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* [SPARK-10938] [SQL] remove typeId in columnar cacheDavies Liu2015-10-061-1/+3
| | | | | | | | This PR remove the typeId in columnar cache, it's not needed anymore, it also remove DATE and TIMESTAMP (use INT/LONG instead). Author: Davies Liu <davies@databricks.com> Closes #8989 from davies/refactor_cache.
* [SPARK-9642] [ML] LinearRegression should supported weighted dataMeihua Wu2015-09-211-2/+6
| | | | | | | | | | In many modeling application, data points are not necessarily sampled with equal probabilities. Linear regression should support weighting which account the over or under sampling. work in progress. Author: Meihua Wu <meihuawu@umich.edu> Closes #8631 from rotationsymmetry/SPARK-9642.
* [SPARK-9808] Remove hash shuffle file consolidation.Reynold Xin2015-09-181-0/+4
| | | | | | Author: Reynold Xin <rxin@databricks.com> Closes #8812 from rxin/SPARK-9808-1.
* [SPARK-10381] Fix mixup of taskAttemptNumber & attemptId in ↵Josh Rosen2015-09-151-1/+35
| | | | | | | | | | | | | | OutputCommitCoordinator When speculative execution is enabled, consider a scenario where the authorized committer of a particular output partition fails during the OutputCommitter.commitTask() call. In this case, the OutputCommitCoordinator is supposed to release that committer's exclusive lock on committing once that task fails. However, due to a unit mismatch (we used task attempt number in one place and task attempt id in another) the lock will not be released, causing Spark to go into an infinite retry loop. This bug was masked by the fact that the OutputCommitCoordinator does not have enough end-to-end tests (the current tests use many mocks). Other factors contributing to this bug are the fact that we have many similarly-named identifiers that have different semantics but the same data types (e.g. attemptNumber and taskAttemptId, with inconsistent variable naming which makes them difficult to distinguish). This patch adds a regression test and fixes this bug by always using task attempt numbers throughout this code. Author: Josh Rosen <joshrosen@databricks.com> Closes #8544 from JoshRosen/SPARK-10381.
* [SPARK-7685] [ML] Apply weights to different samples in Logistic RegressionDB Tsai2015-09-151-1/+9
| | | | | | | | | | | In fraud detection dataset, almost all the samples are negative while only couple of them are positive. This type of high imbalanced data will bias the models toward negative resulting poor performance. In python-scikit, they provide a correction allowing users to Over-/undersample the samples of each class according to the given weights. In auto mode, selects weights inversely proportional to class frequencies in the training set. This can be done in a more efficient way by multiplying the weights into loss and gradient instead of doing actual over/undersampling in the training dataset which is very expensive. http://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html On the other hand, some of the training data maybe more important like the training samples from tenure users while the training samples from new users maybe less important. We should be able to provide another "weight: Double" information in the LabeledPoint to weight them differently in the learning algorithm. Author: DB Tsai <dbt@netflix.com> Author: DB Tsai <dbt@dbs-mac-pro.corp.netflix.com> Closes #7884 from dbtsai/SPARK-7685.
* Update version to 1.6.0-SNAPSHOT.Reynold Xin2015-09-151-2/+11
| | | | | | Author: Reynold Xin <rxin@databricks.com> Closes #8350 from rxin/1.6.
* [SPARK-9767] Remove ConnectionManager.Reynold Xin2015-09-071-627/+630
| | | | | | | | We introduced the Netty network module for shuffle in Spark 1.2, and has turned it on by default for 3 releases. The old ConnectionManager is difficult to maintain. If we merge the patch now, by the time it is released, it would be 1 yr for which ConnectionManager is off by default. It's time to remove it. Author: Reynold Xin <rxin@databricks.com> Closes #8161 from rxin/SPARK-9767.
* [SPARK-10004] [SHUFFLE] Perform auth checks when clients read shuffle data.Marcelo Vanzin2015-09-021-0/+1
| | | | | | | | | | | | | | | To correctly isolate applications, when requests to read shuffle data arrive at the shuffle service, proper authorization checks need to be performed. This change makes sure that only the application that created the shuffle data can read from it. Such checks are only enabled when "spark.authenticate" is enabled, otherwise there's no secure way to make sure that the client is really who it says it is. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #8218 from vanzin/SPARK-10004.
* [SPARK-9580] [SQL] Replace singletons in SQL testsAndrew Or2015-08-131-0/+10
| | | | | | | | | | | | | | A fundamental limitation of the existing SQL tests is that *there is simply no way to create your own `SparkContext`*. This is a serious limitation because the user may wish to use a different master or config. As a case in point, `BroadcastJoinSuite` is entirely commented out because there is no way to make it pass with the existing infrastructure. This patch removes the singletons `TestSQLContext` and `TestData`, and instead introduces a `SharedSQLContext` that starts a context per suite. Unfortunately the singletons were so ingrained in the SQL tests that this patch necessarily needed to touch *all* the SQL test files. <!-- Reviewable:start --> [<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/8111) <!-- Reviewable:end --> Author: Andrew Or <andrew@databricks.com> Closes #8111 from andrewor14/sql-tests-refactor.
* [SPARK-9704] [ML] Made ProbabilisticClassifier, Identifiable, VectorUDT ↵Joseph K. Bradley2015-08-121-0/+4
| | | | | | | | | | | | | | | | | | public APIs Made ProbabilisticClassifier, Identifiable, VectorUDT public. All are annotated as DeveloperApi. CC: mengxr EronWright Author: Joseph K. Bradley <joseph@databricks.com> Closes #8004 from jkbradley/ml-api-public-items and squashes the following commits: 7ebefda [Joseph K. Bradley] update per code review 7ff0768 [Joseph K. Bradley] attepting to add mima fix 756d84c [Joseph K. Bradley] VectorUDT annotated as AlphaComponent ae7767d [Joseph K. Bradley] added another warning 94fd553 [Joseph K. Bradley] Made ProbabilisticClassifier, Identifiable, VectorUDT public APIs
* [SPARK-9763][SQL] Minimize exposure of internal SQL classes.Reynold Xin2015-08-101-3/+21
| | | | | | | | | | | | | | | | | | | | | | | | | | There are a few changes in this pull request: 1. Moved all data sources to execution.datasources, except the public JDBC APIs. 2. In order to maintain backward compatibility from 1, added a backward compatibility translation map in data source resolution. 3. Moved ui and metric package into execution. 4. Added more documentation on some internal classes. 5. Renamed DataSourceRegister.format -> shortName. 6. Added "override" modifier on shortName. 7. Removed IntSQLMetric. Author: Reynold Xin <rxin@databricks.com> Closes #8056 from rxin/SPARK-9763 and squashes the following commits: 9df4801 [Reynold Xin] Removed hardcoded name in test cases. d9babc6 [Reynold Xin] Shorten. e484419 [Reynold Xin] Removed VisibleForTesting. 171b812 [Reynold Xin] MimaExcludes. 2041389 [Reynold Xin] Compile ... 79dda42 [Reynold Xin] Compile. 0818ba3 [Reynold Xin] Removed IntSQLMetric. c46884f [Reynold Xin] Two more fixes. f9aa88d [Reynold Xin] [SPARK-9763][SQL] Minimize exposure of internal SQL classes.
