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* [SPARK-7321][SQL] Add Column expression for conditional statements ↵Reynold Xin2015-05-123-0/+106
| | | | | | | | | | | | | | | | | | | | | | | | | (when/otherwise) This builds on https://github.com/apache/spark/pull/5932 and should close https://github.com/apache/spark/pull/5932 as well. As an example: ```python df.select(when(df['age'] == 2, 3).otherwise(4).alias("age")).collect() ``` Author: Reynold Xin <rxin@databricks.com> Author: kaka1992 <kaka_1992@163.com> Closes #6072 from rxin/when-expr and squashes the following commits: 8f49201 [Reynold Xin] Throw exception if otherwise is applied twice. 0455eda [Reynold Xin] Reset run-tests. bfb9d9f [Reynold Xin] Updated documentation and test cases. 762f6a5 [Reynold Xin] Merge pull request #5932 from kaka1992/IFCASE 95724c6 [kaka1992] Update 8218d0a [kaka1992] Update 801009e [kaka1992] Update 76d6346 [kaka1992] [SPARK-7321][SQL] Add Column expression for conditional statements (if, case)
* [SPARK-7588] Document all SQL/DataFrame public methods with @since tagReynold Xin2015-05-1216-26/+700
| | | | | | | | | | This pull request adds since tag to all public methods/classes in SQL/DataFrame to indicate which version the methods/classes were first added. Author: Reynold Xin <rxin@databricks.com> Closes #6101 from rxin/tbc and squashes the following commits: ed55e11 [Reynold Xin] Add since version to all DataFrame methods.
* [HOTFIX] Use the old Job API to support old Hadoop versionszsxwing2015-05-131-1/+1
| | | | | | | | | | | | #5526 uses `Job.getInstance`, which does not exist in the old Hadoop versions. Just use `new Job` to replace it. cc liancheng Author: zsxwing <zsxwing@gmail.com> Closes #6095 from zsxwing/hotfix and squashes the following commits: b0c2049 [zsxwing] Use the old Job API to support old Hadoop versions
* [SPARK-7484][SQL]Support jdbc connection propertiesVenkata Ramana Gollamudi2015-05-124-31/+148
| | | | | | | | | | | | | | Few jdbc drivers like SybaseIQ support passing username and password only through connection properties. So the same needs to be supported for SQLContext.jdbc, dataframe.createJDBCTable and dataframe.insertIntoJDBC. Added as default arguments or overrided function to support backward compatability. Author: Venkata Ramana Gollamudi <ramana.gollamudi@huawei.com> Closes #6009 from gvramana/add_jdbc_conn_properties and squashes the following commits: 396a0d0 [Venkata Ramana Gollamudi] fixed comments d66dd8c [Venkata Ramana Gollamudi] fixed comments 1b8cd8c [Venkata Ramana Gollamudi] Support jdbc connection properties
* [SPARK-7276] [DATAFRAME] speed up DataFrame.select by collapsing ProjectWenchen Fan2015-05-122-1/+15
| | | | | | | | | | | Author: Wenchen Fan <cloud0fan@outlook.com> Closes #5831 from cloud-fan/7276 and squashes the following commits: ee4a1e1 [Wenchen Fan] fix rebase mistake a3b565d [Wenchen Fan] refactor 99deb5d [Wenchen Fan] add test f1f67ad [Wenchen Fan] fix 7276
* [DataFrame][minor] support column in field accessorWenchen Fan2015-05-122-1/+2
| | | | | | | | | | Minor improvement, now we can use `Column` as extraction expression. Author: Wenchen Fan <cloud0fan@outlook.com> Closes #6080 from cloud-fan/tmp and squashes the following commits: 0fdefb7 [Wenchen Fan] support column in field accessor
* [SPARK-3928] [SPARK-5182] [SQL] Partitioning support for the data sources APICheng Lian2015-05-1313-220/+1313
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 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-7485] [BUILD] Remove pyspark files from assembly.Marcelo Vanzin2015-05-121-8/+0
| | | | | | | | | | | | | | The sbt part of the build is hacky; it basically tricks sbt into generating the zip by using a generator, but returns an empty list for the generated files so that nothing is actually added to the assembly. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #6022 from vanzin/SPARK-7485 and squashes the following commits: 22c1e04 [Marcelo Vanzin] Remove unneeded code. 4893622 [Marcelo Vanzin] [SPARK-7485] [build] Remove pyspark files from assembly.
* [SQL] Rename Dialect -> ParserDialect.Reynold Xin2015-05-112-8/+8
| | | | | | | | Author: Reynold Xin <rxin@databricks.com> Closes #6071 from rxin/parserdialect and squashes the following commits: ca2eb31 [Reynold Xin] Rename Dialect -> ParserDialect.
* [SPARK-7324] [SQL] DataFrame.dropDuplicatesReynold Xin2015-05-112-2/+71
| | | | | | | | | | This should also close https://github.com/apache/spark/pull/5870 Author: Reynold Xin <rxin@databricks.com> Closes #6066 from rxin/dropDups and squashes the following commits: 130692f [Reynold Xin] [SPARK-7324][SQL] DataFrame.dropDuplicates
* Updated DataFrame.saveAsTable Hive warning to include SPARK-7550 ticket.Reynold Xin2015-05-111-6/+6
| | | | | | | | | | So users that are interested in this can track it easily. Author: Reynold Xin <rxin@databricks.com> Closes #6067 from rxin/SPARK-7550 and squashes the following commits: ee0e34c [Reynold Xin] Updated DataFrame.saveAsTable Hive warning to include SPARK-7550 ticket.
