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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 Lian2014-10-053-31/+31
| | | | | | | | | | | | | | | | 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-3212][SQL] Use logical plan matching instead of temporary tables for ↵Michael Armbrust2014-10-036-4/+117
| | | | | | | | | | | | | | | | | | | | | | | | | | | 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-3371][SQL] Renaming a function expression with group by gives errorravipesala2014-10-011-1/+1
| | | | | | | | | | | | | | | | | | | 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-3593][SQL] Add support for sorting BinaryTypeVenkata Ramana Gollamudi2014-10-011-1/+11
| | | | | | | | | | | | 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-3268][SQL] DoubleType, FloatType and DecimalType modulus supportVenkata Ramana Gollamudi2014-09-233-0/+40
| | | | | | | | | | | | | | | | | | | | 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-3598][SQL]cast to timestamp should be the same as hiveDaoyuan Wang2014-09-232-15/+18
| | | | | | | | | | | | | | | | | 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 Armbrust2014-09-206-69/+100
| | | | | | | | | | | | | | | | | | | | | | | | | | **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 Lian2014-09-202-0/+21
| | | | | | | | | | | | | | | 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-2594][SQL] Support CACHE TABLE <name> AS SELECT ...ravipesala2014-09-192-3/+16
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 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 Hao2014-09-191-0/+1
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 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-2890][SQL] Allow reading of data when case insensitive resolution ↵Michael Armbrust2014-09-161-4/+0
| | | | | | | | | | | | | | | 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-3294][SQL] Eliminates boxing costs from in-memory columnar storageCheng Lian2014-09-131-1/+1
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 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-3462 push down filters and projections into UnionsCody Koeninger2014-09-112-0/+110
| | | | | | | | | | Author: Cody Koeninger <cody.koeninger@mediacrossing.com> Closes #2345 from koeninger/SPARK-3462 and squashes the following commits: 5c8d24d [Cody Koeninger] SPARK-3462 remove now-unused parameter 0788691 [Cody Koeninger] SPARK-3462 add tests, handle compatible schema with different aliases, per marmbrus feedback ef47b3b [Cody Koeninger] SPARK-3462 push down filters and projections into Unions
* [SPARK-2917] [SQL] Avoid table creation in logical plan analyzing for CTASCheng Hao2014-09-111-1/+2
| | | | | | | | | Author: Cheng Hao <hao.cheng@intel.com> Closes #1846 from chenghao-intel/ctas and squashes the following commits: 56a0578 [Cheng Hao] remove the unused imports 9a57abc [Cheng Hao] Avoid table creation in logical plan analyzing
* [SPARK-2781][SQL] Check resolution of LogicalPlans in Analyzer.Aaron Staple2014-09-105-6/+49
| | | | | | | | | | | | | | | | | | | | | | | | LogicalPlan contains a ‘resolved’ attribute indicating that all of its execution requirements have been resolved. This attribute is not checked before query execution. The analyzer contains a step to check that all Expressions are resolved, but this is not equivalent to checking all LogicalPlans. In particular, the Union plan’s implementation of ‘resolved’ verifies that the types of its children’s columns are compatible. Because the analyzer does not check that a Union plan is resolved, it is possible to execute a Union plan that outputs different types in the same column. See SPARK-2781 for an example. This patch adds two checks to the analyzer’s CheckResolution rule. First, each logical plan is checked to see if it is not resolved despite its children being resolved. This allows the ‘problem’ unresolved plan to be included in the TreeNodeException for reporting. Then as a backstop the root plan is checked to see if it is resolved, which recursively checks that the entire plan tree is resolved. Note that the resolved attribute is implemented recursively, and this patch also explicitly checks the resolved attribute on each logical plan in the tree. I assume the query plan trees will not be large enough for this redundant checking to meaningfully impact performance. Because this patch starts validating that LogicalPlans are resolved before execution, I had to fix some cases where unresolved plans were passing through the analyzer as part of the implementation of the hive query system. In particular, HiveContext applies the CreateTables and PreInsertionCasts, and ExtractPythonUdfs rules manually after the analyzer runs. I moved these rules to the analyzer stage (for hive queries only), in the process completing a code TODO indicating the rules should be moved to the analyzer. It’s worth noting that moving the CreateTables rule means introducing an analyzer rule with a significant side effect - in this case the side effect is creating a hive table. The rule will only attempt to create a table once even if its batch is executed multiple