aboutsummaryrefslogtreecommitdiff
path: root/sql/core
Commit message (Collapse)AuthorAgeFilesLines
* [SPARK-4742][SQL] The name of Parquet File generated by ↵Sasaki Toru2014-12-111-1/+6
| | | | | | | | | | | | | AppendingParquetOutputFormat should be zero padded When I use Parquet File as a output file using ParquetOutputFormat#getDefaultWorkFile, the file name is not zero padded while RDD#saveAsText does zero padding. Author: Sasaki Toru <sasakitoa@nttdata.co.jp> Closes #3602 from sasakitoa/parquet-zeroPadding and squashes the following commits: 6b0e58f [Sasaki Toru] Merge branch 'master' of git://github.com/apache/spark into parquet-zeroPadding 20dc79d [Sasaki Toru] Fixed the name of Parquet File generated by AppendingParquetOutputFormat
* [SPARK-4713] [SQL] SchemaRDD.unpersist() should not raise exception if it is ↵Cheng Hao2014-12-112-1/+15
| | | | | | | | | | | | | | | | | | | not persisted Unpersist a uncached RDD, will not raise exception, for example: ``` val data = Array(1, 2, 3, 4, 5) val distData = sc.parallelize(data) distData.unpersist(true) ``` But the `SchemaRDD` will raise exception if the `SchemaRDD` is not cached. Since `SchemaRDD` is the subclasses of the `RDD`, we should follow the same behavior. Author: Cheng Hao <hao.cheng@intel.com> Closes #3572 from chenghao-intel/try_uncache and squashes the following commits: 50a7a89 [Cheng Hao] SchemaRDD.unpersist() should not raise exception if it is not persisted
* [SQL] remove unnecessary import in spark-sqlJacky Li2014-12-085-9/+3
| | | | | | | | Author: Jacky Li <jacky.likun@huawei.com> Closes #3630 from jackylk/remove and squashes the following commits: 150e7e0 [Jacky Li] remove unnecessary import
* [SPARK-4753][SQL] Use catalyst for partition pruning in newParquet.Michael Armbrust2014-12-041-30/+28
| | | | | | | | Author: Michael Armbrust <michael@databricks.com> Closes #3613 from marmbrus/parquetPartitionPruning and squashes the following commits: 4f138f8 [Michael Armbrust] Use catalyst for partition pruning in newParquet.
* [SQL] remove unnecessary importJacky Li2014-12-041-1/+0
| | | | | | | | Author: Jacky Li <jacky.likun@huawei.com> Closes #3585 from jackylk/remove and squashes the following commits: 045423d [Jacky Li] remove unnecessary import
* [SPARK-4552][SQL] Avoid exception when reading empty parquet data through HiveMichael Armbrust2014-12-031-1/+4
| | | | | | | | | | | This is a very small fix that catches one specific exception and returns an empty table. #3441 will address this in a more principled way. Author: Michael Armbrust <michael@databricks.com> Closes #3586 from marmbrus/fixEmptyParquet and squashes the following commits: 2781d9f [Michael Armbrust] Handle empty lists for newParquet 04dd376 [Michael Armbrust] Avoid exception when reading empty parquet data through Hive
* [SPARK-4676][SQL] JavaSchemaRDD.schema may throw NullType MatchError if sql ↵YanTangZhai2014-12-025-0/+59
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | has null val jsc = new org.apache.spark.api.java.JavaSparkContext(sc) val jhc = new org.apache.spark.sql.hive.api.java.JavaHiveContext(jsc) val nrdd = jhc.hql("select null from spark_test.for_test") println(nrdd.schema) Then the error is thrown as follows: scala.MatchError: NullType (of class org.apache.spark.sql.catalyst.types.NullType$) at org.apache.spark.sql.types.util.DataTypeConversions$.asJavaDataType(DataTypeConversions.scala:43) Author: YanTangZhai <hakeemzhai@tencent.com> Author: yantangzhai <tyz0303@163.com> Author: Michael Armbrust <michael@databricks.com> Closes #3538 from YanTangZhai/MatchNullType and squashes the following commits: e052dff [yantangzhai] [SPARK-4676] [SQL] JavaSchemaRDD.schema may throw NullType MatchError if sql has null 4b4bb34 [yantangzhai] [SPARK-4676] [SQL] JavaSchemaRDD.schema may throw NullType MatchError if sql has null 896c7b7 [yantangzhai] fix NullType MatchError in JavaSchemaRDD when sql has null 6e643f8 [YanTangZhai] Merge pull request #11 from apache/master e249846 [YanTangZhai] Merge pull request #10 from apache/master d26d982 [YanTangZhai] Merge pull request #9 from apache/master 76d4027 [YanTangZhai] Merge pull request #8 from apache/master 03b62b0 [YanTangZhai] Merge pull request #7 from apache/master 8a00106 [YanTangZhai] Merge pull request #6 from apache/master cbcba66 [YanTangZhai] Merge pull request #3 from apache/master cdef539 [YanTangZhai] Merge pull request #1 from apache/master
