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* Fix indentation for the previous patch.Reynold Xin2016-01-071-10/+8
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* [SPARK-12317][SQL] Support units (m,k,g) in SQLConfKevin Yu2016-01-072-1/+60
| | | | | | | | | | | | | | This PR is continue from previous closed PR 10314. In this PR, SHUFFLE_TARGET_POSTSHUFFLE_INPUT_SIZE will be taken memory string conventions as input. For example, the user can now specify 10g for SHUFFLE_TARGET_POSTSHUFFLE_INPUT_SIZE in SQLConf file. marmbrus srowen : Can you help review this code changes ? Thanks. Author: Kevin Yu <qyu@us.ibm.com> Closes #10629 from kevinyu98/spark-12317.
* [SPARK-12580][SQL] Remove string concatenations from usage and extended in ↵Kazuaki Ishizaki2016-01-072-25/+25
| | | | | | | | | | | | | | @ExpressionDescription Use multi-line string literals for ExpressionDescription with ``// scalastyle:off line.size.limit`` and ``// scalastyle:on line.size.limit`` The policy is here, as describe at https://github.com/apache/spark/pull/10488 Let's use multi-line string literals. If we have to have a line with more than 100 characters, let's use ``// scalastyle:off line.size.limit`` and ``// scalastyle:on line.size.limit`` to just bypass the line number requirement. Author: Kazuaki Ishizaki <ishizaki@jp.ibm.com> Closes #10524 from kiszk/SPARK-12580.
* [MINOR] Fix for BUILD FAILURE for Scala 2.11Jacek Laskowski2016-01-071-18/+1
| | | | | | | | | | It was introduced in 917d3fc069fb9ea1c1487119c9c12b373f4f9b77 /cc cloud-fan rxin Author: Jacek Laskowski <jacek@japila.pl> Closes #10636 from jaceklaskowski/fix-for-build-failure-2.11.
* [SPARK-12662][SQL] Fix DataFrame.randomSplit to avoid creating overlapping ↵Sameer Agarwal2016-01-072-1/+28
| | | | | | | | | | | | splits https://issues.apache.org/jira/browse/SPARK-12662 cc yhuai Author: Sameer Agarwal <sameer@databricks.com> Closes #10626 from sameeragarwal/randomsplit.
* [SPARK-12542][SQL] support except/intersect in HiveQlDavies Liu2016-01-065-5/+65
| | | | | | | | Parse the SQL query with except/intersect in FROM clause for HivQL. Author: Davies Liu <davies@databricks.com> Closes #10622 from davies/intersect.
* [SPARK-12295] [SQL] external spilling for window functionsDavies Liu2016-01-061-86/+228
| | | | | | | | | | This PR manage the memory used by window functions (buffered rows), also enable external spilling. After this PR, we can run window functions on a partition with hundreds of millions of rows with only 1G. Author: Davies Liu <davies@databricks.com> Closes #10605 from davies/unsafe_window.
* [SPARK-12640][SQL] Add simple benchmarking utility class and add Parquet ↵Nong Li2016-01-061-0/+158
| | | | | | | | | | | | | | | scan benchmarks. [SPARK-12640][SQL] Add simple benchmarking utility class and add Parquet scan benchmarks. We've run benchmarks ad hoc to measure the scanner performance. We will continue to invest in this and it makes sense to get these benchmarks into code. This adds a simple benchmarking utility to do this. Author: Nong Li <nong@databricks.com> Author: Nong <nongli@gmail.com> Closes #10589 from nongli/spark-12640.
* [SPARK-12539][SQL] support writing bucketed tableWenchen Fan2016-01-0618-117/+626
| | | | | | | | | | | | | | | | | | | | | | This PR adds bucket write support to Spark SQL. User can specify bucketing columns, numBuckets and sorting columns with or without partition columns. For example: ``` df.write.partitionBy("year").bucketBy(8, "country").sortBy("amount").saveAsTable("sales") ``` When bucketing is used, we will calculate bucket id for each record, and group the records by bucket id. For each group, we will create a file with bucket id in its name, and write data into it. For each bucket file, if sorting columns are specified, the data will be sorted before write. Note that there may be multiply files for one bucket, as the data is distributed. Currently we store the bucket metadata at hive metastore in a non-hive-compatible way. We use different bucketing hash function compared to hive, so we can't be compatible anyway. Limitations: * Can't write bucketed data without hive metastore. * Can't insert bucketed data into existing hive tables. Author: Wenchen Fan <wenchen@databricks.com> Closes #10498 from cloud-fan/bucket-write.
