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* [SPARK-4493][SQL] Don't pushdown Eq, NotEq, Lt, LtEq, Gt and GtEq predicates ↵Cheng Lian2014-12-172-23/+174
| | | | | | | | | | | | | | | | | | | | | with nulls for Parquet Predicates like `a = NULL` and `a < NULL` can't be pushed down since Parquet `Lt`, `LtEq`, `Gt`, `GtEq` doesn't accept null value. Note that `Eq` and `NotEq` can only be used with `null` to represent predicates like `a IS NULL` and `a IS NOT NULL`. However, normally this issue doesn't cause NPE because any value compared to `NULL` results `NULL`, and Spark SQL automatically optimizes out `NULL` predicate in the `SimplifyFilters` rule. Only testing code that intentionally disables the optimizer may trigger this issue. (That's why this issue is not marked as blocker and I do **NOT** think we need to backport this to branch-1.1 This PR restricts `Lt`, `LtEq`, `Gt` and `GtEq` to non-null values only, and only uses `Eq` with null value to pushdown `IsNull` and `IsNotNull`. Also, added support for Parquet `NotEq` filter for completeness and (tiny) performance gain, it's also used to pushdown `IsNotNull`. <!-- Reviewable:start --> [<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/3367) <!-- Reviewable:end --> Author: Cheng Lian <lian@databricks.com> Closes #3367 from liancheng/filters-with-null and squashes the following commits: cc41281 [Cheng Lian] Fixes several styling issues de7de28 [Cheng Lian] Adds stricter rules for Parquet filters with null
* [SPARK-4625] [SQL] Add sort by for DSL & SimpleSqlParserCheng Hao2014-12-173-0/+38
| | | | | | | | | | | | Add `sort by` support for both DSL & SqlParser. This PR is relevant with #3386, either one merged, will cause the other rebased. Author: Cheng Hao <hao.cheng@intel.com> Closes #3481 from chenghao-intel/sortby and squashes the following commits: 041004f [Cheng Hao] Add sort by for DSL & SimpleSqlParser
* [SPARK-4618][SQL] Make foreign DDL commands options case-insensitivescwf2014-12-163-5/+26
| | | | | | | | | | | | | | | | | | | | | | | | | Using lowercase for ```options``` key to make it case-insensitive, then we should use lower case to get value from parameters. So flowing cmd work ``` create temporary table normal_parquet USING org.apache.spark.sql.parquet OPTIONS ( PATH '/xxx/data' ) ``` Author: scwf <wangfei1@huawei.com> Author: wangfei <wangfei1@huawei.com> Closes #3470 from scwf/ddl-ulcase and squashes the following commits: ae78509 [scwf] address comments 8f4f585 [wangfei] address comments 3c132ef [scwf] minor fix a0fc20b [scwf] Merge branch 'master' of https://github.com/apache/spark into ddl-ulcase 4f86401 [scwf] adding CaseInsensitiveMap e244e8d [wangfei] using lower case in json e0cb017 [wangfei] make options in-casesensitive
* [SPARK-4866] support StructType as key in MapTypeDavies Liu2014-12-161-1/+1
| | | | | | | | | | | This PR brings support of using StructType(and other hashable types) as key in MapType. Author: Davies Liu <davies@databricks.com> Closes #3714 from davies/fix_struct_in_map and squashes the following commits: 68585d7 [Davies Liu] fix primitive types in MapType 9601534 [Davies Liu] support StructType as key in MapType
* [SPARK-4375] [SQL] Add 0 argument support for udfCheng Hao2014-12-162-6/+15
| | | | | | | | Author: Cheng Hao <hao.cheng@intel.com> Closes #3595 from chenghao-intel/udf0 and squashes the following commits: a858973 [Cheng Hao] Add 0 arguments support for udf
* [SPARK-4798][SQL] A new set of Parquet testing API and test suitesCheng Lian2014-12-166-0/+945
| | | | | | | | | | | | | | | | | | | | | This PR provides a set Parquet testing API (see trait `ParquetTest`) that enables developers to write more concise test cases. A new set of Parquet test suites built upon this API are added and aim to replace the old `ParquetQuerySuite`. To avoid potential merge conflicts, old testing code are not removed yet. The following classes can be safely removed after most Parquet related PRs are handled: - `ParquetQuerySuite` - `ParquetTestData` <!-- Reviewable:start --> [<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/3644) <!-- Reviewable:end --> Author: Cheng Lian <lian@databricks.com> Closes #3644 from liancheng/parquet-tests and squashes the following commits: 800e745 [Cheng Lian] Enforces ordering of test output 3bb8731 [Cheng Lian] Refactors HiveParquetSuite aa2cb2e [Cheng Lian] Decouples ParquetTest and TestSQLContext 7b43a68 [Cheng Lian] Updates ParquetTest Scaladoc 7f07af0 [Cheng Lian] Adds a new set of Parquet test suites
* [SPARK-4269][SQL] make wait time configurable in BroadcastHashJoinJacky Li2014-12-162-1/+17
| | | | | | | | | | | | | In BroadcastHashJoin, currently it is using a hard coded value (5 minutes) to wait for the execution and broadcast of the small table. In my opinion, it should be a configurable value since broadcast may exceed 5 minutes in some case, like in a busy/congested network environment. Author: Jacky Li <jacky.likun@huawei.com> Closes #3133 from jackylk/timeout-config and squashes the following commits: 733ac08 [Jacky Li] add spark.sql.broadcastTimeout in SQLConf.scala 557acd4 [Jacky Li] switch to sqlContext.getConf 81a5e20 [Jacky Li] make wait time configurable in BroadcastHashJoin
