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* [SPARK-12881] [SQL] subexpress elimination in mutable projectionDavies Liu2016-01-2011-27/+80
| | | | | | Author: Davies Liu <davies@databricks.com> Closes #10814 from davies/mutable_subexpr.
* [SPARK-12912][SQL] Add a test suite for EliminateSubQueriesReynold Xin2016-01-204-26/+103
| | | | | | | | Also updated documentation to explain why ComputeCurrentTime and EliminateSubQueries are in the optimizer rather than analyzer. Author: Reynold Xin <rxin@databricks.com> Closes #10837 from rxin/optimizer-analyzer-comment.
* [SPARK-12871][SQL] Support to specify the option for compression codec.hyukjinkwon2016-01-193-2/+70
| | | | | | | | | | | | https://issues.apache.org/jira/browse/SPARK-12871 This PR added an option to support to specify compression codec. This adds the option `codec` as an alias `compression` as filed in [SPARK-12668 ](https://issues.apache.org/jira/browse/SPARK-12668). Note that I did not add configurations for Hadoop 1.x as this `CsvRelation` is using Hadoop 2.x API and I guess it is going to drop Hadoop 1.x support. Author: hyukjinkwon <gurwls223@gmail.com> Closes #10805 from HyukjinKwon/SPARK-12420.
* [SPARK-12770][SQL] Implement rules for branch elimination for CaseWhenReynold Xin2016-01-192-0/+55
| | | | | | | | | | | | The three optimization cases are: 1. If the first branch's condition is a true literal, remove the CaseWhen and use the value from that branch. 2. If a branch's condition is a false or null literal, remove that branch. 3. If only the else branch is left, remove the CaseWhen and use the value from the else branch. Author: Reynold Xin <rxin@databricks.com> Closes #10827 from rxin/SPARK-12770.
* [SPARK-12816][SQL] De-alias type when generating schemasJakob Odersky2016-01-192-1/+12
| | | | | | | | | | | | | | Call `dealias` on local types to fix schema generation for abstract type members, such as ```scala type KeyValue = (Int, String) ``` Add simple test Author: Jakob Odersky <jodersky@gmail.com> Closes #10749 from jodersky/aliased-schema.
* [SPARK-12560][SQL] SqlTestUtils.stripSparkFilter needs to copy utf8stringsImran Rashid2016-01-191-1/+1
| | | | | | | | | | See https://issues.apache.org/jira/browse/SPARK-12560 This isn't causing any problems currently because the tests for string predicate pushdown are currently disabled. I ran into this while trying to turn them back on with a different version of parquet. Figure it was good to fix now in any case. Author: Imran Rashid <irashid@cloudera.com> Closes #10510 from squito/SPARK-12560.
* [SPARK-12867][SQL] Nullability of Intersect can be strictergatorsmile2016-01-192-6/+33
| | | | | | | | | | | | JIRA: https://issues.apache.org/jira/browse/SPARK-12867 When intersecting one nullable column with one non-nullable column, the result will not contain any null. Thus, we can make nullability of `intersect` stricter. liancheng Could you please check if the code changes are appropriate? Also added test cases to verify the results. Thanks! Author: gatorsmile <gatorsmile@gmail.com> Closes #10812 from gatorsmile/nullabilityIntersect.
* [SPARK-12887] Do not expose var's in TaskMetricsAndrew Or2016-01-192-3/+1
| | | | | | | | | | | | | | | | This is a step in implementing SPARK-10620, which migrates TaskMetrics to accumulators. TaskMetrics has a bunch of var's, some are fully public, some are `private[spark]`. This is bad coding style that makes it easy to accidentally overwrite previously set metrics. This has happened a few times in the past and caused bugs that were difficult to debug. Instead, we should have get-or-create semantics, which are more readily understandable. This makes sense in the case of TaskMetrics because these are just aggregated metrics that we want to collect throughout the task, so it doesn't matter who's incrementing them. Parent PR: #10717 Author: Andrew Or <andrew@databricks.com> Author: Josh Rosen <joshrosen@databricks.com> Author: andrewor14 <andrew@databricks.com> Closes #10815 from andrewor14/get-or-create-metrics.
* [SPARK-12870][SQL] better format bucket id in file nameWenchen Fan2016-01-194-7/+13
| | | | | | | | for normal parquet file without bucket, it's file name ends with a jobUUID which maybe all numbers and mistakeny regarded as bucket id. This PR improves the format of bucket id in file name by using a different seperator, `_`, so that the regex is more robust. Author: Wenchen Fan <wenchen@databricks.com> Closes #10799 from cloud-fan/fix-bucket.