times, because it converts the InsertIntoCreatedTable plan it matches against into an InsertIntoTable. Additionally, these hive rules must be added to the Resolution batch rather than as a separate batch because hive rules rules may be needed to resolve non-root nodes, leaving the root to be resolved on a subsequent batch iteration. For example, the hive compatibility test auto_smb_mapjoin_14, and others, make use of a query plan where the root is a Union and its children are each a hive InsertIntoTable. Mixing the custom hive rules with standard analyzer rules initially resulted in an additional failure because of policy differences between spark sql and hive when casting a boolean to a string. Hive casts booleans to strings as “true” / “false” while spark sql casts booleans to strings as “1” / “0” (causing the cast1.q test to fail). This behavior is a result of the BooleanCasts rule in HiveTypeCoercion.scala, and from looking at the implementation of BooleanCasts I think converting to to “1”/“0” is potentially a programming mistake. (If the BooleanCasts rule is disabled, casting produces “true”/“false” instead.) I believe “true” / “false” should be the behavior for spark sql - I changed the behavior so bools are converted to “true”/“false” to be consistent with hive, and none of the existing spark tests failed. Finally, in some initial testing with hive it appears that an implicit type coercion of boolean to string results in a lowercase string, e.g. CONCAT( TRUE, “” ) -> “true” while an explicit cast produces an all caps string, e.g. CAST( TRUE AS STRING ) -> “TRUE”. The change I’ve made just converts to lowercase strings in all cases. I believe it is at least more correct than the existing spark sql implementation where all Cast expressions become “1” / “0”. Author: Aaron Staple <aaron.staple@gmail.com> Closes #1706 from staple/SPARK-2781 and squashes the following commits: 32683c4 [Aaron Staple] Fix compilation failure due to merge. 7c77fda [Aaron Staple] Move ExtractPythonUdfs to Analyzer's extendedRules in HiveContext. d49bfb3 [Aaron Staple] Address review comments. 915b690 [Aaron Staple] Fix merge issue causing compilation failure. 701dcd2 [Aaron Staple] [SPARK-2781][SQL] Check resolution of LogicalPlans in Analyzer.
* [SPARK-2096][SQL] Correctly parse dot notationsWenchen Fan2014-09-102-7/+12
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | First let me write down the current `projections` grammar of spark sql: expression : orExpression orExpression : andExpression {"or" andExpression} andExpression : comparisonExpression {"and" comparisonExpression} comparisonExpression : termExpression | termExpression "=" termExpression | termExpression ">" termExpression | ... termExpression : productExpression {"+"|"-" productExpression} productExpression : baseExpression {"*"|"/"|"%" baseExpression} baseExpression : expression "[" expression "]" | ... | ident | ... ident : identChar {identChar | digit} | delimiters | ... identChar : letter | "_" | "." delimiters : "," | ";" | "(" | ")" | "[" | "]" | ... projection : expression [["AS"] ident] projections : projection { "," projection} For something like `a.b.c[1]`, it will be parsed as: <img src="http://img51.imgspice.com/i/03008/4iltjsnqgmtt_t.jpg" border=0> But for something like `a[1].b`, the current grammar can't parse it correctly. A simple solution is written in `ParquetQuerySuite#NestedSqlParser`, changed grammars are: delimiters : "." | "," | ";" | "(" | ")" | "[" | "]" | ... identChar : letter | "_" baseExpression : expression "[" expression "]" | expression "." ident | ... | ident | ... This works well, but can't cover some corner case like `select t.a.b from table as t`: <img src="http://img51.imgspice.com/i/03008/v2iau3hoxoxg_t.jpg" border=0> `t.a.b` parsed as `GetField(GetField(UnResolved("t"), "a"), "b")` instead of `GetField(UnResolved("t.a"), "b")` using this new grammar. However, we can't resolve `t` as it's not a filed, but the whole table.(if we could do this, then `select t from table as t` is legal, which is unexpected) My solution is: dotExpressionHeader : ident "." ident baseExpression : expression "[" expression "]" | expression "." ident | ... | dotExpressionHeader | ident | ... I passed all test cases under sql locally and add a more complex case. "arrayOfStruct.field1 to access all values of field1" is not supported yet. Since this PR has changed a lot of code, I will open another PR for it. I'm not familiar with the latter optimize phase, please correct me if I missed something. Author: Wenchen Fan <cloud0fan@163.com> Author: Michael Armbrust <michael@databricks.com> Closes #2230 from cloud-fan/dot and squashes the following commits: e1a8898 [Wenchen Fan] remove support for arbitrary nested arrays ee8a724 [Wenchen Fan] rollback LogicalPlan, support dot operation on nested array type a58df40 [Michael Armbrust] add regression test for doubly nested data 16bc4c6 [Wenchen Fan] some enhance 95d733f [Wenchen Fan] split long line dc31698 [Wenchen Fan] SPARK-2096 Correctly parse dot notations
* [SPARK-3363][SQL] Type Coercion should promote null to all other types.Daoyuan Wang2014-09-102-25/+45
