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* [SPARK-14828][SQL] Start SparkSession in REPL instead of SQLContextAndrew Or2016-04-251-5/+29
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? ``` Spark context available as 'sc' (master = local[*], app id = local-1461283768192). Spark session available as 'spark'. Welcome to ____ __ / __/__ ___ _____/ /__ _\ \/ _ \/ _ `/ __/ '_/ /___/ .__/\_,_/_/ /_/\_\ version 2.0.0-SNAPSHOT /_/ Using Scala version 2.11.8 (Java HotSpot(TM) 64-Bit Server VM, Java 1.7.0_51) Type in expressions to have them evaluated. Type :help for more information. scala> sql("SHOW TABLES").collect() 16/04/21 17:09:39 WARN ObjectStore: Version information not found in metastore. hive.metastore.schema.verification is not enabled so recording the schema version 1.2.0 16/04/21 17:09:39 WARN ObjectStore: Failed to get database default, returning NoSuchObjectException res0: Array[org.apache.spark.sql.Row] = Array([src,false]) scala> sql("SHOW TABLES").collect() res1: Array[org.apache.spark.sql.Row] = Array([src,false]) scala> spark.createDataFrame(Seq((1, 1), (2, 2), (3, 3))) res2: org.apache.spark.sql.DataFrame = [_1: int, _2: int] ``` Hive things are loaded lazily. ## How was this patch tested? Manual. Author: Andrew Or <andrew@databricks.com> Closes #12589 from andrewor14/spark-session-repl.
* [SPARK-13739][SQL] Push Predicate Through Windowgatorsmile2016-04-255-33/+294
| | | | | | | | | | | | | | | | | | | | #### What changes were proposed in this pull request? For performance, predicates can be pushed through Window if and only if the following conditions are satisfied: 1. All the expressions are part of window partitioning key. The expressions can be compound. 2. Deterministic #### How was this patch tested? TODO: - [X] DSL needs to be modified for window - [X] more tests will be added. Author: gatorsmile <gatorsmile@gmail.com> Author: xiaoli <lixiao1983@gmail.com> Author: Xiao Li <xiaoli@Xiaos-MacBook-Pro.local> Closes #11635 from gatorsmile/pushPredicateThroughWindow.
* [SPARK-14721][SQL] Remove HiveContext (part 2)Andrew Or2016-04-2518-100/+78
| | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This removes the class `HiveContext` itself along with all code usages associated with it. The bulk of the work was already done in #12485. This is mainly just code cleanup and actually removing the class. Note: A couple of things will break after this patch. These will be fixed separately. - the python HiveContext - all the documentation / comments referencing HiveContext - there will be no more HiveContext in the REPL (fixed by #12589) ## How was this patch tested? No change in functionality. Author: Andrew Or <andrew@databricks.com> Closes #12585 from andrewor14/delete-hive-context.
* [SPARK-14892][SQL][TEST] Disable the HiveCompatibilitySuite test case for ↵gatorsmile2016-04-251-2/+4
| | | | | | | | | | | | | | INPUTDRIVER and OUTPUTDRIVER. #### What changes were proposed in this pull request? Disable the test case involving INPUTDRIVER and OUTPUTDRIVER, which are not supported #### How was this patch tested? N/A Author: gatorsmile <gatorsmile@gmail.com> Closes #12662 from gatorsmile/disableInOutDriver.
* [SPARK-14875][SQL] Makes OutputWriterFactory.newInstance publicCheng Lian2016-04-252-2/+2
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? This method was accidentally made `private[sql]` in Spark 2.0. This PR makes it public again, since 3rd party data sources like spark-avro depend on it. ## How was this patch tested? N/A Author: Cheng Lian <lian@databricks.com> Closes #12652 from liancheng/spark-14875.
* [SPARK-14870] [SQL] Fix NPE in TPCDS q14aSameer Agarwal2016-04-244-3/+37
| | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR fixes a bug in `TungstenAggregate` that manifests while aggregating by keys over nullable `BigDecimal` columns. This causes a null pointer exception while executing TPCDS q14a. ## How was this patch tested? 1. Added regression test in `DataFrameAggregateSuite`. 2. Verified that TPCDS q14a works Author: Sameer Agarwal <sameer@databricks.com> Closes #12651 from sameeragarwal/tpcds-fix.
