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* [SPARK-3645][SQL] Makes table caching eager by default and adds syntax for ↵Cheng Lian2014-10-055-74/+137
| | | | | | | | | | | | | | | | 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 Armbrust2014-10-0312-184/+382
| | | | | | | | | | | | | | | | | | | | | | | | | | | 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 errorravipesala2014-10-011-0/+5
| | | | | | | | | | | | | | | | | | | 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
* [SQL] Made Command.sideEffectResult protectedCheng Lian2014-10-011-5/+5
| | | | | | | | | | Considering `Command.executeCollect()` simply delegates to `Command.sideEffectResult`, we no longer need to leave the latter `protected[sql]`. Author: Cheng Lian <lian.cs.zju@gmail.com> Closes #2431 from liancheng/narrow-scope and squashes the following commits: 1bfc16a [Cheng Lian] Made Command.sideEffectResult protected
* [SPARK-3593][SQL] Add support for sorting BinaryTypeVenkata Ramana Gollamudi2014-10-012-0/+18
| | | | | | | | | | | | 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-3748] Log thread name in unit test logsReynold Xin2014-10-011-1/+1
| | | | | | | | | | Thread names are useful for correlating failures. Author: Reynold Xin <rxin@apache.org> Closes #2600 from rxin/log4j and squashes the following commits: 83ffe88 [Reynold Xin] [SPARK-3748] Log thread name in unit test logs
* [SPARK-3543] TaskContext remaining cleanup work.Reynold Xin2014-09-281-2/+2
| | | | | | | | Author: Reynold Xin <rxin@apache.org> Closes #2560 from rxin/TaskContext and squashes the following commits: 9eff95a [Reynold Xin] [SPARK-3543] remaining cleanup work.
* [SPARK-3646][SQL] Copy SQL configuration from SparkConf when a SQLContext is ↵Michael Armbrust2014-09-233-2/+20
| | | | | | | | | | | | created. This will allow us to take advantage of things like the spark.defaults file. Author: Michael Armbrust <michael@databricks.com> Closes #2493 from marmbrus/copySparkConf and squashes the following commits: 0bd1377 [Michael Armbrust] Copy SQL configuration from SparkConf when a SQLContext is created.
* [SPARK-3536][SQL] SELECT on empty parquet table throws exceptionravipesala2014-09-232-2/+14
| | | | | | | | | | | | It returns null metadata from parquet if querying on empty parquet file while calculating splits.So added null check and returns the empty splits. Author : ravipesala ravindra.pesalahuawei.com Author: ravipesala <ravindra.pesala@huawei.com> Closes #2456 from ravipesala/SPARK-3536 and squashes the following commits: 1e81a50 [ravipesala] Fixed the issue when querying on empty parquet file.
* [SPARK-3414][SQL] Replace LowerCaseSchema with ResolverMichael Armbrust2014-09-202-3/+1
| | | | | | | | | | | | | | | | | | | | | | | | | | **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 Lian2014-09-202-5/+24
| | | | | | | | | | | | | | | 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-3605. Fix typo in SchemaRDD.Sandy Ryza2014-09-191-3/+2
| | | | | | | | Author: Sandy Ryza <sandy@cloudera.com> Closes #2460 from sryza/sandy-spark-3605 and squashes the following commits: 09d940b [Sandy Ryza] SPARK-3605. Fix typo in SchemaRDD.