* [SPARK-12681] [SQL] split IdentifiersParser.g into two filesDavies Liu2016-01-063-516/+566
| | | | | | | | | | To avoid to have a huge Java source (over 64K loc), that can't be compiled. cc hvanhovell Author: Davies Liu <davies@databricks.com> Closes #10624 from davies/split_ident.
* [SPARK-12573][SPARK-12574][SQL] Move SQL Parser from Hive to CatalystHerman van Hovell2016-01-0623-2746/+2041
| | | | | | | | | | | | | | | | | This PR moves a major part of the new SQL parser to Catalyst. This is a prelude to start using this parser for all of our SQL parsing. The following key changes have been made: The ANTLR Parser & Supporting classes have been moved to the Catalyst project. They are now part of the ```org.apache.spark.sql.catalyst.parser``` package. These classes contained quite a bit of code that was originally from the Hive project, I have added aknowledgements whenever this applied. All Hive dependencies have been factored out. I have also taken this chance to clean-up the ```ASTNode``` class, and to improve the error handling. The HiveQl object that provides the functionality to convert an AST into a LogicalPlan has been refactored into three different classes, one for every SQL sub-project: - ```CatalystQl```: This implements Query and Expression parsing functionality. - ```SparkQl```: This is a subclass of CatalystQL and provides SQL/Core only functionality such as Explain and Describe. - ```HiveQl```: This is a subclass of ```SparkQl``` and this adds Hive-only functionality to the parser such as Analyze, Drop, Views, CTAS & Transforms. This class still depends on Hive. cc rxin Author: Herman van Hovell <hvanhovell@questtec.nl> Closes #10583 from hvanhovell/SPARK-12575.
* [SPARK-11878][SQL] Eliminate distribute by in case group by is present with ↵Yash Datta2016-01-062-0/+45
| | | | | | | | | | | | | exactly the same grouping expressi For queries like : select <> from table group by a distribute by a we can eliminate distribute by ; since group by will anyways do a hash partitioning Also applicable when user uses Dataframe API Author: Yash Datta <Yash.Datta@guavus.com> Closes #9858 from saucam/eliminatedistribute.
* [SPARK-12340][SQL] fix Int overflow in the SparkPlan.executeTake, RDD.take ↵QiangCai2016-01-062-4/+16
| | | | | | | | | | | | | and AsyncRDDActions.takeAsync I have closed pull request https://github.com/apache/spark/pull/10487. And I create this pull request to resolve the problem. spark jira https://issues.apache.org/jira/browse/SPARK-12340 Author: QiangCai <david.caiq@gmail.com> Closes #10562 from QiangCai/bugfix.
* [SPARK-12578][SQL] Distinct should not be silently ignored when used in an ↵Liang-Chi Hsieh2016-01-062-1/+22
| | | | | | | | | | | | aggregate function with OVER clause JIRA: https://issues.apache.org/jira/browse/SPARK-12578 Slightly update to Hive parser. We should keep the distinct keyword when used in an aggregate function with OVER clause. So the CheckAnalysis will detect it and throw exception later. Author: Liang-Chi Hsieh <viirya@gmail.com> Closes #10557 from viirya/keep-distinct-hivesql.
* [SPARK-3873][TESTS] Import ordering fixes.Marcelo Vanzin2016-01-05116-223/+203
| | | | | | Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #10582 from vanzin/SPARK-3873-tests.