* [SQL][MINOR] Fix one little mismatched comment according to the codes in ↵proflin2016-01-191-1/+1
| | | | | | | | interface.scala Author: proflin <proflin.me@gmail.com> Closes #10824 from proflin/master.
* [SPARK-12668][SQL] Providing aliases for CSV options to be similar to Pandas ↵hyukjinkwon2016-01-183-6/+20
| | | | | | | | | | | | | | | and R https://issues.apache.org/jira/browse/SPARK-12668 Spark CSV datasource has been being merged (filed in [SPARK-12420](https://issues.apache.org/jira/browse/SPARK-12420)). This is a quicky PR that simply renames several CSV options to similar Pandas and R. - Alias for delimiter ­-> sep - charset -­> encoding Author: hyukjinkwon <gurwls223@gmail.com> Closes #10800 from HyukjinKwon/SPARK-12668.
* [HOT][BUILD] Changed the import ordergatorsmile2016-01-182-2/+2
| | | | | | | | | | | | | This PR is to fix the master's build break. The following tests failed due to the import order issues in the master. https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/49651/consoleFull https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/49652/consoleFull https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/49653/consoleFull Author: gatorsmile <gatorsmile@gmail.com> Closes #10823 from gatorsmile/importOrder.
* [SPARK-12700] [SQL] embed condition into SMJ and BroadcastHashJoinDavies Liu2016-01-186-72/+96
| | | | | | | | | | | | Currently SortMergeJoin and BroadcastHashJoin do not support condition, the need a followed Filter for that, the result projection to generate UnsafeRow could be very expensive if they generate lots of rows and could be filtered mostly by condition. This PR brings the support of condition for SortMergeJoin and BroadcastHashJoin, just like other outer joins do. This could improve the performance of Q72 by 7x (from 120s to 16.5s). Author: Davies Liu <davies@databricks.com> Closes #10653 from davies/filter_join.
* [SPARK-12889][SQL] Rename ParserDialect -> ParserInterface.Reynold Xin2016-01-187-10/+10
| | | | | | | | Based on discussions in #10801, I'm submitting a pull request to rename ParserDialect to ParserInterface. Author: Reynold Xin <rxin@databricks.com> Closes #10817 from rxin/SPARK-12889.
* [SPARK-12882][SQL] simplify bucket tests and add more commentsWenchen Fan2016-01-182-46/+78
| | | | | | | | Right now, the bucket tests are kind of hard to understand, this PR simplifies them and add more commetns. Author: Wenchen Fan <wenchen@databricks.com> Closes #10813 from cloud-fan/bucket-comment.
* [SPARK-12841][SQL] fix cast in filterWenchen Fan2016-01-183-8/+18
| | | | | | | | In SPARK-10743 we wrap cast with `UnresolvedAlias` to give `Cast` a better alias if possible. However, for cases like `filter`, the `UnresolvedAlias` can't be resolved and actually we don't need a better alias for this case. This PR move the cast wrapping logic to `Column.named` so that we will only do it when we need a alias name. Author: Wenchen Fan <wenchen@databricks.com> Closes #10781 from cloud-fan/bug.
* [SPARK-12855][SQL] Remove parser dialect developer APIReynold Xin2016-01-1812-138/+13
| | | | | | | | This pull request removes the public developer parser API for external parsers. Given everything a parser depends on (e.g. logical plans and expressions) are internal and not stable, external parsers will break with every release of Spark. It is a bad idea to create the illusion that Spark actually supports pluggable parsers. In addition, this also reduces incentives for 3rd party projects to contribute parse improvements back to Spark. Author: Reynold Xin <rxin@databricks.com> Closes #10801 from rxin/SPARK-12855.
* [SPARK-12873][SQL] Add more comment in HiveTypeCoercion for type wideningReynold Xin2016-01-182-40/+49
| | | | | | | | | | I was reading this part of the analyzer code again and got confused by the difference between findWiderTypeForTwo and findTightestCommonTypeOfTwo. I also simplified WidenSetOperationTypes to make it a lot simpler. The easiest way to review this one is to just read the original code, and the new code. The logic is super simple. Author: Reynold Xin <rxin@databricks.com> Closes #10802 from rxin/SPARK-12873.