* [SPARK-7462][SQL] Update documentation for retaining grouping columns in ↵Reynold Xin2015-05-111-2/+12
| | | | | | | | | | DataFrames. Author: Reynold Xin <rxin@databricks.com> Closes #6062 from rxin/agg-retain-doc and squashes the following commits: 43e511e [Reynold Xin] [SPARK-7462][SQL] Update documentation for retaining grouping columns in DataFrames.
* [SPARK-7084] improve saveAsTable documentationmadhukar2015-05-111-0/+18
| | | | | | | | | | | | Author: madhukar <phatak.dev@gmail.com> Closes #5654 from phatak-dev/master and squashes the following commits: 386f407 [madhukar] #5654 updated for all the methods 2c997c5 [madhukar] Merge branch 'master' of https://github.com/apache/spark 00bc819 [madhukar] Merge branch 'master' of https://github.com/apache/spark 2a802c6 [madhukar] #5654 updated the doc according to comments 866e8df [madhukar] [SPARK-7084] improve saveAsTable documentation
* Update Documentation: leftsemi instead of semijoinLCY Vincent2015-05-111-1/+1
| | | | | | | | | | | should sync up with here? https://github.com/apache/spark/blob/119f45d61d7b48d376cca05e1b4f0c7fcf65bfa8/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/joinTypes.scala#L26 Author: LCY Vincent <lauchunyin@gmail.com> Closes #5944 from vincentlaucy/master and squashes the following commits: fc0e454 [LCY Vincent] Update DataFrame.scala
* [SPARK-7462] By default retain group by columns in aggregateReynold Xin2015-05-118-168/+216
| | | | | | | | | | | | | | | | | Updated Java, Scala, Python, and R. Author: Reynold Xin <rxin@databricks.com> Author: Shivaram Venkataraman <shivaram@cs.berkeley.edu> Closes #5996 from rxin/groupby-retain and squashes the following commits: aac7119 [Reynold Xin] Merge branch 'groupby-retain' of github.com:rxin/spark into groupby-retain f6858f6 [Reynold Xin] Merge branch 'master' into groupby-retain 5f923c0 [Reynold Xin] Merge pull request #15 from shivaram/sparkr-groupby-retrain c1de670 [Shivaram Venkataraman] Revert workaround in SparkR to retain grouped cols Based on reverting code added in commit https://github.com/amplab-extras/spark/commit/9a6be746efc9fafad88122fa2267862ef87aa0e1 b8b87e1 [Reynold Xin] Fixed DataFrameJoinSuite. d910141 [Reynold Xin] Updated rest of the files 1e6e666 [Reynold Xin] [SPARK-7462] By default retain group by columns in aggregate
* [MINOR] [SQL] Fixes variable name typoCheng Lian2015-05-108-9/+9
| | | | | | | | | | | | <!-- Reviewable:start --> [<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/6038) <!-- Reviewable:end --> Author: Cheng Lian <lian@databricks.com> Closes #6038 from liancheng/fix-typo and squashes the following commits: 572c2a4 [Cheng Lian] Fixes variable name typo
* [SPARK-7345][SQL] Spark cannot detect renamed columns using JDBC connectorOleg Sidorkin2015-05-102-1/+17
| | | | | | | | | | | | | | | | | | | | | | | | | Issue appears when one tries to create DataFrame using sqlContext.load("jdbc"...) statement when "dbtable" contains query with renamed columns. If original column is used in SQL query once the resulting DataFrame will contain non-renamed column. If original column is used in SQL query several times with different aliases, sqlContext.load will fail. Original implementation of JDBCRDD.resolveTable uses getColumnName to detect column names in RDD schema. Suggested implementation uses getColumnLabel to handle column renames in SQL statement which is aware of SQL "AS" statement. Readings: http://stackoverflow.com/questions/4271152/getcolumnlabel-vs-getcolumnname http://stackoverflow.com/questions/12259829/jdbc-getcolumnname-getcolumnlabel-db2 Official documentation unfortunately a bit misleading in definition of "suggested title" purpose however clearly defines behavior of AS keyword in SQL statement. http://docs.oracle.com/javase/7/docs/api/java/sql/ResultSetMetaData.html getColumnLabel - Gets the designated column's suggested title for use in printouts and displays. The suggested title is usually specified by the SQL AS clause. If a SQL AS is not specified, the value returned from getColumnLabel will be the same as the value returned by the getColumnName method. Author: Oleg Sidorkin <oleg.sidorkin@gmail.com> Closes #6032 from osidorkin/master and squashes the following commits: 10fc44b [Oleg Sidorkin] [SPARK-7345][SQL] Regression test for JDBCSuite (resolved scala style test error) 2aaf6f7 [Oleg Sidorkin] [SPARK-7345][SQL] Regression test for JDBCSuite (renamed fields in JDBC query) b7d5b22 [Oleg Sidorkin] [SPARK-7345][SQL] Regression test for JDBCSuite 09559a0 [Oleg Sidorkin] [SPARK-7345][SQL] Spark cannot detect renamed columns using JDBC connector
* [BUILD] Reference fasterxml.jackson.version in sql/core/pom.xmltedyu2015-05-091-1/+1
| | | | | | | | | | Author: tedyu <yuzhihong@gmail.com> Closes #6031 from tedyu/master and squashes the following commits: 5c2580c [tedyu] Reference fasterxml.jackson.version in sql/core/pom.xml ff2a44f [tedyu] Merge branch 'master' of github.com:apache/spark 28c8394 [tedyu] Upgrade version of jackson-databind in sql/core/pom.xml