* [SPARK-12504][SQL] Masking credentials in the sql plan explain output for ↵sureshthalamati2016-01-052-0/+27
| | | | | | | | | | | | JDBC data sources. This fix masks JDBC credentials in the explain output. URL patterns to specify credential seems to be vary between different databases. Added a new method to dialect to mask the credentials according to the database specific URL pattern. While adding tests I noticed explain output includes array variable for partitions ([Lorg.apache.spark.Partition;3ff74546,). Modified the code to include the first, and last partition information. Author: sureshthalamati <suresh.thalamati@gmail.com> Closes #10452 from sureshthalamati/mask_jdbc_credentials_spark-12504.
* [SPARK-3873][SQL] Import ordering fixes.Marcelo Vanzin2016-01-05164-318/+301
| | | | | | Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #10573 from vanzin/SPARK-3873-sql.
* [SPARK-12636] [SQL] Update UnsafeRowParquetRecordReader to support reading ↵Nong2016-01-053-29/+178
| | | | | | | | | | files directly. As noted in the code, this change is to make this component easier to test in isolation. Author: Nong <nongli@gmail.com> Closes #10581 from nongli/spark-12636.
* [SPARK-12439][SQL] Fix toCatalystArray and MapObjectsLiang-Chi Hsieh2016-01-054-6/+14
| | | | | | | | | | | | JIRA: https://issues.apache.org/jira/browse/SPARK-12439 In toCatalystArray, we should look at the data type returned by dataTypeFor instead of silentSchemaFor, to determine if the element is native type. An obvious problem is when the element is Option[Int] class, catalsilentSchemaFor will return Int, then we will wrongly recognize the element is native type. There is another problem when using Option as array element. When we encode data like Seq(Some(1), Some(2), None) with encoder, we will use MapObjects to construct an array for it later. But in MapObjects, we don't check if the return value of lambdaFunction is null or not. That causes a bug that the decoded data for Seq(Some(1), Some(2), None) would be Seq(1, 2, -1), instead of Seq(1, 2, null). Author: Liang-Chi Hsieh <viirya@gmail.com> Closes #10391 from viirya/fix-catalystarray.
* [SPARK-12615] Remove some deprecated APIs in RDD/SparkContextReynold Xin2016-01-051-1/+1
| | | | | | | | I looked at each case individually and it looks like they can all be removed. The only one that I had to think twice was toArray (I even thought about un-deprecating it, until I realized it was a problem in Java to have toArray returning java.util.List). Author: Reynold Xin <rxin@databricks.com> Closes #10569 from rxin/SPARK-12615.
* [SPARK-12480][FOLLOW-UP] use a single column vararg for hashWenchen Fan2016-01-053-3/+4
| | | | | | | | | | address comments in #10435 This makes the API easier to use if user programmatically generate the call to hash, and they will get analysis exception if the arguments of hash is empty. Author: Wenchen Fan <wenchen@databricks.com> Closes #10588 from cloud-fan/hash.
* [SPARK-12438][SQL] Add SQLUserDefinedType support for encoderLiang-Chi Hsieh2016-01-053-0/+38
| | | | | | | | | | JIRA: https://issues.apache.org/jira/browse/SPARK-12438 ScalaReflection lacks the support of SQLUserDefinedType. We should add it. Author: Liang-Chi Hsieh <viirya@gmail.com> Closes #10390 from viirya/encoder-udt.
* [SPARK-12568][SQL] Add BINARY to EncodersMichael Armbrust2016-01-043-3/+18
| | | | | | Author: Michael Armbrust <michael@databricks.com> Closes #10516 from marmbrus/datasetCleanup.
* [SPARK-12600][SQL] follow up: add range check for DecimalTypeReynold Xin2016-01-041-0/+10
| | | | | | | | This addresses davies' code review feedback in https://github.com/apache/spark/pull/10559 Author: Reynold Xin <rxin@databricks.com> Closes #10586 from rxin/remove-deprecated-sql-followup.
* [SPARK-12480][SQL] add Hash expression that can calculate hash value for a ↵Wenchen Fan2016-01-0410-6/+171
| | | | | | | | | | group of expressions just write the arguments into unsafe row and use murmur3 to calculate hash code Author: Wenchen Fan <wenchen@databricks.com> Closes #10435 from cloud-fan/hash-expr.
