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* [SPARK-3776][SQL] Wrong conversion to Catalyst for Option[Product]Renat Yusupov2014-10-052-4/+19
| | | | | | | | Author: Renat Yusupov <re.yusupov@2gis.ru> Closes #2641 from r3natko/feature/catalyst_option and squashes the following commits: 55d0c06 [Renat Yusupov] [SQL] SPARK-3776: Wrong conversion to Catalyst for Option[Product]
* [SPARK-3645][SQL] Makes table caching eager by default and adds syntax for ↵Cheng Lian2014-10-0511-158/+265
| | | | | | | | | | | | | | | | lazy caching Although lazy caching for in-memory table seems consistent with the `RDD.cache()` API, it's relatively confusing for users who mainly work with SQL and not familiar with Spark internals. The `CACHE TABLE t; SELECT COUNT(*) FROM t;` pattern is also commonly seen just to ensure predictable performance. This PR makes both the `CACHE TABLE t [AS SELECT ...]` statement and the `SQLContext.cacheTable()` API eager by default, and adds a new `CACHE LAZY TABLE t [AS SELECT ...]` syntax to provide lazy in-memory table caching. Also, took the chance to make some refactoring: `CacheCommand` and `CacheTableAsSelectCommand` are now merged and renamed to `CacheTableCommand` since the former is strictly a special case of the latter. A new `UncacheTableCommand` is added for the `UNCACHE TABLE t` statement. Author: Cheng Lian <lian.cs.zju@gmail.com> Closes #2513 from liancheng/eager-caching and squashes the following commits: fe92287 [Cheng Lian] Makes table caching eager by default and adds syntax for lazy caching
* [SPARK-3792][SQL] Enable JavaHiveQLSuitescwf2014-10-051-18/+9
| | | | | | | | | | Do not use TestSQLContext in JavaHiveQLSuite, that may lead to two SparkContexts in one jvm and enable JavaHiveQLSuite Author: scwf <wangfei1@huawei.com> Closes #2652 from scwf/fix-JavaHiveQLSuite and squashes the following commits: be35c91 [scwf] enable JavaHiveQLSuite
* [Minor] Trivial fix to make codes more readableLiang-Chi Hsieh2014-10-051-1/+1
| | | | | | | | | | It should just use `maxResults` there. Author: Liang-Chi Hsieh <viirya@gmail.com> Closes #2654 from viirya/trivial_fix and squashes the following commits: 1362289 [Liang-Chi Hsieh] Trivial fix to make codes more readable.
* [SPARK-3007][SQL] Fixes dynamic partitioning support for lower Hadoop versionsCheng Lian2014-10-051-4/+22
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This is a follow up of #2226 and #2616 to fix Jenkins master SBT build failures for lower Hadoop versions (1.0.x and 2.0.x). The root cause is the semantics difference of `FileSystem.globStatus()` between different versions of Hadoop, as illustrated by the following test code: ```scala object GlobExperiments extends App { val conf = new Configuration() val fs = FileSystem.getLocal(conf) fs.globStatus(new Path("/tmp/wh/*/*/*")).foreach { status => println(status.getPath) } } ``` Target directory structure: ``` /tmp/wh ├── dir0 │   ├── dir1 │   │   └── level2 │   └── level1 └── level0 ``` Hadoop 2.4.1 result: ``` file:/tmp/wh/dir0/dir1/level2 ``` Hadoop 1.0.4 resuet: ``` file:/tmp/wh/dir0/dir1/level2 file:/tmp/wh/dir0/level1 file:/tmp/wh/level0 ``` In #2226 and #2616, we call `FileOutputCommitter.commitJob()` at the end of the job, and the `_SUCCESS` mark file is written. When working with lower Hadoop versions, due to the `globStatus()` semantics issue, `_SUCCESS` is included as a separate partition data file by `Hive.loadDynamicPartitions()`, and fails partition spec checking. The fix introduced in this PR is kind of a hack: when inserting data with dynamic partitioning, we intentionally avoid writing the `_SUCCESS` marker to workaround this issue. Hive doesn't suffer this issue because `FileSinkOperator` doesn't call `FileOutputCommitter.commitJob()`, instead, it calls `Utilities.mvFileToFinalPath()` to cleanup the output directory and then loads it into Hive warehouse by with `loadDynamicPartitions()`/`loadPartition()`/`loadTable()`. This approach is better because it handles failed job and speculative tasks properly. We should add this step to `InsertIntoHiveTable` in another PR. Author: Cheng Lian <lian.cs.zju@gmail.com> Closes #2663 from liancheng/dp-hadoop-1-fix and squashes the following commits: 0177dae [Cheng Lian] Fixes dynamic partitioning support for lower Hadoop versions
* [SPARK-3212][SQL] Use logical plan matching instead of temporary tables for ↵Michael Armbrust2014-10-0323-241/+567
| | | | | | | | | | | | | | | | | | | | | | | | | | | table caching _Also addresses: SPARK-1671, SPARK-1379 and SPARK-3641_ This PR introduces a new trait, `CacheManger`, which replaces the previous temporary table based caching system. Instead of creating a temporary table that shadows an existing table with and equivalent cached representation, the cached manager maintains a separate list of logical plans and their cached data. After optimization, this list is searched for any matching plan fragments. When a matching plan fragment is found it is replaced with the cached data. There are several advantages to this approach: - Calling .cache() on a SchemaRDD now works as you would expect, and uses the more efficient columnar representation. - Its now possible to provide a list of temporary tables, without having to decide if a given table is actually just a cached persistent table. (To be done in a follow-up PR) - In some cases it is possible that cached data will be used, even if a cached table was not explicitly requested. This is because we now look at the logical structure instead of the table name. - We now correctly invalidate when data is inserted into a hive table. Author: Michael Armbrust <michael@databricks.com> Closes #2501 from marmbrus/caching and squashes the following commits: 63fbc2c [Michael Armbrust] Merge remote-tracking branch 'origin/master' into caching. 0ea889e [Michael Armbrust] Address comments. 1e23287 [Michael Armbrust] Add support for cache invalidation for hive inserts. 65ed04a [Michael Armbrust] fix tests. bdf9a3f [Michael Armbrust] Merge remote-tracking branch 'origin/master' into caching b4b77f2 [Michael Armbrust] Address comments 6923c9d [Michael Armbrust] More comments / tests 80f26ac [Michael Armbrust] First draft of improved semantics for Spark SQL caching.