* Upgrade version of jackson-databind in sql/core/pom.xmltedyu2015-05-091-1/+1
| | | | | | | | | | | | | | Currently version of jackson-databind in sql/core/pom.xml is 2.3.0 This is older than the version specified in root pom.xml This PR upgrades the version in sql/core/pom.xml so that they're consistent. Author: tedyu <yuzhihong@gmail.com> Closes #6028 from tedyu/master and squashes the following commits: 28c8394 [tedyu] Upgrade version of jackson-databind in sql/core/pom.xml
* [SPARK-7375] [SQL] Avoid row copying in exchange when ↵Josh Rosen2015-05-081-56/+100
| | | | | | | | | | | | | | | | | | | | | | sort.serializeMapOutputs takes effect This patch refactors the SQL `Exchange` operator's logic for determining whether map outputs need to be copied before being shuffled. As part of this change, we'll now avoid unnecessary copies in cases where sort-based shuffle operates on serialized map outputs (as in #4450 / SPARK-4550). This patch also includes a change to copy the input to RangePartitioner partition bounds calculation, which is necessary because this calculation buffers mutable Java objects. <!-- Reviewable:start --> [<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/5948) <!-- Reviewable:end --> Author: Josh Rosen <joshrosen@databricks.com> Closes #5948 from JoshRosen/SPARK-7375 and squashes the following commits: f305ff3 [Josh Rosen] Reduce scope of some variables in Exchange 899e1d7 [Josh Rosen] Merge remote-tracking branch 'origin/master' into SPARK-7375 6a6bfce [Josh Rosen] Fix issue related to RangePartitioning: ad006a4 [Josh Rosen] [SPARK-7375] Avoid defensive copying in exchange operator when sort.serializeMapOutputs takes effect.
* [SPARK-7231] [SPARKR] Changes to make SparkR DataFrame dplyr friendly.Shivaram Venkataraman2015-05-082-0/+21
| | | | | | | | | | | | | | | | | | | | | | Changes include 1. Rename sortDF to arrange 2. Add new aliases `group_by` and `sample_frac`, `summarize` 3. Add more user friendly column addition (mutate), rename 4. Support mean as an alias for avg in Scala and also support n_distinct, n as in dplyr Using these changes we can pretty much run the examples as described in http://cran.rstudio.com/web/packages/dplyr/vignettes/introduction.html with the same syntax The only thing missing in SparkR is auto resolving column names when used in an expression i.e. making something like `select(flights, delay)` works in dply but we right now need `select(flights, flights$delay)` or `select(flights, "delay")`. But this is a complicated change and I'll file a new issue for it cc sun-rui rxin Author: Shivaram Venkataraman <shivaram@cs.berkeley.edu> Closes #6005 from shivaram/sparkr-df-api and squashes the following commits: 5e0716a [Shivaram Venkataraman] Fix some roxygen bugs 1254953 [Shivaram Venkataraman] Merge branch 'master' of https://github.com/apache/spark into sparkr-df-api 0521149 [Shivaram Venkataraman] Changes to make SparkR DataFrame dplyr friendly. Changes include 1. Rename sortDF to arrange 2. Add new aliases `group_by` and `sample_frac`, `summarize` 3. Add more user friendly column addition (mutate), rename 4. Support mean as an alias for avg in Scala and also support n_distinct, n as in dplyr
* [SPARK-7469] [SQL] DAG visualization: show SQL query operatorsAndrew Or2015-05-0824-41/+52
| | | | | | | | | | | | | | | | | | | | | | | | The DAG visualization currently displays only low-level Spark primitives (e.g. `map`, `reduceByKey`, `filter` etc.). For SQL, these aren't particularly useful. Instead, we should display higher level physical operators (e.g. `Filter`, `Exchange`, `ShuffleHashJoin`). cc marmbrus ----------------- **Before** <img src="https://issues.apache.org/jira/secure/attachment/12731586/before.png" width="600px"/> ----------------- **After** (Pay attention to the words) <img src="https://issues.apache.org/jira/secure/attachment/12731587/after.png" width="600px"/> ----------------- Author: Andrew Or <andrew@databricks.com> Closes #5999 from andrewor14/dag-viz-sql and squashes the following commits: 0db23a4 [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-sql 1e211db [Andrew Or] Update comment 0d49fd6 [Andrew Or] Merge branch 'master' of github.com:apache/spark into dag-viz-sql ffd237a [Andrew Or] Fix style 202dac1 [Andrew Or] Make ignoreParent false by default e61b1ab [Andrew Or] Visualize SQL operators, not low-level Spark primitives 569034a [Andrew Or] Add a flag to ignore parent settings and scopes
* [SPARK-4699] [SQL] Make caseSensitive configurable in spark sql analyzerJacky Li2015-05-084-20/+27