* [SPARK-12600][SQL] Remove deprecated methods in Spark SQLReynold Xin2016-01-0418-1062/+123
| | | | | | Author: Reynold Xin <rxin@databricks.com> Closes #10559 from rxin/remove-deprecated-sql.
* [SPARK-12509][SQL] Fixed error messages for DataFrame correlation and covarianceNarine Kokhlikyan2016-01-041-6/+7
| | | | | | | | | | | | | | Currently, when we call corr or cov on dataframe with invalid input we see these error messages for both corr and cov: - "Currently cov supports calculating the covariance between two columns" - "Covariance calculation for columns with dataType "[DataType Name]" not supported." I've fixed this issue by passing the function name as an argument. We could also do the input checks separately for each function. I avoided doing that because of code duplication. Thanks! Author: Narine Kokhlikyan <narine.kokhlikyan@gmail.com> Closes #10458 from NarineK/sparksqlstatsmessages.
* [SPARK-12589][SQL] Fix UnsafeRowParquetRecordReader to properly set the row ↵Nong Li2016-01-043-0/+37
| | | | | | | | | | | | length. The reader was previously not setting the row length meaning it was wrong if there were variable length columns. This problem does not manifest usually, since the value in the column is correct and projecting the row fixes the issue. Author: Nong Li <nong@databricks.com> Closes #10576 from nongli/spark-12589.
* [SPARK-12541] [SQL] support cube/rollup as functionDavies Liu2016-01-048-48/+87
| | | | | | | | | | | This PR enable cube/rollup as function, so they can be used as this: ``` select a, b, sum(c) from t group by rollup(a, b) ``` Author: Davies Liu <davies@databricks.com> Closes #10522 from davies/rollup.
* [SPARK-12421][SQL] Prevent Internal/External row from exposing state.Herman van Hovell2016-01-042-4/+34
| | | | | | | | | | | | It is currently possible to change the values of the supposedly immutable ```GenericRow``` and ```GenericInternalRow``` classes. This is caused by the fact that scala's ArrayOps ```toArray``` (returned by calling ```toSeq```) will return the backing array instead of a copy. This PR fixes this problem. This PR was inspired by https://github.com/apache/spark/pull/10374 by apo1. cc apo1 sarutak marmbrus cloud-fan nongli (everyone in the previous conversation). Author: Herman van Hovell <hvanhovell@questtec.nl> Closes #10553 from hvanhovell/SPARK-12421.
* [DOC] Adjust coverage for partitionBy()tedyu2016-01-041-1/+1
| | | | | | | | | | | | This is the related thread: http://search-hadoop.com/m/q3RTtO3ReeJ1iF02&subj=Re+partitioning+json+data+in+spark Michael suggested fixing the doc. Please review. Author: tedyu <yuzhihong@gmail.com> Closes #10499 from ted-yu/master.
* [SPARK-12512][SQL] support column name with dot in withColumn()Xiu Guo2016-01-042-12/+27
| | | | | | Author: Xiu Guo <xguo27@gmail.com> Closes #10500 from xguo27/SPARK-12512.
* [SPARK-12470] [SQL] Fix size reduction calculationPete Robbins2016-01-041-4/+4
| | | | | | | | also only allocate required buffer size Author: Pete Robbins <robbinspg@gmail.com> Closes #10421 from robbinspg/master.
* [SPARK-12579][SQL] Force user-specified JDBC driver to take precedenceJosh Rosen2016-01-046-47/+33
| | | | | | | | | | | | | | | | Spark SQL's JDBC data source allows users to specify an explicit JDBC driver to load (using the `driver` argument), but in the current code it's possible that the user-specified driver will not be used when it comes time to actually create a JDBC connection. In a nutshell, the problem is that you might have multiple JDBC drivers on the classpath that claim to be able to handle the same subprotocol, so simply registering the user-provided driver class with the our `DriverRegistry` and JDBC's `DriverManager` is not sufficient to ensure that it's actually used when creating the JDBC connection. This patch addresses this issue by first registering the user-specified driver with the DriverManager, then iterating over the driver manager's loaded drivers in order to obtain the correct driver and use it to create a connection (previously, we just called `DriverManager.getConnection()` directly). If a user did not specify a JDBC driver to use, then we call `DriverManager.getDriver` to figure out the class of the driver to use, then pass that class's name to executors; this guards against corner-case bugs in situations where the driver and executor JVMs might have different sets of JDBC drivers on their classpaths (previously, there was the (rare) potential for `DriverManager.getConnection()` to use different drivers on the driver and executors if the user had not explicitly specified a JDBC driver class and the classpaths were different). This patch is inspired by a similar patch that I made to the `spark-redshift` library (https://github.com/databricks/spark-redshift/pull/143), which contains its own modified fork of some of Spark's JDBC data source code (for cross-Spark-version compatibility reasons). Author: Josh Rosen <joshrosen@databricks.com> Closes #10519 from JoshRosen/jdbc-driver-precedence.