* [SPARK-4483][SQL]Optimization about reduce memory costs during the HashOuterJointianyi2014-12-161-64/+64
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | In `HashOuterJoin.scala`, spark read data from both side of join operation before zip them together. It is a waste for memory. We are trying to read data from only one side, put them into a hashmap, and then generate the `JoinedRow` with data from other side one by one. Currently, we could only do this optimization for `left outer join` and `right outer join`. For `full outer join`, we will do something in another issue. for table test_csv contains 1 million records table dim_csv contains 10 thousand records SQL: `select * from test_csv a left outer join dim_csv b on a.key = b.key` the result is: master: ``` CSV: 12671 ms CSV: 9021 ms CSV: 9200 ms Current Mem Usage:787788984 ``` after patch： ``` CSV: 10382 ms CSV: 7543 ms CSV: 7469 ms Current Mem Usage:208145728 ``` Author: tianyi <tianyi@asiainfo-linkage.com> Author: tianyi <tianyi.asiainfo@gmail.com> Closes #3375 from tianyi/SPARK-4483 and squashes the following commits: 72a8aec [tianyi] avoid having mutable state stored inside of the task 99c5c97 [tianyi] performance optimization d2f94d7 [tianyi] fix bug: missing output when the join-key is null. 2be45d1 [tianyi] fix spell bug 1f2c6f1 [tianyi] remove commented codes a676de6 [tianyi] optimize some codes 9e7d5b5 [tianyi] remove commented old codes 838707d [tianyi] Optimization about reduce memory costs during the HashOuterJoin
* [SPARK-4527][SQl]Add BroadcastNestedLoopJoin operator selection testsuitewangxiaojing2014-12-161-2/+7
| | | | | | | | | | | In `JoinSuite` add BroadcastNestedLoopJoin operator selection testsuite Author: wangxiaojing <u9jing@gmail.com> Closes #3395 from wangxiaojing/SPARK-4527 and squashes the following commits: ea0e495 [wangxiaojing] change style 53c3952 [wangxiaojing] Add BroadcastNestedLoopJoin operator selection testsuite
* [SPARK-4812][SQL] Fix the initialization issue of 'codegenEnabled'zsxwing2014-12-162-3/+1
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | The problem is `codegenEnabled` is `val`, but it uses a `val` `sqlContext`, which can be override by subclasses. Here is a simple example to show this issue. ```Scala scala> :paste // Entering paste mode (ctrl-D to finish) abstract class Foo { protected val sqlContext = "Foo" val codegenEnabled: Boolean = { println(sqlContext) // it will call subclass's `sqlContext` which has not yet been initialized. if (sqlContext != null) { true } else { false } } } class Bar extends Foo { override val sqlContext = "Bar" } println(new Bar().codegenEnabled) // Exiting paste mode, now interpreting. null false defined class Foo defined class Bar ``` We should make `sqlContext` `final` to prevent subclasses from overriding it incorrectly. Author: zsxwing <zsxwing@gmail.com> Closes #3660 from zsxwing/SPARK-4812 and squashes the following commits: 1cbb623 [zsxwing] Make `sqlContext` final to prevent subclasses from overriding it incorrectly
* [SPARK-4847][SQL]Fix "extraStrategies cannot take effect in SQLContext" issuejerryshao2014-12-161-1/+1
| | | | | | | | Author: jerryshao <saisai.shao@intel.com> Closes #3698 from jerryshao/SPARK-4847 and squashes the following commits: 4741130 [jerryshao] Make later added extraStrategies effect when calling strategies
* [SPARK-4742][SQL] The name of Parquet File generated by ↵Sasaki Toru2014-12-111-1/+6
| | | | | | | | | | | | | AppendingParquetOutputFormat should be zero padded When I use Parquet File as a output file using ParquetOutputFormat#getDefaultWorkFile, the file name is not zero padded while RDD#saveAsText does zero padding. Author: Sasaki Toru <sasakitoa@nttdata.co.jp> Closes #3602 from sasakitoa/parquet-zeroPadding and squashes the following commits: 6b0e58f [Sasaki Toru] Merge branch 'master' of git://github.com/apache/spark into parquet-zeroPadding 20dc79d [Sasaki Toru] Fixed the name of Parquet File generated by AppendingParquetOutputFormat
* [SPARK-4713] [SQL] SchemaRDD.unpersist() should not raise exception if it is ↵Cheng Hao2014-12-112-1/+15
| | | | | | | | | | | | | | | | | | | not persisted Unpersist a uncached RDD, will not raise exception, for example: ``` val data = Array(1, 2, 3, 4, 5) val distData = sc.parallelize(data) distData.unpersist(true) ``` But the `SchemaRDD` will raise exception if the `SchemaRDD` is not cached. Since `SchemaRDD` is the subclasses of the `RDD`, we should follow the same behavior. Author: Cheng Hao <hao.cheng@intel.com> Closes #3572 from chenghao-intel/try_uncache and squashes the following commits: 50a7a89 [Cheng Hao] SchemaRDD.unpersist() should not raise exception if it is not persisted
* [SQL] remove unnecessary import in spark-sqlJacky Li2014-12-085-9/+3
| | | | | | | | Author: Jacky Li <jacky.likun@huawei.com> Closes #3630 from jackylk/remove and squashes the following commits: 150e7e0 [Jacky Li] remove unnecessary import
* [SPARK-4753][SQL] Use catalyst for partition pruning in newParquet.Michael Armbrust2014-12-041-30/+28
| | | | | | | | Author: Michael Armbrust <michael@databricks.com> Closes #3613 from marmbrus/parquetPartitionPruning and squashes the following commits: 4f138f8 [Michael Armbrust] Use catalyst for partition pruning in newParquet.