| | | | | | | | | | | | | | | Type Coercion should support every type to have null value Author: Daoyuan Wang <daoyuan.wang@intel.com> Author: Michael Armbrust <michael@databricks.com> Closes #2246 from adrian-wang/spark3363-0 and squashes the following commits: c6241de [Daoyuan Wang] minor code clean 595b417 [Daoyuan Wang] Merge pull request #2 from marmbrus/pr/2246 832e640 [Michael Armbrust] reduce code duplication ef6f986 [Daoyuan Wang] make double boolean miss in jsonRDD compatibleType c619f0a [Daoyuan Wang] Type Coercion should support every type to have null value
* [SPARK-3362][SQL] Fix resolution for casewhen with nulls.Daoyuan Wang2014-09-101-2/+3
| | | | | | | | | | | | | Current implementation will ignore else val type. Author: Daoyuan Wang <daoyuan.wang@intel.com> Closes #2245 from adrian-wang/casewhenbug and squashes the following commits: 3332f6e [Daoyuan Wang] remove wrong comment 83b536c [Daoyuan Wang] a comment to trigger retest d7315b3 [Daoyuan Wang] code improve eed35fc [Daoyuan Wang] bug in casewhen resolve
* [SPARK-3448][SQL] Check for null in SpecificMutableRow.updateCheng Lian2014-09-091-1/+3
| | | | | | | | | | | | `SpecificMutableRow.update` doesn't check for null, and breaks existing `MutableRow` contract. The tricky part here is that for performance considerations, the `update` method of all subclasses of `MutableValue` doesn't check for null and sets the null bit to false. Author: Cheng Lian <lian.cs.zju@gmail.com> Closes #2325 from liancheng/check-for-null and squashes the following commits: 9366c44 [Cheng Lian] Check for null in SpecificMutableRow.update
* [SPARK-3176] Implement 'ABS and 'LAST' for sqlxinyunh2014-09-094-0/+48
| | | | | | | | | | | | | | | | Add support for the mathematical function"ABS" and the analytic function "last" to return a subset of the rows satisfying a query within spark sql. Test-cases included. Author: xinyunh <xinyun.huang@huawei.com> Author: bomeng <golf8lover> Closes #2099 from xinyunh/sqlTest and squashes the following commits: 71d15e7 [xinyunh] remove POWER part 8843643 [xinyunh] fix the code style issue 39f0309 [bomeng] Modify the code of POWER and ABS. Move them to the file arithmetic ff8e51e [bomeng] add abs() function support 7f6980a [xinyunh] fix the bug in 'Last' component b3df91b [xinyunh] add 'Last' component
* SPARK-3423: [SQL] Implement BETWEEN for SQLParserWilliam Benton2014-09-081-0/+4
| | | | | | | | | | This patch improves the SQLParser by adding support for BETWEEN conditions Author: William Benton <willb@redhat.com> Closes #2295 from willb/sql-between and squashes the following commits: 0016d30 [William Benton] Implement BETWEEN for SQLParser
* [SPARK-3397] Bump pom.xml version number of master branch to 1.2.0-SNAPSHOTGuoQiang Li2014-09-061-1/+1
| | | | | | | | Author: GuoQiang Li <witgo@qq.com> Closes #2268 from witgo/SPARK-3397 and squashes the following commits: eaf913f [GuoQiang Li] Bump pom.xml version number of master branch to 1.2.0-SNAPSHOT
* [SPARK-2961][SQL] Use statistics to prune batches within cached partitionsCheng Lian2014-09-032-2/+51
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This PR is based on #1883 authored by marmbrus. Key differences: 1. Batch pruning instead of partition pruning When #1883 was authored, batched column buffer building (#1880) hadn't been introduced. This PR combines these two and provide partition batch level pruning, which leads to smaller memory footprints and can generally skip more elements. The cost is that the pruning predicates are evaluated more frequently (partition number multiplies batch number per partition). 1. More filters are supported Filter predicates consist of `=`, `<`, `<=`, `>`, `>=` and their conjunctions and disjunctions are supported. Author: Cheng Lian <lian.cs.zju@gmail.com> Closes #2188 from liancheng/in-mem-batch-pruning and squashes the following commits: 68cf019 [Cheng Lian] Marked sqlContext as @transient 4254f6c [Cheng Lian] Enables in-memory partition pruning in PartitionBatchPruningSuite 3784105 [Cheng Lian] Overrides InMemoryColumnarTableScan.sqlContext d2a1d66 [Cheng Lian] Disables in-memory partition pruning by default 062c315 [Cheng Lian] HiveCompatibilitySuite code cleanup 16b77bf [Cheng Lian] Fixed pruning predication conjunctions and disjunctions 16195c5 [Cheng Lian] Enabled both disjunction and conjunction 89950d0 [Cheng Lian] Worked around Scala style check 9c167f6 [Cheng Lian] Minor code cleanup 3c4d5c7 [Cheng Lian] Minor code cleanup ea59ee5 [Cheng Lian] Renamed PartitionSkippingSuite to PartitionBatchPruningSuite fc517d0 [Cheng Lian] More test cases 1868c18 [Cheng Lian] Code cleanup, bugfix, and adding tests cb76da4 [Cheng Lian] Added more predicate filters, fixed table scan stats for testing purposes 385474a [Cheng Lian] Merge branch 'inMemStats' into in-mem-batch-pruning
* [SPARK-3341][SQL] The dataType of Sqrt expression should be DoubleType.Takuya UESHIN2014-09-021-1/+1
| | | | | | | | Author: Takuya UESHIN <ueshin@happy-camper.st> Closes #2233 from ueshin/issues/SPARK-3341 and squashes the following commits: e497320 [Takuya UESHIN] Fix data type of Sqrt expression.