* [SPARK-9602] remove "Akka/Actor" words from commentsCodingCat2015-08-041-1/+1
| | | | | | | | | | | | https://issues.apache.org/jira/browse/SPARK-9602 Although we have hidden Akka behind RPC interface, I found that the Akka/Actor-related comments are still spreading everywhere. To make it consistent, we shall remove "actor"/"akka" words from the comments... Author: CodingCat <zhunansjtu@gmail.com> Closes #7936 from CodingCat/SPARK-9602 and squashes the following commits: e8296a3 [CodingCat] remove actor words from comments
* [SPARK-1855] Local checkpointingAndrew Or2015-08-031-2/+7
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Certain use cases of Spark involve RDDs with long lineages that must be truncated periodically (e.g. GraphX). The existing way of doing it is through `rdd.checkpoint()`, which is expensive because it writes to HDFS. This patch provides an alternative to truncate lineages cheaply *without providing the same level of fault tolerance*. **Local checkpointing** writes checkpointed data to the local file system through the block manager. It is much faster than replicating to a reliable storage and provides the same semantics as long as executors do not fail. It is accessible through a new operator `rdd.localCheckpoint()` and leaves the old one unchanged. Users may even decide to combine the two and call the reliable one less frequently. The bulk of this patch involves refactoring the checkpointing interface to accept custom implementations of checkpointing. [Design doc](https://issues.apache.org/jira/secure/attachment/12741708/SPARK-7292-design.pdf). Author: Andrew Or <andrew@databricks.com> Closes #7279 from andrewor14/local-checkpoint and squashes the following commits: 729600f [Andrew Or] Oops, fix tests 34bc059 [Andrew Or] Avoid computing all partitions in local checkpoint e43bbb6 [Andrew Or] Merge branch 'master' of github.com:apache/spark into local-checkpoint 3be5aea [Andrew Or] Address comments bf846a6 [Andrew Or] Merge branch 'master' of github.com:apache/spark into local-checkpoint ab003a3 [Andrew Or] Fix compile c2e111b [Andrew Or] Address comments 33f167a [Andrew Or] Merge branch 'master' of github.com:apache/spark into local-checkpoint e908a42 [Andrew Or] Fix tests f5be0f3 [Andrew Or] Use MEMORY_AND_DISK as the default local checkpoint level a92657d [Andrew Or] Update a few comments e58e3e3 [Andrew Or] Merge branch 'master' of github.com:apache/spark into local-checkpoint 4eb6eb1 [Andrew Or] Merge branch 'master' of github.com:apache/spark into local-checkpoint 1bbe154 [Andrew Or] Simplify LocalCheckpointRDD 48a9996 [Andrew Or] Avoid traversing dependency tree + rewrite tests 62aba3f [Andrew Or] Merge branch 'master' of github.com:apache/spark into local-checkpoint db70dc2 [Andrew Or] Express local checkpointing through caching the original RDD 87d43c6 [Andrew Or] Merge branch 'master' of github.com:apache/spark into local-checkpoint c449b38 [Andrew Or] Fix style 4a182f3 [Andrew Or] Add fine-grained tests for local checkpointing 53b363b [Andrew Or] Rename a few more awkwardly named methods (minor) e4cf071 [Andrew Or] Simplify LocalCheckpointRDD + docs + clean ups 4880deb [Andrew Or] Fix style d096c67 [Andrew Or] Fix mima 172cb66 [Andrew Or] Fix mima? e53d964 [Andrew Or] Fix style 56831c5 [Andrew Or] Add a few warnings and clear exception messages 2e59646 [Andrew Or] Add local checkpoint clean up tests 4dbbab1 [Andrew Or] Refactor CheckpointSuite to test local checkpointing 4514dc9 [Andrew Or] Clean local checkpoint files through RDD cleanups 0477eec [Andrew Or] Rename a few methods with awkward names (minor) 2e902e5 [Andrew Or] First implementation of local checkpointing 8447454 [Andrew Or] Fix tests 4ac1896 [Andrew Or] Refactor checkpoint interface for modularity
* [SPARK-4751] Dynamic allocation in standalone modeAndrew Or2015-08-011-0/+4
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | Dynamic allocation is a feature that allows a Spark application to scale the number of executors up and down dynamically based on the workload. Support was first introduced in YARN since 1.2, and then extended to Mesos coarse-grained mode recently. Today, it is finally supported in standalone mode as well! I tested this locally and it works as expected. This is WIP because unit tests are coming. Author: Andrew Or <andrew@databricks.com> Closes #7532 from andrewor14/standalone-da and squashes the following commits: b3c1736 [Andrew Or] Merge branch 'master' of github.com:apache/spark into standalone-da 879e928 [Andrew Or] Add end-to-end tests for standalone dynamic allocation accc8f6 [Andrew Or] Address comments ee686a8 [Andrew Or] Merge branch 'master' of github.com:apache/spark into standalone-da c0a2c02 [Andrew Or] Fix build after merge conflict 24149eb [Andrew Or] Merge branch 'master' of github.com:apache/spark into standalone-da 2e762d6 [Andrew Or] Merge branch 'master' of github.com:apache/spark into standalone-da 6832bd7 [Andrew Or] Add tests for scheduling with executor limit a82e907 [Andrew Or] Fix comments 0a8be79 [Andrew Or] Simplify logic by removing the worker blacklist b7742af [Andrew Or] Merge branch 'master' of github.com:apache/spark into standalone-da 2eb5f3f [Andrew Or] Merge branch 'master' of github.com:apache/spark into standalone-da 1334e9a [Andrew Or] Fix MiMa 32abe44 [Andrew Or] Fix style 58cb06f [Andrew Or] Privatize worker blacklist for cleanliness 42ac215 [Andrew Or] Clean up comments and rewrite code for readability 49702d1 [Andrew Or] Clean up shuffle files after application exits 80047aa [Andrew Or] First working implementation
* [SPARK-8906][SQL] Move all internal data source classes into ↵Reynold Xin2015-07-211-0/+47
| | | | | | | | | | | | | | execution.datasources. This way, the sources package contains only public facing interfaces. Author: Reynold Xin <rxin@databricks.com> Closes #7565 from rxin/move-ds and squashes the following commits: 7661aff [Reynold Xin] Mima 9d5196a [Reynold Xin] Rearranged imports. 3dd7174 [Reynold Xin] [SPARK-8906][SQL] Move all internal data source classes into execution.datasources.
* [SPARK-9114] [SQL] [PySpark] convert returned object from UDF into internal typeDavies Liu2015-07-201-1/+3
| | | | | | | | | | | | | | This PR also remove the duplicated code between registerFunction and UserDefinedFunction. cc JoshRosen Author: Davies Liu <davies@databricks.com> Closes #7450 from davies/fix_return_type and squashes the following commits: e80bf9f [Davies Liu] remove debugging code f94b1f6 [Davies Liu] fix mima 8f9c58b [Davies Liu] convert returned object from UDF into internal type
* [SPARK-7422] [MLLIB] Add argmax to Vector, SparseVectorGeorge Dittmar2015-07-201-0/+4
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Modifying Vector, DenseVector, and SparseVector to implement argmax functionality. This work is to set the stage for changes to be done in Spark-7423. Author: George Dittmar <georgedittmar@gmail.com> Author: George <dittmar@Georges-MacBook-Pro.local> Author: dittmarg <george.dittmar@webtrends.com> Author: Xiangrui Meng <meng@databricks.com> Closes #6112 from GeorgeDittmar/SPARK-7422 and squashes the following commits: 3e0a939 [George Dittmar] Merge pull request #1 from mengxr/SPARK-7422 127dec5 [Xiangrui Meng] update argmax impl 2ea6a55 [George Dittmar] Added MimaExcludes for Vectors.argmax 98058f4 [George Dittmar] Merge branch 'master' of github.com:apache/spark into SPARK-7422 5fd9380 [George Dittmar] fixing style check error 42341fb [George Dittmar] refactoring arg max check to better handle zero values b22af46 [George Dittmar] Fixing spaces between commas in unit test f2eba2f [George Dittmar] Cleaning up unit tests to be fewer lines aa330e3 [George Dittmar] Fixing some last if else spacing issues ac53c55 [George Dittmar] changing dense vector argmax unit test to be one line call vs 2 d5b5423 [George Dittmar] Fixing code style and updating if logic on when to check for zero values ee1a85a [George Dittmar] Cleaning up unit tests a bit and modifying a few cases 3ee8711 [George Dittmar] Fixing corner case issue with zeros in the active values of the sparse vector. Updated unit tests b1f059f [George Dittmar] Added comment before we start arg max calculation. Updated unit tests to cover corner cases f21dcce [George Dittmar] commit af17981 [dittmarg] Initial work fixing bug that was made clear in pr eeda560 [George] Fixing SparseVector argmax function to ignore zero values while doing the calculation. 4526acc [George] Merge branch 'master' of github.com:apache/spark into SPARK-7422 df9538a [George] Added argmax to sparse vector and added unit test 3cffed4 [George] Adding unit tests for argmax functions for Dense and Sparse vectors 04677af [George] initial work on adding argmax to Vector and SparseVector
* [SPARK-8278] Remove non-streaming JSON reader.Reynold Xin2015-07-181-0/+3
| | | | | | | | | | | Author: Reynold Xin <rxin@databricks.com> Closes #7501 from rxin/jsonrdd and squashes the following commits: 767ec55 [Reynold Xin] More Mima 51f456e [Reynold Xin] Mima exclude. 789cb80 [Reynold Xin] Fixed compilation error. b4cf50d [Reynold Xin] [SPARK-8278] Remove non-streaming JSON reader.
* [SPARK-6797] [SPARKR] Add support for YARN cluster mode.Sun Rui2015-07-131-0/+12
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This PR enables SparkR to dynamically ship the SparkR binary package to the AM node in YARN cluster mode, thus it is no longer required that the SparkR package be installed on each worker node. This PR uses the JDK jar tool to package the SparkR package, because jar is thought to be available on both Linux/Windows platforms where JDK has been installed. This PR does not address the R worker involved in RDD API. Will address it in a separate JIRA issue. This PR does not address SBT build. SparkR installation and packaging by SBT will be addressed in a separate JIRA issue. R/install-dev.bat is not tested. shivaram , Could you help to test it? Author: Sun Rui <rui.sun@intel.com> Closes #6743 from sun-rui/SPARK-6797 and squashes the following commits: ca63c86 [Sun Rui] Adjust MimaExcludes after rebase. 7313374 [Sun Rui] Fix unit test errors. 72695fb [Sun Rui] Fix unit test failures. 193882f [Sun Rui] Fix Mima test error. fe25a33 [Sun Rui] Fix Mima test error. 35ecfa3 [Sun Rui] Fix comments. c38a005 [Sun Rui] Unzipped SparkR binary package is still required for standalone and Mesos modes. b05340c [Sun Rui] Fix scala style. 2ca5048 [Sun Rui] Fix comments. 1acefd1 [Sun Rui] Fix scala style. 0aa1e97 [Sun Rui] Fix scala style. 41d4f17 [Sun Rui] Add support for locating SparkR package for R workers required by RDD APIs. 49ff948 [Sun Rui] Invoke jar.exe with full path in install-dev.bat. 7b916c5 [Sun Rui] Use 'rem' consistently. 3bed438 [Sun Rui] Add a comment. 681afb0 [Sun Rui] Fix a bug that RRunner does not handle client deployment modes. cedfbe2 [Sun Rui] [SPARK-6797][SPARKR] Add support for YARN cluster mode.