* [SQL] remove unnecessary importJacky Li2014-12-041-1/+0
| | | | | | | | Author: Jacky Li <jacky.likun@huawei.com> Closes #3585 from jackylk/remove and squashes the following commits: 045423d [Jacky Li] remove unnecessary import
* [SPARK-4552][SQL] Avoid exception when reading empty parquet data through HiveMichael Armbrust2014-12-031-1/+4
| | | | | | | | | | | This is a very small fix that catches one specific exception and returns an empty table. #3441 will address this in a more principled way. Author: Michael Armbrust <michael@databricks.com> Closes #3586 from marmbrus/fixEmptyParquet and squashes the following commits: 2781d9f [Michael Armbrust] Handle empty lists for newParquet 04dd376 [Michael Armbrust] Avoid exception when reading empty parquet data through Hive
* [SPARK-4676][SQL] JavaSchemaRDD.schema may throw NullType MatchError if sql ↵YanTangZhai2014-12-025-0/+59
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | has null val jsc = new org.apache.spark.api.java.JavaSparkContext(sc) val jhc = new org.apache.spark.sql.hive.api.java.JavaHiveContext(jsc) val nrdd = jhc.hql("select null from spark_test.for_test") println(nrdd.schema) Then the error is thrown as follows: scala.MatchError: NullType (of class org.apache.spark.sql.catalyst.types.NullType$) at org.apache.spark.sql.types.util.DataTypeConversions$.asJavaDataType(DataTypeConversions.scala:43) Author: YanTangZhai <hakeemzhai@tencent.com> Author: yantangzhai <tyz0303@163.com> Author: Michael Armbrust <michael@databricks.com> Closes #3538 from YanTangZhai/MatchNullType and squashes the following commits: e052dff [yantangzhai] [SPARK-4676] [SQL] JavaSchemaRDD.schema may throw NullType MatchError if sql has null 4b4bb34 [yantangzhai] [SPARK-4676] [SQL] JavaSchemaRDD.schema may throw NullType MatchError if sql has null 896c7b7 [yantangzhai] fix NullType MatchError in JavaSchemaRDD when sql has null 6e643f8 [YanTangZhai] Merge pull request #11 from apache/master e249846 [YanTangZhai] Merge pull request #10 from apache/master d26d982 [YanTangZhai] Merge pull request #9 from apache/master 76d4027 [YanTangZhai] Merge pull request #8 from apache/master 03b62b0 [YanTangZhai] Merge pull request #7 from apache/master 8a00106 [YanTangZhai] Merge pull request #6 from apache/master cbcba66 [YanTangZhai] Merge pull request #3 from apache/master cdef539 [YanTangZhai] Merge pull request #1 from apache/master
* [SPARK-4663][sql]add finally to avoid resource leakbaishuo2014-12-021-4/+7
| | | | | | | | | | Author: baishuo <vc_java@hotmail.com> Closes #3526 from baishuo/master-trycatch and squashes the following commits: d446e14 [baishuo] correct the code style b36bf96 [baishuo] correct the code style ae0e447 [baishuo] add finally to avoid resource leak
* [SPARK-4536][SQL] Add sqrt and abs to Spark SQL DSLKousuke Saruta2014-12-022-0/+72
| | | | | | | | | | | | | Spark SQL has embeded sqrt and abs but DSL doesn't support those functions. Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp> Closes #3401 from sarutak/dsl-missing-operator and squashes the following commits: 07700cf [Kousuke Saruta] Modified Literal(null, NullType) to Literal(null) in DslQuerySuite 8f366f8 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into dsl-missing-operator 1b88e2e [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into dsl-missing-operator 0396f89 [Kousuke Saruta] Added sqrt and abs to Spark SQL DSL
* Indent license header properly for interfaces.scala.Reynold Xin2014-12-021-17/+15
| | | | | | | | | | A very small nit update. Author: Reynold Xin <rxin@databricks.com> Closes #3552 from rxin/license-header and squashes the following commits: df8d1a4 [Reynold Xin] Indent license header properly for interfaces.scala.