* [SPARK-3007][SQL] Adds dynamic partitioning supportCheng Lian2014-10-0315-306/+450
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | PR #2226 was reverted because it broke Jenkins builds for unknown reason. This debugging PR aims to fix the Jenkins build. This PR also fixes two bugs: 1. Compression configurations in `InsertIntoHiveTable` are disabled by mistake The `FileSinkDesc` object passed to the writer container doesn't have compression related configurations. These configurations are not taken care of until `saveAsHiveFile` is called. This PR moves compression code forward, right after instantiation of the `FileSinkDesc` object. 1. `PreInsertionCasts` doesn't take table partitions into account In `castChildOutput`, `table.attributes` only contains non-partition columns, thus for partitioned table `childOutputDataTypes` never equals to `tableOutputDataTypes`. This results funny analyzed plan like this: ``` == Analyzed Logical Plan == InsertIntoTable Map(partcol1 -> None, partcol2 -> None), false MetastoreRelation default, dynamic_part_table, None Project [c_0#1164,c_1#1165,c_2#1166] Project [c_0#1164,c_1#1165,c_2#1166] Project [c_0#1164,c_1#1165,c_2#1166] ... (repeats 99 times) ... Project [c_0#1164,c_1#1165,c_2#1166] Project [c_0#1164,c_1#1165,c_2#1166] Project [1 AS c_0#1164,1 AS c_1#1165,1 AS c_2#1166] Filter (key#1170 = 150) MetastoreRelation default, src, None ``` Awful though this logical plan looks, it's harmless because all projects will be eliminated by optimizer. Guess that's why this issue hasn't been caught before. Author: Cheng Lian <lian.cs.zju@gmail.com> Author: baishuo(白硕) <vc_java@hotmail.com> Author: baishuo <vc_java@hotmail.com> Closes #2616 from liancheng/dp-fix and squashes the following commits: 21935b6 [Cheng Lian] Adds back deleted trailing space f471c4b [Cheng Lian] PreInsertionCasts should take table partitions into account a132c80 [Cheng Lian] Fixes output compression 9c6eb2d [Cheng Lian] Adds tests to verify dynamic partitioning folder layout 0eed349 [Cheng Lian] Addresses @yhuai's comments 26632c3 [Cheng Lian] Adds more tests 9227181 [Cheng Lian] Minor refactoring c47470e [Cheng Lian] Refactors InsertIntoHiveTable to a Command 6fb16d7 [Cheng Lian] Fixes typo in test name, regenerated golden answer files d53daa5 [Cheng Lian] Refactors dynamic partitioning support b821611 [baishuo] pass check style 997c990 [baishuo] use HiveConf.DEFAULTPARTITIONNAME to replace hive.exec.default.partition.name 761ecf2 [baishuo] modify according micheal's advice 207c6ac [baishuo] modify for some bad indentation caea6fb [baishuo] modify code to pass scala style checks b660e74 [baishuo] delete a empty else branch cd822f0 [baishuo] do a little modify 8e7268c [baishuo] update file after test 3f91665 [baishuo(白硕)] Update Cast.scala 8ad173c [baishuo(白硕)] Update InsertIntoHiveTable.scala 051ba91 [baishuo(白硕)] Update Cast.scala d452eb3 [baishuo(白硕)] Update HiveQuerySuite.scala 37c603b [baishuo(白硕)] Update InsertIntoHiveTable.scala 98cfb1f [baishuo(白硕)] Update HiveCompatibilitySuite.scala 6af73f4 [baishuo(白硕)] Update InsertIntoHiveTable.scala adf02f1 [baishuo(白硕)] Update InsertIntoHiveTable.scala 1867e23 [baishuo(白硕)] Update SparkHadoopWriter.scala 6bb5880 [baishuo(白硕)] Update HiveQl.scala
* [SPARK-2693][SQL] Supported for UDAF Hive Aggregates like PERCENTILEravipesala2014-10-032-4/+46
| | | | | | | | | | | | Implemented UDAF Hive aggregates by adding wrapper to Spark Hive. Author: ravipesala <ravindra.pesala@huawei.com> Closes #2620 from ravipesala/SPARK-2693 and squashes the following commits: a8df326 [ravipesala] Removed resolver from constructor arguments caf25c6 [ravipesala] Fixed style issues 5786200 [ravipesala] Supported for UDAF Hive Aggregates like PERCENTILE
* [SPARK-3654][SQL] Implement all extended HiveQL statements/commands with a ↵ravipesala2014-10-023-44/+154
| | | | | | | | | | | | | | | | | separate parser combinator Created separate parser for hql. It preparses the commands like cache,uncache,add jar etc.. and then parses with HiveQl Author: ravipesala <ravindra.pesala@huawei.com> Closes #2590 from ravipesala/SPARK-3654 and squashes the following commits: bbca7dd [ravipesala] Fixed code as per admin comments. ae9290a [ravipesala] Fixed style issues as per Admin comments 898ed81 [ravipesala] Removed spaces fb24edf [ravipesala] Updated the code as per admin comments 8947d37 [ravipesala] Removed duplicate code ba26cd1 [ravipesala] Created seperate parser for hql.It pre parses the commands like cache,uncache,add jar etc.. and then parses with HiveQl
* [SQL] Initilize session state before creating CommandProcessorMichael Armbrust2014-10-021-2/+3
| | | | | | | | | | With the old ordering it was possible for commands in the HiveDriver to NPE due to the lack of configuration in the threadlocal session state. Author: Michael Armbrust <michael@databricks.com> Closes #2635 from marmbrus/initOrder and squashes the following commits: 9749850 [Michael Armbrust] Initilize session state before creating CommandProcessor