* [SPARK-14885][SQL] When creating a CatalogColumn, we should use the ↵Yin Huai2016-04-242-3/+3
| | | | | | | | | | | | | | | catalogString of a DataType object. ## What changes were proposed in this pull request? Right now, the data type field of a CatalogColumn is using the string representation. When we create this string from a DataType object, there are places where we use simpleString instead of catalogString. Although catalogString is the same as simpleString right now, it is still good to use catalogString. So, we will not silently introduce issues when we change the semantic of simpleString or the implementation of catalogString. ## How was this patch tested? Existing tests. Author: Yin Huai <yhuai@databricks.com> Closes #12654 from yhuai/useCatalogString.
* [SPARK-14868][BUILD] Enable NewLineAtEofChecker in checkstyle and fix ↵Dongjoon Hyun2016-04-241-1/+0
| | | | | | | | | | | | | | | | | | | | | | | | lint-java errors ## What changes were proposed in this pull request? Spark uses `NewLineAtEofChecker` rule in Scala by ScalaStyle. And, most Java code also comply with the rule. This PR aims to enforce the same rule `NewlineAtEndOfFile` by CheckStyle explicitly. Also, this fixes lint-java errors since SPARK-14465. The followings are the items. - Adds a new line at the end of the files (19 files) - Fixes 25 lint-java errors (12 RedundantModifier, 6 **ArrayTypeStyle**, 2 LineLength, 2 UnusedImports, 2 RegexpSingleline, 1 ModifierOrder) ## How was this patch tested? After the Jenkins test succeeds, `dev/lint-java` should pass. (Currently, Jenkins dose not run lint-java.) ```bash $ dev/lint-java Using `mvn` from path: /usr/local/bin/mvn Checkstyle checks passed. ``` Author: Dongjoon Hyun <dongjoon@apache.org> Closes #12632 from dongjoon-hyun/SPARK-14868.
* [SPARK-14876][SQL] SparkSession should be case insensitive by defaultReynold Xin2016-04-245-190/+208
| | | | | | | | | | | | ## What changes were proposed in this pull request? This patch changes SparkSession to be case insensitive by default, in order to match other database systems. ## How was this patch tested? N/A - I'm sure some tests will fail and I will need to fix those. Author: Reynold Xin <rxin@databricks.com> Closes #12643 from rxin/SPARK-14876.
* Disable flaky script transformation testReynold Xin2016-04-241-2/+2
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* [SPARK-14548][SQL] Support not greater than and not less than operator in ↵jliwork2016-04-245-3/+15
| | | | | | | | | | | | | | | | | Spark SQL !< means not less than which is equivalent to >= !> means not greater than which is equivalent to <= I'd to create a PR to support these two operators. I've added new test cases in: DataFrameSuite, ExpressionParserSuite, JDBCSuite, PlanParserSuite, SQLQuerySuite dilipbiswal viirya gatorsmile Author: jliwork <jiali@us.ibm.com> Closes #12316 from jliwork/SPARK-14548.
* [SPARK-14691][SQL] Simplify and Unify Error Generation for Unsupported Alter ↵gatorsmile2016-04-245-138/+40
| | | | | | | | | | | | | | | | | | Table DDL #### What changes were proposed in this pull request? So far, we are capturing each unsupported Alter Table in separate visit functions. They should be unified and issue the same ParseException instead. This PR is to refactor the existing implementation and make error message consistent for Alter Table DDL. #### How was this patch tested? Updated the existing test cases and also added new test cases to ensure all the unsupported statements are covered. Author: gatorsmile <gatorsmile@gmail.com> Author: xiaoli <lixiao1983@gmail.com> Author: Xiao Li <xiaoli@Xiaos-MacBook-Pro.local> Closes #12459 from gatorsmile/cleanAlterTable.