* [SPARK-2594][SQL] Support CACHE TABLE <name> AS SELECT ...ravipesala2014-09-193-0/+33
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 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-2314][SQL] Override collect and take in python library, and count in ↵Aaron Staple2014-09-162-11/+28
| | | | | | | | | | | | | | | | | | java library, with optimized versions. SchemaRDD overrides RDD functions, including collect, count, and take, with optimized versions making use of the query optimizer. The java and python interface classes wrapping SchemaRDD need to ensure the optimized versions are called as well. This patch overrides relevant calls in the python and java interfaces with optimized versions. Adds a new Row serialization pathway between python and java, based on JList[Array[Byte]] versus the existing RDD[Array[Byte]]. I wasn’t overjoyed about doing this, but I noticed that some QueryPlans implement optimizations in executeCollect(), which outputs an Array[Row] rather than the typical RDD[Row] that can be shipped to python using the existing serialization code. To me it made sense to ship the Array[Row] over to python directly instead of converting it back to an RDD[Row] just for the purpose of sending the Rows to python using the existing serialization code. Author: Aaron Staple <aaron.staple@gmail.com> Closes #1592 from staple/SPARK-2314 and squashes the following commits: 89ff550 [Aaron Staple] Merge with master. 6bb7b6c [Aaron Staple] Fix typo. b56d0ac [Aaron Staple] [SPARK-2314][SQL] Override count in JavaSchemaRDD, forwarding to SchemaRDD's count. 0fc9d40 [Aaron Staple] Fix comment typos. f03cdfa [Aaron Staple] [SPARK-2314][SQL] Override collect and take in sql.py, forwarding to SchemaRDD's collect.
* [SPARK-3308][SQL] Ability to read JSON Arrays as tablesYin Huai2014-09-163-3/+31
| | | | | | | | | | | | This PR aims to support reading top level JSON arrays and take every element in such an array as a row (an empty array will not generate a row). JIRA: https://issues.apache.org/jira/browse/SPARK-3308 Author: Yin Huai <huai@cse.ohio-state.edu> Closes #2400 from yhuai/SPARK-3308 and squashes the following commits: 990077a [Yin Huai] Handle top level JSON arrays.
* [SPARK-3527] [SQL] Strip the string messageCheng Hao2014-09-161-1/+1
| | | | | | | | Author: Cheng Hao <hao.cheng@intel.com> Closes #2392 from chenghao-intel/trim and squashes the following commits: e52024f [Cheng Hao] trim the string message
* [SQL] Decrease partitions when testingMichael Armbrust2014-09-132-106/+45
| | | | | | | | | | | | | Author: Michael Armbrust <michael@databricks.com> Closes #2164 from marmbrus/shufflePartitions and squashes the following commits: 0da1e8c [Michael Armbrust] test hax ef2d985 [Michael Armbrust] more test hacks. 2dabae3 [Michael Armbrust] more test fixes 0bdbf21 [Michael Armbrust] Make parquet tests less order dependent b42eeab [Michael Armbrust] increase test parallelism 80453d5 [Michael Armbrust] Decrease partitions when testing
* [SPARK-3294][SQL] Eliminates boxing costs from in-memory columnar storageCheng Lian2014-09-1321-238/+469
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 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-3390][SQL] sqlContext.jsonRDD fails on a complex structure of JSON ↵Yin Huai2014-09-113-29/+96
| | | | | | | | | | | | | | array and JSON object nesting This PR aims to correctly handle JSON arrays in the type of `ArrayType(...(ArrayType(StructType)))`. JIRA: https://issues.apache.org/jira/browse/SPARK-3390. Author: Yin Huai <huai@cse.ohio-state.edu> Closes #2364 from yhuai/SPARK-3390 and squashes the following commits: 46db418 [Yin Huai] Handle JSON arrays in the type of ArrayType(...(ArrayType(StructType))).