* [SPARK-8701] [STREAMING] [WEBUI] Add input metadata in the batch pagezsxwing2015-07-091-0/+6
| | | | | | | | | | | | | | | | | | | | | | This PR adds `metadata` to `InputInfo`. `InputDStream` can report its metadata for a batch and it will be shown in the batch page. For example, ![screen shot](https://cloud.githubusercontent.com/assets/1000778/8403741/d6ffc7e2-1e79-11e5-9888-c78c1575123a.png) FileInputDStream will display the new files for a batch, and DirectKafkaInputDStream will display its offset ranges. Author: zsxwing <zsxwing@gmail.com> Closes #7081 from zsxwing/input-metadata and squashes the following commits: f7abd9b [zsxwing] Revert the space changes in project/MimaExcludes.scala d906209 [zsxwing] Merge branch 'master' into input-metadata 74762da [zsxwing] Fix MiMa tests 7903e33 [zsxwing] Merge branch 'master' into input-metadata 450a46c [zsxwing] Address comments 1d94582 [zsxwing] Raname InputInfo to StreamInputInfo and change "metadata" to Map[String, Any] d496ae9 [zsxwing] Add input metadata in the batch page
* [SPARK-8450] [SQL] [PYSARK] cleanup type converter for Python DataFrameDavies Liu2015-07-081-1/+4
| | | | | | | | | | | | | | | | | | | | This PR fixes the converter for Python DataFrame, especially for DecimalType Closes #7106 Author: Davies Liu <davies@databricks.com> Closes #7131 from davies/decimal_python and squashes the following commits: 4d3c234 [Davies Liu] Merge branch 'master' of github.com:apache/spark into decimal_python 20531d6 [Davies Liu] Merge branch 'master' of github.com:apache/spark into decimal_python 7d73168 [Davies Liu] fix conflit 6cdd86a [Davies Liu] Merge branch 'master' of github.com:apache/spark into decimal_python 7104e97 [Davies Liu] improve type infer 9cd5a21 [Davies Liu] run python tests with SPARK_PREPEND_CLASSES 829a05b [Davies Liu] fix UDT in python c99e8c5 [Davies Liu] fix mima c46814a [Davies Liu] convert decimal for Python DataFrames
* [SPARK-8914][SQL] Remove RDDApiKousuke Saruta2015-07-081-0/+5
| | | | | | | | | | | As rxin suggested in #7298 , we should consider to remove `RDDApi`. Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp> Closes #7302 from sarutak/remove-rddapi and squashes the following commits: e495d35 [Kousuke Saruta] Fixed mima cb7ebb9 [Kousuke Saruta] Removed overriding RDDApi
* [SPARK-6123] [SPARK-6775] [SPARK-6776] [SQL] Refactors Parquet read path for ↵Cheng Lian2015-07-081-15/+2
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | interoperability and backwards-compatibility This PR is a follow-up of #6617 and is part of [SPARK-6774] [2], which aims to ensure interoperability and backwards-compatibility for Spark SQL Parquet support. And this one fixes the read path. Now Spark SQL is expected to be able to read legacy Parquet data files generated by most (if not all) common libraries/tools like parquet-thrift, parquet-avro, and parquet-hive. However, we still need to refactor the write path to write standard Parquet LISTs and MAPs ([SPARK-8848] [4]). ### Major changes 1. `CatalystConverter` class hierarchy refactoring - Replaces `CatalystConverter` trait with a much simpler `ParentContainerUpdater`. Now instead of extending the original `CatalystConverter` trait, every converter class accepts an updater which is responsible for propagating the converted value to some parent container. For example, appending array elements to a parent array buffer, appending a key-value pairs to a parent mutable map, or setting a converted value to some specific field of a parent row. Root converter doesn't have a parent and thus uses a `NoopUpdater`. This simplifies the design since converters don't need to care about details of their parent converters anymore. - Unifies `CatalystRootConverter`, `CatalystGroupConverter` and `CatalystPrimitiveRowConverter` into `CatalystRowConverter` Specifically, now all row objects are represented by `SpecificMutableRow` during conversion. - Refactors `CatalystArrayConverter`, and removes `CatalystArrayContainsNullConverter` and `CatalystNativeArrayConverter` `CatalystNativeArrayConverter` was probably designed with the intention of avoiding boxing costs. However, the way it uses Scala generics actually doesn't achieve this goal. The new `CatalystArrayConverter` handles both nullable and non-nullable array elements in a consistent way. - Implements backwards-compatibility rules in `CatalystArrayConverter` When Parquet records are being converted, schema of Parquet files should have already been verified. So we only need to care about the structure rather than field names in the Parquet schema. Since all map objects represented in legacy systems have the same structure as the standard one (see [backwards-compatibility rules for MAP] [1]), we only need to deal with LIST (namely array) in `CatalystArrayConverter`. 2. Requested columns handling When specifying requested columns in `RowReadSupport`, we used to use a Parquet `MessageType` converted from a Catalyst `StructType` which contains all requested columns. This is not preferable when taking compatibility and interoperability into consideration. Because the actual Parquet file may have different physical structure from the converted schema. In this PR, the schema for requested columns is constructed using the following method: - For a column that exists in the target Parquet file, we extract the column type by name from the full file schema, and construct a single-field `MessageType` for that column. - For a column that doesn't exist in the target Parquet file, we create a single-field `StructType` and convert it to a `MessageType` using `CatalystSchemaConverter`. - Unions all single-field `MessageType`s into a full schema containing all requested fields With this change, we also fix [SPARK-6123] [3] by validating the global schema against each individual Parquet part-files. ### Testing This PR also adds compatibility tests for parquet-avro, parquet-thrift, and parquet-hive. Please refer to `README.md` under `sql/core/src/test` for more information about these tests. To avoid build time code generation and adding extra complexity to the build system, Java code generated from testing Thrift schema and Avro IDL is also checked in. [1]: https://github.com/apache/incubator-parquet-format/blob/master/LogicalTypes.md#backward-compatibility-rules-1 [2]: https://issues.apache.org/jira/browse/SPARK-6774 [3]: https://issues.apache.org/jira/browse/SPARK-6123 [4]: https://issues.apache.org/jira/browse/SPARK-8848 Author: Cheng Lian <lian@databricks.com> Closes #7231 from liancheng/spark-6776 and squashes the following commits: 360fe18 [Cheng Lian] Adds ParquetHiveCompatibilitySuite c6fbc06 [Cheng Lian] Removes WIP file committed by mistake b8c1295 [Cheng Lian] Excludes the whole parquet package from MiMa 598c3e8 [Cheng Lian] Adds extra Maven repo for hadoop-lzo, which is a transitive dependency of parquet-thrift 926af87 [Cheng Lian] Simplifies Parquet compatibility test suites 7946ee1 [Cheng Lian] Fixes Scala styling issues 3d7ab36 [Cheng Lian] Fixes .rat-excludes a8f13bb [Cheng Lian] Using Parquet writer API to do compatibility tests f2208cd [Cheng Lian] Adds README.md for Thrift/Avro code generation 1d390aa [Cheng Lian] Adds parquet-thrift compatibility test 440f7b3 [Cheng Lian] Adds generated files to .rat-excludes 13b9121 [Cheng Lian] Adds ParquetAvroCompatibilitySuite 06cfe9d [Cheng Lian] Adds comments about TimestampType handling a099d3e [Cheng Lian] More comments 0cc1b37 [Cheng Lian] Fixes MiMa checks 884d3e6 [Cheng Lian] Fixes styling issue and reverts unnecessary changes 802cbd7 [Cheng Lian] Fixes bugs related to schema merging and empty requested columns 38fe1e7 [Cheng Lian] Adds explicit return type 7fb21f1 [Cheng Lian] Reverts an unnecessary debugging change 1781dff [Cheng Lian] Adds test case for SPARK-8811 6437d4b [Cheng Lian] Assembles requested schema from Parquet file schema bcac49f [Cheng Lian] Removes the 16-byte restriction of decimals a74fb2c [Cheng Lian] More comments 0525346 [Cheng Lian] Removes old Parquet record converters 03c3bd9 [Cheng Lian] Refactors Parquet read path to implement backwards-compatibility rules
* [SPARK-8700][ML] Disable feature scaling in Logistic RegressionDB Tsai2015-07-081-0/+2
| | | | | | | | | | | | | | | | | | | | All compressed sensing applications, and some of the regression use-cases will have better result by turning the feature scaling off. However, if we implement this naively by training the dataset without doing any standardization, the rate of convergency will not be good. This can be implemented by still standardizing the training dataset but we penalize each component differently to get effectively the same objective function but a better numerical problem. As a result, for those columns with high variances, they will be penalized less, and vice versa. Without this, since all the features are standardized, so they will be penalized the same. In R, there is an option for this. `standardize` Logical flag for x variable standardization, prior to fitting the model sequence. The coefficients are always returned on the original scale. Default is standardize=TRUE. If variables are in the same units already, you might not wish to standardize. See details below for y standardization with family="gaussian". +cc holdenk mengxr jkbradley Author: DB Tsai <dbt@netflix.com> Closes #7080 from dbtsai/lors and squashes the following commits: 877e6c7 [DB Tsai] repahse the doc 7cf45f2 [DB Tsai] address feedback 78d75c9 [DB Tsai] small change c2c9e60 [DB Tsai] style 6e1a8e0 [DB Tsai] first commit
* [SPARK-8479] [MLLIB] Add numNonzeros and numActives to linalg.MatricesMechCoder2015-07-021-0/+6