* [SQL] Minor fix for doc and commentwangfei2014-12-011-1/+1
| | | | | | | | Author: wangfei <wangfei1@huawei.com> Closes #3533 from scwf/sql-doc1 and squashes the following commits: 962910b [wangfei] doc and comment fix
* [SPARK-4658][SQL] Code documentation issue in DDL of datasource APIravipesala2014-12-012-3/+3
| | | | | | | | | Author: ravipesala <ravindra.pesala@huawei.com> Closes #3516 from ravipesala/ddl_doc and squashes the following commits: d101fdf [ravipesala] Style issues fixed d2238cd [ravipesala] Corrected documentation
* [SPARK-4650][SQL] Supporting multi column support in countDistinct function ↵ravipesala2014-12-011-0/+7
| | | | | | | | | | | | | | like count(distinct c1,c2..) in Spark SQL Supporting multi column support in countDistinct function like count(distinct c1,c2..) in Spark SQL Author: ravipesala <ravindra.pesala@huawei.com> Author: Michael Armbrust <michael@databricks.com> Closes #3511 from ravipesala/countdistinct and squashes the following commits: cc4dbb1 [ravipesala] style 070e12a [ravipesala] Supporting multi column support in count(distinct c1,c2..) in Spark SQL
* [SQL] add @group tab in limit() and count()Jacky Li2014-12-011-0/+4
| | | | | | | | | | group tab is missing for scaladoc Author: Jacky Li <jacky.likun@gmail.com> Closes #3458 from jackylk/patch-7 and squashes the following commits: 0121a70 [Jacky Li] add @group tab in limit() and count()
* [SPARK-4548] []SPARK-4517] improve performance of python broadcastDavies Liu2014-11-242-3/+4
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Re-implement the Python broadcast using file: 1) serialize the python object using cPickle, write into disks. 2) Create a wrapper in JVM (for the dumped file), it read data from during serialization 3) Using TorrentBroadcast or HttpBroadcast to transfer the data (compressed) into executors 4) During deserialization, writing the data into disk. 5) Passing the path into Python worker, read data from disk and unpickle it into python object, until the first access. It fixes the performance regression introduced in #2659, has similar performance as 1.1, but support object larger than 2G, also improve the memory efficiency (only one compressed copy in driver and executor). Testing with a 500M broadcast and 4 tasks (excluding the benefit from reused worker in 1.2): name | 1.1 | 1.2 with this patch | improvement ---------|--------|---------|-------- python-broadcast-w-bytes | 25.20 | 9.33 | 170.13% | python-broadcast-w-set | 4.13 | 4.50 | -8.35% | Testing with 100 tasks (16 CPUs): name | 1.1 | 1.2 with this patch | improvement ---------|--------|---------|-------- python-broadcast-w-bytes | 38.16 | 8.40 | 353.98% python-broadcast-w-set | 23.29 | 9.59 | 142.80% Author: Davies Liu <davies@databricks.com> Closes #3417 from davies/pybroadcast and squashes the following commits: 50a58e0 [Davies Liu] address comments b98de1d [Davies Liu] disable gc while unpickle e5ee6b9 [Davies Liu] support large string 09303b8 [Davies Liu] read all data into memory dde02dd [Davies Liu] improve performance of python broadcast
* [SPARK-4487][SQL] Fix attribute reference resolution error when using ORDER BY.Kousuke Saruta2014-11-241-0/+7
| | | | | | | | | | | | | | | | | | | | | When we use ORDER BY clause, at first, attributes referenced by projection are resolved (1). And then, attributes referenced at ORDER BY clause are resolved (2). But when resolving attributes referenced at ORDER BY clause, the resolution result generated in (1) is discarded so for example, following query fails. SELECT c1 + c2 FROM mytable ORDER BY c1; The query above fails because when resolving the attribute reference 'c1', the resolution result of 'c2' is discarded. Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp> Closes #3363 from sarutak/SPARK-4487 and squashes the following commits: fd314f3 [Kousuke Saruta] Fixed attribute resolution logic in Analyzer 6e60c20 [Kousuke Saruta] Fixed conflicts cb5b7e9 [Kousuke Saruta] Added test case for SPARK-4487 282d529 [Kousuke Saruta] Fixed attributes reference resolution error b6123e6 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into concat-feature 317b7fb [Kousuke Saruta] WIP
* [SPARK-4479][SQL] Avoids unnecessary defensive copies when sort based ↵Cheng Lian2014-11-241-1/+15
| | | | | | | | | | | | | | | | | | | | | | shuffle is on This PR is a workaround for SPARK-4479. Two changes are introduced: when merge sort is bypassed in `ExternalSorter`, 1. also bypass RDD elements buffering as buffering is the reason that `MutableRow` backed row objects must be copied, and 2. avoids defensive copies in `Exchange` operator <!-- Reviewable:start --> [<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/3422) <!-- Reviewable:end --> Author: Cheng Lian <lian@databricks.com> Closes #3422 from liancheng/avoids-defensive-copies and squashes the following commits: 591f2e9 [Cheng Lian] Passes all shuffle suites 0c3c91e [Cheng Lian] Fixes shuffle write metrics when merge sort is bypassed ed5df3c [Cheng Lian] Fixes styling changes f75089b [Cheng Lian] Avoids unnecessary defensive copies when sort based shuffle is on