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | based on #3558 Author: Jacky Li <jacky.likun@huawei.com> Author: wangfei <wangfei1@huawei.com> Author: scwf <wangfei1@huawei.com> Closes #5806 from scwf/case and squashes the following commits: cd51712 [wangfei] fix compile d4b724f [wangfei] address michael's comment af512c7 [wangfei] fix conflicts 4ef1be7 [wangfei] fix conflicts 269cf21 [scwf] fix conflicts b73df6c [scwf] style issue 9e11752 [scwf] improve SimpleCatalystConf b35529e [scwf] minor style a3f7659 [scwf] remove unsed imports 2a56515 [scwf] fix conflicts 6db4bf5 [scwf] also fix for HiveContext 7fc4a98 [scwf] fix test case d5a9933 [wangfei] fix style eee75ba [wangfei] fix EmptyConf 6ef31cf [wangfei] revert pom changes 5d7c456 [wangfei] set CASE_SENSITIVE false in TestHive 966e719 [wangfei] set CASE_SENSITIVE false in hivecontext fd30e25 [wangfei] added override 69b3b70 [wangfei] fix AnalysisSuite 5472b08 [wangfei] fix compile issue 56034ca [wangfei] fix conflicts and improve for catalystconf 664d1e9 [Jacky Li] Merge branch 'master' of https://github.com/apache/spark into case 12eca9a [Jacky Li] solve conflict with master 39e369c [Jacky Li] fix confilct after DataFrame PR dee56e9 [Jacky Li] fix test case failure 05b09a3 [Jacky Li] fix conflict base on the latest master branch 73c16b1 [Jacky Li] fix bug in sql/hive 9bf4cc7 [Jacky Li] fix bug in catalyst 005c56d [Jacky Li] make SQLContext caseSensitivity configurable 6332e0f [Jacky Li] fix bug fcbf0d9 [Jacky Li] fix scalastyle check e7bca31 [Jacky Li] make caseSensitive configuration in Analyzer and Catalog 91b1b96 [Jacky Li] make caseSensitive configurable in Analyzer f57f15c [Jacky Li] add testcase 578d167 [Jacky Li] make caseSensitive configurable
* [SPARK-7390] [SQL] Only merge other CovarianceCounter when its count is ↵Liang-Chi Hsieh2015-05-081-10/+12
| | | | | | | | | | | | | | greater than zero JIRA: https://issues.apache.org/jira/browse/SPARK-7390 Also fix a minor typo. Author: Liang-Chi Hsieh <viirya@gmail.com> Closes #5931 from viirya/fix_covariancecounter and squashes the following commits: 352eda6 [Liang-Chi Hsieh] Only merge other CovarianceCounter when its count is greater than zero.
* [SPARK-7133] [SQL] Implement struct, array, and map field accessorWenchen Fan2015-05-082-5/+24
| | | | | | | | | | | | | | | | | | | | | | It's the first step: generalize UnresolvedGetField to support all map, struct, and array TODO: add `apply` in Scala and `__getitem__` in Python, and unify the `getItem` and `getField` methods to one single API(or should we keep them for compatibility?). Author: Wenchen Fan <cloud0fan@outlook.com> Closes #5744 from cloud-fan/generalize and squashes the following commits: 715c589 [Wenchen Fan] address comments 7ea5b31 [Wenchen Fan] fix python test 4f0833a [Wenchen Fan] add python test f515d69 [Wenchen Fan] add apply method and test cases 8df6199 [Wenchen Fan] fix python test 239730c [Wenchen Fan] fix test compile 2a70526 [Wenchen Fan] use _bin_op in dataframe.py 6bf72bc [Wenchen Fan] address comments 3f880c3 [Wenchen Fan] add java doc ab35ab5 [Wenchen Fan] fix python test b5961a9 [Wenchen Fan] fix style c9d85f5 [Wenchen Fan] generalize UnresolvedGetField to support all map, struct, and array
* [SPARK-6986] [SQL] Use Serializer2 in more cases.Yin Huai2015-05-073-58/+69
| | | | | | | | | | | | | | With https://github.com/apache/spark/commit/0a2b15ce43cf6096e1a7ae060b7c8a4010ce3b92, the serialization stream and deserialization stream has enough information to determine it is handling a key-value pari, a key, or a value. It is safe to use `SparkSqlSerializer2` in more cases. Author: Yin Huai <yhuai@databricks.com> Closes #5849 from yhuai/serializer2MoreCases and squashes the following commits: 53a5eaa [Yin Huai] Josh's comments. 487f540 [Yin Huai] Use BufferedOutputStream. 8385f95 [Yin Huai] Always create a new row at the deserialization side to work with sort merge join. c7e2129 [Yin Huai] Update tests. 4513d13 [Yin Huai] Use Serializer2 in more places.
* [SPARK-6908] [SQL] Use isolated Hive clientMichael Armbrust2015-05-074-10/+22
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 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
* [SPARK-2155] [SQL] [WHEN D THEN E] [ELSE F] add CaseKeyWhen for "CASE a WHEN ↵Wenchen Fan2015-05-071-4/+5
| | | | | | | | | | | | b THEN c * END" Avoid translating to CaseWhen and evaluate the key expression many times. Author: Wenchen Fan <cloud0fan@outlook.com> Closes #5979 from cloud-fan/condition and squashes the following commits: 3ce54e1 [Wenchen Fan] add CaseKeyWhen
* [SPARK-7277] [SQL] Throw exception if the property mapred.reduce.tasks is ↵Liang-Chi Hsieh2015-05-072-2/+18
| | | | | | | | | | | | | | | | | set to -1 JIRA: https://issues.apache.org/jira/browse/SPARK-7277 As automatically determining the number of reducers is not supported (`mapred.reduce.tasks` is set to `-1`), we should throw exception to users. Author: Liang-Chi Hsieh <viirya@gmail.com> Closes #5811 from viirya/no_neg_reduce_tasks and squashes the following commits: e518f96 [Liang-Chi Hsieh] Consider other wrong setting values. fd9c817 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into no_neg_reduce_tasks 4ede705 [Liang-Chi Hsieh] Throw exception instead of warning message. 68a1c70 [Liang-Chi Hsieh] Show warning message if mapred.reduce.tasks is set to -1.
