael Armbrust] Fix comments. e00980f [Michael Armbrust] First draft of python sql programming guide. b0192d3 [Ahir Reddy] Added Long, Double and Boolean as usable types + unit test f98a422 [Ahir Reddy] HiveContexts 79621cf [Ahir Reddy] cleaning up cruft b406ba0 [Ahir Reddy] doctest formatting 20936a5 [Ahir Reddy] Added tests and documentation e4d21b4 [Ahir Reddy] Added pyrolite dependency 79f739d [Ahir Reddy] added more tests 7515ba0 [Ahir Reddy] added more tests :) d26ec5e [Ahir Reddy] added test e9f5b8d [Ahir Reddy] adding tests 906d180 [Ahir Reddy] added todo explaining cost of creating Row object in python 251f99d [Ahir Reddy] for now only allow dictionaries as input 09b9980 [Ahir Reddy] made jrdd explicitly lazy c608947 [Ahir Reddy] SchemaRDD now has all RDD operations 725c91e [Ahir Reddy] awesome row objects 55d1c76 [Ahir Reddy] return row objects 4fe1319 [Ahir Reddy] output dictionaries correctly be079de [Ahir Reddy] returning dictionaries works cd5f79f [Ahir Reddy] Switched to using Scala SQLContext e948bd9 [Ahir Reddy] yippie 4886052 [Ahir Reddy] even better c0fb1c6 [Ahir Reddy] more working 043ca85 [Ahir Reddy] working 5496f9f [Ahir Reddy] doesn't crash b8b904b [Ahir Reddy] Added schema rdd class 67ba875 [Ahir Reddy] java to python, and python to java bcc0f23 [Ahir Reddy] Java to python ab6025d [Ahir Reddy] compiling
2014-04-15 03:07:55 -04:00
<dependency>
<groupId>org.spark-project</groupId>
<artifactId>pyrolite</artifactId>
<version>2.0.1</version>
SPARK-1374: PySpark API for SparkSQL An initial API that exposes SparkSQL functionality in PySpark. A PythonRDD composed of dictionaries, with string keys and primitive values (boolean, float, int, long, string) can be converted into a SchemaRDD that supports sql queries. ``` from pyspark.context import SQLContext sqlCtx = SQLContext(sc) rdd = sc.parallelize([{"field1" : 1, "field2" : "row1"}, {"field1" : 2, "field2": "row2"}, {"field1" : 3, "field2": "row3"}]) srdd = sqlCtx.applySchema(rdd) sqlCtx.registerRDDAsTable(srdd, "table1") srdd2 = sqlCtx.sql("SELECT field1 AS f1, field2 as f2 from table1") srdd2.collect() ``` The last line yields ```[{"f1" : 1, "f2" : "row1"}, {"f1" : 2, "f2": "row2"}, {"f1" : 3, "f2": "row3"}]``` Author: Ahir Reddy <ahirreddy@gmail.com> Author: Michael Armbrust <michael@databricks.com> Closes #363 from ahirreddy/pysql and squashes the following commits: 0294497 [Ahir Reddy] Updated log4j properties to supress Hive Warns 307d6e0 [Ahir Reddy] Style fix 6f7b8f6 [Ahir Reddy] Temporary fix MIMA checker. Since we now assemble Spark jar with Hive, we don't want to check the interfaces of all of our hive dependencies 3ef074a [Ahir Reddy] Updated documentation because classes moved to sql.py 29245bf [Ahir Reddy] Cache underlying SchemaRDD instead of generating and caching PythonRDD f2312c7 [Ahir Reddy] Moved everything into sql.py a19afe4 [Ahir Reddy] Doc fixes 6d658ba [Ahir Reddy] Remove the metastore directory created by the HiveContext tests in SparkSQL 521ff6d [Ahir Reddy] Trying to get spark to build with hive ab95eba [Ahir Reddy] Set SPARK_HIVE=true on jenkins ded03e7 [Ahir Reddy] Added doc test for HiveContext 22de1d4 [Ahir Reddy] Fixed maven pyrolite dependency e4da06c [Ahir Reddy] Display message if hive is not built into spark 227a0be [Michael Armbrust] Update API links. Fix Hive example. 58e2aa9 [Michael Armbrust] Build Docs for pyspark SQL Api. Minor fixes. 4285340 [Michael Armbrust] Fix building of Hive API Docs. 38a92b0 [Michael Armbrust] Add note to future non-python developers about python docs. 337b201 [Ahir Reddy] Changed com.clearspring.analytics stream version from 2.4.0 to 2.5.1 to match SBT build, and added pyrolite to maven build 40491c9 [Ahir Reddy] PR Changes + Method Visibility 1836944 [Michael Armbrust] Fix comments. e00980f [Michael Armbrust] First draft of python sql programming guide. b0192d3 [Ahir Reddy] Added Long, Double and Boolean as usable types + unit test f98a422 [Ahir Reddy] HiveContexts 79621cf [Ahir Reddy] cleaning up cruft b406ba0 [Ahir Reddy] doctest formatting 20936a5 [Ahir Reddy] Added