* [SPARK-3371][SQL] Renaming a function expression with group by gives errorravipesala2014-10-012-1/+6
| | | | | | | | | | | | | | | | | | | The following code gives error. ``` sqlContext.registerFunction("len", (s: String) => s.length) sqlContext.sql("select len(foo) as a, count(1) from t1 group by len(foo)").collect() ``` Because SQl parser creates the aliases to the functions in grouping expressions with generated alias names. So if user gives the alias names to the functions inside projection then it does not match the generated alias name of grouping expression. This kind of queries are working in Hive. So the fix I have given that if user provides alias to the function in projection then don't generate alias in grouping expression,use the same alias. Author: ravipesala <ravindra.pesala@huawei.com> Closes #2511 from ravipesala/SPARK-3371 and squashes the following commits: 9fb973f [ravipesala] Removed aliases to grouping expressions. f8ace79 [ravipesala] Fixed the testcase issue bad2fd0 [ravipesala] SPARK-3371 : Fixed Renaming a function expression with group by gives error
* [SPARK-3704][SQL] Fix ColumnValue type for Short values in thrift serverscwf2014-10-011-2/+2
| | | | | | | | | | case ```ShortType```, we should add short value to hive row. Int value may lead to some problems. Author: scwf <wangfei1@huawei.com> Closes #2551 from scwf/fix-addColumnValue and squashes the following commits: 08bcc59 [scwf] ColumnValue.shortValue for short type
* [SPARK-3729][SQL] Do all hive session state initialization in lazy valMichael Armbrust2014-10-012-5/+7
| | | | | | | | | | This change avoids a NPE during context initialization when settings are present. Author: Michael Armbrust <michael@databricks.com> Closes #2583 from marmbrus/configNPE and squashes the following commits: da2ec57 [Michael Armbrust] Do all hive session state initilialization in lazy val
* [SQL] Made Command.sideEffectResult protectedCheng Lian2014-10-016-19/+19
| | | | | | | | | | Considering `Command.executeCollect()` simply delegates to `Command.sideEffectResult`, we no longer need to leave the latter `protected[sql]`. Author: Cheng Lian <lian.cs.zju@gmail.com> Closes #2431 from liancheng/narrow-scope and squashes the following commits: 1bfc16a [Cheng Lian] Made Command.sideEffectResult protected
* [SPARK-3593][SQL] Add support for sorting BinaryTypeVenkata Ramana Gollamudi2014-10-013-1/+29
| | | | | | | | | | | | BinaryType is derived from NativeType and added Ordering support. Author: Venkata Ramana G <ramana.gollamudihuawei.com> Author: Venkata Ramana Gollamudi <ramana.gollamudi@huawei.com> Closes #2617 from gvramana/binarytype_sort and squashes the following commits: 1cf26f3 [Venkata Ramana Gollamudi] Supported Sorting of BinaryType
* [SPARK-3705][SQL] Add case for VoidObjectInspector to cover NullTypescwf2014-10-011-0/+2
| | | | | | | | | | add case for VoidObjectInspector in ```inspectorToDataType``` Author: scwf <wangfei1@huawei.com> Closes #2552 from scwf/inspectorToDataType and squashes the following commits: 453d892 [scwf] add case for VoidObjectInspector
* [SPARK-3708][SQL] Backticks aren't handled correctly is aliasesravipesala2014-10-012-1/+7
| | | | | | | | | | | | The below query gives error sql("SELECT k FROM (SELECT \`key\` AS \`k\` FROM src) a") It gives error because the aliases are not cleaned so it could not be resolved in further processing. Author: ravipesala <ravindra.pesala@huawei.com> Closes #2594 from ravipesala/SPARK-3708 and squashes the following commits: d55db54 [ravipesala] Fixed SPARK-3708 (Backticks aren't handled correctly is aliases)
* [SPARK-3746][SQL] Lock hive client when creating tablesMichael Armbrust2014-10-011-4/+6
| | | | | | | | Author: Michael Armbrust <michael@databricks.com> Closes #2598 from marmbrus/hiveClientLock and squashes the following commits: ca89fe8 [Michael Armbrust] Lock hive client when creating tables
* [SQL] Kill dangerous trailing space in query stringCheng Lian2014-10-012-1/+1
| | | | | | | | | | | | MD5 of query strings in `createQueryTest` calls are used to generate golden files, leaving trailing spaces there can be really dangerous. Got bitten by this while working on #2616: my "smart" IDE automatically removed a trailing space and makes Jenkins fail. (Really should add "no trailing space" to our coding style guidelines!) Author: Cheng Lian <lian.cs.zju@gmail.com> Closes #2619 from liancheng/kill-trailing-space and squashes the following commits: 034f119 [Cheng Lian] Kill dangerous trailing space in query string
* [SPARK-3748] Log thread name in unit test logsReynold Xin2014-10-012-2/+2
| | | | | | | | | | Thread names are useful for correlating failures. Author: Reynold Xin <rxin@apache.org> Closes #2600 from rxin/log4j and squashes the following commits: 83ffe88 [Reynold Xin] [SPARK-3748] Log thread name in unit test logs
* Revert "[SPARK-3007][SQL]Add Dynamic Partition support to Spark Sql hive"Patrick Wendell2014-09-3014-443/+299
| | | | This reverts commit 0bbe7faeffa17577ae8a33dfcd8c4c783db5c909.