* [SPARK-7116] [SQL] [PYSPARK] Remove cache() causing memory leakksonj2015-05-071-4/+3
| | | | | | | | | | | This patch simply removes a `cache()` on an intermediate RDD when evaluating Python UDFs. Author: ksonj <kson@siberie.de> Closes #5973 from ksonj/udf and squashes the following commits: db5b564 [ksonj] removed TODO about cleaning up fe70c54 [ksonj] Remove cache() causing memory leak
* [SPARK-7330] [SQL] avoid NPE at jdbc rddDaoyuan Wang2015-05-072-1/+32
| | | | | | | | | | Thank nadavoosh point this out in #5590 Author: Daoyuan Wang <daoyuan.wang@intel.com> Closes #5877 from adrian-wang/jdbcrdd and squashes the following commits: cc11900 [Daoyuan Wang] avoid NPE in jdbcrdd
* [SPARK-7295][SQL] bitwise operations for DataFrame DSLShiti2015-05-074-2/+77
| | | | | | | | Author: Shiti <ssaxena.ece@gmail.com> Closes #5867 from Shiti/spark-7295 and squashes the following commits: 71a9913 [Shiti] implementation for bitwise and,or, not and xor on Column with tests and docs
* [SPARK-5938] [SPARK-5443] [SQL] Improve JsonRDD performanceNathan Howell2015-05-0611-108/+688
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This patch comprises of a few related pieces of work: * Schema inference is performed directly on the JSON token stream * `String => Row` conversion populate Spark SQL structures without intermediate types * Projection pushdown is implemented via CatalystScan for DataFrame queries * Support for the legacy parser by setting `spark.sql.json.useJacksonStreamingAPI` to `false` Performance improvements depend on the schema and queries being executed, but it should be faster across the board. Below are benchmarks using the last.fm Million Song dataset: ``` Command | Baseline | Patched ---------------------------------------------------|----------|-------- import sqlContext.implicits._ | | val df = sqlContext.jsonFile("/tmp/lastfm.json") | 70.0s | 14.6s df.count() | 28.8s | 6.2s df.rdd.count() | 35.3s | 21.5s df.where($"artist" === "Robert Hood").collect() | 28.3s | 16.9s ``` To prepare this dataset for benchmarking, follow these steps: ``` # Fetch the datasets from http://labrosa.ee.columbia.edu/millionsong/lastfm wget http://labrosa.ee.columbia.edu/millionsong/sites/default/files/lastfm/lastfm_test.zip \ http://labrosa.ee.columbia.edu/millionsong/sites/default/files/lastfm/lastfm_train.zip # Decompress and combine, pipe through `jq -c` to ensure there is one record per line unzip -p lastfm_test.zip lastfm_train.zip | jq -c . > lastfm.json ``` Author: Nathan Howell <nhowell@godaddy.com> Closes #5801 from NathanHowell/json-performance and squashes the following commits: 26fea31 [Nathan Howell] Recreate the baseRDD each for each scan operation a7ebeb2 [Nathan Howell] Increase coverage of inserts into a JSONRelation e06a1dd [Nathan Howell] Add comments to the `useJacksonStreamingAPI` config flag 6822712 [Nathan Howell] Split up JsonRDD2 into multiple objects fa8234f [Nathan Howell] Wrap long lines b31917b [Nathan Howell] Rename `useJsonRDD2` to `useJacksonStreamingAPI` 15c5d1b [Nathan Howell] JSONRelation's baseRDD need not be lazy f8add6e [Nathan Howell] Add comments on lack of support for precision and scale DecimalTypes fa0be47 [Nathan Howell] Remove unused default case in the field parser 80dba17 [Nathan Howell] Add comments regarding null handling and empty strings 842846d [Nathan Howell] Point the empty schema inference test at JsonRDD2 ab6ee87 [Nathan Howell] Add projection pushdown support to JsonRDD/JsonRDD2 f636c14 [Nathan Howell] Enable JsonRDD2 by default, add a flag to switch back to JsonRDD 0bbc445 [Nathan Howell] Improve JSON parsing and type inference performance 7ca70c1 [Nathan Howell] Eliminate arrow pattern, replace with pattern matches
* [SPARK-7311] Introduce internal Serializer API for determining if ↵Josh Rosen2015-05-061-0/+5
| | | | | | | | | | | | | | | | | | | | | | | | serializers support object relocation This patch extends the `Serializer` interface with a new `Private` API which allows serializers to indicate whether they support relocation of serialized objects in serializer stream output. This relocatibilty property is described in more detail in `Serializer.scala`, but in a nutshell a serializer supports relocation if reordering the bytes of serialized objects in serialization stream output is equivalent to having re-ordered those elements prior to serializing them. The optimized shuffle path introduced in #4450 and #5868 both rely on serializers having this property; this patch just centralizes the logic for determining whether a serializer has this property. I also added tests and comments clarifying when this works for KryoSerializer. This change allows the optimizations in #4450 to be applied for shuffles that use `SqlSerializer2`. Author: Josh Rosen <joshrosen@databricks.com> Closes #5924 from JoshRosen/SPARK-7311 and squashes the following commits: 50a68ca [Josh Rosen] Address minor nits 0a7ebd7 [Josh Rosen] Clarify reason why SqlSerializer2 supports this serializer 123b992 [Josh Rosen] Cleanup for submitting as standalone patch. 4aa61b2 [Josh Rosen] Add missing newline 2c1233a [Josh Rosen] Small refactoring of SerializerPropertiesSuite to enable test re-use: 0ba75e6 [Josh Rosen] Add tests for serializer relocation property. 450fa21 [Josh Rosen] Back out accidental log4j.properties change 86d4dcd [Josh Rosen] Flag that SparkSqlSerializer2 supports relocation b9624ee [Josh Rosen] Expand serializer API and use new function to help control when new UnsafeShuffle path is used.
