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* [HOTFIX] Fix Scala 2.10 compilationReynold Xin2016-07-181-2/+2
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* [SPARK-16590][SQL] Improve LogicalPlanToSQLSuite to check generated SQL directlyDongjoon Hyun2016-07-18103-153/+820
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR improves `LogicalPlanToSQLSuite` to check the generated SQL directly by **structure**. So far, `LogicalPlanToSQLSuite` relies on `checkHiveQl` to ensure the **successful SQL generation** and **answer equality**. However, it does not guarantee the generated SQL is the same or will not be changed unnoticeably. ## How was this patch tested? Pass the Jenkins. This is only a testsuite change. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #14235 from dongjoon-hyun/SPARK-16590.
* [SPARK-16515][SQL] set default record reader and writer for script ↵Daoyuan Wang2016-07-182-0/+34
| | | | | | | | | | | | | | | | | transformation ## What changes were proposed in this pull request? In ScriptInputOutputSchema, we read default RecordReader and RecordWriter from conf. Since Spark 2.0 has deleted those config keys from hive conf, we have to set default reader/writer class name by ourselves. Otherwise we will get None for LazySimpleSerde, the data written would not be able to read by script. The test case added worked fine with previous version of Spark, but would fail now. ## How was this patch tested? added a test case in SQLQuerySuite. Closes #14169 Author: Daoyuan Wang <daoyuan.wang@intel.com> Author: Yin Huai <yhuai@databricks.com> Closes #14249 from yhuai/scriptTransformation.
* [SPARK-16528][SQL] Fix NPE problem in HiveClientImplJacek Lewandowski2016-07-141-6/+8
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? There are some calls to methods or fields (getParameters, properties) which are then passed to Java/Scala collection converters. Unfortunately those fields can be null in some cases and then the conversions throws NPE. We fix it by wrapping calls to those fields and methods with option and then do the conversion. ## How was this patch tested? Manually tested with a custom Hive metastore. Author: Jacek Lewandowski <lewandowski.jacek@gmail.com> Closes #14200 from jacek-lewandowski/SPARK-16528.
* [SPARK-16482][SQL] Describe Table Command for Tables Requiring Runtime ↵gatorsmile2016-07-131-7/+9
| | | | | | | | | | | | | | | | | | Inferred Schema #### What changes were proposed in this pull request? If we create a table pointing to a parquet/json datasets without specifying the schema, describe table command does not show the schema at all. It only shows `# Schema of this table is inferred at runtime`. In 1.6, describe table does show the schema of such a table. ~~For data source tables, to infer the schema, we need to load the data source tables at runtime. Thus, this PR calls the function `lookupRelation`.~~ For data source tables, we infer the schema before table creation. Thus, this PR set the inferred schema as the table schema when table creation. #### How was this patch tested? Added test cases Author: gatorsmile <gatorsmile@gmail.com> Closes #14148 from gatorsmile/describeSchema.
* [SPARK-16284][SQL] Implement reflect SQL functionpetermaxlee2016-07-132-25/+5
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? This patch implements reflect SQL function, which can be used to invoke a Java method in SQL. Slightly different from Hive, this implementation requires the class name and the method name to be literals. This implementation also supports only a smaller number of data types, and requires the function to be static, as suggested by rxin in #13969. java_method is an alias for reflect, so this should also resolve SPARK-16277. ## How was this patch tested? Added expression unit tests and an end-to-end test. Author: petermaxlee <petermaxlee@gmail.com> Closes #14138 from petermaxlee/reflect-static.
* [SPARK-16119][SQL] Support PURGE option to drop table / partition.Marcelo Vanzin2016-07-129-19/+146
| | | | | | | | | | | | | | | | | | | | | | | | | This option is used by Hive to directly delete the files instead of moving them to the trash. This is needed in certain configurations where moving the files does not work. For non-Hive tables and partitions, Spark already behaves as if the PURGE option was set, so there's no need to do anything. Hive support for PURGE was added in 0.14 (for tables) and 1.2 (for partitions), so the code reflects that: trying to use the option with older versions of Hive will cause an exception to be thrown. The change is a little noisier than I would like, because of the code to propagate the new flag through all the interfaces and implementations; the main changes are in the parser and in HiveShim, aside from the tests (DDLCommandSuite, VersionsSuite). Tested by running sql and catalyst unit tests, plus VersionsSuite which has been updated to test the version-specific behavior. I also ran an internal test suite that uses PURGE and would not pass previously. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #13831 from vanzin/SPARK-16119.