* [SPARK-14879][SQL] Move CreateMetastoreDataSource and ↵Yin Huai2016-04-239-451/+497
| | | | | | | | | | | | | | | CreateMetastoreDataSourceAsSelect to sql/core ## What changes were proposed in this pull request? CreateMetastoreDataSource and CreateMetastoreDataSourceAsSelect are not Hive-specific. So, this PR moves them from sql/hive to sql/core. Also, I am adding `Command` suffix to these two classes. ## How was this patch tested? Existing tests. Author: Yin Huai <yhuai@databricks.com> Closes #12645 from yhuai/moveCreateDataSource.
* [SPARK-14833][SQL][STREAMING][TEST] Refactor StreamTests to test for source ↵Tathagata Das2016-04-232-197/+233
| | | | | | | | | | | | | | | | | | | | | | | | | fault-tolerance correctly. ## What changes were proposed in this pull request? Current StreamTest allows testing of a streaming Dataset generated explicitly wraps a source. This is different from the actual production code path where the source object is dynamically created through a DataSource object every time a query is started. So all the fault-tolerance testing in FileSourceSuite and FileSourceStressSuite is not really testing the actual code path as they are just reusing the FileStreamSource object. This PR fixes StreamTest and the FileSource***Suite to test this correctly. Instead of maintaining a mapping of source --> expected offset in StreamTest (which requires reuse of source object), it now maintains a mapping of source index --> offset, so that it is independent of the source object. Summary of changes - StreamTest refactored to keep track of offset by source index instead of source - AddData, AddTextData and AddParquetData updated to find the FileStreamSource object from an active query, so that it can work with sources generated when query is started. - Refactored unit tests in FileSource***Suite to test using DataFrame/Dataset generated with public, rather than reusing the same FileStreamSource. This correctly tests fault tolerance. The refactoring changed a lot of indents in FileSourceSuite, so its recommended to hide whitespace changes with this - https://github.com/apache/spark/pull/12592/files?w=1 ## How was this patch tested? Refactored unit tests. Author: Tathagata Das <tathagata.das1565@gmail.com> Closes #12592 from tdas/SPARK-14833.
* [SPARK-14838] [SQL] Set default size for ObjecType to avoid failure when ↵Liang-Chi Hsieh2016-04-232-2/+24
| | | | | | | | | | | | | | | | estimating sizeInBytes in ObjectProducer ## What changes were proposed in this pull request? We have logical plans that produce domain objects which are `ObjectType`. As we can't estimate the size of `ObjectType`, we throw an `UnsupportedOperationException` if trying to do that. We should set a default size for `ObjectType` to avoid this failure. ## How was this patch tested? `DatasetSuite`. Author: Liang-Chi Hsieh <simonh@tw.ibm.com> Closes #12599 from viirya/skip-broadcast-objectproducer.
* [SPARK-14856] Correct message in assertion for 'returning batch for wide table'tedyu2016-04-231-1/+1
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? There was a typo in the message for second assertion in "returning batch for wide table" test ## How was this patch tested? Existing tests. Author: tedyu <yuzhihong@gmail.com> Closes #12639 from tedyu/master.
* [MINOR] [SQL] Fix error message string in nullSafeEvel of TernaryExpressionDongjoon Hyun2016-04-231-1/+2
| | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? TernaryExpressions should thows proper error message for itself. ```scala protected def nullSafeEval(input1: Any, input2: Any, input3: Any): Any = - sys.error(s"BinaryExpressions must override either eval or nullSafeEval") + sys.error(s"TernaryExpressions must override either eval or nullSafeEval") ``` ## How was this patch tested? Manual. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #12642 from dongjoon-hyun/minor_fix_error_msg_in_ternaryexpression.
* [SPARK-14877][SQL] Remove HiveMetastoreTypes classReynold Xin2016-04-238-60/+23
| | | | | | | | | | | | ## What changes were proposed in this pull request? It is unnecessary as DataType.catalogString largely replaces the need for this class. ## How was this patch tested? Mostly removing dead code and should be covered by existing tests. Author: Reynold Xin <rxin@databricks.com> Closes #12644 from rxin/SPARK-14877.