* [SPARK-3173][SQL] Timestamp support in the parserZdenek Farana2014-08-292-1/+12
| | | | | | | | | | | | | | | | | | | | | | | If you have a table with TIMESTAMP column, that column can't be used in WHERE clause properly - it is not evaluated properly. [More](https://issues.apache.org/jira/browse/SPARK-3173) Motivation: http://www.aproint.com/aggregation-with-spark-sql/ - [x] modify SqlParser so it supports casting to TIMESTAMP (workaround for item 2) - [x] the string literal should be converted into Timestamp if the column is Timestamp. Author: Zdenek Farana <zdenek.farana@gmail.com> Author: Zdenek Farana <zdenek.farana@aproint.com> Closes #2084 from byF/SPARK-3173 and squashes the following commits: 442b59d [Zdenek Farana] Fixed test merge conflict 2dbf4f6 [Zdenek Farana] Merge remote-tracking branch 'origin/SPARK-3173' into SPARK-3173 65b6215 [Zdenek Farana] Fixed timezone sensitivity in the test 47b27b4 [Zdenek Farana] Now works in the case of "StringLiteral=TimestampColumn" 96a661b [Zdenek Farana] Code style change 491dfcf [Zdenek Farana] Added test cases for SPARK-3173 4446b1e [Zdenek Farana] A string literal is casted into Timestamp when the column is Timestamp. 59af397 [Zdenek Farana] Added a new TIMESTAMP keyword; CAST to TIMESTAMP now can be used in SQL expression.
* [SPARK-3198] [SQL] Remove the TreeNode.idCheng Hao2014-08-295-34/+29
| | | | | | | | | | | | Thus id property of the TreeNode API does save time in a faster way to compare 2 TreeNodes, it is kind of performance bottleneck during the expression object creation in a multi-threading env (because of the memory barrier). Fortunately, the tree node comparison only happen once in master, so even we remove it, the entire performance will not be affected. Author: Cheng Hao <hao.cheng@intel.com> Closes #2155 from chenghao-intel/treenode and squashes the following commits: 7cf2cd2 [Cheng Hao] Remove the implicit keyword for TreeNodeRef and some other small issues 5873415 [Cheng Hao] Remove the TreeNode.id
* SPARK-2813: [SQL] Implement SQRT() directly in Spark SQLWilliam Benton2014-08-294-0/+30
| | | | | | | | | | | | | | | This PR adds a native implementation for SQL SQRT() and thus avoids delegating this function to Hive. Author: William Benton <willb@redhat.com> Closes #1750 from willb/spark-2813 and squashes the following commits: 22c8a79 [William Benton] Fixed missed newline from rebase d673861 [William Benton] Added string coercions for SQRT and associated test case e125df4 [William Benton] Added ExpressionEvaluationSuite test cases for SQRT 7b84bcd [William Benton] SQL SQRT now properly returns NULL for NULL inputs 8256971 [William Benton] added SQRT test to SqlQuerySuite 504d2e5 [William Benton] Added native SQRT implementation
* [SPARK-3230][SQL] Fix udfs that return structsMichael Armbrust2014-08-282-3/+16
| | | | | | | | | | | | We need to convert the case classes into Rows. Author: Michael Armbrust <michael@databricks.com> Closes #2133 from marmbrus/structUdfs and squashes the following commits: 189722f [Michael Armbrust] Merge remote-tracking branch 'origin/master' into structUdfs 8e29b1c [Michael Armbrust] Use existing function d8d0b76 [Michael Armbrust] Fix udfs that return structs
* [HOTFIX][SQL] Remove cleaning of UDFsMichael Armbrust2014-08-271-3/+0
| | | | | | | | | | It is not safe to run the closure cleaner on slaves. #2153 introduced this which broke all UDF execution on slaves. Will re-add cleaning of UDF closures in a follow-up PR. Author: Michael Armbrust <michael@databricks.com> Closes #2174 from marmbrus/fixUdfs and squashes the following commits: 55406de [Michael Armbrust] [HOTFIX] Remove cleaning of UDFs
* [SPARK-3235][SQL] Ensure in-memory tables don't always broadcast.Michael Armbrust2014-08-271-6/+8
| | | | | | | | | | | Author: Michael Armbrust <michael@databricks.com> Closes #2147 from marmbrus/inMemDefaultSize and squashes the following commits: 5390360 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into inMemDefaultSize 14204d3 [Michael Armbrust] Set the context before creating SparkLogicalPlans. 8da4414 [Michael Armbrust] Make sure we throw errors when leaf nodes fail to provide statistcs 18ce029 [Michael Armbrust] Ensure in-memory tables don't always broadcast.