* [SPARK-4663][sql]add finally to avoid resource leakbaishuo2014-12-021-4/+7
| | | | | | | | | | Author: baishuo <vc_java@hotmail.com> Closes #3526 from baishuo/master-trycatch and squashes the following commits: d446e14 [baishuo] correct the code style b36bf96 [baishuo] correct the code style ae0e447 [baishuo] add finally to avoid resource leak
* [SPARK-4536][SQL] Add sqrt and abs to Spark SQL DSLKousuke Saruta2014-12-022-0/+72
| | | | | | | | | | | | | Spark SQL has embeded sqrt and abs but DSL doesn't support those functions. Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp> Closes #3401 from sarutak/dsl-missing-operator and squashes the following commits: 07700cf [Kousuke Saruta] Modified Literal(null, NullType) to Literal(null) in DslQuerySuite 8f366f8 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into dsl-missing-operator 1b88e2e [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into dsl-missing-operator 0396f89 [Kousuke Saruta] Added sqrt and abs to Spark SQL DSL
* Indent license header properly for interfaces.scala.Reynold Xin2014-12-021-17/+15
| | | | | | | | | | A very small nit update. Author: Reynold Xin <rxin@databricks.com> Closes #3552 from rxin/license-header and squashes the following commits: df8d1a4 [Reynold Xin] Indent license header properly for interfaces.scala.
* [SQL] Minor fix for doc and commentwangfei2014-12-011-1/+1
| | | | | | | | Author: wangfei <wangfei1@huawei.com> Closes #3533 from scwf/sql-doc1 and squashes the following commits: 962910b [wangfei] doc and comment fix
* [SPARK-4658][SQL] Code documentation issue in DDL of datasource APIravipesala2014-12-012-3/+3
| | | | | | | | | Author: ravipesala <ravindra.pesala@huawei.com> Closes #3516 from ravipesala/ddl_doc and squashes the following commits: d101fdf [ravipesala] Style issues fixed d2238cd [ravipesala] Corrected documentation
* [SPARK-4650][SQL] Supporting multi column support in countDistinct function ↵ravipesala2014-12-011-0/+7
| | | | | | | | | | | | | | like count(distinct c1,c2..) in Spark SQL Supporting multi column support in countDistinct function like count(distinct c1,c2..) in Spark SQL Author: ravipesala <ravindra.pesala@huawei.com> Author: Michael Armbrust <michael@databricks.com> Closes #3511 from ravipesala/countdistinct and squashes the following commits: cc4dbb1 [ravipesala] style 070e12a [ravipesala] Supporting multi column support in count(distinct c1,c2..) in Spark SQL
* [SQL] add @group tab in limit() and count()Jacky Li2014-12-011-0/+4
| | | | | | | | | | group tab is missing for scaladoc Author: Jacky Li <jacky.likun@gmail.com> Closes #3458 from jackylk/patch-7 and squashes the following commits: 0121a70 [Jacky Li] add @group tab in limit() and count()
* [SPARK-4548] []SPARK-4517] improve performance of python broadcastDavies Liu2014-11-242-3/+4
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Re-implement the Python broadcast using file: 1) serialize the python object using cPickle, write into disks. 