* [SPARK-12558][FOLLOW-UP] AnalysisException when multiple functions applied ↵Dilip Biswal2016-01-181-5/+9
| | | | | | | | | | | in GROUP BY clause Addresses the comments from Yin. https://github.com/apache/spark/pull/10520 Author: Dilip Biswal <dbiswal@us.ibm.com> Closes #10758 from dilipbiswal/spark-12558-followup.
* [SPARK-12860] [SQL] speed up safe projection for primitive typesWenchen Fan2016-01-171-2/+3
| | | | | | | | | | The idea is simple, use `SpecificMutableRow` instead of `GenericMutableRow` as result row for safe projection. A simple benchmark shows about 1.5x speed up for primitive types, code: https://gist.github.com/cloud-fan/fa77713ccebf0823b2ab#file-safeprojectionbenchmark-scala Author: Wenchen Fan <wenchen@databricks.com> Closes #10790 from cloud-fan/safe-projection.
* [SPARK-12796] [SQL] Whole stage codegenDavies Liu2016-01-1637-107/+694
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This is the initial work for whole stage codegen, it support Projection/Filter/Range, we will continue work on this to support more physical operators. A micro benchmark show that a query with range, filter and projection could be 3X faster then before. It's turned on by default. For a tree that have at least two chained plans, a WholeStageCodegen will be inserted into it, for example, the following plan ``` Limit 10 +- Project [(id#5L + 1) AS (id + 1)#6L] +- Filter ((id#5L & 1) = 1) +- Range 0, 1, 4, 10, [id#5L] ``` will be translated into ``` Limit 10 +- WholeStageCodegen +- Project [(id#1L + 1) AS (id + 1)#2L] +- Filter ((id#1L & 1) = 1) +- Range 0, 1, 4, 10, [id#1L] ``` Here is the call graph to generate Java source for A and B (A support codegen, but B does not): ``` * WholeStageCodegen Plan A FakeInput Plan B * ========================================================================= * * -> execute() * | * doExecute() --------> produce() * | * doProduce() -------> produce() * | * doProduce() ---> execute() * | * consume() * doConsume() ------------| * | * doConsume() <----- consume() ``` A SparkPlan that support codegen need to implement doProduce() and doConsume(): ``` def doProduce(ctx: CodegenContext): (RDD[InternalRow], String) def doConsume(ctx: CodegenContext, child: SparkPlan, input: Seq[ExprCode]): String ``` Author: Davies Liu <davies@databricks.com> Closes #10735 from davies/whole2.
* [SPARK-12856] [SQL] speed up hashCode of unsafe arrayWenchen Fan2016-01-161-5/+2
| | | | | | | | | | We iterate the bytes to calculate hashCode before, but now we have `Murmur3_x86_32.hashUnsafeBytes` that don't require the bytes to be word algned, we should use that instead. A simple benchmark shows it's about 3 X faster, benchmark code: https://gist.github.com/cloud-fan/fa77713ccebf0823b2ab#file-arrayhashbenchmark-scala Author: Wenchen Fan <wenchen@databricks.com> Closes #10784 from cloud-fan/array-hashcode.
* [SPARK-12840] [SQL] Support passing arbitrary objects (not just expressions) ↵Davies Liu2016-01-1511-49/+48
| | | | | | | | | | into code generated classes This is a refactor to support codegen for aggregation and broadcast join. Author: Davies Liu <davies@databricks.com> Closes #10777 from davies/rename2.
* [SPARK-12644][SQL] Update parquet reader to be vectorized.Nong Li2016-01-1511-53/+622
| | | | | | | | | | | | | | | | | This inlines a few of the Parquet decoders and adds vectorized APIs to support decoding in batch. There are a few particulars in the Parquet encodings that make this much more efficient. In particular, RLE encodings are very well suited for batch decoding. The Parquet 2.0 encodings are also very suited for this. This is a work in progress and does not affect the current execution. In subsequent patches, we will support more encodings and types before enabling this. Simple benchmarks indicate this can decode single ints about > 3x faster. Author: Nong Li <nong@databricks.com> Author: Nong <nongli@gmail.com> Closes #10593 from nongli/spark-12644.
* [SPARK-12649][SQL] support reading bucketed tableWenchen Fan2016-01-1518-45/+314
| | | | | | | | | | | | | | | This PR adds the support to read bucketed tables, and correctly populate `outputPartitioning`, so that we can avoid shuffle for some cases. TODO(follow-up PRs): * bucket pruning * avoid shuffle for bucketed table join when use any super-set of the bucketing key. (we should re-visit it after https://issues.apache.org/jira/browse/SPARK-12704 is fixed) * recognize hive bucketed table Author: Wenchen Fan <wenchen@databricks.com> Closes #10604 from cloud-fan/bucket-read.