* [SPARK-4413][SQL] Parquet support through datasource APIMichael Armbrust2014-11-204-13/+346
| | | | | | | | | | | | | | | | | | | Goals: - Support for accessing parquet using SQL but not requiring Hive (thus allowing support of parquet tables with decimal columns) - Support for folder based partitioning with automatic discovery of available partitions - Caching of file metadata See scaladoc of `ParquetRelation2` for more details. Author: Michael Armbrust <michael@databricks.com> Closes #3269 from marmbrus/newParquet and squashes the following commits: 1dd75f1 [Michael Armbrust] Pass all paths for FileInputFormat at once. 645768b [Michael Armbrust] Review comments. abd8e2f [Michael Armbrust] Alternative implementation of parquet based on the datasources API. 938019e [Michael Armbrust] Add an experimental interface to data sources that exposes catalyst expressions. e9d2641 [Michael Armbrust] logging / formatting improvements.
* [SQL] fix function description mistakeJacky Li2014-11-201-1/+1
| | | | | | | | | | Sample code in the description of SchemaRDD.where is not correct Author: Jacky Li <jacky.likun@gmail.com> Closes #3344 from jackylk/patch-6 and squashes the following commits: 62cd126 [Jacky Li] [SQL] fix function description mistake
* [SPARK-4318][SQL] Fix empty sum distinct.Takuya UESHIN2014-11-203-28/+116
| | | | | | | | | | | | | | | | | | | Executing sum distinct for empty table throws `java.lang.UnsupportedOperationException: empty.reduceLeft`. Author: Takuya UESHIN <ueshin@happy-camper.st> Closes #3184 from ueshin/issues/SPARK-4318 and squashes the following commits: 8168c42 [Takuya UESHIN] Merge branch 'master' into issues/SPARK-4318 66fdb0a [Takuya UESHIN] Re-refine aggregate functions. 6186eb4 [Takuya UESHIN] Fix Sum of GeneratedAggregate. d2975f6 [Takuya UESHIN] Refine Sum and Average of GeneratedAggregate. 1bba675 [Takuya UESHIN] Refine Sum, SumDistinct and Average functions. 917e533 [Takuya UESHIN] Use aggregate instead of groupBy(). 1a5f874 [Takuya UESHIN] Add tests to be executed as non-partial aggregation. a5a57d2 [Takuya UESHIN] Fix empty Average. 22799dc [Takuya UESHIN] Fix empty Sum and SumDistinct. 65b7dd2 [Takuya UESHIN] Fix empty sum distinct.
* [SPARK-4513][SQL] Support relational operator '<=>' in Spark SQLravipesala2014-11-201-0/+12
| | | | | | | | | | The relational operator '<=>' is not working in Spark SQL. Same works in Spark HiveQL Author: ravipesala <ravindra.pesala@huawei.com> Closes #3387 from ravipesala/<=> and squashes the following commits: 7198e90 [ravipesala] Supporting relational operator '<=>' in Spark SQL
* [SPARK-4228][SQL] SchemaRDD to JSONDan McClary2014-11-204-3/+208
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Here's a simple fix for SchemaRDD to JSON. Author: Dan McClary <dan.mcclary@gmail.com> Closes #3213 from dwmclary/SPARK-4228 and squashes the following commits: d714e1d [Dan McClary] fixed PEP 8 error cac2879 [Dan McClary] move pyspark comment and doctest to correct location f9471d3 [Dan McClary] added pyspark doc and doctest 6598cee [Dan McClary] adding complex type queries 1a5fd30 [Dan McClary] removing SPARK-4228 from SQLQuerySuite 4a651f0 [Dan McClary] cleaned PEP and Scala style failures. Moved tests to JsonSuite 47ceff6 [Dan McClary] cleaned up scala style issues 2ee1e70 [Dan McClary] moved rowToJSON to JsonRDD 4387dd5 [Dan McClary] Added UserDefinedType, cleaned up case formatting 8f7bfb6 [Dan McClary] Map type added to SchemaRDD.toJSON 1b11980 [Dan McClary] Map and UserDefinedTypes partially done 11d2016 [Dan McClary] formatting and unicode deserialization default fixed 6af72d1 [Dan McClary] deleted extaneous comment 4d11c0c [Dan McClary] JsonFactory rewrite of toJSON for SchemaRDD 149dafd [Dan McClary] wrapped scala toJSON in sql.py 5e5eb1b [Dan McClary] switched to Jackson for JSON processing 6c94a54 [Dan McClary] added toJSON to pyspark SchemaRDD aaeba58 [Dan McClary] added toJSON to pyspark SchemaRDD 1d171aa [Dan McClary] upated missing brace on if statement 319e3ba [Dan McClary] updated to upstream master with merged SPARK-4228 424f130 [Dan McClary] tests pass, ready for pull and PR 626a5b1 [Dan McClary] added toJSON to SchemaRDD f7d166a [Dan McClary] added toJSON method 5d34e37 [Dan McClary] merge resolved d6d19e9 [Dan McClary] pr example
* [SPARK-3938][SQL] Names in-memory columnar RDD with corresponding table nameCheng Lian2014-11-206-16/+23