* [SPARK-14865][SQL] Better error handling for view creation.Reynold Xin2016-04-233-71/+100
| | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This patch improves error handling in view creation. CreateViewCommand itself will analyze the view SQL query first, and if it cannot successfully analyze it, throw an AnalysisException. In addition, I also added the following two conservative guards for easier identification of Spark bugs: 1. If there is a bug and the generated view SQL cannot be analyzed, throw an exception at runtime. Note that this is not an AnalysisException because it is not caused by the user and more likely indicate a bug in Spark. 2. SQLBuilder when it gets an unresolved plan, it will also show the plan in the error message. I also took the chance to simplify the internal implementation of CreateViewCommand, and *removed* a fallback path that would've masked an exception from before. ## How was this patch tested? 1. Added a unit test for the user facing error handling. 2. Manually introduced some bugs in Spark to test the internal defensive error handling. 3. Also added a test case to test nested views (not super relevant). Author: Reynold Xin <rxin@databricks.com> Closes #12633 from rxin/SPARK-14865.
* [SPARK-14869][SQL] Don't mask exceptions in ResolveRelationsReynold Xin2016-04-239-17/+25
| | | | | | | | | | | | ## What changes were proposed in this pull request? In order to support running SQL directly on files, we added some code in ResolveRelations to catch the exception thrown by catalog.lookupRelation and ignore it. This unfortunately masks all the exceptions. This patch changes the logic to simply test the table's existence. ## How was this patch tested? I manually hacked some bugs into Spark and made sure the exceptions were being propagated up. Author: Reynold Xin <rxin@databricks.com> Closes #12634 from rxin/SPARK-14869.
* [SPARK-14872][SQL] Restructure command packageReynold Xin2016-04-237-257/+317
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? This patch restructures sql.execution.command package to break the commands into multiple files, in some logical organization: databases, tables, views, functions. I also renamed basicOperators.scala to basicLogicalOperators.scala and basicPhysicalOperators.scala. ## How was this patch tested? N/A - all I did was moving code around. Author: Reynold Xin <rxin@databricks.com> Closes #12636 from rxin/SPARK-14872.
* [SPARK-14871][SQL] Disable StatsReportListener to declutter outputReynold Xin2016-04-231-2/+0
| | | | | | | | | | | | ## What changes were proposed in this pull request? Spark SQL inherited from Shark to use the StatsReportListener. Unfortunately this clutters the spark-sql CLI output and makes it very difficult to read the actual query results. ## How was this patch tested? Built and tested in spark-sql CLI. Author: Reynold Xin <rxin@databricks.com> Closes #12635 from rxin/SPARK-14871.
* [HOTFIX] disable generated aggregate mapDavies Liu2016-04-231-1/+1
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* Turn script transformation back on.Reynold Xin2016-04-231-2/+2
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? (Please fill in changes proposed in this fix) ## How was this patch tested? (Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests) (If this patch involves UI changes, please attach a screenshot; otherwise, remove this) Author: Reynold Xin <rxin@databricks.com> Closes #12565 from rxin/test-flaky.
* [MINOR][ML][MLLIB] Remove unused importsZheng RuiFeng2016-04-224-5/+2
| | | | | | | | | | | | ## What changes were proposed in this pull request? del unused imports in ML/MLLIB ## How was this patch tested? unit tests Author: Zheng RuiFeng <ruifengz@foxmail.com> Closes #12497 from zhengruifeng/del_unused_imports.