* [SPARK-15752][SQL] Optimize metadata only query that has an aggregate whose ↵Lianhui Wang2016-07-121-0/+89
| | | | | | | | | | | | | | | | children are deterministic project or filter operators. ## What changes were proposed in this pull request? when query only use metadata (example: partition key), it can return results based on metadata without scanning files. Hive did it in HIVE-1003. ## How was this patch tested? add unit tests Author: Lianhui Wang <lianhuiwang09@gmail.com> Author: Wenchen Fan <wenchen@databricks.com> Author: Lianhui Wang <lianhuiwang@users.noreply.github.com> Closes #13494 from lianhuiwang/metadata-only.
* [SPARK-12639][SQL] Mark Filters Fully Handled By Sources with *Russell Spitzer2016-07-111-2/+2
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? In order to make it clear which filters are fully handled by the underlying datasource we will mark them with an *. This will give a clear visual queue to users that the filter is being treated differently by catalyst than filters which are just presented to the underlying DataSource. Examples from the FilteredScanSuite, in this example `c IN (...)` is handled by the source, `b < ...` is not ### Before ``` //SELECT a FROM oneToTenFiltered WHERE a + b > 9 AND b < 16 AND c IN ('bbbbbBBBBB', 'cccccCCCCC', 'dddddDDDDD', 'foo') == Physical Plan == Project [a#0] +- Filter (((a#0 + b#1) > 9) && (b#1 < 16)) +- Scan SimpleFilteredScan(1,10)[a#0,b#1] PushedFilters: [LessThan(b,16), In(c, [bbbbbBBBBB,cccccCCCCC,dddddDDDDD,foo]] ``` ### After ``` == Physical Plan == Project [a#0] +- Filter (((a#0 + b#1) > 9) && (b#1 < 16)) +- Scan SimpleFilteredScan(1,10)[a#0,b#1] PushedFilters: [LessThan(b,16), *In(c, [bbbbbBBBBB,cccccCCCCC,dddddDDDDD,foo]] ``` ## How was the this patch tested? Manually tested with the Spark Cassandra Connector, a source which fully handles underlying filters. Now fully handled filters appear with an * next to their names. I can add an automated test as well if requested Post 1.6.1 Tested by modifying the FilteredScanSuite to run explains. Author: Russell Spitzer <Russell.Spitzer@gmail.com> Closes #11317 from RussellSpitzer/SPARK-12639-Star.
* [SPARK-16349][SQL] Fall back to isolated class loader when classes not found.Marcelo Vanzin2016-07-111-3/+9
| | | | | | | | | | | | | | Some Hadoop classes needed by the Hive metastore client jars are not present in Spark's packaging (for example, "org/apache/hadoop/mapred/MRVersion"). So if the parent class loader fails to find a class, try to load it from the isolated class loader, in case it's available there. Tested by setting spark.sql.hive.metastore.jars to local paths with Hive/Hadoop libraries and verifying that Spark can talk to the metastore. Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #14020 from vanzin/SPARK-16349.
* [SPARK-16477] Bump master version to 2.1.0-SNAPSHOTReynold Xin2016-07-111-1/+1
| | | | | | | | | | | | ## What changes were proposed in this pull request? After SPARK-16476 (committed earlier today as #14128), we can finally bump the version number. ## How was this patch tested? N/A Author: Reynold Xin <rxin@databricks.com> Closes #14130 from rxin/SPARK-16477.
* [SPARK-16459][SQL] Prevent dropping current databaseDongjoon Hyun2016-07-112-0/+3
| | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR prevents dropping the current database to avoid errors like the followings. ```scala scala> sql("create database delete_db") scala> sql("use delete_db") scala> sql("drop database delete_db") scala> sql("create table t as select 1") org.apache.spark.sql.catalyst.analysis.NoSuchDatabaseException: Database `delete_db` not found; ``` ## How was this patch tested? Pass the Jenkins tests including an updated testcase. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #14115 from dongjoon-hyun/SPARK-16459.
* [SPARK-16318][SQL] Implement all remaining xpath functionspetermaxlee2016-07-111-3/+1
| | | | | | | | | | | | ## What changes were proposed in this pull request? This patch implements all remaining xpath functions that Hive supports and not natively supported in Spark: xpath_int, xpath_short, xpath_long, xpath_float, xpath_double, xpath_string, and xpath. ## How was this patch tested? Added unit tests and end-to-end tests. Author: petermaxlee <petermaxlee@gmail.com> Closes #13991 from petermaxlee/SPARK-16318.