* [SPARK-3007][SQL]Add Dynamic Partition support to Spark Sql hivebaishuo(白硕)2014-09-2914-299/+443
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | a new PR base on new master. changes are the same as https://github.com/apache/spark/pull/1919 Author: baishuo(白硕) <vc_java@hotmail.com> Author: baishuo <vc_java@hotmail.com> Author: Cheng Lian <lian.cs.zju@gmail.com> Closes #2226 from baishuo/patch-3007 and squashes the following commits: e69ce88 [Cheng Lian] Adds tests to verify dynamic partitioning folder layout b20a3dc [Cheng Lian] Addresses @yhuai's comments 096bbbc [baishuo(白硕)] Merge pull request #1 from liancheng/refactor-dp 1093c20 [Cheng Lian] Adds more tests 5004542 [Cheng Lian] Minor refactoring fae9eff [Cheng Lian] Refactors InsertIntoHiveTable to a Command 528e84c [Cheng Lian] Fixes typo in test name, regenerated golden answer files c464b26 [Cheng Lian] Refactors dynamic partitioning support 5033928 [baishuo] pass check style 2201c75 [baishuo] use HiveConf.DEFAULTPARTITIONNAME to replace hive.exec.default.partition.name b47c9bf [baishuo] modify according micheal's advice c3ab36d [baishuo] modify for some bad indentation 7ce2d9f [baishuo] modify code to pass scala style checks 37c1c43 [baishuo] delete a empty else branch 66e33fc [baishuo] do a little modify 88d0110 [baishuo] update file after test a3961d9 [baishuo(白硕)] Update Cast.scala f7467d0 [baishuo(白硕)] Update InsertIntoHiveTable.scala c1a59dd [baishuo(白硕)] Update Cast.scala 0e18496 [baishuo(白硕)] Update HiveQuerySuite.scala 60f70aa [baishuo(白硕)] Update InsertIntoHiveTable.scala 0a50db9 [baishuo(白硕)] Update HiveCompatibilitySuite.scala 491c7d0 [baishuo(白硕)] Update InsertIntoHiveTable.scala a2374a8 [baishuo(白硕)] Update InsertIntoHiveTable.scala 701a814 [baishuo(白硕)] Update SparkHadoopWriter.scala dc24c41 [baishuo(白硕)] Update HiveQl.scala
* [SPARK-3543] TaskContext remaining cleanup work.Reynold Xin2014-09-281-2/+2
| | | | | | | | Author: Reynold Xin <rxin@apache.org> Closes #2560 from rxin/TaskContext and squashes the following commits: 9eff95a [Reynold Xin] [SPARK-3543] remaining cleanup work.
* [SPARK-3680][SQL] Fix bug caused by eager typing of HiveGenericUDFsMichael Armbrust2014-09-272-5/+12
| | | | | | | | | | Typing of UDFs should be lazy as it is often not valid to call `dataType` on an expression until after all of its children are `resolved`. Author: Michael Armbrust <michael@databricks.com> Closes #2525 from marmbrus/concatBug and squashes the following commits: 5b8efe7 [Michael Armbrust] fix bug with eager typing of udfs
* [SPARK-3676][SQL] Fix hive test suite failure due to diffs in JDK 1.6/1.7w002289702014-09-273-6/+11
| | | | | | | | | | | | | | | | | This is a bug in JDK6: http://bugs.java.com/bugdatabase/view_bug.do?bug_id=4428022 this is because jdk get different result to operate ```double```, ```System.out.println(1/500d)``` in different jdk get different result jdk 1.6.0(_31) ---- 0.0020 jdk 1.7.0(_05) ---- 0.002 this leads to HiveQuerySuite failed when generate golden answer in jdk 1.7 and run tests in jdk 1.6, result did not match Author: w00228970 <wangfei1@huawei.com> Closes #2517 from scwf/HiveQuerySuite and squashes the following commits: 0cb5e8d [w00228970] delete golden answer of division-0 and timestamp cast #1 1df3964 [w00228970] Jdk version leads to different query output for Double, this make HiveQuerySuite failed
* [SPARK-3675][SQL] Allow starting a JDBC server on an existing contextMichael Armbrust2014-09-261-1/+14
| | | | | | | | Author: Michael Armbrust <michael@databricks.com> Closes #2515 from marmbrus/jdbcExistingContext and squashes the following commits: 7866fad [Michael Armbrust] Allows starting a JDBC server on an existing context.