* [SPARK-14551][SQL] Reduce number of NameNode calls in OrcRelationRajesh Balamohan2016-04-222-11/+108
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? When FileSourceStrategy is used, record reader is created which incurs a NN call internally. Later in OrcRelation.unwrapOrcStructs, it ends ups reading the file information to get the ObjectInspector. This incurs additional NN call. It would be good to avoid this additional NN call (specifically for partitioned datasets). Added OrcRecordReader which is very similar to OrcNewInputFormat.OrcRecordReader with an option of exposing the ObjectInspector. This eliminates the need to look up the file later for generating the object inspector. This would be specifically be useful for partitioned tables/datasets. ## How was this patch tested? Ran tpc-ds queries manually and also verified by running org.apache.spark.sql.hive.orc.OrcSuite,org.apache.spark.sql.hive.orc.OrcQuerySuite,org.apache.spark.sql.hive.orc.OrcPartitionDiscoverySuite,OrcPartitionDiscoverySuite.OrcHadoopFsRelationSuite,org.apache.spark.sql.hive.execution.HiveCompatibilitySuite …SourceStrategy mode Author: Rajesh Balamohan <rbalamohan@apache.org> Closes #12319 from rajeshbalamohan/SPARK-14551.
* [SPARK-14866][SQL] Break SQLQuerySuite out into smaller test suitesReynold Xin2016-04-224-512/+572
| | | | | | | | | | | | ## What changes were proposed in this pull request? This patch breaks SQLQuerySuite out into smaller test suites. It was a little bit too large for debugging. ## How was this patch tested? This is a test only change. Author: Reynold Xin <rxin@databricks.com> Closes #12630 from rxin/SPARK-14866.
* [SPARK-14863][SQL] Cache TreeNode's hashCode by defaultJosh Rosen2016-04-231-0/+5
| | | | | | | | Caching TreeNode's `hashCode` can lead to orders-of-magnitude performance improvement in certain optimizer rules when operating on huge/complex schemas. Author: Josh Rosen <joshrosen@databricks.com> Closes #12626 from JoshRosen/cache-treenode-hashcode.
* [SPARK-14856] [SQL] returning batch correctlyDavies Liu2016-04-223-10/+35
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Currently, the Parquet reader decide whether to return batch based on required schema or full schema, it's not consistent, this PR fix that. ## How was this patch tested? Added regression tests. Author: Davies Liu <davies@databricks.com> Closes #12619 from davies/fix_return_batch.
* [SPARK-14842][SQL] Implement view creation in sql/coreReynold Xin2016-04-229-182/+140
| | | | | | | | | | | | ## What changes were proposed in this pull request? This patch re-implements view creation command in sql/core, based on the pre-existing view creation command in the Hive module. This consolidates the view creation logical command and physical command into a single one, called CreateViewCommand. ## How was this patch tested? All the code should've been tested by existing tests. Author: Reynold Xin <rxin@databricks.com> Closes #12615 from rxin/SPARK-14842-2.
* [SPARK-14807] Create a compatibility moduleYin Huai2016-04-221-0/+50
| | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR creates a compatibility module in sql (called `hive-1-x-compatibility`), which will host HiveContext in Spark 2.0 (moving HiveContext to here will be done separately). This module is not included in assembly because only users who still want to access HiveContext need it. ## How was this patch tested? I manually tested `sbt/sbt -Phive package` and `mvn -Phive package -DskipTests`. Author: Yin Huai <yhuai@databricks.com> Closes #12580 from yhuai/compatibility.
* [SPARK-14855][SQL] Add "Exec" suffix to physical operatorsReynold Xin2016-04-2277-436/+473
| | | | | | | | | | | | ## What changes were proposed in this pull request? This patch adds "Exec" suffix to all physical operators. Before this patch, Spark's physical operators and logical operators are named the same (e.g. Project could be logical.Project or execution.Project), which caused small issues in code review and bigger issues in code refactoring. ## How was this patch tested? N/A Author: Reynold Xin <rxin@databricks.com> Closes #12617 from rxin/exec-node.
* [SPARK-14832][SQL][STREAMING] Refactor DataSource to ensure schema is ↵Tathagata Das2016-04-224-49/+116
| | | | | | | | | | | | | | | | | | | | | inferred only once when creating a file stream ## What changes were proposed in this pull request? When creating a file stream using sqlContext.write.stream(), existing files are scanned twice for finding the schema - Once, when creating a DataSource + StreamingRelation in the DataFrameReader.stream() - Again, when creating streaming Source from the DataSource, in DataSource.createSource() Instead, the schema should be generated only once, at the time of creating the dataframe, and when the streaming source is created, it should just reuse that schema The solution proposed in this PR is to add a lazy field in DataSource that caches the schema. Then streaming Source created by the DataSource can just reuse the schema. ## How was this patch tested? Refactored unit tests. Author: Tathagata Das <tathagata.das1565@gmail.com> Closes #12591 from tdas/SPARK-14832.