| | | | | | | | | | | | | | | | | | | | | | | | This PR enables the Web UI storage tab to show the in-memory table name instead of the mysterious query plan string as the name of the in-memory columnar RDD. Note that after #2501, a single columnar RDD can be shared by multiple in-memory tables, as long as their query results are the same. In this case, only the first cached table name is shown. For example: ```sql CACHE TABLE first AS SELECT * FROM src; CACHE TABLE second AS SELECT * FROM src; ``` The Web UI only shows "In-memory table first". <!-- Reviewable:start --> [<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/3383) <!-- Reviewable:end --> Author: Cheng Lian <lian@databricks.com> Closes #3383 from liancheng/columnar-rdd-name and squashes the following commits: 071907f [Cheng Lian] Fixes tests 12ddfa6 [Cheng Lian] Names in-memory columnar RDD with corresponding table name
* [SPARK-4468][SQL] Fixes Parquet filter creation for inequality predicates ↵Cheng Lian2014-11-182-4/+16
| | | | | | | | | | | | | | | | | | with literals on the left hand side For expressions like `10 < someVar`, we should create an `Operators.Gt` filter, but right now an `Operators.Lt` is created. This issue affects all inequality predicates with literals on the left hand side. (This bug existed before #3317 and affects branch-1.1. #3338 was opened to backport this to branch-1.1.) <!-- Reviewable:start --> [<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/3334) <!-- Reviewable:end --> Author: Cheng Lian <lian@databricks.com> Closes #3334 from liancheng/fix-parquet-comp-filter and squashes the following commits: 0130897 [Cheng Lian] Fixes Parquet comparison filter generation
* [SPARK-3721] [PySpark] broadcast objects larger than 2GDavies Liu2014-11-182-2/+2
| | | | | | | | | | | | | | | | | | | | | | | | | | | This patch will bring support for broadcasting objects larger than 2G. pickle, zlib, FrameSerializer and Array[Byte] all can not support objects larger than 2G, so this patch introduce LargeObjectSerializer to serialize broadcast objects, the object will be serialized and compressed into small chunks, it also change the type of Broadcast[Array[Byte]]] into Broadcast[Array[Array[Byte]]]]. Testing for support broadcast objects larger than 2G is slow and memory hungry, so this is tested manually, could be added into SparkPerf. Author: Davies Liu <davies@databricks.com> Author: Davies Liu <davies.liu@gmail.com> Closes #2659 from davies/huge and squashes the following commits: 7b57a14 [Davies Liu] add more tests for broadcast 28acff9 [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge a2f6a02 [Davies Liu] bug fix 4820613 [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge 5875c73 [Davies Liu] address comments 10a349b [Davies Liu] address comments 0c33016 [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge 6182c8f [Davies Liu] Merge branch 'master' into huge d94b68f [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge 2514848 [Davies Liu] address comments fda395b [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge 1c2d928 [Davies Liu] fix scala style 091b107 [Davies Liu] broadcast objects larger than 2G
* [SPARK-4453][SPARK-4213][SQL] Simplifies Parquet filter generation codeCheng Lian2014-11-174-693/+160
| | | | | | | | | | | | | | | | | | | While reviewing PR #3083 and #3161, I noticed that Parquet record filter generation code can be simplified significantly according to the clue stated in [SPARK-4453](https://issues.apache.org/jira/browse/SPARK-4213). This PR addresses both SPARK-4453 and SPARK-4213 with this simplification. While generating `ParquetTableScan` operator, we need to remove all Catalyst predicates that have already been pushed down to Parquet. Originally, we first generate the record filter, and then call `findExpression` to traverse the generated filter to find out all pushed down predicates [[1](https://github.com/apache/spark/blob/64c6b9bad559c21f25cd9fbe37c8813cdab939f2/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala#L213-L228)]. In this way, we have to introduce the `CatalystFilter` class hierarchy to bind the Catalyst predicates together with their generated Parquet filter, and complicate the code base a lot. The basic idea of this PR is that, we don't need `findExpression` after filter generation, because we already know a predicate can be pushed down if we can successfully generate its corresponding Parquet filter. SPARK-4213 is fixed by returning `None` for any unsupported predicate type. <!-- Reviewable:start --> [<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/3317) <!-- Reviewable:end --> Author: Cheng Lian <lian@databricks.com> Closes #3317 from liancheng/simplify-parquet-filters and squashes the following commits: d6a9499 [Cheng Lian] Fixes import styling issue 43760e8 [Cheng Lian] Simplifies Parquet filter generation logic