* [SPARK-3197] [SQL] Reduce the Expression tree object creations for ↵Cheng Hao2014-08-272-17/+18
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | aggregation function (min/max) Aggregation function min/max in catalyst will create expression tree for each single row, however, the expression tree creation is quite expensive in a multithreading env currently. Hence we got a very bad performance for the min/max. Here is the benchmark that I've done in my local. Master | Previous Result (ms) | Current Result (ms) ------------ | ------------- | ------------- local | 3645 | 3416 local[6] | 3602 | 1002 The Benchmark source code. ``` case class Record(key: Int, value: Int) object TestHive2 extends HiveContext(new SparkContext("local[6]", "TestSQLContext", new SparkConf())) object DataPrepare extends App { import TestHive2._ val rdd = sparkContext.parallelize((1 to 10000000).map(i => Record(i % 3000, i)), 12) runSqlHive("SHOW TABLES") runSqlHive("DROP TABLE if exists a") runSqlHive("DROP TABLE if exists result") rdd.registerAsTable("records") runSqlHive("""CREATE TABLE a (key INT, value INT) | ROW FORMAT SERDE | 'org.apache.hadoop.hive.serde2.columnar.LazyBinaryColumnarSerDe' | STORED AS RCFILE """.stripMargin) runSqlHive("""CREATE TABLE result (key INT, value INT) | ROW FORMAT SERDE | 'org.apache.hadoop.hive.serde2.columnar.LazyBinaryColumnarSerDe' | STORED AS RCFILE """.stripMargin) hql(s"""from records | insert into table a | select key, value """.stripMargin) } object PerformanceTest extends App { import TestHive2._ hql("SHOW TABLES") hql("set spark.sql.shuffle.partitions=12") val cmd = "select min(value), max(value) from a group by key" val results = ("Result1", benchmark(cmd)) :: ("Result2", benchmark(cmd)) :: ("Result3", benchmark(cmd)) :: Nil results.foreach { case (prompt, result) => { println(s"$prompt: took ${result._1} ms (${result._2} records)") } } def benchmark(cmd: String) = { val begin = System.currentTimeMillis() val count = hql(cmd).count val end = System.currentTimeMillis() ((end - begin), count) } } ``` Author: Cheng Hao <hao.cheng@intel.com> Closes #2113 from chenghao-intel/aggregation_expression_optimization and squashes the following commits: db40395 [Cheng Hao] remove the transient and add val for the expression property d56167d [Cheng Hao] Reduce the Expressions creation
* [SPARK-3237][SQL] Fix parquet filters with UDFsMichael Armbrust2014-08-271-0/+4
| | | | | | | | | Author: Michael Armbrust <michael@databricks.com> Closes #2153 from marmbrus/parquetFilters and squashes the following commits: 712731a [Michael Armbrust] Use closure serializer for sending filters. 1e83f80 [Michael Armbrust] Clean udf functions.
* [SPARK-3194][SQL] Add AttributeSet to fix bugs with invalid comparisons of ↵Michael Armbrust2014-08-2627-102/+149
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | AttributeReferences It is common to want to describe sets of attributes that are in various parts of a query plan. However, the semantics of putting `AttributeReference` objects into a standard Scala `Set` result in subtle bugs when references differ cosmetically. For example, with case insensitive resolution it is possible to have two references to the same attribute whose names are not equal. In this PR I introduce a new abstraction, an `AttributeSet`, which performs all comparisons using the globally unique `ExpressionId` instead of case class equality. (There is already a related class, [`AttributeMap`](https://github.com/marmbrus/spark/blob/inMemStats/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/AttributeMap.scala#L32)) This new type of set is used to fix a bug in the optimizer where needed attributes were getting projected away underneath join operators. I also took this opportunity to refactor the expression and query plan base classes. In all but one instance the logic for computing the `references` of an `Expression` were the same. Thus, I moved this logic into the base class. For query plans the semantics of the `references` method were ill defined (is it the references output? or is it those used by expression evaluation? or what?). As a result, this method wasn't really used very much. So, I removed it. TODO: - [x] Finish scala doc for `AttributeSet` - [x] Scan the code for other instances of `Set[Attribute]` and refactor them. - [x] Finish removing `references` from `QueryPlan` Author: Michael Armbrust <michael@databricks.com> Closes #2109 from marmbrus/attributeSets and squashes the following commits: 1c0dae5 [Michael Armbrust] work on serialization bug. 9ba868d [Michael Armbrust] Merge remote-tracking branch 'origin/master' into attributeSets 3ae5288 [Michael Armbrust] review comments 40ce7f6 [Michael Armbrust] style d577cc7 [Michael Armbrust] Scaladoc cae5d22 [Michael Armbrust] remove more references implementations d6e16be [Michael Armbrust] Remove more instances of "def references" and normal sets of attributes. fc26b49 [Michael Armbrust] Add AttributeSet class, remove references from Expression.