* [SPARK-16281][SQL] Implement parse_url SQL functionwujian2016-07-081-1/+1
| | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR adds parse_url SQL functions in order to remove Hive fallback. A new implementation of #13999 ## How was this patch tested? Pass the exist tests including new testcases. Author: wujian <jan.chou.wu@gmail.com> Closes #14008 from janplus/SPARK-16281.
* [SPARK-16285][SQL] Implement sentences SQL functionsDongjoon Hyun2016-07-081-1/+1
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR implements `sentences` SQL function. ## How was this patch tested? Pass the Jenkins tests with a new testcase. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #14004 from dongjoon-hyun/SPARK_16285.
* [SPARK-16415][SQL] fix catalog string errorDaoyuan Wang2016-07-071-3/+11
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? In #13537 we truncate `simpleString` if it is a long `StructType`. But sometimes we need `catalogString` to reconstruct `TypeInfo`, for example in description of [SPARK-16415 ](https://issues.apache.org/jira/browse/SPARK-16415). So we need to keep the implementation of `catalogString` not affected by our truncate. ## How was this patch tested? added a test case. Author: Daoyuan Wang <daoyuan.wang@intel.com> Closes #14089 from adrian-wang/catalogstring.
* [SPARK-16368][SQL] Fix Strange Errors When Creating View With Unmatched ↵gatorsmile2016-07-071-0/+23
| | | | | | | | | | | | | | | | | | | | | | | | | | | | Column Num #### What changes were proposed in this pull request? When creating a view, a common user error is the number of columns produced by the `SELECT` clause does not match the number of column names specified by `CREATE VIEW`. For example, given Table `t1` only has 3 columns ```SQL create view v1(col2, col4, col3, col5) as select * from t1 ``` Currently, Spark SQL reports the following error: ``` requirement failed java.lang.IllegalArgumentException: requirement failed at scala.Predef$.require(Predef.scala:212) at org.apache.spark.sql.execution.command.CreateViewCommand.run(views.scala:90) ``` This error message is very confusing. This PR is to detect the error and issue a meaningful error message. #### How was this patch tested? Added test cases Author: gatorsmile <gatorsmile@gmail.com> Closes #14047 from gatorsmile/viewMismatchedColumns.
* [SPARK-16374][SQL] Remove Alias from MetastoreRelation and SimpleCatalogRelationgatorsmile2016-07-072-10/+10
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | #### What changes were proposed in this pull request? Different from the other leaf nodes, `MetastoreRelation` and `SimpleCatalogRelation` have a pre-defined `alias`, which is used to change the qualifier of the node. However, based on the existing alias handling, alias should be put in `SubqueryAlias`. This PR is to separate alias handling from `MetastoreRelation` and `SimpleCatalogRelation` to make it consistent with the other nodes. It simplifies the signature and conversion to a `BaseRelation`. For example, below is an example query for `MetastoreRelation`, which is converted to a `LogicalRelation`: ```SQL SELECT tmp.a + 1 FROM test_parquet_ctas tmp WHERE tmp.a > 2 ``` Before changes, the analyzed plan is ``` == Analyzed Logical Plan == (a + 1): int Project [(a#951 + 1) AS (a + 1)#952] +- Filter (a#951 > 2) +- SubqueryAlias tmp +- Relation[a#951] parquet ``` After changes, the analyzed plan becomes ``` == Analyzed Logical Plan == (a + 1): int Project [(a#951 + 1) AS (a + 1)#952] +- Filter (a#951 > 2) +- SubqueryAlias tmp +- SubqueryAlias test_parquet_ctas +- Relation[a#951] parquet ``` **Note: the optimized plans are the same.** For `SimpleCatalogRelation`, the existing code always generates two Subqueries. Thus, no change is needed. #### How was this patch tested? Added test cases. Author: gatorsmile <gatorsmile@gmail.com> Closes #14053 from gatorsmile/removeAliasFromMetastoreRelation.
* [SPARK-16229][SQL] Drop Empty Table After CREATE TABLE AS SELECT failsgatorsmile2016-07-062-2/+26
| | | | | | | | | | | | | | | | | | | | | #### What changes were proposed in this pull request? In `CREATE TABLE AS SELECT`, if the `SELECT` query failed, the table should not exist. For example, ```SQL CREATE TABLE tab STORED AS TEXTFILE SELECT 1 AS a, (SELECT a FROM (SELECT 1 AS a UNION ALL SELECT 2 AS a) t) AS b ``` The above query failed as expected but an empty table `t` is created. This PR is to drop the created table when hitting any non-fatal exception. #### How was this patch tested? Added a test case to verify the behavior Author: gatorsmile <gatorsmile@gmail.com> Closes #13926 from gatorsmile/dropTableAfterException.