* [SPARK-12833][HOT-FIX] Reset the locale after we set it.Yin Huai2016-01-151-4/+9
| | | | | | Author: Yin Huai <yhuai@databricks.com> Closes #10778 from yhuai/resetLocale.
* [SPARK-12575][SQL] Grammar parity with existing SQL parserHerman van Hovell2016-01-1531-970/+271
| | | | | | | | | | | | | | | | In this PR the new CatalystQl parser stack reaches grammar parity with the old Parser-Combinator based SQL Parser. This PR also replaces all uses of the old Parser, and removes it from the code base. Although the existing Hive and SQL parser dialects were mostly the same, some kinks had to be worked out: - The SQL Parser allowed syntax like ```APPROXIMATE(0.01) COUNT(DISTINCT a)```. In order to make this work we needed to hardcode approximate operators in the parser, or we would have to create an approximate expression. ```APPROXIMATE_COUNT_DISTINCT(a, 0.01)``` would also do the job and is much easier to maintain. So, this PR **removes** this keyword. - The old SQL Parser supports ```LIMIT``` clauses in nested queries. This is **not supported** anymore. See https://github.com/apache/spark/pull/10689 for the rationale for this. - Hive has a charset name char set literal combination it supports, for instance the following expression ```_ISO-8859-1 0x4341464562616265``` would yield this string: ```CAFEbabe```. Hive will only allow charset names to start with an underscore. This is quite annoying in spark because as soon as you use a tuple names will start with an underscore. In this PR we **remove** this feature from the parser. It would be quite easy to implement such a feature as an Expression later on. - Hive and the SQL Parser treat decimal literals differently. Hive will turn any decimal into a ```Double``` whereas the SQL Parser would convert a non-scientific decimal into a ```BigDecimal```, and would turn a scientific decimal into a Double. We follow Hive's behavior here. The new parser supports a big decimal literal, for instance: ```81923801.42BD```, which can be used when a big decimal is needed. cc rxin viirya marmbrus yhuai cloud-fan Author: Herman van Hovell <hvanhovell@questtec.nl> Closes #10745 from hvanhovell/SPARK-12575-2.
* [SQL][MINOR] BoundReference do not need to be NamedExpressionWenchen Fan2016-01-151-11/+1
| | | | | | | | We made it a `NamedExpression` to workaroud some hacky cases long time ago, and now seems it's safe to remove it. Author: Wenchen Fan <wenchen@databricks.com> Closes #10765 from cloud-fan/minor.
* Fix typoJulien Baley2016-01-151-3/+3
| | | | | | | | disvoered => discovered Author: Julien Baley <julien.baley@gmail.com> Closes #10773 from julienbaley/patch-1.
* [SPARK-12833][HOT-FIX] Fix scala 2.11 compilation.Yin Huai2016-01-151-3/+3
| | | | | | | | Seems https://github.com/apache/spark/commit/5f83c6991c95616ecbc2878f8860c69b2826f56c breaks scala 2.11 compilation. Author: Yin Huai <yhuai@databricks.com> Closes #10774 from yhuai/fixScala211Compile.
* [SPARK-12833][SQL] Initial import of spark-csvHossein2016-01-1521-7/+1610
| | | | | | | | | | | CSV is the most common data format in the "small data" world. It is often the first format people want to try when they see Spark on a single node. Having to rely on a 3rd party component for this leads to poor user experience for new users. This PR merges the popular spark-csv data source package (https://github.com/databricks/spark-csv) with SparkSQL. This is a first PR to bring the functionality to spark 2.0 master. We will complete items outlines in the design document (see JIRA attachment) in follow up pull requests. Author: Hossein <hossein@databricks.com> Author: Reynold Xin <rxin@databricks.com> Closes #10766 from rxin/csv.
* [MINOR] [SQL] GeneratedExpressionCode -> ExprCodeDavies Liu2016-01-1532-249/+249
| | | | | | | | GeneratedExpressionCode is too long Author: Davies Liu <davies@databricks.com> Closes #10767 from davies/renaming.
* [SPARK-12830] Java style: disallow trailing whitespaces.Reynold Xin2016-01-141-1/+1
| | | | | | Author: Reynold Xin <rxin@databricks.com> Closes #10764 from rxin/SPARK-12830.