* [SPARK-2969][SQL] Make ScalaReflection be able to handle ↵Takuya UESHIN2014-08-263-8/+27
| | | | | | | | | | | | | | | | | | | | | | | ArrayType.containsNull and MapType.valueContainsNull. Make `ScalaReflection` be able to handle like: - `Seq[Int]` as `ArrayType(IntegerType, containsNull = false)` - `Seq[java.lang.Integer]` as `ArrayType(IntegerType, containsNull = true)` - `Map[Int, Long]` as `MapType(IntegerType, LongType, valueContainsNull = false)` - `Map[Int, java.lang.Long]` as `MapType(IntegerType, LongType, valueContainsNull = true)` Author: Takuya UESHIN <ueshin@happy-camper.st> Closes #1889 from ueshin/issues/SPARK-2969 and squashes the following commits: 24f1c5c [Takuya UESHIN] Change the default value of ArrayType.containsNull to true in Python API. 79f5b65 [Takuya UESHIN] Change the default value of ArrayType.containsNull to true in Java API. 7cd1a7a [Takuya UESHIN] Fix json test failures. 2cfb862 [Takuya UESHIN] Change the default value of ArrayType.containsNull to true. 2f38e61 [Takuya UESHIN] Revert the default value of MapTypes.valueContainsNull. 9fa02f5 [Takuya UESHIN] Fix a test failure. 1a9a96b [Takuya UESHIN] Modify ScalaReflection to handle ArrayType.containsNull and MapType.valueContainsNull.
* [SPARK-3058] [SQL] Support EXTENDED for EXPLAINCheng Hao2014-08-251-1/+1
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Provide `extended` keyword support for `explain` command in SQL. e.g. ``` explain extended select key as a1, value as a2 from src where key=1; == Parsed Logical Plan == Project ['key AS a1#3,'value AS a2#4] Filter ('key = 1) UnresolvedRelation None, src, None == Analyzed Logical Plan == Project [key#8 AS a1#3,value#9 AS a2#4] Filter (CAST(key#8, DoubleType) = CAST(1, DoubleType)) MetastoreRelation default, src, None == Optimized Logical Plan == Project [key#8 AS a1#3,value#9 AS a2#4] Filter (CAST(key#8, DoubleType) = 1.0) MetastoreRelation default, src, None == Physical Plan == Project [key#8 AS a1#3,value#9 AS a2#4] Filter (CAST(key#8, DoubleType) = 1.0) HiveTableScan [key#8,value#9], (MetastoreRelation default, src, None), None Code Generation: false == RDD == (2) MappedRDD[14] at map at HiveContext.scala:350 MapPartitionsRDD[13] at mapPartitions at basicOperators.scala:42 MapPartitionsRDD[12] at mapPartitions at basicOperators.scala:57 MapPartitionsRDD[11] at mapPartitions at TableReader.scala:112 MappedRDD[10] at map at TableReader.scala:240 HadoopRDD[9] at HadoopRDD at TableReader.scala:230 ``` It's the sub task of #1847. But can go without any dependency. Author: Cheng Hao <hao.cheng@intel.com> Closes #1962 from chenghao-intel/explain_extended and squashes the following commits: 295db74 [Cheng Hao] Fix bug in printing the simple execution plan 48bc989 [Cheng Hao] Support EXTENDED for EXPLAIN
* [SPARK-3204][SQL] MaxOf would be foldable if both left and right are foldable.Takuya UESHIN2014-08-251-0/+2
| | | | | | | | Author: Takuya UESHIN <ueshin@happy-camper.st> Closes #2116 from ueshin/issues/SPARK-3204 and squashes the following commits: 7d9b107 [Takuya UESHIN] Make MaxOf foldable if both left and right are foldable.
* [SPARK-2554][SQL] CountDistinct partial aggregation and object allocation ↵Michael Armbrust2014-08-2310-15/+1006
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | improvements Author: Michael Armbrust <michael@databricks.com> Author: Gregory Owen <greowen@gmail.com> Closes #1935 from marmbrus/countDistinctPartial and squashes the following commits: 5c7848d [Michael Armbrust] turn off caching in the constructor 8074a80 [Michael Armbrust] fix tests 32d216f [Michael Armbrust] reynolds comments c122cca [Michael Armbrust] Address comments, add tests b2e8ef3 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into countDistinctPartial fae38f4 [Michael Armbrust] Fix style fdca896 [Michael Armbrust] cleanup 93d0f64 [Michael Armbrust] metastore concurrency fix. db44a30 [Michael Armbrust] JIT hax. 3868f6c [Michael Armbrust] Merge pull request #9 from GregOwen/countDistinctPartial c9e67de [Gregory Owen] Made SpecificRow and types serializable by Kryo 2b46c4b [Michael Armbrust] Merge remote-tracking branch 'origin/master' into countDistinctPartial 8ff6402 [Michael Armbrust] Add specific row. 58d15f1 [Michael Armbrust] disable codegen logging 87d101d [Michael Armbrust] Fix isNullAt bug abee26d [Michael Armbrust] WIP 27984d0 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into countDistinctPartial 57ae3b1 [Michael Armbrust] Fix order dependent test b3d0f64 [Michael Armbrust] Add golden files. c1f7114 [Michael Armbrust] Improve tests / fix serialization. f31b8ad [Michael Armbrust] more fixes 38c7449 [Michael Armbrust] comments and style 9153652 [Michael Armbrust] better toString d494598 [Michael Armbrust] Fix tests now that the planner is better 41fbd1d [Michael Armbrust] Never try and create an empty hash set. 050bb97 [Michael Armbrust] Skip no-arg constructors for kryo, bd08239 [Michael Armbrust] WIP 213ada8 [Michael Armbrust] First draft of partially aggregated and code generated count distinct / max
* [SQL] Improve debug logging and toStrings.Michael Armbrust2014-08-172-2/+21
| | | | | | | | Author: Michael Armbrust <michael@databricks.com> Closes #2004 from marmbrus/codgenDebugging and squashes the following commits: b7a7e41 [Michael Armbrust] Improve debug logging and toStrings.