| | | | | | | | | | | | | Matrices allow zeros to be stored in values. Sometimes a method is handy to check if the numNonZeros are same as number of Active values. Author: MechCoder <manojkumarsivaraj334@gmail.com> Closes #6904 from MechCoder/nnz_matrix and squashes the following commits: 252c6b7 [MechCoder] Add to MiMa excludes e2390f5 [MechCoder] Use count instead of foreach 2f62b2f [MechCoder] Add to MiMa excludes d6e96ef [MechCoder] [SPARK-8479] Add numNonzeros and numActives to linalg.Matrices
* [SPARK-6777] [SQL] Implements backwards compatibility rules in ↵Cheng Lian2015-06-241-1/+6
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | CatalystSchemaConverter This PR introduces `CatalystSchemaConverter` for converting Parquet schema to Spark SQL schema and vice versa. Original conversion code in `ParquetTypesConverter` is removed. Benefits of the new version are: 1. When converting Spark SQL schemas, it generates standard Parquet schemas conforming to [the most updated Parquet format spec] [1]. Converting to old style Parquet schemas is also supported via feature flag `spark.sql.parquet.followParquetFormatSpec` (which is set to `false` for now, and should be set to `true` after both read and write paths are fixed). Note that although this version of Parquet format spec hasn't been officially release yet, Parquet MR 1.7.0 already sticks to it. So it should be safe to follow. 1. It implements backwards-compatibility rules described in the most updated Parquet format spec. Thus can recognize more schema patterns generated by other/legacy systems/tools. 1. Code organization follows convention used in [parquet-mr] [2], which is easier to follow. (Structure of `CatalystSchemaConverter` is similar to `AvroSchemaConverter`). To fully implement backwards-compatibility rules in both read and write path, we also need to update `CatalystRowConverter` (which is responsible for converting Parquet records to `Row`s), `RowReadSupport`, and `RowWriteSupport`. These would be done in follow-up PRs. TODO - [x] More schema conversion test cases for legacy schema patterns. [1]: https://github.com/apache/parquet-format/blob/ea095226597fdbecd60c2419d96b54b2fdb4ae6c/LogicalTypes.md [2]: https://github.com/apache/parquet-mr/ Author: Cheng Lian <lian@databricks.com> Closes #6617 from liancheng/spark-6777 and squashes the following commits: 2a2062d [Cheng Lian] Don't convert decimals without precision information b60979b [Cheng Lian] Adds a constructor which accepts a Configuration, and fixes default value of assumeBinaryIsString 743730f [Cheng Lian] Decimal scale shouldn't be larger than precision a104a9e [Cheng Lian] Fixes Scala style issue 1f71d8d [Cheng Lian] Adds feature flag to allow falling back to old style Parquet schema conversion ba84f4b [Cheng Lian] Fixes MapType schema conversion bug 13cb8d5 [Cheng Lian] Fixes MiMa failure 81de5b0 [Cheng Lian] Fixes UDT, workaround read path, and add tests 28ef95b [Cheng Lian] More AnalysisExceptions b10c322 [Cheng Lian] Replaces require() with analysisRequire() which throws AnalysisException cceaf3f [Cheng Lian] Implements backwards compatibility rules in CatalystSchemaConverter
* [SPARK-7888] Be able to disable intercept in linear regression in ml packageHolden Karau2015-06-231-0/+5
| | | | | | | | | | | | | | | | | | | Author: Holden Karau <holden@pigscanfly.ca> Closes #6927 from holdenk/SPARK-7888-Be-able-to-disable-intercept-in-Linear-Regression-in-ML-package and squashes the following commits: 0ad384c [Holden Karau] Add MiMa excludes 4016fac [Holden Karau] Switch to wild card import, remove extra blank lines ae5baa8 [Holden Karau] CR feedback, move the fitIntercept down rather than changing ymean and etc above f34971c [Holden Karau] Fix some more long lines 319bd3f [Holden Karau] Fix long lines 3bb9ee1 [Holden Karau] Update the regression suite tests 7015b9f [Holden Karau] Our code performs the same with R, except we need more than one data point but that seems reasonable 0b0c8c0 [Holden Karau] fix the issue with the sample R code e2140ba [Holden Karau] Add a test, it fails! 5e84a0b [Holden Karau] Write out thoughts and use the correct trait 91ffc0a [Holden Karau] more murh 006246c [Holden Karau] murp?
* [SPARK-8307] [SQL] improve timestamp from parquetDavies Liu2015-06-221-1/+11
| | | | | | | | | | | | | | | | | | | | | | | | | | | This PR change to convert julian day to unix timestamp directly (without Calendar and Timestamp). cc adrian-wang rxin Author: Davies Liu <davies@databricks.com> Closes #6759 from davies/improve_ts and squashes the following commits: 849e301 [Davies Liu] Merge branch 'master' of github.com:apache/spark into improve_ts b0e4cad [Davies Liu] Merge branch 'master' of github.com:apache/spark into improve_ts 8e2d56f [Davies Liu] address comments 634b9f5 [Davies Liu] fix mima 4891efb [Davies Liu] address comment bfc437c [Davies Liu] fix build ae5979c [Davies Liu] Merge branch 'master' of github.com:apache/spark into improve_ts 602b969 [Davies Liu] remove jodd 2f2e48c [Davies Liu] fix test 8ace611 [Davies Liu] fix mima 212143b [Davies Liu] fix mina c834108 [Davies Liu] Merge branch 'master' of github.com:apache/spark into improve_ts a3171b8 [Davies Liu] Merge branch 'master' of github.com:apache/spark into improve_ts 5233974 [Davies Liu] fix scala style 361fd62 [Davies Liu] address comments ea196d4 [Davies Liu] improve timestamp from parquet
* [SPARK-8127] [STREAMING] [KAFKA] KafkaRDD optimize count() take() isEmpty()cody koeninger2015-06-191-0/+3
| | | | | | | | | | | | | | | | …ed KafkaRDD methods. Possible fix for [SPARK-7122], but probably a worthwhile optimization regardless. Author: cody koeninger <cody@koeninger.org> Closes #6632 from koeninger/kafka-rdd-count and squashes the following commits: 321340d [cody koeninger] [SPARK-8127][Streaming][Kafka] additional test of ordering of take() 5a05d0f [cody koeninger] [SPARK-8127][Streaming][Kafka] additional test of isEmpty f68bd32 [cody koeninger] [Streaming][Kafka][SPARK-8127] code cleanup 9555b73 [cody koeninger] Merge branch 'master' into kafka-rdd-count 253031d [cody koeninger] [Streaming][Kafka][SPARK-8127] mima exclusion for change to private method 8974b9e [cody koeninger] [Streaming][Kafka][SPARK-8127] check offset ranges before constructing KafkaRDD c3768c5 [cody koeninger] [Streaming][Kafka] Take advantage of offset range info for size-related KafkaRDD methods. Possible fix for [SPARK-7122], but probably a worthwhile optimization regardless.
* [SPARK-2808] [STREAMING] [KAFKA] cleanup tests fromcody koeninger2015-06-071-0/+3
| | | | | | | | | | | | | | see if requiring producer acks eliminates the need for waitUntilLeaderOffset calls in tests Author: cody koeninger <cody@koeninger.org> Closes #5921 from koeninger/kafka-0.8.2-test-cleanup and squashes the following commits: 1e89dc8 [cody koeninger] Merge branch 'master' into kafka-0.8.2-test-cleanup 4662828 [cody koeninger] [Streaming][Kafka] filter mima issue for removal of method from private test class af1e083 [cody koeninger] Merge branch 'master' into kafka-0.8.2-test-cleanup 4298ac2 [cody koeninger] [Streaming][Kafka] update comment to trigger jenkins attempt 1274afb [cody koeninger] [Streaming][Kafka] see if requiring producer acks eliminates the need for waitUntilLeaderOffset calls in tests
* [SPARK-7440][SQL] Remove physical Distinct operator in favor of AggregateReynold Xin2015-06-041-1/+3
| | | | | | | | | | | | | This patch replaces Distinct with Aggregate in the optimizer, so Distinct will become more efficient over time as we optimize Aggregate (via Tungsten). Author: Reynold Xin <rxin@databricks.com> Closes #6637 from rxin/replace-distinct and squashes the following commits: b3cc50e [Reynold Xin] Mima excludes. 93d6117 [Reynold Xin] Code review feedback. 87e4741 [Reynold Xin] [SPARK-7440][SQL] Remove physical Distinct operator in favor of Aggregate.
* [SPARK-7801] [BUILD] Updating versions to SPARK 1.5.0Patrick Wendell2015-06-031-0/+14
| | | | | | | | | | | | | Author: Patrick Wendell <patrick@databricks.com> Closes #6328 from pwendell/spark-1.5-update and squashes the following commits: 2f42d02 [Patrick Wendell] A few more excludes 4bebcf0 [Patrick Wendell] Update to RC4 61aaf46 [Patrick Wendell] Using new release candidate 55f1610 [Patrick Wendell] Another exclude 04b4f04 [Patrick Wendell] More issues with transient 1.4 changes 36f549b [Patrick Wendell] [SPARK-7801] [BUILD] Updating versions to SPARK 1.5.0
* [SPARK-7910] [TINY] [JAVAAPI] expose partitioner information in javarddHolden Karau2015-05-291-0/+2
| | | | | | | | | | | Author: Holden Karau <holden@pigscanfly.ca> Closes #6464 from holdenk/SPARK-7910-expose-partitioner-information-in-javardd and squashes the following commits: de1e644 [Holden Karau] Fix the test to get the partitioner bdb31cc [Holden Karau] Add Mima exclude for the new method 347ef4c [Holden Karau] Add a quick little test for the partitioner JavaAPI f49dca9 [Holden Karau] Add partitoner information to JavaRDDLike and fix some whitespace
* [SPARK-7805] [SQL] Move SQLTestUtils.scala and ParquetTest.scala to src/testYin Huai2015-05-241-1/+4
| | | | | | | | | | | | | https://issues.apache.org/jira/browse/SPARK-7805 Because `sql/hive`'s tests depend on the test jar of `sql/core`, we do not need to store `SQLTestUtils` and `ParquetTest` in `src/main`. We should only add stuff that will be needed by `sql/console` or Python tests (for Python, we need it in `src/main`, right? davies). Author: Yin Huai <yhuai@databricks.com> Closes #6334 from yhuai/SPARK-7805 and squashes the following commits: af6d0c9 [Yin Huai] mima b86746a [Yin Huai] Move SQLTestUtils.scala and ParquetTest.scala to src/test.