* [SQL] Makes conjunction pushdown more aggressive for in-memory tableCheng Lian2014-11-172-5/+11
| | | | | | | | | | | | | | This is inspired by the [Parquet record filter generation code](https://github.com/apache/spark/blob/64c6b9bad559c21f25cd9fbe37c8813cdab939f2/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetFilters.scala#L387-L400). <!-- Reviewable:start --> [<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/3318) <!-- Reviewable:end --> Author: Cheng Lian <lian@databricks.com> Closes #3318 from liancheng/aggresive-conj-pushdown and squashes the following commits: 78b69d2 [Cheng Lian] Makes conjunction pushdown more aggressive
* [SPARK-4410][SQL] Add support for external sortMichael Armbrust2014-11-164-6/+59
| | | | | | | | | | | | Adds a new operator that uses Spark's `ExternalSort` class. It is off by default now, but we might consider making it the default if benchmarks show that it does not regress performance. Author: Michael Armbrust <michael@databricks.com> Closes #3268 from marmbrus/externalSort and squashes the following commits: 48b9726 [Michael Armbrust] comments b98799d [Michael Armbrust] Add test afd7562 [Michael Armbrust] Add support for external sort.
* [SPARK-4412][SQL] Fix Spark's control of Parquet logging.Jim Carroll2014-11-141-0/+15
| | | | | | | | | | | | | | The Spark ParquetRelation.scala code makes the assumption that the parquet.Log class has already been loaded. If ParquetRelation.enableLogForwarding executes prior to the parquet.Log class being loaded then the code in enableLogForwarding has no affect. ParquetRelation.scala attempts to override the parquet logger but, at least currently (and if your application simply reads a parquet file before it does anything else with Parquet), the parquet.Log class hasn't been loaded yet. Therefore the code in ParquetRelation.enableLogForwarding has no affect. If you look at the code in parquet.Log there's a static initializer that needs to be called prior to enableLogForwarding or whatever enableLogForwarding does gets undone by this static initializer. The "fix" would be to force the static initializer to get called in parquet.Log as part of enableForwardLogging. Author: Jim Carroll <jim@dontcallme.com> Closes #3271 from jimfcarroll/parquet-logging and squashes the following commits: 37bdff7 [Jim Carroll] Fix Spark's control of Parquet logging.
* [SPARK-4365][SQL] Remove unnecessary filter call on records returned from ↵Yash Datta2014-11-141-1/+1
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | parquet library Since parquet library has been updated , we no longer need to filter the records returned from parquet library for null records , as now the library skips those : from parquet-hadoop/src/main/java/parquet/hadoop/InternalParquetRecordReader.java public boolean nextKeyValue() throws IOException, InterruptedException { boolean recordFound = false; while (!recordFound) { // no more records left if (current >= total) { return false; } try { checkRead(); currentValue = recordReader.read(); current ++; if (recordReader.shouldSkipCurrentRecord()) { // this record is being filtered via the filter2 package if (DEBUG) LOG.debug("skipping record"); continue; } if (currentValue == null) { // only happens with FilteredRecordReader at end of block current = totalCountLoadedSoFar; if (DEBUG) LOG.debug("filtered record reader reached end of block"); continue; } recordFound = true; if (DEBUG) LOG.debug("read value: " + currentValue); } catch (RuntimeException e) { throw new ParquetDecodingException(format("Can not read value at %d in block %d in file %s", current, currentBlock, file), e); } } return true; } Author: Yash Datta <Yash.Datta@guavus.com> Closes #3229 from saucam/remove_filter and squashes the following commits: 8909ae9 [Yash Datta] SPARK-4365: Remove unnecessary filter call on records returned from parquet library
* [SPARK-4386] Improve performance when writing Parquet files.Jim Carroll2014-11-141-6/+8
| | | | | | | | | | | | If you profile the writing of a Parquet file, the single worst time consuming call inside of org.apache.spark.sql.parquet.MutableRowWriteSupport.write is actually in the scala.collection.AbstractSequence.size call. This is because the size call actually ends up COUNTING the elements in a scala.collection.LinearSeqOptimized.length ("optimized?"). This doesn't need to be done. "size" is called repeatedly where needed rather than called once at the top of the method and stored in a 'val'. Author: Jim Carroll <jim@dontcallme.com> Closes #3254 from jimfcarroll/parquet-perf and squashes the following commits: 30cc0b5 [Jim Carroll] Improve performance when writing Parquet files.