* [SPARK-16388][SQL] Remove spark.sql.nativeView and ↵Reynold Xin2016-07-061-118/+88
| | | | | | | | | | | | | | spark.sql.nativeView.canonical config ## What changes were proposed in this pull request? These two configs should always be true after Spark 2.0. This patch removes them from the config list. Note that ideally this should've gone into branch-2.0, but due to the timing of the release we should only merge this in master for Spark 2.1. ## How was this patch tested? Updated test cases. Author: Reynold Xin <rxin@databricks.com> Closes #14061 from rxin/SPARK-16388.
* [SPARK-16339][CORE] ScriptTransform does not print stderr when outstream is lostTejas Patil2016-07-061-4/+4
| | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Currently, if due to some failure, the outstream gets destroyed or closed and later `outstream.close()` leads to IOException in such case. Due to this, the `stderrBuffer` does not get logged and there is no way for users to see why the job failed. The change is to first display the stderr buffer and then try closing the outstream. ## How was this patch tested? The correct way to test this fix would be to grep the log to see if the `stderrBuffer` gets logged but I dont think having test cases which do that is a good idea. (If this patch involves UI changes, please attach a screenshot; otherwise, remove this) … Author: Tejas Patil <tejasp@fb.com> Closes #13834 from tejasapatil/script_transform.
* [SPARK-16389][SQL] Remove MetastoreRelation from SparkHiveWriterContainer ↵gatorsmile2016-07-062-15/+9
| | | | | | | | | | | | | | | and SparkHiveDynamicPartitionWriterContainer #### What changes were proposed in this pull request? - Remove useless `MetastoreRelation` from the signature of `SparkHiveWriterContainer` and `SparkHiveDynamicPartitionWriterContainer`. - Avoid unnecessary metadata retrieval using Hive client in `InsertIntoHiveTable`. #### How was this patch tested? Existing test cases already cover it. Author: gatorsmile <gatorsmile@gmail.com> Closes #14062 from gatorsmile/removeMetastoreRelation.
* [SPARK-16286][SQL] Implement stack table generating functionDongjoon Hyun2016-07-061-1/+1
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR implements `stack` table generating function. ## How was this patch tested? Pass the Jenkins tests including new testcases. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #14033 from dongjoon-hyun/SPARK-16286.
* [SPARK-16383][SQL] Remove `SessionState.executeSql`Dongjoon Hyun2016-07-051-3/+3
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR removes `SessionState.executeSql` in favor of `SparkSession.sql`. We can remove this safely since the visibility `SessionState` is `private[sql]` and `executeSql` is only used in one **ignored** test, `test("Multiple Hive Instances")`. ## How was this patch tested? Pass the Jenkins tests. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #14055 from dongjoon-hyun/SPARK-16383.
* [HOTFIX] Fix build break.Reynold Xin2016-07-051-1/+1
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* [SPARK-16311][SQL] Metadata refresh should work on temporary viewsReynold Xin2016-07-055-19/+74
| | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This patch fixes the bug that the refresh command does not work on temporary views. This patch is based on https://github.com/apache/spark/pull/13989, but removes the public Dataset.refresh() API as well as improved test coverage. Note that I actually think the public refresh() API is very useful. We can in the future implement it by also invalidating the lazy vals in QueryExecution (or alternatively just create a new QueryExecution). ## How was this patch tested? Re-enabled a previously ignored test, and added a new test suite for Hive testing behavior of temporary views against MetastoreRelation. Author: Reynold Xin <rxin@databricks.com> Author: petermaxlee <petermaxlee@gmail.com> Closes #14009 from rxin/SPARK-16311.
* [SPARK-15198][SQL] Support for pushing down filters for boolean types in ORC ↵hyukjinkwon2016-07-054-11/+39
| | | | | | | | | | | | | | | | | | | | data source ## What changes were proposed in this pull request? It seems ORC supports all the types in ([`PredicateLeaf.Type`](https://github.com/apache/hive/blob/e085b7e9bd059d91aaf013df0db4d71dca90ec6f/storage-api/src/java/org/apache/hadoop/hive/ql/io/sarg/PredicateLeaf.java#L50-L56)) which includes boolean types. So, this was tested first. This PR adds the support for pushing filters down for `BooleanType` in ORC data source. This PR also removes `OrcTableScan` class and the companion object, which is not used anymore. ## How was this patch tested? Unittest in `OrcFilterSuite` and `OrcQuerySuite`. Author: hyukjinkwon <gurwls223@gmail.com> Closes #12972 from HyukjinKwon/SPARK-15198.