* [SPARK-7681] [MLLIB] remove mima excludes for 1.3Xiangrui Meng2015-05-191-8/+1
| | | | | | | | | | There excludes are unnecessary for 1.3 because the changes were made in 1.4.x. Author: Xiangrui Meng <meng@databricks.com> Closes #6254 from mengxr/SPARK-7681-mima and squashes the following commits: 7f0cea0 [Xiangrui Meng] remove mima excludes for 1.3
* [SPARK-7681] [MLLIB] Add SparseVector support for gemvLiang-Chi Hsieh2015-05-181-2/+16
| | | | | | | | | | | | | | | | | | JIRA: https://issues.apache.org/jira/browse/SPARK-7681 Author: Liang-Chi Hsieh <viirya@gmail.com> Closes #6209 from viirya/sparsevector_gemv and squashes the following commits: ce0bb8b [Liang-Chi Hsieh] Still need to scal y when beta is 0.0 because it clears out y. b890e63 [Liang-Chi Hsieh] Do not delete multiply for DenseVector. 57a8c1e [Liang-Chi Hsieh] Add MimaExcludes for v1.4. 458d1ae [Liang-Chi Hsieh] List DenseMatrix.multiply and SparseMatrix.multiply to MimaExcludes too. 054f05d [Liang-Chi Hsieh] Fix scala style. 410381a [Liang-Chi Hsieh] Address comments. Make Matrix.multiply more generalized. 4616696 [Liang-Chi Hsieh] Add support for SparseVector with SparseMatrix. 5d6d07a [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into sparsevector_gemv c069507 [Liang-Chi Hsieh] Add SparseVector support for gemv with DenseMatrix.
* [SPARK-6888] [SQL] Make the jdbc driver handling user-definableRene Treffer2015-05-181-0/+8
| | | | | | | | | | | | | | | | | | | | | | | Replace the DriverQuirks with JdbcDialect(s) (and MySQLDialect/PostgresDialect) and allow developers to change the dialects on the fly (for new JDBCRRDs only). Some types (like an unsigned 64bit number) can be trivially mapped to java. The status quo is that the RRD will fail to load. This patch makes it possible to overwrite the type mapping to read e.g. 64Bit numbers as strings and handle them afterwards in software. JDBCSuite has an example that maps all types to String, which should always work (at the cost of extra code afterwards). As a side effect it should now be possible to develop simple dialects out-of-tree and even with spark-shell. Author: Rene Treffer <treffer@measite.de> Closes #5555 from rtreffer/jdbc-dialects and squashes the following commits: 3cbafd7 [Rene Treffer] [SPARK-6888] ignore classes belonging to changed API in MIMA report fe7e2e8 [Rene Treffer] [SPARK-6888] Make the jdbc driver handling user-definable
* [SPARK-7081] Faster sort-based shuffle path using binary processing ↵Josh Rosen2015-05-131-0/+6
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | cache-aware sort This patch introduces a new shuffle manager that enhances the existing sort-based shuffle with a new cache-friendly sort algorithm that operates directly on binary data. The goals of this patch are to lower memory usage and Java object overheads during shuffle and to speed up sorting. It also lays groundwork for follow-up patches that will enable end-to-end processing of serialized records. The new shuffle manager, `UnsafeShuffleManager`, can be enabled by setting `spark.shuffle.manager=tungsten-sort` in SparkConf. The new shuffle manager uses directly-managed memory to implement several performance optimizations for certain types of shuffles. In cases where the new performance optimizations cannot be applied, the new shuffle manager delegates to SortShuffleManager to handle those shuffles. UnsafeShuffleManager's optimizations will apply when _all_ of the following conditions hold: - The shuffle dependency specifies no aggregation or output ordering. - The shuffle serializer supports relocation of serialized values (this is currently supported by KryoSerializer and Spark SQL's custom serializers). - The shuffle produces fewer than 16777216 output partitions. - No individual record is larger than 128 MB when serialized. In addition, extra spill-merging optimizations are automatically applied when the shuffle compression codec supports concatenation of serialized streams. This is currently supported by Spark's LZF serializer. At a high-level, UnsafeShuffleManager's design is similar to Spark's existing SortShuffleManager. In sort-based shuffle, incoming records are sorted according to their target partition ids, then written to a single map output file. Reducers fetch contiguous regions of this file in order to read their portion of the map output. In cases where the map output data is too large to fit in memory, sorted subsets of the output can are spilled to disk and those on-disk files are merged to produce the final output file. UnsafeShuffleManager optimizes this process in several ways: - Its sort operates on serialized binary data rather than Java objects, which reduces memory consumption and GC overheads. This optimization requires the record serializer to have certain properties to allow serialized records to be re-ordered without requiring deserialization. See SPARK-4550, where this optimization was first proposed and implemented, for more details. - It uses a specialized cache-efficient sorter (UnsafeShuffleExternalSorter) that sorts arrays of compressed record pointers and partition ids. By using only 8 bytes of space per record in the sorting array, this fits more of the array into cache. - The spill merging procedure operates on blocks of serialized records that belong to the same partition and does not need to deserialize records during the merge. - When the spill compression codec supports concatenation of compressed data, the spill merge simply concatenates the serialized and compressed spill partitions to produce the final output partition. This allows efficient data copying methods, like NIO's `transferTo`, to be used and avoids the need to allocate decompression or copying buffers during the merge. The shuffle read path is unchanged. This patch is similar to [SPARK-4550](http://issues.apache.org/jira/browse/SPARK-4550) / #4450 but uses a slightly different implementation. The `unsafe`-based implementation featured in this patch lays the groundwork for followup patches that will enable sorting to operate on serialized data pages that will be prepared by Spark SQL's new `unsafe` operators (such as the new aggregation operator introduced in #5725). ### Future work There are several tasks that build upon this patch, which will be left to future work: - [SPARK-7271](https://issues.apache.org/jira/browse/SPARK-7271) Redesign / extend the shuffle interfaces to accept binary data as input. The goal here is to let us bypass serialization steps in cases where the sort input is produced by an operator that operates directly on binary data. - Extension / redesign of the `Serializer` API. We can add new methods which allow serializers to determine the size requirements for serializing objects and for serializing objects directly to a specified memory address (similar to how `UnsafeRowConverter` works in Spark SQL). <!-- Reviewable:start --> [<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/5868) <!-- Reviewable:end --> Author: Josh Rosen <joshrosen@databricks.com> Closes #5868 from JoshRosen/unsafe-sort and squashes the following commits: ef0a86e [Josh Rosen] Fix scalastyle errors 7610f2f [Josh Rosen] Add tests for proper cleanup of shuffle data. d494ffe [Josh Rosen] Fix deserialization of JavaSerializer instances. 52a9981 [Josh Rosen] Fix some bugs in the address packing code. 51812a7 [Josh Rosen] Change shuffle manager sort name to tungsten-sort 4023fa4 [Josh Rosen] Add @Private annotation to some Java classes. de40b9d [Josh Rosen] More comments to try to explain metrics code df07699 [Josh Rosen] Attempt to clarify confusing metrics update code 5e189c6 [Josh Rosen] Track time spend closing / flushing files; split TimeTrackingOutputStream into separate file. d5779c6 [Josh Rosen] Merge remote-tracking branch 'origin/master' into unsafe-sort c2ce78e [Josh Rosen] Fix a missed usage of MAX_PARTITION_ID e3b8855 [Josh Rosen] Cleanup in UnsafeShuffleWriter 4a2c785 [Josh Rosen] rename 'sort buffer' to 'pointer array' 6276168 [Josh Rosen] Remove ability to disable spilling in UnsafeShuffleExternalSorter. 57312c9 [Josh Rosen] Clarify fileBufferSize units 2d4e4f4 [Josh Rosen] Address some minor comments in UnsafeShuffleExternalSorter. fdcac08 [Josh Rosen] Guard against overflow when expanding sort buffer. 85da63f [Josh Rosen] Cleanup in UnsafeShuffleSorterIterator. 0ad34da [Josh Rosen] Fix off-by-one in nextInt() call 56781a1 [Josh Rosen] Rename UnsafeShuffleSorter to UnsafeShuffleInMemorySorter e995d1a [Josh Rosen] Introduce MAX_SHUFFLE_OUTPUT_PARTITIONS. e58a6b4 [Josh Rosen] Add more tests for PackedRecordPointer encoding. 4f0b770 [Josh Rosen] Attempt to implement proper shuffle write metrics. d4e6d89 [Josh Rosen] Update to bit shifting constants 69d5899 [Josh Rosen] Remove some unnecessary override vals 8531286 [Josh Rosen] Add tests that automatically trigger spills. 7c953f9 [Josh Rosen] Add test that covers UnsafeShuffleSortDataFormat.swap(). e1855e5 [Josh Rosen] Fix a handful of misc. IntelliJ inspections 39434f9 [Josh Rosen] Avoid integer multiplication overflow in getMemoryUsage (thanks FindBugs!) 