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* [SPARK-9065][STREAMING][PYSPARK] Add MessageHandler for Kafka Python APIjerryshao2015-11-171-0/+6
| | | | | | | | | | | | Fixed the merge conflicts in #7410 Closes #7410 Author: Shixiong Zhu <shixiong@databricks.com> Author: jerryshao <saisai.shao@intel.com> Author: jerryshao <sshao@hortonworks.com> Closes #9742 from zsxwing/pr7410.
* [SPARK-11732] Removes some MiMa false positivesTimothy Hunter2015-11-171-6/+1
| | | | | | | | This adds an extra filter for private or protected classes. We only filter for package private right now. Author: Timothy Hunter <timhunter@databricks.com> Closes #9697 from thunterdb/spark-11732.
* [SPARK-11766][MLLIB] add toJson/fromJson to Vector/VectorsXiangrui Meng2015-11-171-0/+4
| | | | | | | | This is to support JSON serialization of Param[Vector] in the pipeline API. It could be used for other purposes too. The schema is the same as `VectorUDT`. jkbradley Author: Xiangrui Meng <meng@databricks.com> Closes #9751 from mengxr/SPARK-11766.
* [SPARK-10565][CORE] add missing web UI stats to /api/v1/applications JSONCharles Yeh2015-11-091-0/+3
| | | | | | | | | | I looked at the other endpoints, and they don't seem to be missing any fields. Added fields: ![image](https://cloud.githubusercontent.com/assets/613879/10948801/58159982-82e4-11e5-86dc-62da201af910.png) Author: Charles Yeh <charlesyeh@dropbox.com> Closes #9472 from CharlesYeh/api_vars.
* [SPARK-11541][SQL] Break JdbcDialects.scala into multiple files and mark ↵Reynold Xin2015-11-051-1/+18
| | | | | | | | various dialects as private. Author: Reynold Xin <rxin@databricks.com> Closes #9511 from rxin/SPARK-11541.
* Revert "[SPARK-11469][SQL] Allow users to define nondeterministic udfs."Reynold Xin2015-11-051-47/+0
| | | | This reverts commit 9cf56c96b7d02a14175d40b336da14c2e1c88339.
* [SPARK-11485][SQL] Make DataFrameHolder and DatasetHolder public.Reynold Xin2015-11-041-0/+3
| | | | | | | | These two classes should be public, since they are used in public code. Author: Reynold Xin <rxin@databricks.com> Closes #9445 from rxin/SPARK-11485.
* [SPARK-9492][ML][R] LogisticRegression in R should provide model statisticsYanbo Liang2015-11-041-1/+3
| | | | | | | | Like ml ```LinearRegression```, ```LogisticRegression``` should provide a training summary including feature names and their coefficients. Author: Yanbo Liang <ybliang8@gmail.com> Closes #9303 from yanboliang/spark-9492.
* [SPARK-11469][SQL] Allow users to define nondeterministic udfs.Yin Huai2015-11-021-0/+47
| | | | | | | | This is the first task (https://issues.apache.org/jira/browse/SPARK-11469) of https://issues.apache.org/jira/browse/SPARK-11438 Author: Yin Huai <yhuai@databricks.com> Closes #9393 from yhuai/udfNondeterministic.
* [SPARK-11423] remove MapPartitionsWithPreparationRDDDavies Liu2015-10-301-1/+5
| | | | | | | | | | Since we do not need to preserve a page before calling compute(), MapPartitionsWithPreparationRDD is not needed anymore. This PR basically revert #8543, #8511, #8038, #8011 Author: Davies Liu <davies@databricks.com> Closes #9381 from davies/remove_prepare2.
* [SPARK-10708] Consolidate sort shuffle implementationsJosh Rosen2015-10-221-2/+7
| | | | | | | | There's a lot of duplication between SortShuffleManager and UnsafeShuffleManager. Given that these now provide the same set of functionality, now that UnsafeShuffleManager supports large records, I think that we should replace SortShuffleManager's serialized shuffle implementation with UnsafeShuffleManager's and should merge the two managers together. Author: Josh Rosen <joshrosen@databricks.com> Closes #8829 from JoshRosen/consolidate-sort-shuffle-implementations.
* [SPARK-10921][YARN] Completely remove the use of SparkContext.prefer…Jacek Laskowski2015-10-191-0/+3
| | | | | | | | …redNodeLocationData Author: Jacek Laskowski <jacek.laskowski@deepsense.io> Closes #8976 from jaceklaskowski/SPARK-10921.
* [SPARK-10810] [SPARK-10902] [SQL] Improve session management in SQLDavies Liu2015-10-081-1/+21
| | | | | | | | | | | | | | | | | | | | | This PR improve the sessions management by replacing the thread-local based to one SQLContext per session approach, introduce separated temporary tables and UDFs/UDAFs for each session. A new session of SQLContext could be created by: 1) create an new SQLContext 2) call newSession() on existing SQLContext For HiveContext, in order to reduce the cost for each session, the classloader and Hive client are shared across multiple sessions (created by newSession). CacheManager is also shared by multiple sessions, so cache a table multiple times in different sessions will not cause multiple copies of in-memory cache. Added jars are still shared by all the sessions, because SparkContext does not support sessions. cc marmbrus yhuai rxin Author: Davies Liu <davies@databricks.com> Closes #8909 from davies/sessions.
* [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
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