* [SPARK-15968][SQL] Nonempty partitioned metastore tables are not cachedMichael Allman2016-07-053-19/+59
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | (Please note this is a revision of PR #13686, which has been closed in favor of this PR.) This PR addresses [SPARK-15968](https://issues.apache.org/jira/browse/SPARK-15968). ## What changes were proposed in this pull request? The `getCached` method of [HiveMetastoreCatalog](https://github.com/apache/spark/blob/master/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala) computes `pathsInMetastore` from the metastore relation's catalog table. This only returns the table base path, which is incomplete/inaccurate for a nonempty partitioned table. As a result, cached lookups on nonempty partitioned tables always miss. Rather than get `pathsInMetastore` from metastoreRelation.catalogTable.storage.locationUri.toSeq I modified the `getCached` method to take a `pathsInMetastore` argument. Calls to this method pass in the paths computed from calls to the Hive metastore. This is how `getCached` was implemented in Spark 1.5: https://github.com/apache/spark/blob/e0c3212a9b42e3e704b070da4ac25b68c584427f/sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveMetastoreCatalog.scala#L444. I also added a call in `InsertIntoHiveTable.scala` to invalidate the table from the SQL session catalog. ## How was this patch tested? I've added a new unit test to `parquetSuites.scala`: SPARK-15968: nonempty partitioned metastore Parquet table lookup should use cached relation Note that the only difference between this new test and the one above it in the file is that the new test populates its partitioned table with a single value, while the existing test leaves the table empty. This reveals a subtle, unexpected hole in test coverage present before this patch. Note I also modified a different but related unit test in `parquetSuites.scala`: SPARK-15248: explicitly added partitions should be readable This unit test asserts that Spark SQL should return data from a table partition which has been placed there outside a metastore query immediately after it is added. I changed the test so that, instead of adding the data as a parquet file saved in the partition's location, the data is added through a SQL `INSERT` query. I made this change because I could find no way to efficiently support partitioned table caching without failing that test. In addition to my primary motivation, I can offer a few reasons I believe this is an acceptable weakening of that test. First, it still validates a fix for [SPARK-15248](https://issues.apache.org/jira/browse/SPARK-15248), the issue for which it was written. Second, the assertion made is stronger than that required for non-partitioned tables. If you write data to the storage location of a non-partitioned metastore table without using a proper SQL DML query, a subsequent call to show that data will not return it. I believe this is an intentional limitation put in place to make table caching feasible, but I'm only speculating. Building a large `HadoopFsRelation` requires `stat`-ing all of its data files. In our environment, where we have tables with 10's of thousands of partitions, the difference between using a cached relation versus a new one is a matter of seconds versus minutes. Caching partitioned table metadata vastly improves the usability of Spark SQL for these cases. Thanks. Author: Michael Allman <michael@videoamp.com> Closes #13818 from mallman/spark-15968.
* [SPARK-16358][SQL] Remove InsertIntoHiveTable From Logical Plangatorsmile2016-07-043-47/+1
| | | | | | | | | | | | #### What changes were proposed in this pull request? LogicalPlan `InsertIntoHiveTable` is useless. Thus, we can remove it from the code base. #### How was this patch tested? The existing test cases Author: gatorsmile <gatorsmile@gmail.com> Closes #14037 from gatorsmile/InsertIntoHiveTable.
* [SPARK-16288][SQL] Implement inline table generating functionDongjoon Hyun2016-07-041-4/+1
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR implements `inline` table generating function. ## How was this patch tested? Pass the Jenkins tests with new testcase. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #13976 from dongjoon-hyun/SPARK-16288.
* [SPARK-16278][SPARK-16279][SQL] Implement map_keys/map_values SQL functionsDongjoon Hyun2016-07-031-1/+0
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR adds `map_keys` and `map_values` SQL functions in order to remove Hive fallback. ## How was this patch tested? Pass the Jenkins tests including new testcases. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #13967 from dongjoon-hyun/SPARK-16278.
* [SPARK-15954][SQL] Disable loading test tables in Python testsReynold Xin2016-06-301-160/+184
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? This patch introduces a flag to disable loading test tables in TestHiveSparkSession and disables that in Python. This fixes an issue in which python/run-tests would fail due to failure to load test tables. Note that these test tables are not used outside of HiveCompatibilitySuite. In the long run we should probably decouple the loading of test tables from the test Hive setup. ## How was this patch tested? This is a test only change. Author: Reynold Xin <rxin@databricks.com> Closes #14005 from rxin/SPARK-15954.