2) Create a wrapper in JVM (for the dumped file), it read data from during serialization 3) Using TorrentBroadcast or HttpBroadcast to transfer the data (compressed) into executors 4) During deserialization, writing the data into disk. 5) Passing the path into Python worker, read data from disk and unpickle it into python object, until the first access. It fixes the performance regression introduced in #2659, has similar performance as 1.1, but support object larger than 2G, also improve the memory efficiency (only one compressed copy in driver and executor). Testing with a 500M broadcast and 4 tasks (excluding the benefit from reused worker in 1.2): name | 1.1 | 1.2 with this patch | improvement ---------|--------|---------|-------- python-broadcast-w-bytes | 25.20 | 9.33 | 170.13% | python-broadcast-w-set | 4.13 | 4.50 | -8.35% | Testing with 100 tasks (16 CPUs): name | 1.1 | 1.2 with this patch | improvement ---------|--------|---------|-------- python-broadcast-w-bytes | 38.16 | 8.40 | 353.98% python-broadcast-w-set | 23.29 | 9.59 | 142.80% Author: Davies Liu <davies@databricks.com> Closes #3417 from davies/pybroadcast and squashes the following commits: 50a58e0 [Davies Liu] address comments b98de1d [Davies Liu] disable gc while unpickle e5ee6b9 [Davies Liu] support large string 09303b8 [Davies Liu] read all data into memory dde02dd [Davies Liu] improve performance of python broadcast
* [SPARK-4487][SQL] Fix attribute reference resolution error when using ORDER BY.Kousuke Saruta2014-11-241-0/+7
| | | | | | | | | | | | | | | | | | | | | When we use ORDER BY clause, at first, attributes referenced by projection are resolved (1). And then, attributes referenced at ORDER BY clause are resolved (2). But when resolving attributes referenced at ORDER BY clause, the resolution result generated in (1) is discarded so for example, following query fails. SELECT c1 + c2 FROM mytable ORDER BY c1; The query above fails because when resolving the attribute reference 'c1', the resolution result of 'c2' is discarded. Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp> Closes #3363 from sarutak/SPARK-4487 and squashes the following commits: fd314f3 [Kousuke Saruta] Fixed attribute resolution logic in Analyzer 6e60c20 [Kousuke Saruta] Fixed conflicts cb5b7e9 [Kousuke Saruta] Added test case for SPARK-4487 282d529 [Kousuke Saruta] Fixed attributes reference resolution error b6123e6 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into concat-feature 317b7fb [Kousuke Saruta] WIP
* [SPARK-4479][SQL] Avoids unnecessary defensive copies when sort based ↵Cheng Lian2014-11-241-1/+15
| | | | | | | | | | | | | | | | | | | | | | shuffle is on This PR is a workaround for SPARK-4479. Two changes are introduced: when merge sort is bypassed in `ExternalSorter`, 1. also bypass RDD elements buffering as buffering is the reason that `MutableRow` backed row objects must be copied, and 2. avoids defensive copies in `Exchange` operator <!-- Reviewable:start --> [<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/3422) <!-- Reviewable:end --> Author: Cheng Lian <lian@databricks.com> Closes #3422 from liancheng/avoids-defensive-copies and squashes the following commits: 591f2e9 [Cheng Lian] Passes all shuffle suites 0c3c91e [Cheng Lian] Fixes shuffle write metrics when merge sort is bypassed ed5df3c [Cheng Lian] Fixes styling changes f75089b [Cheng Lian] Avoids unnecessary defensive copies when sort based shuffle is on
* [SPARK-4413][SQL] Parquet support through datasource APIMichael Armbrust2014-11-204-13/+346
| | | | | | | | | | | | | | | | | | | Goals: - Support for accessing parquet using SQL but not requiring Hive (thus allowing support of parquet tables with decimal columns) - Support for folder based partitioning with automatic discovery of available partitions - Caching of file metadata See scaladoc of `ParquetRelation2` for more details. Author: Michael Armbrust <michael@databricks.com> Closes #3269 from marmbrus/newParquet and squashes the following commits: 1dd75f1 [Michael Armbrust] Pass all paths for FileInputFormat at once. 645768b [Michael Armbrust] Review comments. abd8e2f [Michael Armbrust] Alternative implementation of parquet based on the datasources API. 938019e [Michael Armbrust] Add an experimental interface to data sources that exposes catalyst expressions. e9d2641 [Michael Armbrust] logging / formatting improvements.