* [SPARK-12813][SQL] Eliminate serialization for back to back operationsMichael Armbrust2016-01-1417-274/+518
| | | | | | | | | | | | | | | The goal of this PR is to eliminate unnecessary translations when there are back-to-back `MapPartitions` operations. In order to achieve this I also made the following simplifications: - Operators no longer have hold encoders, instead they have only the expressions that they need. The benefits here are twofold: the expressions are visible to transformations so go through the normal resolution/binding process. now that they are visible we can change them on a case by case basis. - Operators no longer have type parameters. Since the engine is responsible for its own type checking, having the types visible to the complier was an unnecessary complication. We still leverage the scala compiler in the companion factory when constructing a new operator, but after this the types are discarded. Deferred to a follow up PR: - Remove as much of the resolution/binding from Dataset/GroupedDataset as possible. We should still eagerly check resolution and throw an error though in the case of mismatches for an `as` operation. - Eliminate serializations in more cases by adding more cases to `EliminateSerialization` Author: Michael Armbrust <michael@databricks.com> Closes #10747 from marmbrus/encoderExpressions.
* [SPARK-12771][SQL] Simplify CaseWhen code generationReynold Xin2016-01-141-25/+35
| | | | | | | | | | The generated code for CaseWhen uses a control variable "got" to make sure we do not evaluate more branches once a branch is true. Changing that to generate just simple "if / else" would be slightly more efficient. This closes #10737. Author: Reynold Xin <rxin@databricks.com> Closes #10755 from rxin/SPARK-12771.
* [SPARK-12756][SQL] use hash expression in ExchangeWenchen Fan2016-01-139-47/+67
| | | | | | | | | | This PR makes bucketing and exchange share one common hash algorithm, so that we can guarantee the data distribution is same between shuffle and bucketed data source, which enables us to only shuffle one side when join a bucketed table and a normal one. This PR also fixes the tests that are broken by the new hash behaviour in shuffle. Author: Wenchen Fan <wenchen@databricks.com> Closes #10703 from cloud-fan/use-hash-expr-in-shuffle.
* [SPARK-12791][SQL] Simplify CaseWhen by breaking "branches" into ↵Reynold Xin2016-01-1311-126/+144
| | | | | | | | | | | | "conditions" and "values" This pull request rewrites CaseWhen expression to break the single, monolithic "branches" field into a sequence of tuples (Seq[(condition, value)]) and an explicit optional elseValue field. Prior to this pull request, each even position in "branches" represents the condition for each branch, and each odd position represents the value for each branch. The use of them have been pretty confusing with a lot sliding windows or grouped(2) calls. Author: Reynold Xin <rxin@databricks.com> Closes #10734 from rxin/simplify-case.
* [SPARK-12642][SQL] improve the hash expression to be decoupled from unsafe rowWenchen Fan2016-01-134-27/+260
| | | | | | | | https://issues.apache.org/jira/browse/SPARK-12642 Author: Wenchen Fan <wenchen@databricks.com> Closes #10694 from cloud-fan/hash-expr.
* [SPARK-9297] [SQL] Add covar_pop and covar_sampLiang-Chi Hsieh2016-01-134-0/+272
| | | | | | | | | | | JIRA: https://issues.apache.org/jira/browse/SPARK-9297 Add two aggregation functions: covar_pop and covar_samp. Author: Liang-Chi Hsieh <viirya@gmail.com> Author: Liang-Chi Hsieh <viirya@appier.com> Closes #10029 from viirya/covar-funcs.
* [SPARK-12692][BUILD][SQL] Scala style: Fix the style violation (Space before ↵Kousuke Saruta2016-01-1210-22/+22
| | | | | | | | | | | ",") Fix the style violation (space before , and :). This PR is a followup for #10643 and rework of #10685 . Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp> Closes #10732 from sarutak/SPARK-12692-followup-sql.
* [SPARK-12558][SQL] AnalysisException when multiple functions applied in ↵Dilip Biswal2016-01-122-0/+30
| | | | | | | | | | | | GROUP BY clause cloud-fan Can you please take a look ? In this case, we are failing during check analysis while validating the aggregation expression. I have added a semanticEquals for HiveGenericUDF to fix this. Please let me know if this is the right way to address this issue. Author: Dilip Biswal <dbiswal@us.ibm.com> Closes #10520 from dilipbiswal/spark-12558.