* [SPARK-1442] [SQL] Window Function Support for Spark SQLYin Huai2015-05-062-0/+482
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Adding more information about the implementation... This PR is adding the support of window functions to Spark SQL (specifically OVER and WINDOW clause). For every expression having a OVER clause, we use a WindowExpression as the container of a WindowFunction and the corresponding WindowSpecDefinition (the definition of a window frame, i.e. partition specification, order specification, and frame specification appearing in a OVER clause). # Implementation # The high level work flow of the implementation is described as follows. * Query parsing: In the query parse process, all WindowExpressions are originally placed in the projectList of a Project operator or the aggregateExpressions of an Aggregate operator. It makes our changes to simple and keep all of parsing rules for window functions at a single place (nodesToWindowSpecification). For the WINDOWclause in a query, we use a WithWindowDefinition as the container as the mapping from the name of a window specification to a WindowSpecDefinition. This changes is similar with our common table expression support. * Analysis: The query analysis process has three steps for window functions. * Resolve all WindowSpecReferences by replacing them with WindowSpecReferences according to the mapping table stored in the node of WithWindowDefinition. * Resolve WindowFunctions in the projectList of a Project operator or the aggregateExpressions of an Aggregate operator. For this PR, we use Hive's functions for window functions because we will have a major refactoring of our internal UDAFs and it is better to switch our UDAFs after that refactoring work. * Once we have resolved all WindowFunctions, we will use ResolveWindowFunction to extract WindowExpressions from projectList and aggregateExpressions and then create a Window operator for every distinct WindowSpecDefinition. With this choice, at the execution time, we can rely on the Exchange operator to do all of work on reorganizing the table and we do not need to worry about it in the physical Window operator. An example analyzed plan is shown as follows ``` sql(""" SELECT year, country, product, sales, avg(sales) over(partition by product) avg_product, sum(sales) over(partition by country) sum_country FROM sales ORDER BY year, country, product """).explain(true) == Analyzed Logical Plan == Sort [year#34 ASC,country#35 ASC,product#36 ASC], true Project [year#34,country#35,product#36,sales#37,avg_product#27,sum_country#28] Window [year#34,country#35,product#36,sales#37,avg_product#27], [HiveWindowFunction#org.apache.hadoop.hive.ql.udf.generic.GenericUDAFSum(sales#37) WindowSpecDefinition [country#35], [], ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING AS sum_country#28], WindowSpecDefinition [country#35], [], ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING Window [year#34,country#35,product#36,sales#37], [HiveWindowFunction#org.apache.hadoop.hive.ql.udf.generic.GenericUDAFAverage(sales#37) WindowSpecDefinition [product#36], [], ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING AS avg_product#27], WindowSpecDefinition [product#36], [], ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING Project [year#34,country#35,product#36,sales#37] MetastoreRelation default, sales, None ``` * Query planning: In the process of query planning, we simple generate the physical Window operator based on the logical Window operator. Then, to prepare the executedPlan, the EnsureRequirements rule will add Exchange and Sort operators if necessary. The EnsureRequirements rule will analyze the data properties and try to not add unnecessary shuffle and sort. The physical plan for the above example query is shown below. ``` == Physical Plan == Sort [year#34 ASC,country#35 ASC,product#36 ASC], true Exchange (RangePartitioning [year#34 ASC,country#35 ASC,product#36 ASC], 200), [] Window [year#34,country#35,product#36,sales#37,avg_product#27], [HiveWindowFunction#org.apache.hadoop.hive.ql.udf.generic.GenericUDAFSum(sales#37) WindowSpecDefinition [country#35], [], ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING AS sum_country#28], WindowSpecDefinition [country#35], [], ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING Exchange (HashPartitioning [country#35], 200), [country#35 ASC] Window [year#34,country#35,product#36,sales#37], [HiveWindowFunction#org.apache.hadoop.hive.ql.udf.generic.GenericUDAFAverage(sales#37) WindowSpecDefinition [product#36], [], ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING AS avg_product#27], WindowSpecDefinition [product#36], [], ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING Exchange (HashPartitioning [product#36], 200), [product#36 ASC] HiveTableScan [year#34,country#35,product#36,sales#37], (MetastoreRelation default, sales, None), None ``` * Execution time: At execution time, a physical Window operator buffers all rows in a partition specified in the partition spec of a OVER clause. If necessary, it also maintains a sliding window frame. The current implementation tries to buffer the input parameters of a window function according to the window frame to avoid evaluating a row multiple times. # Future work # Here are three improvements that are not hard to add: * Taking advantage of the window frame specification to reduce the number of rows buffered in the physical Window operator. For some cases, we only need to buffer the rows appearing in the sliding window. But for other cases, we will not be able to reduce the number of rows buffered (e.g. ROWS BETWEEN UNBOUNDED PRECEDING AND UNBOUNDED FOLLOWING). * When aRAGEN frame is used, for <value> PRECEDING and <value> FOLLOWING, it will be great if the <value> part is an expression (we can start with Literal). So, when the data type of ORDER BY expression is a FractionalType, we can support FractionalType as the type <value> (<value> still needs to be evaluated as a positive value). * When aRAGEN frame is used, we need to support DateType and TimestampType as the data type of the expression appearing in the order specification. Then, the <value> part of <value> PRECEDING and <value> FOLLOWING can support interval types (once we support them). This is a joint work with guowei2 and yhuai Thanks hbutani hvanhovell for his comments Thanks scwf for his comments and unit tests Author: Yin Huai <yhuai@databricks.com> Closes #5604 from guowei2/windowImplement and squashes the following commits: 76fe1c8 [Yin Huai] Implementation. aa2b0ae [Yin Huai] Tests.