* [SPARK-2917] [SQL] Avoid table creation in logical plan analyzing for CTASCheng Hao2014-09-111-2/+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 Staple2014-09-101-4/+41
| | | | | | | | | | | | | | | | | | | | | | | | 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-3447][SQL] Remove explicit conversion with JListWrapper to avoid NPEMichael Armbrust2014-09-101-3/+1
| | | | | | | | | | | Author: Michael Armbrust <michael@databricks.com> Closes #2323 from marmbrus/kryoJListNPE and squashes the following commits: 9634f11 [Michael Armbrust] Rollback JSON RDD changes 4d4d93c [Michael Armbrust] Merge remote-tracking branch 'origin/master' into kryoJListNPE 646976b [Michael Armbrust] Fix JSON RDD Conversion too 59065bc [Michael Armbrust] Remove explicit conversion to avoid NPE
* [SPARK-2096][SQL] Correctly parse dot notationsWenchen Fan2014-09-103-78/+64
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 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 Wang2014-09-101-29/+22
| | | | | | | | | | | | | | | 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-3395] [SQL] DSL sometimes incorrectly reuses attribute ids, breaking ↵Eric Liang2014-09-092-1/+16
| | | | | | | | | | | | | queries This resolves https://issues.apache.org/jira/browse/SPARK-3395 Author: Eric Liang <ekl@google.com> Closes #2266 from ericl/spark-3395 and squashes the following commits: 7f2b6f0 [Eric Liang] add regression test 05bd1e4 [Eric Liang] in the dsl, create a new schema instance in each applySchema
* [SPARK-3448][SQL] Check for null in SpecificMutableRow.updateCheng Lian2014-09-091-1/+7
| | | | | | | | | | | | `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 sqlxinyunh2014-09-091-2/+21
| | | | | | | | | | | | | | | | 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-3455] [SQL] **HOT FIX** Fix the unit test failureCheng Hao2014-09-091-0/+2
| | | | | | | | | | Unit test failed due to can not resolve the attribute references. Temporally disable this test case for a quick fixing, otherwise it will block the others. Author: Cheng Hao <hao.cheng@intel.com> Closes #2334 from chenghao-intel/unit_test_failure and squashes the following commits: 661f784 [Cheng Hao] temporally disable the failed test case
* [SPARK-3414][SQL] Stores analyzed logical plan when registering a temp tableCheng Lian2014-09-081-2/+2
| | | | | | | | | | Case insensitivity breaks when unresolved relation contains attributes with uppercase letters in their names, because we store unanalyzed logical plan when registering temp tables while the `CaseInsensitivityAttributeReferences` batch runs before the `Resolution` batch. To fix this issue, we need to store analyzed logical plan. Author: Cheng Lian <lian.cs.zju@gmail.com> Closes #2293 from liancheng/spark-3414 and squashes the following commits: d9fa1d6 [Cheng Lian] Stores analyzed logical plan when registering a temp table
* SPARK-3423: [SQL] Implement BETWEEN for SQLParserWilliam Benton2014-09-081-0/+18
| | | | | | | | | | 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-3349][SQL] Output partitioning of limit should not be inherited from ↵Eric Liang2014-09-082-1/+20
| | | | | | | | | | | | | child This resolves https://issues.apache.org/jira/browse/SPARK-3349 Author: Eric Liang <ekl@google.com> Closes #2262 from ericl/spark-3349 and squashes the following commits: 3e1b05c [Eric Liang] add regression test ac32723 [Eric Liang] make limit/takeOrdered output SinglePartition
* [SPARK-3408] Fixed Limit operator so it works with sort-based shuffle.Reynold Xin2014-09-071-5/+14
| | | | | | | | Author: Reynold Xin <rxin@apache.org> Closes #2281 from rxin/sql-limit-sort and squashes the following commits: 1ef7780 [Reynold Xin] [SPARK-3408] Fixed Limit operator so it works with sort-based shuffle.
* [SQL] Update SQL Programming GuideMichael Armbrust2014-09-075-5/+5
| | | | | | | | | | | | | | | | | Author: Michael Armbrust <michael@databricks.com> Author: Yin Huai <huai@cse.ohio-state.edu> Closes #2258 from marmbrus/sqlDocUpdate and squashes the following commits: f3d450b [Michael Armbrust] fix brackets bea3bfa [Michael Armbrust] Davies suggestions 3a29fe2 [Michael Armbrust] tighten visibility a71aa36 [Michael Armbrust] Draft of doc updates 52932c0 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into sqlDocUpdate 1e8c849 [Yin Huai] Update the example used for applySchema. 9457c39 [Yin Huai] Update doc. 31ba240 [Yin Huai] Merge remote-tracking branch 'upstream/master' into dataTypeDoc 29bc668 [Yin Huai] Draft doc for data type and schema APIs.