* [SPARK-14582][SQL] increase parallelism for small tablesDavies Liu2016-04-222-1/+9
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR try to increase the parallelism for small table (a few of big files) to reduce the query time, by decrease the maxSplitBytes, the goal is to have at least one task per CPU in the cluster, if the total size of all files is bigger than openCostInBytes * 2 * nCPU. For example, a small/medium table could be used as dimension table in huge query, this will be useful to reduce the time waiting for broadcast. ## How was this patch tested? Existing tests. Author: Davies Liu <davies@databricks.com> Closes #12344 from davies/more_partition.
* [SPARK-14796][SQL] Add spark.sql.optimizer.inSetConversionThreshold config ↵Dongjoon Hyun2016-04-225-7/+40
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | option. ## What changes were proposed in this pull request? Currently, `OptimizeIn` optimizer replaces `In` expression into `InSet` expression if the size of set is greater than a constant, 10. This issue aims to make a configuration `spark.sql.optimizer.inSetConversionThreshold` for that. After this PR, `OptimizerIn` is configurable. ```scala scala> sql("select a in (1,2,3) from (select explode(array(1,2)) a) T").explain() == Physical Plan == WholeStageCodegen : +- Project [a#7 IN (1,2,3) AS (a IN (1, 2, 3))#8] : +- INPUT +- Generate explode([1,2]), false, false, [a#7] +- Scan OneRowRelation[] scala> sqlContext.setConf("spark.sql.optimizer.inSetConversionThreshold", "2") scala> sql("select a in (1,2,3) from (select explode(array(1,2)) a) T").explain() == Physical Plan == WholeStageCodegen : +- Project [a#16 INSET (1,2,3) AS (a IN (1, 2, 3))#17] : +- INPUT +- Generate explode([1,2]), false, false, [a#16] +- Scan OneRowRelation[] ``` ## How was this patch tested? Pass the Jenkins tests (with a new testcase) Author: Dongjoon Hyun <dongjoon@apache.org> Closes #12562 from dongjoon-hyun/SPARK-14796.
* [SPARK-14669] [SQL] Fix some SQL metrics in codegen and added moreDavies Liu2016-04-229-31/+99
| | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? 1. Fix the "spill size" of TungstenAggregate and Sort 2. Rename "data size" to "peak memory" to match the actual meaning (also consistent with task metrics) 3. Added "data size" for ShuffleExchange and BroadcastExchange 4. Added some timing for Sort, Aggregate and BroadcastExchange (this requires another patch to work) ## How was this patch tested? Existing tests. ![metrics](https://cloud.githubusercontent.com/assets/40902/14573908/21ad2f00-030d-11e6-9e2c-c544f30039ea.png) Author: Davies Liu <davies@databricks.com> Closes #12425 from davies/fix_metrics.
* [SPARK-14791] [SQL] fix risk condition between broadcast and subqueryDavies Liu2016-04-224-15/+34
| | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? SparkPlan.prepare() could be called in different threads (BroadcastExchange will call it in a thread pool), it only make sure that doPrepare() will only be called once, the second call to prepare() may return earlier before all the children had finished prepare(). Then some operator may call doProduce() before prepareSubqueries(), `null` will be used as the result of subquery, which is wrong. This cause TPCDS Q23B returns wrong answer sometimes. This PR added synchronization for prepare(), make sure all the children had finished prepare() before return. Also call prepare() in produce() (similar to execute()). Added checking for ScalarSubquery to make sure that the subquery has finished before using the result. ## How was this patch tested? Manually tested with Q23B, no wrong answer anymore. Author: Davies Liu <davies@databricks.com> Closes #12600 from davies/fix_risk.