* [SPARK-6201] [SQL] promote string and do widen types for INDaoyuan Wang2015-05-061-0/+9
| | | | | | | | | | | | | | | | huangjs Acutally spark sql will first go through analysis period, in which we do widen types and promote strings, and then optimization, where constant IN will be converted into INSET. So it turn out that we only need to fix this for IN. Author: Daoyuan Wang <daoyuan.wang@intel.com> Closes #4945 from adrian-wang/inset and squashes the following commits: 71e05cc [Daoyuan Wang] minor fix 581fa1c [Daoyuan Wang] mysql way f3f7baf [Daoyuan Wang] address comments 5eed4bc [Daoyuan Wang] promote string and do widen types for IN
* [SPARK-5456] [SQL] fix decimal compare for jdbc rddDaoyuan Wang2015-05-062-2/+11
| | | | | | | | | Author: Daoyuan Wang <daoyuan.wang@intel.com> Closes #5803 from adrian-wang/decimalcompare and squashes the following commits: aef0e96 [Daoyuan Wang] add null handle ec455b9 [Daoyuan Wang] fix decimal compare for jdbc rdd
* [SQL] JavaDoc update for various DataFrame functions.Reynold Xin2015-05-064-21/+32
| | | | | | | | Author: Reynold Xin <rxin@databricks.com> Closes #5935 from rxin/df-doc1 and squashes the following commits: aaeaadb [Reynold Xin] [SQL] JavaDoc update for various DataFrame functions.
* [SPARK-7358][SQL] Move DataFrame mathfunctions into functionsBurak Yavuz2015-05-054-388/+488
| | | | | | | | | | | | | After a discussion on the user mailing list, it was decided to put all UDF's under `o.a.s.sql.functions` cc rxin Author: Burak Yavuz <brkyvz@gmail.com> Closes #5923 from brkyvz/move-math-funcs and squashes the following commits: a8dc3f7 [Burak Yavuz] address comments cf7a7bb [Burak Yavuz] [SPARK-7358] Move DataFrame mathfunctions into functions
* [SPARK-6231][SQL/DF] Automatically resolve join condition ambiguity for ↵Reynold Xin2015-05-054-43/+127
| | | | | | | | | | | | | | | self-joins. See the comment in join function for more information. Author: Reynold Xin <rxin@databricks.com> Closes #5919 from rxin/self-join-resolve and squashes the following commits: e2fb0da [Reynold Xin] Updated SQLConf comment. 7233a86 [Reynold Xin] Updated comment. 6be2b4d [Reynold Xin] Removed println 9f6b72f [Reynold Xin] [SPARK-6231][SQL/DF] Automatically resolve ambiguity in join condition for self-joins.
* [SPARK-7294][SQL] ADD BETWEEN云峤2015-05-052-0/+23
| | | | | | | | | | | | | | | | | | | Author: 云峤 <chensong.cs@alibaba-inc.com> Author: kaka1992 <kaka_1992@163.com> Closes #5839 from kaka1992/master and squashes the following commits: b15360d [kaka1992] Fix python unit test in sql/test. =_= I forget to commit this file last time. f928816 [kaka1992] Fix python style in sql/test. d2e7f72 [kaka1992] Fix python style in sql/test. c54d904 [kaka1992] Fix empty map bug. 7e64d1e [云峤] Update 7b9b858 [云峤] undo f080f8d [云峤] update pep8 76f0c51 [云峤] Merge remote-tracking branch 'remotes/upstream/master' 7d62368 [云峤] [SPARK-7294] ADD BETWEEN baf839b [云峤] [SPARK-7294] ADD BETWEEN d11d5b9 [云峤] [SPARK-7294] ADD BETWEEN
* [SPARK-7243][SQL] Reduce size for Contingency Tables in DataFramesBurak Yavuz2015-05-052-7/+8
| | | | | | | | | | | | | | Reduced take size from 1e8 to 1e6. cc rxin Author: Burak Yavuz <brkyvz@gmail.com> Closes #5900 from brkyvz/df-cont-followup and squashes the following commits: c11e762 [Burak Yavuz] fix grammar b30ace2 [Burak Yavuz] address comments a417ba5 [Burak Yavuz] [SPARK-7243][SQL] Reduce size for Contingency Tables in DataFrames
* [SPARK-7243][SQL] Contingency Tables for DataFramesBurak Yavuz2015-05-044-31/+126
| | | | | | | | | | | | | | | | | | | | | Computes a pair-wise frequency table of the given columns. Also known as cross-tabulation. cc mengxr rxin Author: Burak Yavuz <brkyvz@gmail.com> Closes #5842 from brkyvz/df-cont and squashes the following commits: a07c01e [Burak Yavuz] addressed comments v4.1 ae9e01d [Burak Yavuz] fix test 9106585 [Burak Yavuz] addressed comments v4.0 bced829 [Burak Yavuz] fix merge conflicts a63ad00 [Burak Yavuz] addressed comments v3.0 a0cad97 [Burak Yavuz] addressed comments v3.0 6805df8 [Burak Yavuz] addressed comments and fixed test 939b7c4 [Burak Yavuz] lint python 7f098bc [Burak Yavuz] add crosstab pyTest fd53b00 [Burak Yavuz] added python support for crosstab 27a5a81 [Burak Yavuz] implemented crosstab
* [SPARK-7319][SQL] Improve the output from DataFrame.show()云峤2015-05-042-6/+41