* SPARK-2955 [BUILD] Test code fails to compile with "mvn compile" without ↵Sean Owen2014-08-141-14/+14
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | "install" (This is the corrected follow-up to https://issues.apache.org/jira/browse/SPARK-2903) Right now, `mvn compile test-compile` fails to compile Spark. (Don't worry; `mvn package` works, so this is not major.) The issue stems from test code in some modules depending on test code in other modules. That is perfectly fine and supported by Maven. It takes extra work to get this to work with scalatest, and this has been attempted: https://github.com/apache/spark/blob/master/sql/catalyst/pom.xml#L86 This formulation is not quite enough, since the SQL Core module's tests fail to compile for lack of finding test classes in SQL Catalyst, and likewise for most Streaming integration modules depending on core Streaming test code. Example: ``` [error] /Users/srowen/Documents/spark/sql/core/src/test/scala/org/apache/spark/sql/QueryTest.scala:23: not found: type PlanTest [error] class QueryTest extends PlanTest { [error] ^ [error] /Users/srowen/Documents/spark/sql/core/src/test/scala/org/apache/spark/sql/CachedTableSuite.scala:28: package org.apache.spark.sql.test is not a value [error] test("SPARK-1669: cacheTable should be idempotent") { [error] ^ ... ``` The issue I believe is that generation of a `test-jar` is bound here to the `compile` phase, but the test classes are not being compiled in this phase. It should bind to the `test-compile` phase. It works when executing `mvn package` or `mvn install` since test-jar artifacts are actually generated available through normal Maven mechanisms as each module is built. They are then found normally, regardless of scalatest configuration. It would be nice for a simple `mvn compile test-compile` to work since the test code is perfectly compilable given the Maven declarations. On the plus side, this change is low-risk as it only affects tests. yhuai made the original scalatest change and has glanced at this and thinks it makes sense. Author: Sean Owen <srowen@gmail.com> Closes #1879 from srowen/SPARK-2955 and squashes the following commits: ad8242f [Sean Owen] Generate test-jar on test-compile for modules whose tests are needed by others' tests
* [SPARK-2968][SQL] Fix nullabilities of Explode.Takuya UESHIN2014-08-111-4/+4
| | | | | | | | | | Output nullabilities of `Explode` could be detemined by `ArrayType.containsNull` or `MapType.valueContainsNull`. Author: Takuya UESHIN <ueshin@happy-camper.st> Closes #1888 from ueshin/issues/SPARK-2968 and squashes the following commits: d128c95 [Takuya UESHIN] Fix nullability of Explode.
* [SQL] Fix logging warn -> debugMichael Armbrust2014-08-051-2/+2
| | | | | | | | Author: Michael Armbrust <michael@databricks.com> Closes #1800 from marmbrus/warning and squashes the following commits: 8ea9cf1 [Michael Armbrust] [SQL] Fix logging warn -> debug.
* [SPARK-2866][SQL] Support attributes in ORDER BY that aren't in SELECTMichael Armbrust2014-08-052-7/+66
| | | | | | | | | | | | | Minor refactoring to allow resolution either using a nodes input or output. Author: Michael Armbrust <michael@databricks.com> Closes #1795 from marmbrus/ordering and squashes the following commits: 237f580 [Michael Armbrust] style 74d833b [Michael Armbrust] newline 705d963 [Michael Armbrust] Add a rule for resolving ORDER BY expressions that reference attributes not present in the SELECT clause. 82cabda [Michael Armbrust] Generalize attribute resolution.
* [SPARK-2860][SQL] Fix coercion of CASE WHEN.Michael Armbrust2014-08-051-24/+32
| | | | | | | | | Author: Michael Armbrust <michael@databricks.com> Closes #1785 from marmbrus/caseNull and squashes the following commits: 126006d [Michael Armbrust] better error message 2fe357f [Michael Armbrust] Fix coercion of CASE WHEN.