* [SPARK-3393] [SQL] Align the log4j configuration for Spark & SparkSQLCLICheng Hao2014-09-261-17/+0
| | | | | | | | | | | | User may be confused for the HQL logging & configurations, we'd better provide a default templates. Both files are copied from Hive. Author: Cheng Hao <hao.cheng@intel.com> Closes #2263 from chenghao-intel/hive_template and squashes the following commits: 53bffa9 [Cheng Hao] Remove the hive-log4j.properties initialization
* [SPARK-3531][SQL]select null from table would throw a MatchErrorDaoyuan Wang2014-09-263-0/+5
| | | | | | | | Author: Daoyuan Wang <daoyuan.wang@intel.com> Closes #2396 from adrian-wang/selectnull and squashes the following commits: 2458229 [Daoyuan Wang] rebase solution
* [SPARK-3646][SQL] Copy SQL configuration from SparkConf when a SQLContext is ↵Michael Armbrust2014-09-233-2/+20
| | | | | | | | | | | | created. This will allow us to take advantage of things like the spark.defaults file. Author: Michael Armbrust <michael@databricks.com> Closes #2493 from marmbrus/copySparkConf and squashes the following commits: 0bd1377 [Michael Armbrust] Copy SQL configuration from SparkConf when a SQLContext is created.
* [SPARK-3268][SQL] DoubleType, FloatType and DecimalType modulus supportVenkata Ramana Gollamudi2014-09-235-0/+44
| | | | | | | | | | | | | | | | | | | | Supported modulus operation using % operator on fractional datatypes FloatType, DoubleType and DecimalType Example: SELECT 1388632775.0 % 60 from tablename LIMIT 1 Author : Venkata Ramana Gollamudi ramana.gollamudihuawei.com Author: Venkata Ramana Gollamudi <ramana.gollamudi@huawei.com> Closes #2457 from gvramana/double_modulus_support and squashes the following commits: 79172a8 [Venkata Ramana Gollamudi] Add hive cache to testcase c09bd5b [Venkata Ramana Gollamudi] Added a HiveQuerySuite testcase 193fa81 [Venkata Ramana Gollamudi] corrected testcase 3624471 [Venkata Ramana Gollamudi] modified testcase e112c09 [Venkata Ramana Gollamudi] corrected the testcase 513d0e0 [Venkata Ramana Gollamudi] modified to add modulus support to fractional types float,double,decimal 296d253 [Venkata Ramana Gollamudi] modified to add modulus support to fractional types float,double,decimal
* [SPARK-3481][SQL] removes the evil MINOR HACKwangfei2014-09-231-2/+0
| | | | | | | | | | a follow up of https://github.com/apache/spark/pull/2377 and https://github.com/apache/spark/pull/2352, see detail there. Author: wangfei <wangfei1@huawei.com> Closes #2505 from scwf/patch-6 and squashes the following commits: 4874ec8 [wangfei] removes the evil MINOR HACK
* [SPARK-3536][SQL] SELECT on empty parquet table throws exceptionravipesala2014-09-232-2/+14
| | | | | | | | | | | | It returns null metadata from parquet if querying on empty parquet file while calculating splits.So added null check and returns the empty splits. Author : ravipesala ravindra.pesalahuawei.com Author: ravipesala <ravindra.pesala@huawei.com> Closes #2456 from ravipesala/SPARK-3536 and squashes the following commits: 1e81a50 [ravipesala] Fixed the issue when querying on empty parquet file.
* [SPARK-3582][SQL] not limit argument type for hive simple udfDaoyuan Wang2014-09-232-22/+4
| | | | | | | | | | Since we have moved to `ConventionHelper`, it is quite easy to avoid call `javaClassToDataType` in hive simple udf. This will solve SPARK-3582. Author: Daoyuan Wang <daoyuan.wang@intel.com> Closes #2506 from adrian-wang/spark3582 and squashes the following commits: 450c28e [Daoyuan Wang] not limit argument type for hive simple udf
* [SPARK-3598][SQL]cast to timestamp should be the same as hiveDaoyuan Wang2014-09-2311-15/+50
| | | | | | | | | | | | | | | | | this patch fixes timestamp smaller than 0 and cast int as timestamp select cast(1000 as timestamp) from src limit 1; should return 1970-01-01 00:00:01, but we now take it as 1000 seconds. also, current implementation has bug when the time is before 1970-01-01 00:00:00. rxin marmbrus chenghao-intel Author: Daoyuan Wang <daoyuan.wang@intel.com> Closes #2458 from adrian-wang/timestamp and squashes the following commits: 4274b1d [Daoyuan Wang] set test not related to timezone 1234f66 [Daoyuan Wang] fix timestamp smaller than 0 and cast int as timestamp
* [SPARK-3414][SQL] Replace LowerCaseSchema with ResolverMichael Armbrust2014-09-2015-99/+125
| | | | | | | | | | | | | | | | | | | | | | | | | | **This PR introduces a subtle change in semantics for HiveContext when using the results in Python or Scala. Specifically, while resolution remains case insensitive, it is now case preserving.** _This PR is a follow up to #2293 (and to a lesser extent #2262 #2334)._ In #2293 the catalog was changed to store analyzed logical plans instead of unresolved ones. While this change fixed the reported bug (which was caused by yet another instance of us forgetting to put in a `LowerCaseSchema` operator) it had the consequence of breaking assumptions made by `MultiInstanceRelation`. Specifically, we can't replace swap out leaf operators in a tree without rewriting changed expression ids (which happens when you self join the same RDD that has been registered as a temp table). In this PR, I instead remove the need to insert `LowerCaseSchema` operators at all, by moving the concern of matching up identifiers completely into analysis. Doing so allows the test cases from both #2293 and #2262 to pass at the same time (and likely fixes a slew of other "unknown unknown" bugs). While it is rolled back in this PR, storing the analyzed plan might actually be a good idea. For instance, it is kind of confusing if you register a temporary table, change the case sensitivity of resolution and now you can't query that table anymore. This can be addressed in a follow up PR. Follow-ups: - Configurable case sensitivity - Consider storing analyzed plans for temp tables Author: Michael Armbrust <michael@databricks.com> Closes #2382 from marmbrus/lowercase and squashes the following commits: c21171e [Michael Armbrust] Ensure the resolver is used for field lookups and ensure that case insensitive resolution is still case preserving. d4320f1 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into lowercase 2de881e [Michael Armbrust] Address comments. 219805a [Michael Armbrust] style 5b93711 [Michael Armbrust] Replace LowerCaseSchema with Resolver.