tests and documentation e4d21b4 [Ahir Reddy] Added pyrolite dependency 79f739d [Ahir Reddy] added more tests 7515ba0 [Ahir Reddy] added more tests :) d26ec5e [Ahir Reddy] added test e9f5b8d [Ahir Reddy] adding tests 906d180 [Ahir Reddy] added todo explaining cost of creating Row object in python 251f99d [Ahir Reddy] for now only allow dictionaries as input 09b9980 [Ahir Reddy] made jrdd explicitly lazy c608947 [Ahir Reddy] SchemaRDD now has all RDD operations 725c91e [Ahir Reddy] awesome row objects 55d1c76 [Ahir Reddy] return row objects 4fe1319 [Ahir Reddy] output dictionaries correctly be079de [Ahir Reddy] returning dictionaries works cd5f79f [Ahir Reddy] Switched to using Scala SQLContext e948bd9 [Ahir Reddy] yippie 4886052 [Ahir Reddy] even better c0fb1c6 [Ahir Reddy] more working 043ca85 [Ahir Reddy] working 5496f9f [Ahir Reddy] doesn't crash b8b904b [Ahir Reddy] Added schema rdd class 67ba875 [Ahir Reddy] java to python, and python to java bcc0f23 [Ahir Reddy] Java to python ab6025d [Ahir Reddy] compiling
2014-04-15 03:07:55 -04:00
</dependency>
[SPARK-1549] Add Python support to spark-submit This PR updates spark-submit to allow submitting Python scripts (currently only with deploy-mode=client, but that's all that was supported before) and updates the PySpark code to properly find various paths, etc. One significant change is that we assume we can always find the Python files either from the Spark assembly JAR (which will happen with the Maven assembly build in make-distribution.sh) or from SPARK_HOME (which will exist in local mode even if you use sbt assembly, and should be enough for testing). This means we no longer need a weird hack to modify the environment for YARN. This patch also updates the Python worker manager to run python with -u, which means unbuffered output (send it to our logs right away instead of waiting a while after stuff was written); this should simplify debugging. In addition, it fixes https://issues.apache.org/jira/browse/SPARK-1709, setting the main class from a JAR's Main-Class attribute if not specified by the user, and fixes a few help strings and style issues in spark-submit. In the future we may want to make the `pyspark` shell use spark-submit as well, but it seems unnecessary for 1.0. Author: Matei Zaharia <matei@databricks.com> Closes #664 from mateiz/py-submit and squashes the following commits: 15e9669 [Matei Zaharia] Fix some uses of path.separator property 051278c [Matei Zaharia] Small style fixes 0afe886 [Matei Zaharia] Add license headers 4650412 [Matei Zaharia] Add pyFiles to PYTHONPATH in executors, remove old YARN stuff, add tests 15f8e1e [Matei Zaharia] Set PYTHONPATH in PythonWorkerFactory in case it wasn't set from outside 47c0655 [Matei Zaharia] More work to make spark-submit work with Python: d4375bd [Matei Zaharia] Clean up description of spark-submit args a bit and add Python ones
2014-05-06 18:12:35 -04:00
<dependency>
<groupId>net.sf.py4j</groupId>
<artifactId>py4j</artifactId>
<version>0.8.2.1</version>
[SPARK-1549] Add Python support to spark-submit This PR updates spark-submit to allow submitting Python scripts (currently only with deploy-mode=client, but that's all that was supported before) and updates the PySpark code to properly find various paths, etc. One significant change is that we assume we can always find the Python files either from the Spark assembly JAR (which will happen with the Maven assembly build in make-distribution.sh) or from SPARK_HOME (which will exist in local mode even if you use sbt assembly, and should be enough for testing). This means we no longer need a weird hack to modify the environment for YARN. This patch also updates the Python worker manager to run python with -u, which means unbuffered output (send it to our logs right away instead of waiting a while after stuff was written); this should simplify debugging. In addition, it fixes https://issues.apache.org/jira/browse/SPARK-1709, setting the main class from a JAR's Main-Class attribute if not specified by the user, and fixes a few help strings