* [SPARK-12562][SQL] DataFrame.write.format(text) requires the column name to ↵Xiu Guo2016-01-032-6/+7
| | | | | | | | be called value Author: Xiu Guo <xguo27@gmail.com> Closes #10515 from xguo27/SPARK-12562.
* [SPARK-12537][SQL] Add option to accept quoting of all character backslash ↵Cazen2016-01-033-2/+28
| | | | | | | | | | | | | quoting mechanism We can provides the option to choose JSON parser can be enabled to accept quoting of all character or not. Author: Cazen <Cazen@korea.com> Author: Cazen Lee <cazen.lee@samsung.com> Author: Cazen Lee <Cazen@korea.com> Author: cazen.lee <cazen.lee@samsung.com> Closes #10497 from Cazen/master.
* [SPARK-12533][SQL] hiveContext.table() throws the wrong exceptionthomastechs2016-01-032-4/+4
| | | | | | | | Avoiding the the No such table exception and throwing analysis exception as per the bug: SPARK-12533 Author: thomastechs <thomas.sebastian@tcs.com> Closes #10529 from thomastechs/topic-branch.
* Revert "Revert "[SPARK-12286][SPARK-12290][SPARK-12294][SPARK-12284][SQL] ↵Reynold Xin2016-01-0234-574/+74
| | | | | | always output UnsafeRow"" This reverts commit 44ee920fd49d35b421ae562ea99bcc8f2b98ced6.
* [SPARK-12599][MLLIB][SQL] Remove the use of callUDF in MLlibReynold Xin2016-01-021-0/+14
| | | | | | | | callUDF has been deprecated. However, we do not have an alternative for users to specify the output data type without type tags. This pull request introduced a new API for that, and replaces the invocation of the deprecated callUDF with that. Author: Reynold Xin <rxin@databricks.com> Closes #10547 from rxin/SPARK-12599.
* [SPARK-12481][CORE][STREAMING][SQL] Remove usage of Hadoop deprecated APIs ↵Sean Owen2016-01-0215-156/+60
| | | | | | | | | | and reflection that supported 1.x Remove use of deprecated Hadoop APIs now that 2.2+ is required Author: Sean Owen <sowen@cloudera.com> Closes #10446 from srowen/SPARK-12481.
* [SPARK-10180][SQL] JDBC datasource are not processing EqualNullSafe filterhyukjinkwon2016-01-022-2/+7
| | | | | | | | | | This PR is followed by https://github.com/apache/spark/pull/8391. Previous PR fixes JDBCRDD to support null-safe equality comparison for JDBC datasource. This PR fixes the problem that it can actually return null as a result of the comparison resulting error as using the value of that comparison. Author: hyukjinkwon <gurwls223@gmail.com> Author: HyukjinKwon <gurwls223@gmail.com> Closes #8743 from HyukjinKwon/SPARK-10180.
* [SPARK-12362][SQL][WIP] Inline Hive ParserHerman van Hovell2016-01-0115-71/+5392
| | | | | | | | | | | | | | This PR inlines the Hive SQL parser in Spark SQL. The previous (merged) incarnation of this PR passed all tests, but had and still has problems with the build. These problems are caused by a the fact that - for some reason - in some cases the ANTLR generated code is not included in the compilation fase. This PR is a WIP and should not be merged until we have sorted out the build issues. Author: Herman van Hovell <hvanhovell@questtec.nl> Author: Nong Li <nong@databricks.com> Author: Nong Li <nongli@gmail.com> Closes #10525 from hvanhovell/SPARK-12362.