* [SPARK-16276][SQL] Implement elt SQL functionpetermaxlee2016-07-011-1/+1
| | | | | | | | | | | | ## What changes were proposed in this pull request? This patch implements the elt function, as it is implemented in Hive. ## How was this patch tested? Added expression unit test in StringExpressionsSuite and end-to-end test in StringFunctionsSuite. Author: petermaxlee <petermaxlee@gmail.com> Closes #13966 from petermaxlee/SPARK-16276.
* [SPARK-16289][SQL] Implement posexplode table generating functionDongjoon Hyun2016-06-301-1/+1
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? This PR implements `posexplode` table generating function. Currently, master branch raises the following exception for `map` argument. It's different from Hive. **Before** ```scala scala> sql("select posexplode(map('a', 1, 'b', 2))").show org.apache.spark.sql.AnalysisException: No handler for Hive UDF ... posexplode() takes an array as a parameter; line 1 pos 7 ``` **After** ```scala scala> sql("select posexplode(map('a', 1, 'b', 2))").show +---+---+-----+ |pos|key|value| +---+---+-----+ | 0| a| 1| | 1| b| 2| +---+---+-----+ ``` For `array` argument, `after` is the same with `before`. ``` scala> sql("select posexplode(array(1, 2, 3))").show +---+---+ |pos|col| +---+---+ | 0| 1| | 1| 2| | 2| 3| +---+---+ ``` ## How was this patch tested? Pass the Jenkins tests with newly added testcases. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #13971 from dongjoon-hyun/SPARK-16289.
* [SPARK-13850] Force the sorter to Spill when number of elements in th…Sital Kedia2016-06-301-1/+4
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? Force the sorter to Spill when number of elements in the pointer array reach a certain size. This is to workaround the issue of timSort failing on large buffer size. ## How was this patch tested? Tested by running a job which was failing without this change due to TimSort bug. Author: Sital Kedia <skedia@fb.com> Closes #13107 from sitalkedia/fix_TimSort.
* [SPARK-16274][SQL] Implement xpath_booleanpetermaxlee2016-06-301-1/+1
| | | | | | | | | | | | ## What changes were proposed in this pull request? This patch implements xpath_boolean expression for Spark SQL, a xpath function that returns true or false. The implementation is modelled after Hive's xpath_boolean, except that how the expression handles null inputs. Hive throws a NullPointerException at runtime if either of the input is null. This implementation returns null if either of the input is null. ## How was this patch tested? Created two new test suites. One for unit tests covering the expression, and the other for end-to-end test in SQL. Author: petermaxlee <petermaxlee@gmail.com> Closes #13964 from petermaxlee/SPARK-16274.
* [SPARK-16267][TEST] Replace deprecated `CREATE TEMPORARY TABLE ... USING` ↵Dongjoon Hyun2016-06-292-7/+7
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | from testsuites. ## What changes were proposed in this pull request? After SPARK-15674, `DDLStrategy` prints out the following deprecation messages in the testsuites. ``` 12:10:53.284 WARN org.apache.spark.sql.execution.SparkStrategies$DDLStrategy: CREATE TEMPORARY TABLE normal_orc_source USING... is deprecated, please use CREATE TEMPORARY VIEW viewName USING... instead ``` Total : 40 - JDBCWriteSuite: 14 - DDLSuite: 6 - TableScanSuite: 6 - ParquetSourceSuite: 5 - OrcSourceSuite: 2 - SQLQuerySuite: 2 - HiveCommandSuite: 2 - JsonSuite: 1 - PrunedScanSuite: 1 - FilteredScanSuite 1 This PR replaces `CREATE TEMPORARY TABLE` with `CREATE TEMPORARY VIEW` in order to remove the deprecation messages in the above testsuites except `DDLSuite`, `SQLQuerySuite`, `HiveCommandSuite`. The Jenkins results shows only remaining 10 messages. https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/61422/consoleFull ## How was this patch tested? This is a testsuite-only change. Author: Dongjoon Hyun <dongjoon@apache.org> Closes #13956 from dongjoon-hyun/SPARK-16267.