and style issues in spark-submit. In the future we may want to make the `pyspark` shell use spark-submit as well, but it seems unnecessary for 1.0. Author: Matei Zaharia <matei@databricks.com> Closes #664 from mateiz/py-submit and squashes the following commits: 15e9669 [Matei Zaharia] Fix some uses of path.separator property 051278c [Matei Zaharia] Small style fixes 0afe886 [Matei Zaharia] Add license headers 4650412 [Matei Zaharia] Add pyFiles to PYTHONPATH in executors, remove old YARN stuff, add tests 15f8e1e [Matei Zaharia] Set PYTHONPATH in PythonWorkerFactory in case it wasn't set from outside 47c0655 [Matei Zaharia] More work to make spark-submit work with Python: d4375bd [Matei Zaharia] Clean up description of spark-submit args a bit and add Python ones
2014-05-06 18:12:35 -04:00
</dependency>
</dependencies>
<build>
<outputDirectory>target/scala-${scala.binary.version}/classes</outputDirectory>
<testOutputDirectory>target/scala-${scala.binary.version}/test-classes</testOutputDirectory>
<plugins>
<plugin>
<groupId>org.scalatest</groupId>
<artifactId>scalatest-maven-plugin</artifactId>
<configuration>
<environmentVariables>
<SPARK_HOME>${basedir}/..</SPARK_HOME>
<SPARK_TESTING>1</SPARK_TESTING>
<SPARK_CLASSPATH>${spark.classpath}</SPARK_CLASSPATH>
</environmentVariables>
</configuration>
</plugin>
<!-- Unzip py4j so we can include its files in the jar -->
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-antrun-plugin</artifactId>
<executions>
<execution>
<phase>generate-resources</phase>
<goals>
<goal>run</goal>
</goals>
</execution>
</executions>
<configuration>
<tasks>
<unzip src="../python/lib/py4j-0.8.2.1-src.zip" dest="../python/build" />
</tasks>
</configuration>
</plugin>
<plugin>
<artifactId>maven-clean-plugin</artifactId>
<configuration>
<filesets>
<fileset>
<directory>${basedir}/../python/build</directory>
</fileset>
</filesets>
<verbose>true</verbose>
</configuration>
</plugin>
[SPARK-2848] Shade Guava in uber-jars. For further discussion, please check the JIRA entry. This change moves Guava classes to a different package so that they don't conflict with the user-provided Guava (or the Hadoop-provided one). Since one class (Optional) was exposed through Spark's public API, that class was forked from Guava at the current dependency version (14.0.1) so that it can be kept going forward (until the API is cleaned). Note this change has a few implications: - *all* classes in the final jars will reference the relocated classes. If Hadoop classes are included (i.e. "-Phadoop-provided" is not activated), those will also reference the Guava 14 classes (instead of the Guava 11 classes from the Hadoop classpath). - if the Guava version in Spark is ever changed, the new Guava will still reference the forked Optional class; this may or may not be a problem, but in the long term it's better to think about removing Optional from the public API. For the end user, there are two visible implications: - Guava is not provided as a transitive dependency anymore (since it's "provided" in Spark) - At runtime, unless they provide their own, they'll either have no Guava or Hadoop's version of Guava (11), depending on how they set up their classpath. Note that this patch does not change the sbt deliverables; those will still contain guava in its original package, and provide guava as a compile-time dependency. This assumes that maven is the canonical build, and sbt-built artifacts are not (officially) published. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #1813 from vanzin/SPARK-2848 and squashes the following commits: 9bdffb0 [Marcelo Vanzin] Undo sbt build changes. 819b445 [Marcelo Vanzin] Review feedback. 05e0a3d [Marcelo Vanzin] Merge branch 'master' into SPARK-2848 fef4370 [Marcelo Vanzin] Unfork Optional.java. d3ea8e1 [Marcelo Vanzin] Exclude asm classes from final jar. 637189b [Marcelo Vanzin] Add hacky filter to prefer Spark's copy of Optional. 2fec990 [Marcelo Vanzin] Shade Guava in the sbt build. 616998e [Marcelo Vanzin] Shade Guava in the maven build, fork Guava's Optional.java.