* [SPARK-12788][SQL] Simplify BooleanEquality by using casts.Reynold Xin2016-01-122-26/+32
| | | | | | Author: Reynold Xin <rxin@databricks.com> Closes #10730 from rxin/SPARK-12788.
* [SPARK-12785][SQL] Add ColumnarBatch, an in memory columnar format for ↵Nong Li2016-01-126-0/+1463
| | | | | | | | | | | | | | | | | | | | | | | | | execution. There are many potential benefits of having an efficient in memory columnar format as an alternate to UnsafeRow. This patch introduces ColumnarBatch/ColumnarVector which starts this effort. The remaining implementation can be done as follow up patches. As stated in the in the JIRA, there are useful external components that operate on memory in a simple columnar format. ColumnarBatch would serve that purpose and could server as a zero-serialization/zero-copy exchange for this use case. This patch supports running the underlying data either on heap or off heap. On heap runs a bit faster but we would need offheap for zero-copy exchanges. Currently, this mode is hidden behind one interface (ColumnVector). This differs from Parquet or the existing columnar cache because this is *not* intended to be used as a storage format. The focus is entirely on CPU efficiency as we expect to only have 1 of these batches in memory per task. The layout of the values is just dense arrays of the value type. Author: Nong Li <nong@databricks.com> Author: Nong <nongli@gmail.com> Closes #10628 from nongli/spark-12635.
* [SPARK-12724] SQL generation support for persisted data source tablesCheng Lian2016-01-1217-51/+55
| | | | | | | | This PR implements SQL generation support for persisted data source tables. A new field `metastoreTableIdentifier: Option[TableIdentifier]` is added to `LogicalRelation`. When a `LogicalRelation` representing a persisted data source relation is created, this field holds the database name and table name of the relation. Author: Cheng Lian <lian@databricks.com> Closes #10712 from liancheng/spark-12724-datasources-sql-gen.
* Revert "[SPARK-12692][BUILD][SQL] Scala style: Fix the style violation ↵Reynold Xin2016-01-1253-149/+140
| | | | | | (Space before "," or ":")" This reverts commit 8cfa218f4f1b05f4d076ec15dd0a033ad3e4500d.
* [SPARK-12768][SQL] Remove CaseKeyWhen expressionReynold Xin2016-01-123-171/+38
| | | | | | | | | | This patch removes CaseKeyWhen expression and replaces it with a factory method that generates the equivalent CaseWhen. This reduces the amount of code we'd need to maintain in the future for both code generation and optimizer. Note that we introduced CaseKeyWhen to avoid duplicate evaluations of the key. This is no longer a problem because we now have common subexpression elimination. Author: Reynold Xin <rxin@databricks.com> Closes #10722 from rxin/SPARK-12768.
* [SPARK-9843][SQL] Make catalyst optimizer pass pluggable at runtimeRobert Kruszewski2016-01-124-2/+46
| | | | | | | | Let me know whether you'd like to see it in other place Author: Robert Kruszewski <robertk@palantir.com> Closes #10210 from robert3005/feature/pluggable-optimizer.
* [SPARK-12762][SQL] Add unit test for SimplifyConditionals optimization ruleReynold Xin2016-01-125-7/+69
| | | | | | | | | | | | | | This pull request does a few small things: 1. Separated if simplification from BooleanSimplification and created a new rule SimplifyConditionals. In the future we can also simplify other conditional expressions here. 2. Added unit test for SimplifyConditionals. 3. Renamed SimplifyCaseConversionExpressionsSuite to SimplifyStringCaseConversionSuite Author: Reynold Xin <rxin@databricks.com> Closes #10716 from rxin/SPARK-12762.
* [SPARK-12692][BUILD][SQL] Scala style: Fix the style violation (Space before ↵Kousuke Saruta2016-01-1253-140/+149
| | | | | | | | | | | "," or ":") Fix the style violation (space before , and :). This PR is a followup for #10643. Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp> Closes #10718 from sarutak/SPARK-12692-followup-sql.
* [SPARK-11823] Ignores HiveThriftBinaryServerSuite's test jdbc cancelYin Huai2016-01-111-1/+3
| | | | | | | | | | https://issues.apache.org/jira/browse/SPARK-11823 This test often hangs and times out, leaving hanging processes. Let's ignore it for now and improve the test. Author: Yin Huai <yhuai@databricks.com> Closes #10715 from yhuai/SPARK-11823-ignore.
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