* [SPARK-16228][SQL] HiveSessionCatalog should return `double`-param functions ↵Dongjoon Hyun2016-06-292-1/+22
| | | | | | | | | | | | | | | | | | | | | | | | | for decimal param lookups ## What changes were proposed in this pull request? This PR supports a fallback lookup by casting `DecimalType` into `DoubleType` for the external functions with `double`-type parameter. **Reported Error Scenarios** ```scala scala> sql("select percentile(value, 0.5) from values 1,2,3 T(value)") org.apache.spark.sql.AnalysisException: ... No matching method for class org.apache.hadoop.hive.ql.udf.UDAFPercentile with (int, decimal(38,18)). Possible choices: _FUNC_(bigint, array<double>) _FUNC_(bigint, double) ; line 1 pos 7 scala> sql("select percentile_approx(value, 0.5) from values 1.0,2.0,3.0 T(value)") org.apache.spark.sql.AnalysisException: ... Only a float/double or float/double array argument is accepted as parameter 2, but decimal(38,18) was passed instead.; line 1 pos 7 ``` ## How was this patch tested? Pass the Jenkins tests (including a new testcase). Author: Dongjoon Hyun <dongjoon@apache.org> Closes #13930 from dongjoon-hyun/SPARK-16228.
* [SPARK-16157][SQL] Add New Methods for comments in StructField and StructTypegatorsmile2016-06-291-0/+22
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | #### What changes were proposed in this pull request? Based on the previous discussion with cloud-fan hvanhovell in another related PR https://github.com/apache/spark/pull/13764#discussion_r67994276, it looks reasonable to add convenience methods for users to add `comment` when defining `StructField`. Currently, the column-related `comment` attribute is stored in `Metadata` of `StructField`. For example, users can add the `comment` attribute using the following way: ```Scala StructType( StructField( "cl1", IntegerType, nullable = false, new MetadataBuilder().putString("comment", "test").build()) :: Nil) ``` This PR is to add more user friendly methods for the `comment` attribute when defining a `StructField`. After the changes, users are provided three different ways to do it: ```Scala val struct = (new StructType) .add("a", "int", true, "test1") val struct = (new StructType) .add("c", StringType, true, "test3") val struct = (new StructType) .add(StructField("d", StringType).withComment("test4")) ``` #### How was this patch tested? Added test cases: - `DataTypeSuite` is for testing three types of API changes, - `DataFrameReaderWriterSuite` is for parquet, json and csv formats - using in-memory catalog - `OrcQuerySuite.scala` is for orc format using Hive-metastore Author: gatorsmile <gatorsmile@gmail.com> Closes #13860 from gatorsmile/newMethodForComment.
* [SPARK-16248][SQL] Whitelist the list of Hive fallback functionsReynold Xin2016-06-283-50/+39
| | | | | | | | | | | | ## What changes were proposed in this pull request? This patch removes the blind fallback into Hive for functions. Instead, it creates a whitelist and adds only a small number of functions to the whitelist, i.e. the ones we intend to support in the long run in Spark. ## How was this patch tested? Updated tests to reflect the change. Author: Reynold Xin <rxin@databricks.com> Closes #13939 from rxin/hive-whitelist.
* [SPARK-16220][SQL] Revert Change to Bring Back SHOW FUNCTIONS FunctionalityBill Chambers2016-06-271-0/+5
| | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? - Fix tests regarding show functions functionality - Revert `catalog.ListFunctions` and `SHOW FUNCTIONS` to return to `Spark 1.X` functionality. Cherry picked changes from this PR: https://github.com/apache/spark/pull/13413/files ## How was this patch tested? Unit tests. Author: Bill Chambers <bill@databricks.com> Author: Bill Chambers <wchambers@ischool.berkeley.edu> Closes #13916 from anabranch/master.
* [SPARK-13709][SQL] Initialize deserializer with both table and partition ↵Cheng Lian2016-06-232-1/+97
| | | | | | | | | | | | | | | | | | properties when reading partitioned tables ## What changes were proposed in this pull request? When reading partitions of a partitioned Hive SerDe table, we only initializes the deserializer using partition properties. However, for SerDes like `AvroSerDe`, essential properties (e.g. Avro schema information) may be defined in table properties. We should merge both table properties and partition properties before initializing the deserializer. Note that an individual partition may have different properties than the one defined in the table properties (e.g. partitions within a table can have different SerDes). Thus, for any property key defined in both partition and table properties, the value set in partition properties wins. ## How was this patch tested? New test case added in `QueryPartitionSuite`. Author: Cheng Lian <lian@databricks.com> Closes #13865 from liancheng/spark-13709-partitioned-avro-table.
* [SPARK-16162] Remove dead code OrcTableScan.Brian Cho2016-06-221-66/+1
| | | | | | | | | | | | | | ## What changes were proposed in this pull request? SPARK-14535 removed all calls to class OrcTableScan. This removes the dead code. ## How was this patch tested? Existing unit tests. Author: Brian Cho <bcho@fb.com> Closes #13869 from dafrista/clean-up-orctablescan.