| | | | | | | | | | | | | | | | | | | | Author: 云峤 <chensong.cs@alibaba-inc.com> Closes #5865 from kaka1992/df.show and squashes the following commits: c79204b [云峤] Update a1338f6 [云峤] Update python dataFrame show test and add empty df unit test. 734369c [云峤] Update python dataFrame show test and add empty df unit test. 84aec3e [云峤] Update python dataFrame show test and add empty df unit test. 159b3d5 [云峤] update 03ef434 [云峤] update 7394fd5 [云峤] update test show ced487a [云峤] update pep8 b6e690b [云峤] Merge remote-tracking branch 'upstream/master' into df.show 30ac311 [云峤] [SPARK-7294] ADD BETWEEN 7d62368 [云峤] [SPARK-7294] ADD BETWEEN baf839b [云峤] [SPARK-7294] ADD BETWEEN d11d5b9 [云峤] [SPARK-7294] ADD BETWEEN
* [SPARK-5100] [SQL] add webui for thriftservertianyi2015-05-041-0/+2
| | | | | | | | | | | | | | | | | | | | | | | | | | | | This PR is a rebased version of #3946 , and mainly focused on creating an independent tab for the thrift server in spark web UI. Features: 1. Session related statistics ( username and IP are only supported in hive-0.13.1 ) 2. List all the SQL executing or executed on this server 3. Provide links to the job generated by SQL 4. Provide link to show all SQL executing or executed in a specified session Prototype snapshots: This is the main page for thrift server ![image](https://cloud.githubusercontent.com/assets/1411869/7361379/df7dcc64-ed89-11e4-9964-4df0b32f475e.png) Author: tianyi <tianyi.asiainfo@gmail.com> Closes #5730 from tianyi/SPARK-5100 and squashes the following commits: cfd14c7 [tianyi] style fix 0efe3d5 [tianyi] revert part of pom change c0f2fa0 [tianyi] extends HiveThriftJdbcTest to start/stop thriftserver for UI test aa20408 [tianyi] fix style problem c9df6f9 [tianyi] add testsuite for thriftserver ui and fix some style issue 9830199 [tianyi] add webui for thriftserver
* [SPARK-7241] Pearson correlation for DataFramesBurak Yavuz2015-05-034-26/+98
| | | | | | | | | | | | | | | | | submitting this PR from a phone, excuse the brevity. adds Pearson correlation to Dataframes, reusing the covariance calculation code cc mengxr rxin Author: Burak Yavuz <brkyvz@gmail.com> Closes #5858 from brkyvz/df-corr and squashes the following commits: 285b838 [Burak Yavuz] addressed comments v2.0 d10babb [Burak Yavuz] addressed comments v0.2 4b74b24 [Burak Yavuz] Merge branch 'master' of github.com:apache/spark into df-corr 4fe693b [Burak Yavuz] addressed comments v0.1 a682d06 [Burak Yavuz] ready for PR
* [SPARK-5213] [SQL] Pluggable SQL Parser SupportCheng Hao2015-05-023-14/+90
| | | | | | | | | | | | | | | | | | | based on #4015, we should not delete `sqlParser` from sqlcontext, that leads to mima failed. Users implement dialect to give a fallback for `sqlParser` and we should construct `sqlParser` in sqlcontext according to the dialect `protected[sql] val sqlParser = new SparkSQLParser(getSQLDialect().parse(_))` Author: Cheng Hao <hao.cheng@intel.com> Author: scwf <wangfei1@huawei.com> Closes #5827 from scwf/sqlparser1 and squashes the following commits: 81b9737 [scwf] comment fix 0878bd1 [scwf] remove comments c19780b [scwf] fix mima tests c2895cf [scwf] Merge branch 'master' of https://github.com/apache/spark into sqlparser1 493775c [Cheng Hao] update the code as feedback 81a731f [Cheng Hao] remove the unecessary comment aab0b0b [Cheng Hao] polish the code a little bit 49b9d81 [Cheng Hao] shrink the comment for rebasing
* [SPARK-7242] added python api for freqItems in DataFramesBurak Yavuz2015-05-011-3/+6
| | | | | | | | | | | | The python api for DataFrame's plus addressed your comments from previous PR. rxin Author: Burak Yavuz <brkyvz@gmail.com> Closes #5859 from brkyvz/df-freq-py2 and squashes the following commits: f9aa9ce [Burak Yavuz] addressed comments v0.1 4b25056 [Burak Yavuz] added python api for freqItems
* [SPARK-6999] [SQL] Remove the infinite recursive method (useless)Cheng Hao2015-05-011-14/+0
| | | | | | | | | | | Remove the method, since it causes infinite recursive calls. And seems it's a dummy method, since we have the API: `def createDataFrame(rowRDD: JavaRDD[Row], schema: StructType): DataFrame` Author: Cheng Hao <hao.cheng@intel.com> Closes #5804 from chenghao-intel/spark_6999 and squashes the following commits: 63220a8 [Cheng Hao] remove the infinite recursive method (useless)
* [SPARK-7312][SQL] SPARK-6913 broke jdk6 buildYin Huai2015-05-011-2/+4
| | | | | | | | | | JIRA: https://issues.apache.org/jira/browse/SPARK-7312 Author: Yin Huai <yhuai@databricks.com> Closes #5847 from yhuai/jdbcJava6 and squashes the following commits: 68433a2 [Yin Huai] compile with Java 6
generated by cgit v1.2.3 (git 2.39.1) at 2024-08-14 20:26:44 +0000