* [SPARK-2097][SQL] UDF SupportMichael Armbrust2014-08-022-0/+339
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This patch adds the ability to register lambda functions written in Python, Java or Scala as UDFs for use in SQL or HiveQL. Scala: ```scala registerFunction("strLenScala", (_: String).length) sql("SELECT strLenScala('test')") ``` Python: ```python sqlCtx.registerFunction("strLenPython", lambda x: len(x), IntegerType()) sqlCtx.sql("SELECT strLenPython('test')") ``` Java: ```java sqlContext.registerFunction("stringLengthJava", new UDF1<String, Integer>() { Override public Integer call(String str) throws Exception { return str.length(); } }, DataType.IntegerType); sqlContext.sql("SELECT stringLengthJava('test')"); ``` Author: Michael Armbrust <michael@databricks.com> Closes #1063 from marmbrus/udfs and squashes the following commits: 9eda0fe [Michael Armbrust] newline 747c05e [Michael Armbrust] Add some scala UDF tests. d92727d [Michael Armbrust] Merge remote-tracking branch 'apache/master' into udfs 005d684 [Michael Armbrust] Fix naming and formatting. d14dac8 [Michael Armbrust] Fix last line of autogened java files. 8135c48 [Michael Armbrust] Move UDF unit tests to pyspark. 40b0ffd [Michael Armbrust] Merge remote-tracking branch 'apache/master' into udfs 6a36890 [Michael Armbrust] Switch logging so that SQLContext can be serializable. 7a83101 [Michael Armbrust] Drop toString 795fd15 [Michael Armbrust] Try to avoid capturing SQLContext. e54fb45 [Michael Armbrust] Docs and tests. 437cbe3 [Michael Armbrust] Update use of dataTypes, fix some python tests, address review comments. 01517d6 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into udfs 8e6c932 [Michael Armbrust] WIP 3f96a52 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into udfs 6237c8d [Michael Armbrust] WIP 2766f0b [Michael Armbrust] Move udfs support to SQL from hive. Add support for Java UDFs. 0f7d50c [Michael Armbrust] Draft of native Spark SQL UDFs for Scala and Python.
* SPARK-2804: Remove scalalogging-slf4j dependencyGuoQiang Li2014-08-0211-29/+25
| | | | | | | | | | This also Closes #1701. Author: GuoQiang Li <witgo@qq.com> Closes #1208 from witgo/SPARK-1470 and squashes the following commits: 422646b [GuoQiang Li] Remove scalalogging-slf4j dependency
* [SPARK-1812] sql/catalyst - Provide explicit type informationAnand Avati2014-08-021-1/+1
| | | | | | | | | | | | | | | | | | | | | | | | | | | | For Scala 2.11 compatibility. Without the explicit type specification, withNullability return type is inferred to be Attribute, and thus calling at() on the returned object fails in these tests: [ERROR] /Users/avati/work/spark/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala:370: value at is not a [ERROR] val c4_notNull = 'a.boolean.notNull.at(3) [ERROR] ^ [ERROR] /Users/avati/work/spark/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala:371: value at is not a [ERROR] val c5_notNull = 'a.boolean.notNull.at(4) [ERROR] ^ [ERROR] /Users/avati/work/spark/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala:372: value at is not a [ERROR] val c6_notNull = 'a.boolean.notNull.at(5) [ERROR] ^ [ERROR] /Users/avati/work/spark/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/ExpressionEvaluationSuite.scala:558: value at is not a [ERROR] val s_notNull = 'a.string.notNull.at(0) Signed-off-by: Anand Avati <avatiredhat.com> Author: Anand Avati <avati@redhat.com> Closes #1709 from avati/SPARK-1812-notnull and squashes the following commits: 0470eb3 [Anand Avati] SPARK-1812: sql/catalyst - Provide explicit type information
* Revert "[SPARK-1470][SPARK-1842] Use the scala-logging wrapper instead of ↵Patrick Wendell2014-08-0111-25/+29
| | | | | | the directly sfl4j api" This reverts commit adc8303294e26efb4ed15e5f5ba1062f7988625d.
* [SPARK-1470][SPARK-1842] Use the scala-logging wrapper instead of the ↵GuoQiang Li2014-08-0111-29/+25
| | | | | | | | | | | directly sfl4j api Author: GuoQiang Li <witgo@qq.com> Closes #1369 from witgo/SPARK-1470_new and squashes the following commits: 66a1641 [GuoQiang Li] IncompatibleResultTypeProblem 73a89ba [GuoQiang Li] Use the scala-logging wrapper instead of the directly sfl4j api.
* SPARK-2766: ScalaReflectionSuite throw an llegalArgumentException in JDK 6GuoQiang Li2014-07-311-1/+1
| | | | | | | | Author: GuoQiang Li <witgo@qq.com> Closes #1683 from witgo/SPARK-2766 and squashes the following commits: d0db00c [GuoQiang Li] ScalaReflectionSuite throw an llegalArgumentException in JDK 6
generated by cgit v1.2.3 (git 2.39.1) at 2024-08-01 11:10:34 +0000