* Revert "[SPARK-12286][SPARK-12290][SPARK-12294][SPARK-12284][SQL] always ↵Reynold Xin2016-01-0134-74/+574
| | | | | | output UnsafeRow" This reverts commit 0da7bd50ddf0fb9e0e8aeadb9c7fb3edf6f0ee6e.
* [SPARK-12286][SPARK-12290][SPARK-12294][SPARK-12284][SQL] always output ↵Davies Liu2016-01-0134-574/+74
| | | | | | | | | | | | | | | | UnsafeRow It's confusing that some operator output UnsafeRow but some not, easy to make mistake. This PR change to only output UnsafeRow for all the operators (SparkPlan), removed the rule to insert Unsafe/Safe conversions. For those that can't output UnsafeRow directly, added UnsafeProjection into them. Closes #10330 cc JoshRosen rxin Author: Davies Liu <davies@databricks.com> Closes #10511 from davies/unsafe_row.
* [SPARK-12592][SQL][TEST] Don't mute Spark loggers in TestHive.reset()Cheng Lian2016-01-011-1/+4
| | | | | | | | There's a hack done in `TestHive.reset()`, which intended to mute noisy Hive loggers. However, Spark testing loggers are also muted. Author: Cheng Lian <lian@databricks.com> Closes #10540 from liancheng/spark-12592.dont-mute-spark-loggers.
* [SPARK-12409][SPARK-12387][SPARK-12391][SQL] Refactor filter pushdown for ↵Liang-Chi Hsieh2016-01-012-31/+45
| | | | | | | | | | | | JDBCRDD and add few filters This patch refactors the filter pushdown for JDBCRDD and also adds few filters. Added filters are basically from #10468 with some refactoring. Test cases are from #10468. Author: Liang-Chi Hsieh <viirya@gmail.com> Closes #10470 from viirya/refactor-jdbc-filter.
* [SPARK-11743][SQL] Move the test for arrayOfUDTLiang-Chi Hsieh2015-12-311-13/+2
| | | | | | | | A following pr for #9712. Move the test for arrayOfUDT. Author: Liang-Chi Hsieh <viirya@gmail.com> Closes #10538 from viirya/move-udt-test.
* [SPARK-12039][SQL] Re-enable HiveSparkSubmitSuite's SPARK-9757 Persist ↵Yin Huai2015-12-311-1/+1
| | | | | | | | | | | | Parquet relation with decimal column https://issues.apache.org/jira/browse/SPARK-12039 since we do not support hadoop1, we can re-enable this test in master. Author: Yin Huai <yhuai@databricks.com> Closes #10533 from yhuai/SPARK-12039-enable.
* [SPARK-12585] [SQL] move numFields to constructor of UnsafeRowDavies Liu2015-12-3016-137/+86
| | | | | | | | | | Right now, numFields will be passed in by pointTo(), then bitSetWidthInBytes is calculated, making pointTo() a little bit heavy. It should be part of constructor of UnsafeRow. Author: Davies Liu <davies@databricks.com> Closes #10528 from davies/numFields.
* [SPARK-8641][SPARK-12455][SQL] Native Spark Window functions - Follow-up ↵Herman van Hovell2015-12-303-3/+162
| | | | | | | | | | | | | | | | | | (docs & tests) This PR is a follow-up for PR https://github.com/apache/spark/pull/9819. It adds documentation for the window functions and a couple of NULL tests. The documentation was largely based on the documentation in (the source of) Hive and Presto: * https://prestodb.io/docs/current/functions/window.html * https://cwiki.apache.org/confluence/display/Hive/LanguageManual+WindowingAndAnalytics I am not sure if we need to add the licenses of these two projects to the licenses directory. They are both under the ASL. srowen any thoughts? cc yhuai Author: Herman van Hovell <hvanhovell@questtec.nl> Closes #10402 from hvanhovell/SPARK-8641-docs.
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