* [SPARK-3609][SQL] Adds sizeInBytes statistics for Limit operator when all ↵Cheng Lian2014-09-204-5/+45
| | | | | | | | | | | | | | | output attributes are of native data types This helps to replace shuffled hash joins with broadcast hash joins in some cases. Author: Cheng Lian <lian.cs.zju@gmail.com> Closes #2468 from liancheng/more-stats and squashes the following commits: 32687dc [Cheng Lian] Moved the test case to PlannerSuite 5595a91 [Cheng Lian] Removes debugging code 73faf69 [Cheng Lian] Test case for auto choosing broadcast hash join f30fe1d [Cheng Lian] Adds sizeInBytes estimation for Limit when all output types are native types
* [SPARK-3485][SQL] Use GenericUDFUtils.ConversionHelper for Simple UDF type ↵Daoyuan Wang2014-09-192-39/+17
| | | | | | | | | | | | | | | conversions This is just another solution to SPARK-3485, in addition to PR #2355 In this patch, we will use ConventionHelper and FunctionRegistry to invoke a simple udf evaluation, which rely more on hive, but much cleaner and safer. We can discuss which one is better. Author: Daoyuan Wang <daoyuan.wang@intel.com> Closes #2407 from adrian-wang/simpleudf and squashes the following commits: 15762d2 [Daoyuan Wang] add posmod test which would fail the test but now ok 0d69eb4 [Daoyuan Wang] another way to pass to hive simple udf
* SPARK-3605. Fix typo in SchemaRDD.Sandy Ryza2014-09-191-3/+2
| | | | | | | | Author: Sandy Ryza <sandy@cloudera.com> Closes #2460 from sryza/sandy-spark-3605 and squashes the following commits: 09d940b [Sandy Ryza] SPARK-3605. Fix typo in SchemaRDD.
* [SPARK-2594][SQL] Support CACHE TABLE <name> AS SELECT ...ravipesala2014-09-196-13/+69
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This feature allows user to add cache table from the select query. Example : ```CACHE TABLE testCacheTable AS SELECT * FROM TEST_TABLE``` Spark takes this type of SQL as command and it does lazy caching just like ```SQLContext.cacheTable```, ```CACHE TABLE <name>``` does. It can be executed from both SQLContext and HiveContext. Recreated the pull request after rebasing with master.And fixed all the comments raised in previous pull requests. https://github.com/apache/spark/pull/2381 https://github.com/apache/spark/pull/2390 Author : ravipesala ravindra.pesalahuawei.com Author: ravipesala <ravindra.pesala@huawei.com> Closes #2397 from ravipesala/SPARK-2594 and squashes the following commits: a5f0beb [ravipesala] Simplified the code as per Admin comment. 8059cd2 [ravipesala] Changed the behaviour from eager caching to lazy caching. d6e469d [ravipesala] Code review comments by Admin are handled. c18aa38 [ravipesala] Merge remote-tracking branch 'remotes/ravipesala/Add-Cache-table-as' into SPARK-2594 394d5ca [ravipesala] Changed style fb1759b [ravipesala] Updated as per Admin comments 8c9993c [ravipesala] Changed the style d8b37b2 [ravipesala] Updated as per the comments by Admin bc0bffc [ravipesala] Merge remote-tracking branch 'ravipesala/Add-Cache-table-as' into Add-Cache-table-as e3265d0 [ravipesala] Updated the code as per the comments by Admin in pull request. 724b9db [ravipesala] Changed style aaf5b59 [ravipesala] Added comment dc33895 [ravipesala] Updated parser to support add cache table command b5276b2 [ravipesala] Updated parser to support add cache table command eebc0c1 [ravipesala] Add CACHE TABLE <name> AS SELECT ... 6758f80 [ravipesala] Changed style 7459ce3 [ravipesala] Added comment 13c8e27 [ravipesala] Updated parser to support add cache table command 4e858d8 [ravipesala] Updated parser to support add cache table command b803fc8 [ravipesala] Add CACHE TABLE <name> AS SELECT ...