1e3ad52 [Josh Rosen] Delete unused ByteBufferOutputStream class. ea4f85f [Josh Rosen] Roll back an unnecessary change in Spillable. ae538dc [Josh Rosen] Document UnsafeShuffleManager. ec6d626 [Josh Rosen] Add notes on maximum # of supported shuffle partitions. 0d4d199 [Josh Rosen] Bump up shuffle.memoryFraction to make tests pass. b3b1924 [Josh Rosen] Properly implement close() and flush() in DummySerializerInstance. 1ef56c7 [Josh Rosen] Revise compression codec support in merger; test cross product of configurations. b57c17f [Josh Rosen] Disable some overly-verbose logs that rendered DEBUG useless. f780fb1 [Josh Rosen] Add test demonstrating which compression codecs support concatenation. 4a01c45 [Josh Rosen] Remove unnecessary log message 27b18b0 [Josh Rosen] That for inserting records AT the max record size. fcd9a3c [Josh Rosen] Add notes + tests for maximum record / page sizes. 9d1ee7c [Josh Rosen] Fix MiMa excludes for ShuffleWriter change fd4bb9e [Josh Rosen] Use own ByteBufferOutputStream rather than Kryo's 67d25ba [Josh Rosen] Update Exchange operator's copying logic to account for new shuffle manager 8f5061a [Josh Rosen] Strengthen assertion to check partitioning 01afc74 [Josh Rosen] Actually read data in UnsafeShuffleWriterSuite 1929a74 [Josh Rosen] Update to reflect upstream ShuffleBlockManager -> ShuffleBlockResolver rename. e8718dd [Josh Rosen] Merge remote-tracking branch 'origin/master' into unsafe-sort 9b7ebed [Josh Rosen] More defensive programming RE: cleaning up spill files and memory after errors 7cd013b [Josh Rosen] Begin refactoring to enable proper tests for spilling. 722849b [Josh Rosen] Add workaround for transferTo() bug in merging code; refactor tests. 9883e30 [Josh Rosen] Merge remote-tracking branch 'origin/master' into unsafe-sort b95e642 [Josh Rosen] Refactor and document logic that decides when to spill. 1ce1300 [Josh Rosen] More minor cleanup 5e8cf75 [Josh Rosen] More minor cleanup e67f1ea [Josh Rosen] Remove upper type bound in ShuffleWriter interface. cfe0ec4 [Josh Rosen] Address a number of minor review comments: 8a6fe52 [Josh Rosen] Rename UnsafeShuffleSpillWriter to UnsafeShuffleExternalSorter 11feeb6 [Josh Rosen] Update TODOs related to shuffle write metrics. b674412 [Josh Rosen] Merge remote-tracking branch 'origin/master' into unsafe-sort aaea17b [Josh Rosen] Add comments to UnsafeShuffleSpillWriter. 4f70141 [Josh Rosen] Fix merging; now passes UnsafeShuffleSuite tests. 133c8c9 [Josh Rosen] WIP towards testing UnsafeShuffleWriter. f480fb2 [Josh Rosen] WIP in mega-refactoring towards shuffle-specific sort. 57f1ec0 [Josh Rosen] WIP towards packed record pointers for use in optimized shuffle sort. 69232fd [Josh Rosen] Enable compressible address encoding for off-heap mode. 7ee918e [Josh Rosen] Re-order imports in tests 3aeaff7 [Josh Rosen] More refactoring and cleanup; begin cleaning iterator interfaces 3490512 [Josh Rosen] Misc. cleanup f156a8f [Josh Rosen] Hacky metrics integration; refactor some interfaces. 2776aca [Josh Rosen] First passing test for ExternalSorter. 5e100b2 [Josh Rosen] Super-messy WIP on external sort 595923a [Josh Rosen] Remove some unused variables. 8958584 [Josh Rosen] Fix bug in calculating free space in current page. f17fa8f [Josh Rosen] Add missing newline c2fca17 [Josh Rosen] Small refactoring of SerializerPropertiesSuite to enable test re-use: b8a09fe [Josh Rosen] Back out accidental log4j.properties change bfc12d3 [Josh Rosen] Add tests for serializer relocation property. 240864c [Josh Rosen] Remove PrefixComputer and require prefix to be specified as part of insert() 1433b42 [Josh Rosen] Store record length as int instead of long. 026b497 [Josh Rosen] Re-use a buffer in UnsafeShuffleWriter 0748458 [Josh Rosen] Port UnsafeShuffleWriter to Java. 87e721b [Josh Rosen] Renaming and comments d3cc310 [Josh Rosen] Flag that SparkSqlSerializer2 supports relocation e2d96ca [Josh Rosen] Expand serializer API and use new function to help control when new UnsafeShuffle path is used. e267cee [Josh Rosen] Fix compilation of UnsafeSorterSuite 9c6cf58 [Josh Rosen] Refactor to use DiskBlockObjectWriter. 253f13e [Josh Rosen] More cleanup 8e3ec20 [Josh Rosen] Begin code cleanup. 4d2f5e1 [Josh Rosen] WIP 3db12de [Josh Rosen] Minor simplification and sanity checks in UnsafeSorter 767d3ca [Josh Rosen] Fix invalid range in UnsafeSorter. e900152 [Josh Rosen] Add test for empty iterator in UnsafeSorter 57a4ea0 [Josh Rosen] Make initialSize configurable in UnsafeSorter abf7bfe [Josh Rosen] Add basic test case. 81d52c5 [Josh Rosen] WIP on UnsafeSorter
* [SQL] Move some classes into packages that are more appropriate.Reynold Xin2015-05-131-1/+4
| | | | | | | | | | | | | | | | JavaTypeInference into catalyst types.DateUtils into catalyst CacheManager into execution DefaultParserDialect into catalyst Author: Reynold Xin <rxin@databricks.com> Closes #6108 from rxin/sql-rename and squashes the following commits: 3fc9613 [Reynold Xin] Fixed import ordering. 83d9ff4 [Reynold Xin] Fixed codegen tests. e271e86 [Reynold Xin] mima f4e24a6 [Reynold Xin] [SQL] Move some classes into packages that are more appropriate.
* [SPARK-7567] [SQL] Migrating Parquet data source to FSBasedRelationCheng Lian2015-05-131-0/+6
| | | | | | | | | | | | | | | | | | | | | | | | | This PR migrates Parquet data source to the newly introduced `FSBasedRelation`. `FSBasedParquetRelation` is created to replace `ParquetRelation2`. Major differences are: 1. Partition discovery code has been factored out to `FSBasedRelation` 1. `AppendingParquetOutputFormat` is not used now. Instead, an anonymous subclass of `ParquetOutputFormat` is used to handle appending and writing dynamic partitions 1. When scanning partitioned tables, `FSBasedParquetRelation.buildScan` only builds an `RDD[Row]` for a single selected partition 1. `FSBasedParquetRelation` doesn't rely on Catalyst expressions for filter push down, thus it doesn't extend `CatalystScan` anymore After migrating `JSONRelation` (which extends `CatalystScan`), we can remove `CatalystScan`. <!-- Reviewable:start --> [<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/6090) <!-- Reviewable:end --> Author: Cheng Lian <lian@databricks.com> Closes #6090 from liancheng/parquet-migration and squashes the following commits: 6063f87 [Cheng Lian] Casts to OutputCommitter rather than FileOutputCommtter bfd1cf0 [Cheng Lian] Fixes compilation error introduced while rebasing f9ea56e [Cheng Lian] Adds ParquetRelation2 related classes to MiMa check whitelist 261d8c1 [Cheng Lian] Minor bug fix and more tests db65660 [Cheng Lian] Migrates Parquet data source to FSBasedRelation
* [SPARK-3928] [SPARK-5182] [SQL] Partitioning support for the data sources APICheng Lian2015-05-131-1/+13
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This PR adds partitioning support for the external data sources API. It aims to simplify development of file system based data sources, and provide first class partitioning support for both read path and write path. Existing data sources like JSON and Parquet can be simplified with this work. ## New features provided 1. Hive compatible partition discovery This actually generalizes the partition discovery strategy used in Parquet data source in Spark 1.3.0. 1. Generalized partition pruning optimization Now partition pruning is handled during physical planning phase. Specific data sources don't need to worry about this harness anymore. (This also implies that we can remove `CatalystScan` after migrating the Parquet data source, since now we don't need to pass Catalyst expressions to data source implementations.) 1. Insertion with dynamic partitions When inserting data to a `FSBasedRelation`, data can be partitioned dynamically by specified partition columns. ## New structures provided ### Developer API 1. `FSBasedRelation` Base abstract class for file system based data sources. 1. `OutputWriter` Base abstract class for output row writers, responsible for writing a single row object. 