* [SPARK-14763][SQL] fix subquery resolutionDavies Liu2016-04-227-49/+173
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Currently, a column could be resolved wrongly if there are columns from both outer table and subquery have the same name, we should only resolve the attributes that can't be resolved within subquery. They may have same exprId than other attributes in subquery, so we should create alias for them. Also, the column in IN subquery could have same exprId, we should create alias for them. ## How was this patch tested? Added regression tests. Manually tests TPCDS Q70 and Q95, work well after this patch. Author: Davies Liu <davies@databricks.com> Closes #12539 from davies/fix_subquery.
* [SPARK-14762] [SQL] TPCDS Q90 fails to parseHerman van Hovell2016-04-222-6/+51
| | | | | | | | | | | | | | | | | ### What changes were proposed in this pull request? TPCDS Q90 fails to parse because it uses a reserved keyword as an Identifier; `AT` was used as an alias for one of the subqueries. `AT` is not a reserved keyword and should have been registerd as a in the `nonReserved` rule. In order to prevent this from happening again I have added tests for all keywords that are non-reserved in Hive. See the `nonReserved`, `sql11ReservedKeywordsUsedAsCastFunctionName` & `sql11ReservedKeywordsUsedAsIdentifier` rules in https://github.com/apache/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/parse/IdentifiersParser.g. ### How was this patch tested? Added tests to for all Hive non reserved keywords to `TableIdentifierParserSuite`. cc davies Author: Herman van Hovell <hvanhovell@questtec.nl> Closes #12537 from hvanhovell/SPARK-14762.
* [SPARK-14841][SQL] Move SQLBuilder into sql/coreReynold Xin2016-04-228-19/+19
| | | | | | | | | | | | | ## What changes were proposed in this pull request? This patch moves SQLBuilder into sql/core so we can in the future move view generation also into sql/core. ## How was this patch tested? Also moved unit tests. Author: Reynold Xin <rxin@databricks.com> Author: Wenchen Fan <wenchen@databricks.com> Closes #12602 from rxin/SPARK-14841.
* [SPARK-13266] [SQL] None read/writer options were not transalated to "null"Liang-Chi Hsieh2016-04-221-1/+5
| | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? In Python, the `option` and `options` method of `DataFrameReader` and `DataFrameWriter` were sending the string "None" instead of `null` when passed `None`, therefore making it impossible to send an actual `null`. This fixes that problem. This is based on #11305 from mathieulongtin. ## How was this patch tested? Added test to readwriter.py. Author: Liang-Chi Hsieh <simonh@tw.ibm.com> Author: mathieu longtin <mathieu.longtin@nuance.com> Closes #12494 from viirya/py-df-none-option.
* [SPARK-14848][SQL] Compare as Set in DatasetSuite - Java encoderPete Robbins2016-04-221-2/+2
| | | | | | | | | | | | ## What changes were proposed in this pull request? Change test to compare sets rather than sequence ## How was this patch tested? Full test runs on little endian and big endian platforms Author: Pete Robbins <robbinspg@gmail.com> Closes #12610 from robbinspg/DatasetSuiteFix.
* [SPARK-6429] Implement hashCode and equals togetherJoan2016-04-2213-18/+57
| | | | | | | | | | | ## What changes were proposed in this pull request? Implement some `hashCode` and `equals` together in order to enable the scalastyle. This is a first batch, I will continue to implement them but I wanted to know your thoughts. Author: Joan <joan@goyeau.com> Closes #12157 from joan38/SPARK-6429-HashCode-Equals.
* [SPARK-14609][SQL] Native support for LOAD DATA DDL commandLiang-Chi Hsieh2016-04-2211-8/+427
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Add the native support for LOAD DATA DDL command that loads data into Hive table/partition. ## How was this patch tested? `HiveDDLCommandSuite` and `HiveQuerySuite`. Besides, few Hive tests (`WindowQuerySuite`, `HiveTableScanSuite` and `HiveSerDeSuite`) also use `LOAD DATA` command. Author: Liang-Chi Hsieh <simonh@tw.ibm.com> Closes #12412 from viirya/ddl-load-data.