* [SPARK-16024][SQL][TEST] Verify Column Comment for Data Source Tablesgatorsmile2016-06-231-0/+14
| | | | | | | | | | | | | | #### What changes were proposed in this pull request? This PR is to improve test coverage. It verifies whether `Comment` of `Column` can be appropriate handled. The test cases verify the related parts in Parser, both SQL and DataFrameWriter interface, and both Hive Metastore catalog and In-memory catalog. #### How was this patch tested? N/A Author: gatorsmile <gatorsmile@gmail.com> Closes #13764 from gatorsmile/dataSourceComment.
* [SPARK-15956][SQL] When unwrapping ORC avoid pattern matching at runtimeBrian Cho2016-06-225-150/+314
| | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Extend the returning of unwrapper functions from primitive types to all types. This PR is based on https://github.com/apache/spark/pull/13676. It only fixes a bug with scala-2.10 compilation. All credit should go to dafrista. ## How was this patch tested? The patch should pass all unit tests. Reading ORC files with non-primitive types with this change reduced the read time by ~15%. Author: Brian Cho <bcho@fb.com> Author: Herman van Hovell <hvanhovell@databricks.com> Closes #13854 from hvanhovell/SPARK-15956-scala210.
* [SPARK-15956][SQL] Revert "[] When unwrapping ORC avoid pattern matching…Herman van Hovell2016-06-225-314/+150
| | | | | | | | This reverts commit 0a9c02759515c41de37db6381750bc3a316c860c. It breaks the 2.10 build, I'll fix this in a different PR. Author: Herman van Hovell <hvanhovell@databricks.com> Closes #13853 from hvanhovell/SPARK-15956-revert.
* [SPARK-15956][SQL] When unwrapping ORC avoid pattern matching at runtimeBrian Cho2016-06-225-150/+314
| | | | | | | | | | | | | | | | | | | | | | ## What changes were proposed in this pull request? Extend the returning of unwrapper functions from primitive types to all types. ## How was this patch tested? The patch should pass all unit tests. Reading ORC files with non-primitive types with this change reduced the read time by ~15%. === The github diff is very noisy. Attaching the screenshots below for improved readability: ![screen shot 2016-06-14 at 5 33 16 pm](https://cloud.githubusercontent.com/assets/1514239/16064580/4d6f7a98-3257-11e6-9172-65e4baff948b.png) ![screen shot 2016-06-14 at 5 33 28 pm](https://cloud.githubusercontent.com/assets/1514239/16064587/5ae6c244-3257-11e6-8460-69eee70de219.png) Author: Brian Cho <bcho@fb.com> Closes #13676 from dafrista/improve-orc-master.
* [SPARK-16037][SQL] Follow-up: add DataFrameWriter.insertInto() test cases ↵Cheng Lian2016-06-211-0/+48
| | | | | | | | | | | | | | | | | | for by position resolution ## What changes were proposed in this pull request? This PR migrates some test cases introduced in #12313 as a follow-up of #13754 and #13766. These test cases cover `DataFrameWriter.insertInto()`, while the former two only cover SQL `INSERT` statements. Note that the `testPartitionedTable` utility method tests both Hive SerDe tables and data source tables. ## How was this patch tested? N/A Author: Cheng Lian <lian@databricks.com> Closes #13810 from liancheng/spark-16037-follow-up-tests.
* [SPARK-16030][SQL] Allow specifying static partitions when inserting to data ↵Yin Huai2016-06-204-13/+91
| | | | | | | | | | | | | | | | source tables ## What changes were proposed in this pull request? This PR adds the static partition support to INSERT statement when the target table is a data source table. ## How was this patch tested? New tests in InsertIntoHiveTableSuite and DataSourceAnalysisSuite. **Note: This PR is based on https://github.com/apache/spark/pull/13766. The last commit is the actual change.** Author: Yin Huai <yhuai@databricks.com> Closes #13769 from yhuai/SPARK-16030-1.
* [SPARK-16036][SPARK-16037][SPARK-16034][SQL] Follow up code clean up and ↵Yin Huai2016-06-194-33/+56
| | | | | | | | | | | | | | improvement ## What changes were proposed in this pull request? This PR is the follow-up PR for https://github.com/apache/spark/pull/13754/files and https://github.com/apache/spark/pull/13749. I will comment inline to explain my changes. ## How was this patch tested? Existing tests. Author: Yin Huai <yhuai@databricks.com> Closes #13766 from yhuai/caseSensitivity.
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