1. `FSBasedRelationProvider` A new relation provider for `FSBasedRelation` subclasses. Note that data sources extending `FSBasedRelation` don't need to extend `RelationProvider` and `SchemaRelationProvider`. ### User API New overloaded versions of 1. `DataFrame.save()` 1. `DataFrame.saveAsTable()` 1. `SQLContext.load()` are provided to allow users to save/load DataFrames with user defined dynamic partition columns. ### Spark SQL query planning 1. `InsertIntoFSBasedRelation` Used to implement write path for `FSBasedRelation`s. 1. New rules for `FSBasedRelation` in `DataSourceStrategy` These are added to hook `FSBasedRelation` into physical query plan in read path, and perform partition pruning. ## TODO - [ ] Use scratch directories when overwriting a table with data selected from itself. Currently, this is not supported, because the table been overwritten is always deleted before writing any data to it. - [ ] When inserting with dynamic partition columns, use external sorter to group the data first. This ensures that we only need to open a single `OutputWriter` at a time. For data sources like Parquet, `OutputWriter`s can be quite memory consuming. One issue is that, this approach breaks the row distribution in the original DataFrame. However, we did't promise to preserve data distribution when writing a DataFrame. - [x] More tests. Specifically, test cases for - [x] Self-join - [x] Loading partitioned relations with a subset of partition columns stored in data files. - [x] `SQLContext.load()` with user defined dynamic partition columns. ## Parquet data source migration Parquet data source migration is covered in PR https://github.com/liancheng/spark/pull/6, which is against this PR branch and for preview only. A formal PR need to be made after this one is merged. Author: Cheng Lian <lian@databricks.com> Closes #5526 from liancheng/partitioning-support and squashes the following commits: 5351a1b [Cheng Lian] Fixes compilation error introduced while rebasing 1f9b1a5 [Cheng Lian] Tweaks data schema passed to FSBasedRelations 43ba50e [Cheng Lian] Avoids serializing generated projection code edf49e7 [Cheng Lian] Removed commented stale code block 348a922 [Cheng Lian] Adds projection in FSBasedRelation.buildScan(requiredColumns, inputPaths) ad4d4de [Cheng Lian] Enables HDFS style globbing 8d12e69 [Cheng Lian] Fixes compilation error c71ac6c [Cheng Lian] Addresses comments from @marmbrus 7552168 [Cheng Lian] Fixes typo in MimaExclude.scala 0349e09 [Cheng Lian] Fixes compilation error introduced while rebasing 52b0c9b [Cheng Lian] Adjusts project/MimaExclude.scala c466de6 [Cheng Lian] Addresses comments bc3f9b4 [Cheng Lian] Uses projection to separate partition columns and data columns while inserting rows 795920a [Cheng Lian] Fixes compilation error after rebasing 0b8cd70 [Cheng Lian] Adds Scala/Catalyst row conversion when writing non-partitioned tables fa543f3 [Cheng Lian] Addresses comments 5849dd0 [Cheng Lian] Fixes doc typos. Fixes partition discovery refresh. 51be443 [Cheng Lian] Replaces FSBasedRelation.outputCommitterClass with FSBasedRelation.prepareForWrite c4ed4fe [Cheng Lian] Bug fixes and a new test suite a29e663 [Cheng Lian] Bug fix: should only pass actuall data files to FSBaseRelation.buildScan 5f423d3 [Cheng Lian] Bug fixes. Lets data source to customize OutputCommitter rather than OutputFormat 54c3d7b [Cheng Lian] Enforces that FileOutputFormat must be used be0c268 [Cheng Lian] Uses TaskAttempContext rather than Configuration in OutputWriter.init 0bc6ad1 [Cheng Lian] Resorts to new Hadoop API, and now FSBasedRelation can customize output format class f320766 [Cheng Lian] Adds prepareForWrite() hook, refactored writer containers 422ff4a [Cheng Lian] Fixes style issue ce52353 [Cheng Lian] Adds new SQLContext.load() overload with user defined dynamic partition columns 8d2ff71 [Cheng Lian] Merges partition columns when reading partitioned relations ca1805b [Cheng Lian] Removes duplicated partition discovery code in new Parquet f18dec2 [Cheng Lian] More strict schema checking b746ab5 [Cheng Lian] More tests 9b487bf [Cheng Lian] Fixes compilation errors introduced while rebasing ea6c8dd [Cheng Lian] Removes remote debugging stuff 327bb1d [Cheng Lian] Implements partitioning support for data sources API 3c5073a [Cheng Lian] Fixes SaveModes used in test cases fb5a607 [Cheng Lian] Fixes compilation error 9d17607 [Cheng Lian] Adds the contract that OutputWriter should have zero-arg constructor 5de194a [Cheng Lian] Forgot Apache licence header 95d0b4d [Cheng Lian] Renames PartitionedSchemaRelationProvider to FSBasedRelationProvider 770b5ba [Cheng Lian] Adds tests for FSBasedRelation 3ba9bbf [Cheng Lian] Adds DataFrame.saveAsTable() overrides which support partitioning 1b8231f [Cheng Lian] Renames FSBasedPrunedFilteredScan to FSBasedRelation aa8ba9a [Cheng Lian] Javadoc fix 012ed2d [Cheng Lian] Adds PartitioningOptions 7dd8dd5 [Cheng Lian] Adds new interfaces and stub methods for data sources API partitioning support
* [SPARK-7530] [STREAMING] Added StreamingContext.getState() to expose the ↵Tathagata Das2015-05-111-0/+4
| | | | | | | | | | | | | | | | | | | | | | current state of the context Author: Tathagata Das <tathagata.das1565@gmail.com> Closes #6058 from tdas/SPARK-7530 and squashes the following commits: 80ee0e6 [Tathagata Das] STARTED --> ACTIVE 3da6547 [Tathagata Das] Added synchronized dd88444 [Tathagata Das] Added more docs e1a8505 [Tathagata Das] Fixed comment length 89f9980 [Tathagata Das] Change to Java enum and added Java test 7c57351 [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into SPARK-7530 dd4e702 [Tathagata Das] Addressed comments. 3d56106 [Tathagata Das] Added Mima excludes 2b86ba1 [Tathagata Das] Added scala docs. 1722433 [Tathagata Das] Fixed style 976b094 [Tathagata Das] Added license 0585130 [Tathagata Das] Merge remote-tracking branch 'apache-github/master' into SPARK-7530 e0f0a05 [Tathagata Das] Added getState and exposed StreamingContextState
* [SPARK-6908] [SQL] Use isolated Hive clientMichael Armbrust2015-05-071-0/+2
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This PR switches Spark SQL's Hive support to use the isolated hive client interface introduced by #5851, instead of directly interacting with the client. By using this isolated client we can now allow users to dynamically configure the version of Hive that they are connecting to by setting `spark.sql.hive.metastore.version` without the need recompile. This also greatly reduces the surface area for our interaction with the hive libraries, hopefully making it easier to support other versions in the future. Jars for the desired hive version can be configured using `spark.sql.hive.metastore.jars`, which accepts the following options: - a colon-separated list of jar files or directories for hive and hadoop. - `builtin` - attempt to discover the jars that were used to load Spark SQL and use those. This option is only valid when using the execution version of Hive. - `maven` - download the correct version of hive on demand from maven. By default, `builtin` is used for Hive 13. This PR also removes the test step for building against Hive 12, as this will no longer be required to talk to Hive 12 metastores. However, the full removal of the Shim is deferred until a later PR. Remaining TODOs: - Remove the Hive Shims and inline code for Hive 13. - Several HiveCompatibility tests are not yet passing. - `nullformatCTAS` - As detailed below, we now are handling CTAS parsing ourselves instead of hacking into the Hive semantic analyzer. However, we currently only handle the common cases and not things like CTAS where the null format is specified. - `combine1` now leaks state about compression somehow, breaking all subsequent tests. As such we currently add it to the blacklist - `part_inherit_tbl_props` and `part_inherit_tbl_props_with_star` do not work anymore. We are correctly propagating the information - "load_dyn_part14.*" - These tests pass when run on their own, but fail when run with all other tests. It seems our `RESET` mechanism may not be as robust as it used to be? Other required changes: - `CreateTableAsSelect` no longer carries parts of the HiveQL AST with it through the query execution pipeline. Instead, we parse CTAS during the HiveQL conversion and construct a `HiveTable`. The full parsing here is not yet complete as detailed above in the remaining TODOs. Since the operator is Hive specific, it is moved to the hive package. - `Command` is simplified to be a trait that simply acts as a marker for a LogicalPlan that should be eagerly evaluated. Author: Michael Armbrust <michael@databricks.com> Closes #5876 from marmbrus/useIsolatedClient and squashes the following commits: 258d000 [Michael Armbrust] really really correct path handling e56fd4a [Michael Armbrust] getAbsolutePath 5a259f5 [Michael Armbrust] fix typos 81bb366 [Michael Armbrust] comments from vanzin 5f3945e [Michael Armbrust] Merge remote-tracking branch 'origin/master' into useIsolatedClient 4b5cd41 [Michael Armbrust] yin's comments f5de7de [Michael Armbrust] cleanup 11e9c72 [Michael Armbrust] better coverage in versions suite 7e8f010 [Michael Armbrust] better error messages and jar handling e7b3941 [Michael Armbrust] more permisive checking for function registration da91ba7 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into useIsolatedClient 5fe5894 [Michael Armbrust] fix serialization suite 81711c4 [Michael Armbrust] Initial support for running without maven 1d8ae44 [Michael Armbrust] fix final tests? 1c50813 [Michael Armbrust] more comments a3bee70 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into useIsolatedClient a6f5df1 [Michael Armbrust] style ab07f7e [Michael Armbrust] WIP 4d8bf02 [Michael Armbrust] Remove hive 12 compilation 8843a25 [Michael Armbrust] [SPARK-6908] [SQL] Use isolated Hive client
* [Build] Enable MiMa checks for SQLJosh Rosen2015-04-301-0/+16
| | | | | | | | | | | | | | Now that 1.3 has been released, we should enable MiMa checks for the `sql` subproject. Author: Josh Rosen <joshrosen@databricks.com> Closes #5727 from JoshRosen/enable-more-mima-checks and squashes the following commits: 3ad302b [Josh Rosen] Merge remote-tracking branch 'origin/master' into enable-more-mima-checks 0c48e4d [Josh Rosen] Merge remote-tracking branch 'origin/master' into enable-more-mima-checks e276cee [Josh Rosen] Fix SQL MiMa checks via excludes and private[sql] 44d0d01 [Josh Rosen] Add back 'launcher' exclude 1aae027 [Josh Rosen] Enable MiMa checks for launcher and sql projects.