* [SPARK-14826][SQL] Remove HiveQueryExecutionReynold Xin2016-04-2220-436/+420
| | | | | | | | | | | | ## What changes were proposed in this pull request? This patch removes HiveQueryExecution. As part of this, I consolidated all the describe commands into DescribeTableCommand. ## How was this patch tested? Should be covered by existing tests. Author: Reynold Xin <rxin@databricks.com> Closes #12588 from rxin/SPARK-14826.
* [SPARK-14835][SQL] Remove MetastoreRelation dependency from SQLBuilderReynold Xin2016-04-212-8/+22
| | | | | | | | | | | | ## What changes were proposed in this pull request? This patch removes SQLBuilder's dependency on MetastoreRelation. We should be able to move SQLBuilder into the sql/core package after this change. ## How was this patch tested? N/A - covered by existing tests. Author: Reynold Xin <rxin@databricks.com> Closes #12594 from rxin/SPARK-14835.
* [SPARK-14369] [SQL] Locality support for FileScanRDDCheng Lian2016-04-216-37/+291
| | | | | | | | | | | | | | | | | | | | | | | | | | (This PR is a rebased version of PR #12153.) ## What changes were proposed in this pull request? This PR adds preliminary locality support for `FileFormat` data sources by overriding `FileScanRDD.preferredLocations()`. The strategy can be divided into two parts: 1. Block location lookup Unlike `HadoopRDD` or `NewHadoopRDD`, `FileScanRDD` doesn't have access to the underlying `InputFormat` or `InputSplit`, and thus can't rely on `InputSplit.getLocations()` to gather locality information. Instead, this PR queries block locations using `FileSystem.getBlockLocations()` after listing all `FileStatus`es in `HDFSFileCatalog` and convert all `FileStatus`es into `LocatedFileStatus`es. Note that although S3/S3A/S3N file systems don't provide valid locality information, their `getLocatedStatus()` implementations don't actually issue remote calls either. So there's no need to special case these file systems. 2. Selecting preferred locations For each `FilePartition`, we pick up top 3 locations that containing the most data to be retrieved. This isn't necessarily the best algorithm out there. Further improvements may be brought up in follow-up PRs. ## How was this patch tested? Tested by overriding default `FileSystem` implementation for `file:///` with a mocked one, which returns mocked block locations. Author: Cheng Lian <lian@databricks.com> Closes #12527 from liancheng/spark-14369-locality-rebased.
* [SPARK-14680] [SQL] Support all datatypes to use VectorizedHashmap in ↵Sameer Agarwal2016-04-215-39/+322
| | | | | | | | | | | | | | | | TungstenAggregate ## What changes were proposed in this pull request? This PR adds support for all primitive datatypes, decimal types and stringtypes in the VectorizedHashmap during aggregation. ## How was this patch tested? Existing tests for group-by aggregates should already test for all these datatypes. Additionally, manually inspected the generated code for all supported datatypes (details below). Author: Sameer Agarwal <sameer@databricks.com> Closes #12440 from sameeragarwal/all-datatypes.
* [SPARK-14793] [SQL] Code generation for large complex type exceeds JVM size ↵Takuya UESHIN2016-04-213-53/+144
| | | | | | | | | | | | | | | | | | limit. ## What changes were proposed in this pull request? Code generation for complex type, `CreateArray`, `CreateMap`, `CreateStruct`, `CreateNamedStruct`, exceeds JVM size limit for large elements. We should split generated code into multiple `apply` functions if the complex types have large elements, like `UnsafeProjection` or others for large expressions. ## How was this patch tested? I added some tests to check if the generated codes for the expressions exceed or not. Author: Takuya UESHIN <ueshin@happy-camper.st> Closes #12559 from ueshin/issues/SPARK-14793.
* [SPARK-14824][SQL] Rename HiveContext object to HiveUtilsAndrew Or2016-04-2120-55/+55
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Just a rename so we can get rid of `HiveContext.scala`. Note that this will conflict with #12585. ## How was this patch tested? No change in functionality. Author: Andrew Or <andrew@databricks.com> Closes #12586 from andrewor14/rename-hc-object.
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