* [SPARK-3501] [SQL] Fix the bug of Hive SimpleUDF creates unnecessary type castCheng Hao2014-09-194-2/+14
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | When do the query like: ``` select datediff(cast(value as timestamp), cast('2002-03-21 00:00:00' as timestamp)) from src; ``` SparkSQL will raise exception: ``` [info] scala.MatchError: TimestampType (of class org.apache.spark.sql.catalyst.types.TimestampType$) [info] at org.apache.spark.sql.catalyst.expressions.Cast.castToTimestamp(Cast.scala:77) [info] at org.apache.spark.sql.catalyst.expressions.Cast.cast$lzycompute(Cast.scala:251) [info] at org.apache.spark.sql.catalyst.expressions.Cast.cast(Cast.scala:247) [info] at org.apache.spark.sql.catalyst.expressions.Cast.eval(Cast.scala:263) [info] at org.apache.spark.sql.catalyst.optimizer.ConstantFolding$$anonfun$apply$5$$anonfun$applyOrElse$2.applyOrElse(Optimizer.scala:217) [info] at org.apache.spark.sql.catalyst.optimizer.ConstantFolding$$anonfun$apply$5$$anonfun$applyOrElse$2.applyOrElse(Optimizer.scala:210) [info] at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:144) [info] at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4$$anonfun$apply$2.apply(TreeNode.scala:180) [info] at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244) [info] at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244) ``` Author: Cheng Hao <hao.cheng@intel.com> Closes #2368 from chenghao-intel/cast_exception and squashes the following commits: 5c9c3a5 [Cheng Hao] make more clear code 49dfc50 [Cheng Hao] Add no-op for Cast and revert the position of SimplifyCasts b804abd [Cheng Hao] Add unit test to show the failure in identical data type casting 330a5c8 [Cheng Hao] Update Code based on comments b834ed4 [Cheng Hao] Fix bug of HiveSimpleUDF with unnecessary type cast which cause exception in constant folding
* [SPARK-2314][SQL] Override collect and take in python library, and count in ↵Aaron Staple2014-09-162-11/+28
| | | | | | | | | | | | | | | | | | java library, with optimized versions. SchemaRDD overrides RDD functions, including collect, count, and take, with optimized versions making use of the query optimizer. The java and python interface classes wrapping SchemaRDD need to ensure the optimized versions are called as well. This patch overrides relevant calls in the python and java interfaces with optimized versions. Adds a new Row serialization pathway between python and java, based on JList[Array[Byte]] versus the existing RDD[Array[Byte]]. I wasn’t overjoyed about doing this, but I noticed that some QueryPlans implement optimizations in executeCollect(), which outputs an Array[Row] rather than the typical RDD[Row] that can be shipped to python using the existing serialization code. To me it made sense to ship the Array[Row] over to python directly instead of converting it back to an RDD[Row] just for the purpose of sending the Rows to python using the existing serialization code. Author: Aaron Staple <aaron.staple@gmail.com> Closes #1592 from staple/SPARK-2314 and squashes the following commits: 89ff550 [Aaron Staple] Merge with master. 6bb7b6c [Aaron Staple] Fix typo. b56d0ac [Aaron Staple] [SPARK-2314][SQL] Override count in JavaSchemaRDD, forwarding to SchemaRDD's count. 0fc9d40 [Aaron Staple] Fix comment typos. f03cdfa [Aaron Staple] [SPARK-2314][SQL] Override collect and take in sql.py, forwarding to SchemaRDD's collect.
* [SPARK-2890][SQL] Allow reading of data when case insensitive resolution ↵Michael Armbrust2014-09-162-27/+44
| | | | | | | | | | | | | | | could cause possible ambiguity. Throwing an error in the constructor makes it possible to run queries, even when there is no actual ambiguity. Remove this check in favor of throwing an error in analysis when they query is actually is ambiguous. Also took the opportunity to add test cases that would have caught a subtle bug in my first attempt at fixing this and refactor some other test code. Author: Michael Armbrust <michael@databricks.com> Closes #2209 from marmbrus/sameNameStruct and squashes the following commits: 729cca4 [Michael Armbrust] Better tests. a003aeb [Michael Armbrust] Remove error (it'll be caught in analysis).
* [SPARK-3308][SQL] Ability to read JSON Arrays as tablesYin Huai2014-09-163-3/+31
| | | | | | | | | | | | This PR aims to support reading top level JSON arrays and take every element in such an array as a row (an empty array will not generate a row). JIRA: https://issues.apache.org/jira/browse/SPARK-3308 Author: Yin Huai <huai@cse.ohio-state.edu> Closes #2400 from yhuai/SPARK-3308 and squashes the following commits: 990077a [Yin Huai] Handle top level JSON arrays.