* [SPARK-4322][SQL] Enables struct fields as sub expressions of grouping fieldsCheng Lian2014-11-141-1/+11
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | While resolving struct fields, the resulted `GetField` expression is wrapped with an `Alias` to make it a named expression. Assume `a` is a struct instance with a field `b`, then `"a.b"` will be resolved as `Alias(GetField(a, "b"), "b")`. Thus, for this following SQL query: ```sql SELECT a.b + 1 FROM t GROUP BY a.b + 1 ``` the grouping expression is ```scala Add(GetField(a, "b"), Literal(1, IntegerType)) ``` while the aggregation expression is ```scala Add(Alias(GetField(a, "b"), "b"), Literal(1, IntegerType)) ``` This mismatch makes the above SQL query fail during the both analysis and execution phases. This PR fixes this issue by removing the alias when substituting aggregation expressions. <!-- Reviewable:start --> [<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/3248) <!-- Reviewable:end --> Author: Cheng Lian <lian@databricks.com> Closes #3248 from liancheng/spark-4322 and squashes the following commits: 23a46ea [Cheng Lian] Code simplification dd20a79 [Cheng Lian] Should only trim aliases around `GetField`s 7f46532 [Cheng Lian] Enables struct fields as sub expressions of grouping fields
* [SQL] Don't shuffle code generated rowsMichael Armbrust2014-11-142-2/+9
| | | | | | | | | | When sort based shuffle and code gen are on we were trying to ship the code generated rows during a shuffle. This doesn't work because the classes don't exist on the other side. Instead we now copy into a generic row before shipping. Author: Michael Armbrust <michael@databricks.com> Closes #3263 from marmbrus/aggCodeGen and squashes the following commits: f6ba8cf [Michael Armbrust] fix and test
* [SPARK-4391][SQL] Configure parquet filters using SQLConfMichael Armbrust2014-11-145-11/+21
| | | | | | | | | | | | | | This is more uniform with the rest of SQL configuration and allows it to be turned on and off without restarting the SparkContext. In this PR I also turn off filter pushdown by default due to a number of outstanding issues (in particular SPARK-4258). When those are fixed we should turn it back on by default. Author: Michael Armbrust <michael@databricks.com> Closes #3258 from marmbrus/parquetFilters and squashes the following commits: 5655bfe [Michael Armbrust] Remove extra line. 15e9a98 [Michael Armbrust] Enable filters for tests 75afd39 [Michael Armbrust] Fix comments 78fa02d [Michael Armbrust] off by default e7f9e16 [Michael Armbrust] First draft of correctly configuring parquet filter pushdown
* [SPARK-4394][SQL] Data Sources API ImprovementsMichael Armbrust2014-11-145-3/+21
| | | | | | | | | | | | | | | This PR adds two features to the data sources API: - Support for pushing down `IN` filters - The ability for relations to optionally provide information about their `sizeInBytes`. Author: Michael Armbrust <michael@databricks.com> Closes #3260 from marmbrus/sourcesImprovements and squashes the following commits: 9a5e171 [Michael Armbrust] Use method instead of configuration directly 99c0e6b [Michael Armbrust] Add support for sizeInBytes. 416f167 [Michael Armbrust] Support for IN in data sources API. 2a04ab3 [Michael Armbrust] Simplify implementation of InSet.
* [SPARK-4274] [SQL] Fix NPE in printing the details of the query planCheng Hao2014-11-101-1/+1
| | | | | | | | Author: Cheng Hao <hao.cheng@intel.com> Closes #3139 from chenghao-intel/comparison_test and squashes the following commits: f5d7146 [Cheng Hao] avoid exception in printing the codegen enabled
* [SPARK-4149][SQL] ISO 8601 support for json date time stringsDaoyuan Wang2014-11-103-2/+40
| | | | | | | | | | This implement the feature davies mentioned in https://github.com/apache/spark/pull/2901#discussion-diff-19313312 Author: Daoyuan Wang <daoyuan.wang@intel.com> Closes #3012 from adrian-wang/iso8601 and squashes the following commits: 50df6e7 [Daoyuan Wang] json data timestamp ISO8601 support
* [SQL] remove a decimal case branch that has no effect at runtimeXiangrui Meng2014-11-101-1/+0
| | | | | | | | | | it generates warnings at compile time marmbrus Author: Xiangrui Meng <meng@databricks.com> Closes #3192 from mengxr/dtc-decimal and squashes the following commits: 955e9fb [Xiangrui Meng] remove a decimal case branch that has no effect
* [SPARK-4319][SQL] Enable an ignored test "null count".Takuya UESHIN2014-11-102-9/+9
| | | | | | | | Author: Takuya UESHIN <ueshin@happy-camper.st> Closes #3185 from ueshin/issues/SPARK-4319 and squashes the following commits: a44a38e [Takuya UESHIN] Enable an ignored test "null count".
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