2014-08-20 19:23:10 -04:00
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-shade-plugin</artifactId>
<executions>
<execution>
<phase>package</phase>
<goals>
<goal>shade</goal>
</goals>
<configuration>
<shadedArtifactAttached>false</shadedArtifactAttached>
<artifactSet>
<includes>
<include>com.google.guava:guava</include>
</includes>
</artifactSet>
<filters>
<!-- See comment in the guava dependency declaration above. -->
<filter>
<artifact>com.google.guava:guava</artifact>
<includes>
<include>com/google/common/base/Absent*</include>
[SPARK-2848] Shade Guava in uber-jars. For further discussion, please check the JIRA entry. This change moves Guava classes to a different package so that they don't conflict with the user-provided Guava (or the Hadoop-provided one). Since one class (Optional) was exposed through Spark's public API, that class was forked from Guava at the current dependency version (14.0.1) so that it can be kept going forward (until the API is cleaned). Note this change has a few implications: - *all* classes in the final jars will reference the relocated classes. If Hadoop classes are included (i.e. "-Phadoop-provided" is not activated), those will also reference the Guava 14 classes (instead of the Guava 11 classes from the Hadoop classpath). - if the Guava version in Spark is ever changed, the new Guava will still reference the forked Optional class; this may or may not be a problem, but in the long term it's better to think about removing Optional from the public API. For the end user, there are two visible implications: - Guava is not provided as a transitive dependency anymore (since it's "provided" in Spark) - At runtime, unless they provide their own, they'll either have no Guava or Hadoop's version of Guava (11), depending on how they set up their classpath. Note that this patch does not change the sbt deliverables; those will still contain guava in its original package, and provide guava as a compile-time dependency. This assumes that maven is the canonical build, and sbt-built artifacts are not (officially) published. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #1813 from vanzin/SPARK-2848 and squashes the following commits: 9bdffb0 [Marcelo Vanzin] Undo sbt build changes. 819b445 [Marcelo Vanzin] Review feedback. 05e0a3d [Marcelo Vanzin] Merge branch 'master' into SPARK-2848 fef4370 [Marcelo Vanzin] Unfork Optional.java. d3ea8e1 [Marcelo Vanzin] Exclude asm classes from final jar. 637189b [Marcelo Vanzin] Add hacky filter to prefer Spark's copy of Optional. 2fec990 [Marcelo Vanzin] Shade Guava in the sbt build. 616998e [Marcelo Vanzin] Shade Guava in the maven build, fork Guava's Optional.java.
2014-08-20 19:23:10 -04:00
<include>com/google/common/base/Optional*</include>
<include>com/google/common/base/Present*</include>
[SPARK-2848] Shade Guava in uber-jars. For further discussion, please check the JIRA entry. This change moves Guava classes to a different package so that they don't conflict with the user-provided Guava (or the Hadoop-provided one). Since one class (Optional) was exposed through Spark's public API, that class was forked from Guava at the current dependency version (14.0.1) so that it can be kept going forward (until the API is cleaned). Note this change has a few implications: - *all* classes in the final jars will reference the relocated classes. If Hadoop classes are included (i.e. "-Phadoop-provided" is not activated), those will also reference the Guava 14 classes (instead of the Guava 11 classes from the Hadoop classpath). - if the Guava version in Spark is ever changed, the new Guava will still reference the forked Optional class; this may or may not be a problem, but in the long term it's better to think about removing Optional from the public API. For the end user, there are two visible implications: - Guava is not provided as a transitive dependency anymore (since it's "provided" in Spark) - At runtime, unless they provide their own, they'll either have no Guava or Hadoop's version of Guava (11), depending on how they set up their classpath. Note that this patch does not change the sbt deliverables; those will still contain guava in its original package, and provide guava as a compile-time dependency. This assumes that maven is the canonical build, and sbt-built artifacts are not (officially) published. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #1813 from vanzin/SPARK-2848 and squashes the following commits: 9bdffb0 [Marcelo Vanzin] Undo sbt build changes. 819b445 [Marcelo Vanzin] Review feedback. 05e0a3d [Marcelo Vanzin] Merge branch 'master' into SPARK-2848 fef4370 [Marcelo Vanzin] Unfork Optional.java. d3ea8e1 [Marcelo Vanzin] Exclude asm classes from final jar. 637189b [Marcelo Vanzin] Add hacky filter to prefer Spark's copy of Optional. 2fec990 [Marcelo Vanzin] Shade Guava in the sbt build. 616998e [Marcelo Vanzin] Shade Guava in the maven build, fork Guava's Optional.java.
2014-08-20 19:23:10 -04:00
</includes>
</filter>
</filters>
</configuration>
</execution>
</executions>
</plugin>
<!--
Copy guava to the build directory. This is needed to make the SPARK_PREPEND_CLASSES
option work in compute-classpath.sh, since it would put the non-shaded Spark classes in
the runtime classpath.
-->
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-dependency-plugin</artifactId>
<executions>
<execution>
<id>copy-dependencies</id>
<phase>package</phase>
<goals>
<goal>copy-dependencies</goal>
</goals>
<configuration>
<outputDirectory>${project.build.directory}</outputDirectory>
<overWriteReleases>false</overWriteReleases>
<overWriteSnapshots>false</overWriteSnapshots>
<overWriteIfNewer>true</overWriteIfNewer>
<useSubDirectoryPerType>true</useSubDirectoryPerType>
<includeArtifactIds>guava</includeArtifactIds>
<silent>true</silent>
</configuration>
</execution>
</executions>
</plugin>
</plugins>
<resources>
<resource>
<directory>src/main/resources</directory>
</resource>
<resource>
<directory>../python</directory>
<includes>
<include>pyspark/*.py</include>
</includes>
</resource>
<resource>
<directory>../python/build</directory>
<includes>
<include>py4j/*.py</include>
</includes>
</resource>
</resources>
</build>
2013-12-31 22:30:08 -05:00
</project>