* [SPARK-6756] [MLLIB] add toSparse, toDense, numActives, numNonzeros, and ↵Xiangrui Meng2015-04-281-0/+12
| | | | | | | | | | | | | compressed to Vector Add `compressed` to `Vector` with some other methods: `numActives`, `numNonzeros`, `toSparse`, and `toDense`. jkbradley Author: Xiangrui Meng <meng@databricks.com> Closes #5756 from mengxr/SPARK-6756 and squashes the following commits: 8d4ecbd [Xiangrui Meng] address comment and add mima excludes da54179 [Xiangrui Meng] add toSparse, toDense, numActives, numNonzeros, and compressed to Vector
* [SPARK-7090] [MLLIB] Introduce LDAOptimizer to LDA to further improve ↵Yuhao Yang2015-04-271-0/+4
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | extensibility jira: https://issues.apache.org/jira/browse/SPARK-7090 LDA was implemented with extensibility in mind. And with the development of OnlineLDA and Gibbs Sampling, we are collecting more detailed requirements from different algorithms. As Joseph Bradley jkbradley proposed in https://github.com/apache/spark/pull/4807 and with some further discussion, we'd like to adjust the code structure a little to present the common interface and extension point clearly. Basically class LDA would be a common entrance for LDA computing. And each LDA object will refer to a LDAOptimizer for the concrete algorithm implementation. Users can customize LDAOptimizer with specific parameters and assign it to LDA. Concrete changes: 1. Add a trait `LDAOptimizer`, which defines the common iterface for concrete implementations. Each subClass is a wrapper for a specific LDA algorithm. 2. Move EMOptimizer to file LDAOptimizer and inherits from LDAOptimizer, rename to EMLDAOptimizer. (in case a more generic EMOptimizer comes in the future) -adjust the constructor of EMOptimizer, since all the parameters should be passed in through initialState method. This can avoid unwanted confusion or overwrite. -move the code from LDA.initalState to initalState of EMLDAOptimizer 3. Add property ldaOptimizer to LDA and its getter/setter, and EMLDAOptimizer is the default Optimizer. 4. Change the return type of LDA.run from DistributedLDAModel to LDAModel. Further work: add OnlineLDAOptimizer and other possible Optimizers once ready. Author: Yuhao Yang <hhbyyh@gmail.com> Closes #5661 from hhbyyh/ldaRefactor and squashes the following commits: 0e2e006 [Yuhao Yang] respond to review comments 08a45da [Yuhao Yang] Merge remote-tracking branch 'upstream/master' into ldaRefactor e756ce4 [Yuhao Yang] solve mima exception d74fd8f [Yuhao Yang] Merge remote-tracking branch 'upstream/master' into ldaRefactor 0bb8400 [Yuhao Yang] refactor LDA with Optimizer ec2f857 [Yuhao Yang] protoptype for discussion
* [SPARK-6703][Core] Provide a way to discover existing SparkContext'sIlya Ganelin2015-04-171-0/+4
| | | | | | | | | | | | | | | | | | | | | | | | I've added a static getOrCreate method to the static SparkContext object that allows one to either retrieve a previously created SparkContext or to instantiate a new one with the provided config. The method accepts an optional SparkConf to make usage intuitive. Still working on a test for this, basically want to create a new context from scratch, then ensure that subsequent calls don't overwrite that. Author: Ilya Ganelin <ilya.ganelin@capitalone.com> Closes #5501 from ilganeli/SPARK-6703 and squashes the following commits: db9a963 [Ilya Ganelin] Closing second spark context 1dc0444 [Ilya Ganelin] Added ref equality check 8c884fa [Ilya Ganelin] Made getOrCreate synchronized cb0c6b7 [Ilya Ganelin] Doc updates and code cleanup 270cfe3 [Ilya Ganelin] [SPARK-6703] Documentation fixes 15e8dea [Ilya Ganelin] Updated comments and added MiMa Exclude 0e1567c [Ilya Ganelin] Got rid of unecessary option for AtomicReference dfec4da [Ilya Ganelin] Changed activeContext to AtomicReference 733ec9f [Ilya Ganelin] Fixed some bugs in test code 8be2f83 [Ilya Ganelin] Replaced match with if e92caf7 [Ilya Ganelin] [SPARK-6703] Added test to ensure that getOrCreate both allows creation, retrieval, and a second context if desired a99032f [Ilya Ganelin] Spacing fix d7a06b8 [Ilya Ganelin] Updated SparkConf class to add getOrCreate method. Started test suite implementation
* [Spark-6693][MLlib]add tostring with max lines and width for matrixYuhao Yang2015-04-091-0/+4
| | | | | | | | | | | | | | | | | | | | | | | | | jira: https://issues.apache.org/jira/browse/SPARK-6693 It's kind of annoying when debugging and found you cannot print out the matrix as you want. original toString of Matrix only print like following, 0.17810102596909183 0.5616906241468385 ... (10 total) 0.9692861997823815 0.015558159784155756 ... 0.8513015122819192 0.031523763918528847 ... 0.5396875653953941 0.3267864552779176 ... The def toString(maxLines : Int, maxWidth : Int) is useful when debuging, logging and saving matrix to files. Author: Yuhao Yang <hhbyyh@gmail.com> Closes #5344 from hhbyyh/addToString and squashes the following commits: 19a6836 [Yuhao Yang] remove extra line 6314b21 [Yuhao Yang] add exclude 736c324 [Yuhao Yang] add ut and exclude 420da39 [Yuhao Yang] Merge remote-tracking branch 'upstream/master' into addToString c22f352 [Yuhao Yang] style change 64a9e0f [Yuhao Yang] add specific to string to matrix
* [SPARK-6492][CORE] SparkContext.stop() can deadlock when ↵Ilya Ganelin2015-04-031-0/+4
| | | | | | | | | | | | | | | | | | | | | | DAGSchedulerEventProcessLoop dies I've added a timeout and retry loop around the SparkContext shutdown code that should fix this deadlock. If a SparkContext shutdown is in progress when another thread comes knocking, it will wait for 10 seconds for the lock, then fall through where the outer loop will re-submit the request. Author: Ilya Ganelin <ilya.ganelin@capitalone.com> Closes #5277 from ilganeli/SPARK-6492 and squashes the following commits: 8617a7e [Ilya Ganelin] Resolved merge conflict 2fbab66 [Ilya Ganelin] Added MIMA Exclude a0e2c70 [Ilya Ganelin] Deleted stale imports fa28ce7 [Ilya Ganelin] reverted to just having a single stopped 76fc825 [Ilya Ganelin] Updated to use atomic booleans instead of the synchronized vars 6e8a7f7 [Ilya Ganelin] Removing unecessary null check for now since i'm not fixing stop ordering yet cdf7073 [Ilya Ganelin] [SPARK-6492] Moved stopped=true back to the start of the shutdown sequence so this can be addressed in a seperate PR 7fb795b [Ilya Ganelin] Spacing b7a0c5c [Ilya Ganelin] Import ordering df8224f [Ilya Ganelin] Added comment for added lock 343cb94 [Ilya Ganelin] [SPARK-6492] Added timeout/retry logic to fix a deadlock in SparkContext shutdown
* [SPARK-4655][Core] Split Stage into ShuffleMapStage and ResultStage subclassesIlya Ganelin2015-04-011-1/+5
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Hi all - this patch changes the Stage class to an abstract class and introduces two new classes that extend it: ShuffleMapStage and ResultStage - with the goal of increasing readability of the DAGScheduler class. Their usage is updated within DAGScheduler. Author: Ilya Ganelin <ilya.ganelin@capitalone.com> Author: Ilya Ganelin <ilganeli@gmail.com> Closes #4708 from ilganeli/SPARK-4655 and squashes the following commits: c248924 [Ilya Ganelin] Merge branch 'SPARK-4655' of github.com:ilganeli/spark into SPARK-4655 d930385 [Ilya Ganelin] Fixed merge conflict from a9a765f [Ilya Ganelin] Update DAGScheduler.scala c03563c [Ilya Ganelin] Minor fixeS c39e971 [Ilya Ganelin] Added return typing for public methods 845bc87 [Ilya Ganelin] Merge branch 'SPARK-4655' of github.com:ilganeli/spark into SPARK-4655 e8031d8 [Ilya Ganelin] Minor string fixes 4ec53ac [Ilya Ganelin] Merge remote-tracking branch 'upstream/master' into SPARK-4655 c004f62 [Ilya Ganelin] Update DAGScheduler.scala a2cb03f [Ilya Ganelin] [SPARK-4655] Replaced usages of Nil and eliminated some code reuse 3d5cf20 [Ilya Ganelin] [SPARK-4655] Moved mima exclude to 1.4 6912c55 [Ilya Ganelin] Resolved merge conflict 4bff208 [Ilya Ganelin] Minor stylistic fixes c6fffbb [Ilya Ganelin] newline 41402ad [Ilya Ganelin] Style fixes 02c6981 [Ilya Ganelin] Merge branch 'SPARK-4655' of github.com:ilganeli/spark into SPARK-4655 c755a09 [Ilya Ganelin] Some more stylistic updates and minor refactoring b6257a0 [Ilya Ganelin] Update MimaExcludes.scala 0f0c624 [Ilya Ganelin] Fixed merge conflict 2eba262 [Ilya Ganelin] Merge remote-tracking branch 'upstream/master' into SPARK-4655 6b43d7b [Ilya Ganelin] Got rid of some spaces 6f1a5db [Ilya Ganelin] Revert "More minor formatting and refactoring" 1b3471b [Ilya Ganelin] Merge remote-tracking branch 'upstream/master' into SPARK-4655 c9288e2 [Ilya Ganelin] More minor formatting and refactoring d548caf [Ilya Ganelin] Formatting fix c3ae5c2 [Ilya Ganelin] Explicit typing 0dacaf3 [Ilya Ganelin] Got rid of stale import 6da3a71 [Ilya Ganelin] Trailing whitespace b85c5fe [Ilya Ganelin] Added minor fixes a57dfcd [Ilya Ganelin] Added MiMA exclusion to get around binary compatibility check 83ed849 [Ilya Ganelin] moved braces for consistency 96dd161 [Ilya Ganelin] Fixed minor style error cfd6f10 [Ilya Ganelin] Updated DAGScheduler to use new ResultStage and ShuffleMapStage classes 83494e9 [Ilya Ganelin] Added new Stage classes
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