* [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-3409][SQL] Avoid pulling in Exchange operator itself in Exchange's ↵Reynold Xin2014-09-061-22/+21
| | | | | | | | | | | | closures. This is a tiny teeny optimization to move the if check of sortBasedShuffledOn to outside the closures so the closures don't need to pull in the entire Exchange operator object. Author: Reynold Xin <rxin@apache.org> Closes #2282 from rxin/SPARK-3409 and squashes the following commits: 1de3f88 [Reynold Xin] [SPARK-3409][SQL] Avoid pulling in Exchange operator itself in Exchange's closures.
* [SPARK-3392] [SQL] Show value spark.sql.shuffle.partitions for ↵Cheng Hao2014-09-041-4/+12
| | | | | | | | | | | | | mapred.reduce.tasks This is a tiny fix for getting the value of "mapred.reduce.tasks", which make more sense for the hive user. As well as the command "set -v", which should output verbose information for all of the key/values. Author: Cheng Hao <hao.cheng@intel.com> Closes #2261 from chenghao-intel/set_mapreduce_tasks and squashes the following commits: 653858a [Cheng Hao] show value spark.sql.shuffle.partitions for mapred.reduce.tasks
* [SPARK-3310][SQL] Directly use currentTable without unnecessary implicit ↵Liang-Chi Hsieh2014-09-041-1/+1
| | | | | | | | | | | | | conversion We can directly use currentTable there without unnecessary implicit conversion. Author: Liang-Chi Hsieh <viirya@gmail.com> Closes #2203 from viirya/direct_use_inmemoryrelation and squashes the following commits: 4741d02 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into direct_use_inmemoryrelation b671f67 [Liang-Chi Hsieh] Can directly use currentTable there without unnecessary implicit conversion.
* [SPARK-3378] [DOCS] Replace the word "SparkSQL" with right word "Spark SQL"Kousuke Saruta2014-09-041-1/+1
| | | | | | | | | | Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp> Closes #2251 from sarutak/SPARK-3378 and squashes the following commits: 0bfe234 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-3378 bb5938f [Kousuke Saruta] Replaced rest of "SparkSQL" with "Spark SQL" 6df66de [Kousuke Saruta] Replaced "SparkSQL" with "Spark SQL"
* [SPARK-3335] [SQL] [PySpark] support broadcast in Python UDFDavies Liu2014-09-032-1/+5
| | | | | | | | | | After this patch, broadcast can be used in Python UDF. Author: Davies Liu <davies.liu@gmail.com> Closes #2243 from davies/udf_broadcast and squashes the following commits: 7b88861 [Davies Liu] support broadcast in UDF
* [SPARK-2961][SQL] Use statistics to prune batches within cached partitionsCheng Lian2014-09-0314-352/+387
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | 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-2973][SQL] Lightweight SQL commands without distributed jobs when ↵Cheng Lian2014-09-031-40/+23
| | | | | | | | | | | | | | | | | | | calling .collect() By overriding `executeCollect()` in physical plan classes of all commands, we can avoid to kick off a distributed job when collecting result of a SQL command, e.g. `sql("SET").collect()`. Previously, `Command.sideEffectResult` returns a `Seq[Any]`, and the `execute()` method in sub-classes of `Command` typically convert that to a `Seq[Row]` then parallelize it to an RDD. Now with this PR, `sideEffectResult` is required to return a `Seq[Row]` directly, so that `executeCollect()` can directly leverage that and be factored to the `Command` parent class. Author: Cheng Lian <lian.cs.zju@gmail.com> Closes #2215 from liancheng/lightweight-commands and squashes the following commits: 3fbef60 [Cheng Lian] Factored execute() method of physical commands to parent class Command 5a0e16c [Cheng Lian] Passes test suites e0e12e9 [Cheng Lian] Refactored Command.sideEffectResult and Command.executeCollect 995bdd8 [Cheng Lian] Cleaned up DescribeHiveTableCommand 542977c [Cheng Lian] Avoids confusion between logical and physical plan by adding package prefixes 55b2aa5 [Cheng Lian] Avoids distributed jobs when execution SQL commands
* [SPARK-3300][SQL] No need to call clear() and shorten build()Liang-Chi Hsieh2014-09-021-3/+1
| | | | | | | | | | | The function `ensureFreeSpace` in object `ColumnBuilder` clears old buffer before copying its content to new buffer. This PR fixes it. Author: Liang-Chi Hsieh <viirya@gmail.com> Closes #2195 from viirya/fix_buffer_clear and squashes the following commits: 792f009 [Liang-Chi Hsieh] no need to call clear(). use flip() instead of calling limit(), position() and rewind(). df2169f [Liang-Chi Hsieh] should clean old buffer after copying its content.
* [SQL] Renamed ColumnStat to ColumnMetrics to avoid confusion between ColumnStatsCheng Lian2014-09-021-5/+5
| | | | | | | | | | Class names of these two are just too similar. Author: Cheng Lian <lian.cs.zju@gmail.com> Closes #2189 from liancheng/column-metrics and squashes the following commits: 8bb3b21 [Cheng Lian] Renamed ColumnStat to ColumnMetrics to avoid confusion between ColumnStats
* [SPARK-3010] fix redundant conditionalscwf2014-08-311-3/+1
| | | | | | | | | | | | | | | | | | | | | | | | https://issues.apache.org/jira/browse/SPARK-3010 this pr is to fix redundant conditional in spark, such as 1. private[spark] def codegenEnabled: Boolean = if (getConf(CODEGEN_ENABLED, "false") == "true") true else false 2. x => if (x == 2) true else false ... Author: scwf <wangfei1@huawei.com> Author: wangfei <wangfei_hello@126.com> Closes #1992 from scwf/condition and squashes the following commits: b2a044a [scwf] merge SecurityManager e16239c [scwf] fix confilct 6811401 [scwf] fix merge confilct 0824df4 [scwf] Merge branch 'master' of https://github.com/apache/spark into patch-4 e274515 [scwf] fix redundant conditions d032bf9 [wangfei] [SQL]Excess judgment
* [SPARK-3320][SQL] Made batched in-memory column buffer building work for ↵Cheng Lian2014-08-293-34/+39
| | | | | | | | | | | SchemaRDDs with empty partitions Author: Cheng Lian <lian.cs.zju@gmail.com> Closes #2213 from liancheng/spark-3320 and squashes the following commits: 45a0139 [Cheng Lian] Fixed typo in InMemoryColumnarQuerySuite f67067d [Cheng Lian] Fixed SPARK-3320
* [SPARK-3173][SQL] Timestamp support in the parserZdenek Farana2014-08-291-1/+42
| | | | | | | | | | | | | | | | | | | | | | | 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 Hao2014-08-293-8/+11
| | | | | | | | | | | | 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 Benton2014-08-291-0/+14
| | | | | | | | | | | | | | | 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 Armbrust2014-08-282-9/+14
| | | | | | | | | | | | 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
* [SQL] Fixed 2 comment typos in SQLConfCheng Lian2014-08-281-3/+4
| | | | | | | | Author: Cheng Lian <lian.cs.zju@gmail.com> Closes #2172 from liancheng/sqlconf-typo and squashes the following commits: 115cc71 [Cheng Lian] Fixed 2 comment typos in SQLConf
generated by cgit v1.2.3 (git 2.39.1) at 2024-08-01 07:09:21 +0000