* [SPARK-3527] [SQL] Strip the string messageCheng Hao2014-09-161-1/+1
| | | | | | | | Author: Cheng Hao <hao.cheng@intel.com> Closes #2392 from chenghao-intel/trim and squashes the following commits: e52024f [Cheng Hao] trim the string message
* SPARK-3039: Allow spark to be built using avro-mapred for hadoop2Bertrand Bossy2014-09-141-0/+9
| | | | | | | | | | | | SPARK-3039: Adds the maven property "avro.mapred.classifier" to build spark-assembly with avro-mapred with support for the new Hadoop API. Sets this property to hadoop2 for Hadoop 2 profiles. I am not very familiar with maven, nor do I know whether this potentially breaks something in the hive part of spark. There might be a more elegant way of doing this. Author: Bertrand Bossy <bertrandbossy@gmail.com> Closes #1945 from bbossy/SPARK-3039 and squashes the following commits: c32ce59 [Bertrand Bossy] SPARK-3039: Allow spark to be built using avro-mapred for hadoop2
* [SQL] Decrease partitions when testingMichael Armbrust2014-09-133-107/+51
| | | | | | | | | | | | | Author: Michael Armbrust <michael@databricks.com> Closes #2164 from marmbrus/shufflePartitions and squashes the following commits: 0da1e8c [Michael Armbrust] test hax ef2d985 [Michael Armbrust] more test hacks. 2dabae3 [Michael Armbrust] more test fixes 0bdbf21 [Michael Armbrust] Make parquet tests less order dependent b42eeab [Michael Armbrust] increase test parallelism 80453d5 [Michael Armbrust] Decrease partitions when testing
* [SPARK-3294][SQL] Eliminates boxing costs from in-memory columnar storageCheng Lian2014-09-1324-292/+554
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This is a major refactoring of the in-memory columnar storage implementation, aims to eliminate boxing costs from critical paths (building/accessing column buffers) as much as possible. The basic idea is to refactor all major interfaces into a row-based form and use them together with `SpecificMutableRow`. The difficult part is how to adapt all compression schemes, esp. `RunLengthEncoding` and `DictionaryEncoding`, to this design. Since in-memory compression is disabled by default for now, and this PR should be strictly better than before no matter in-memory compression is enabled or not, maybe I'll finish that part in another PR. **UPDATE** This PR also took the chance to optimize `HiveTableScan` by 1. leveraging `SpecificMutableRow` to avoid boxing cost, and 1. building specific `Writable` unwrapper functions a head of time to avoid per row pattern matching and branching costs. TODO - [x] Benchmark - [ ] ~~Eliminate boxing costs in `RunLengthEncoding`~~ (left to future PRs) - [ ] ~~Eliminate boxing costs in `DictionaryEncoding` (seems not easy to do without specializing `DictionaryEncoding` for every supported column type)~~ (left to future PRs) ## Micro benchmark The benchmark uses a 10 million line CSV table consists of bytes, shorts, integers, longs, floats and doubles, measures the time to build the in-memory version of this table, and the time to scan the whole in-memory table. Benchmark code can be found [here](https://gist.github.com/liancheng/fe70a148de82e77bd2c8#file-hivetablescanbenchmark-scala). Script used to generate the input table can be found [here](https://gist.github.com/liancheng/fe70a148de82e77bd2c8#file-tablegen-scala). Speedup: - Hive table scanning + column buffer building: **18.74%** The original benchmark uses 1K as in-memory batch size, when increased to 10K, it can be 28.32% faster. - In-memory table scanning: **7.95%** Before: | Building | Scanning ------- | -------- | -------- 1 | 16472 | 525 2 | 16168 | 530 3 | 16386 | 529 4 | 16184 | 538 5 | 16209 | 521 Average | 16283.8 | 528.6 After: | Building | Scanning ------- | -------- | -------- 1 | 13124 | 458 2 | 13260 | 529 3 | 12981 | 463 4 | 13214 | 483 5 | 13583 | 500 Average | 13232.4 | 486.6 Author: Cheng Lian <lian.cs.zju@gmail.com> Closes #2327 from liancheng/prevent-boxing/unboxing and squashes the following commits: 4419fe4 [Cheng Lian] Addressing comments e5d2cf2 [Cheng Lian] Bug fix: should call setNullAt when field value is null to avoid NPE 8b8552b [Cheng Lian] Only checks for partition batch pruning flag once 489f97b [Cheng Lian] Bug fix: TableReader.fillObject uses wrong ordinals 97bbc4e [Cheng Lian] Optimizes hive.TableReader by by providing specific Writable unwrappers a head of time 3dc1f94 [Cheng Lian] Minor changes to eliminate row object creation 5b39cb9 [Cheng Lian] Lowers log level of compression scheme details f2a7890 [Cheng Lian] Use SpecificMutableRow in InMemoryColumnarTableScan to avoid boxing 9cf30b0 [Cheng Lian] Added row based ColumnType.append/extract 456c366 [Cheng Lian] Made compression decoder row based edac3cd [Cheng Lian] Makes ColumnAccessor.extractSingle row based 8216936 [Cheng Lian] Removes boxing cost in IntDelta and LongDelta by providing specialized implementations b70d519 [Cheng Lian] Made some in-memory columnar storage interfaces row-based
* [SPARK-3481][SQL] Removes the evil MINOR HACKCheng Lian2014-09-131-3/+3
| | | | | | | | | | This is a follow up of #2352. Now we can finally remove the evil "MINOR HACK", which covered up the eldest bug in the history of Spark SQL (see details [here](https://github.com/apache/spark/pull/2352#issuecomment-55440621)). Author: Cheng Lian <lian.cs.zju@gmail.com> Closes #2377 from liancheng/remove-evil-minor-hack and squashes the following commits: 0869c78 [Cheng Lian] Removes the evil MINOR HACK
* [SPARK-3515][SQL] Moves test suite setup code to beforeAll rather than in ↵Cheng Lian2014-09-121-29/+24
| | | | | | | | | | | | | | constructor Please refer to the JIRA ticket for details. **NOTE** We should check all test suites that do similar initialization-like side effects in their constructors. This PR only fixes `ParquetMetastoreSuite` because it breaks our Jenkins Maven build. Author: Cheng Lian <lian.cs.zju@gmail.com> Closes #2375 from liancheng/say-no-to-constructor and squashes the following commits: 0ceb75b [Cheng Lian] Moves test suite setup code to beforeAll rather than in constructor
* [SPARK-3481] [SQL] Eliminate the error log in local Hive comparison testCheng Hao2014-09-121-9/+8
| | | | | | | | | | | Logically, we should remove the Hive Table/Database first and then reset the Hive configuration, repoint to the new data warehouse directory etc. Otherwise it raised exceptions like "Database doesn't not exists: default" in the local testing. Author: Cheng Hao <hao.cheng@intel.com> Closes #2352 from chenghao-intel/test_hive and squashes the following commits: 74fd76b [Cheng Hao] eliminate the error log
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