* [SQL] fix function description mistakeJacky Li2014-11-201-1/+1
| | | | | | | | | | Sample code in the description of SchemaRDD.where is not correct Author: Jacky Li <jacky.likun@gmail.com> Closes #3344 from jackylk/patch-6 and squashes the following commits: 62cd126 [Jacky Li] [SQL] fix function description mistake
* [SPARK-4318][SQL] Fix empty sum distinct.Takuya UESHIN2014-11-203-28/+116
| | | | | | | | | | | | | | | | | | | Executing sum distinct for empty table throws `java.lang.UnsupportedOperationException: empty.reduceLeft`. Author: Takuya UESHIN <ueshin@happy-camper.st> Closes #3184 from ueshin/issues/SPARK-4318 and squashes the following commits: 8168c42 [Takuya UESHIN] Merge branch 'master' into issues/SPARK-4318 66fdb0a [Takuya UESHIN] Re-refine aggregate functions. 6186eb4 [Takuya UESHIN] Fix Sum of GeneratedAggregate. d2975f6 [Takuya UESHIN] Refine Sum and Average of GeneratedAggregate. 1bba675 [Takuya UESHIN] Refine Sum, SumDistinct and Average functions. 917e533 [Takuya UESHIN] Use aggregate instead of groupBy(). 1a5f874 [Takuya UESHIN] Add tests to be executed as non-partial aggregation. a5a57d2 [Takuya UESHIN] Fix empty Average. 22799dc [Takuya UESHIN] Fix empty Sum and SumDistinct. 65b7dd2 [Takuya UESHIN] Fix empty sum distinct.
* [SPARK-4513][SQL] Support relational operator '<=>' in Spark SQLravipesala2014-11-201-0/+12
| | | | | | | | | | The relational operator '<=>' is not working in Spark SQL. Same works in Spark HiveQL Author: ravipesala <ravindra.pesala@huawei.com> Closes #3387 from ravipesala/<=> and squashes the following commits: 7198e90 [ravipesala] Supporting relational operator '<=>' in Spark SQL
* [SPARK-4228][SQL] SchemaRDD to JSONDan McClary2014-11-204-3/+208
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Here's a simple fix for SchemaRDD to JSON. Author: Dan McClary <dan.mcclary@gmail.com> Closes #3213 from dwmclary/SPARK-4228 and squashes the following commits: d714e1d [Dan McClary] fixed PEP 8 error cac2879 [Dan McClary] move pyspark comment and doctest to correct location f9471d3 [Dan McClary] added pyspark doc and doctest 6598cee [Dan McClary] adding complex type queries 1a5fd30 [Dan McClary] removing SPARK-4228 from SQLQuerySuite 4a651f0 [Dan McClary] cleaned PEP and Scala style failures. Moved tests to JsonSuite 47ceff6 [Dan McClary] cleaned up scala style issues 2ee1e70 [Dan McClary] moved rowToJSON to JsonRDD 4387dd5 [Dan McClary] Added UserDefinedType, cleaned up case formatting 8f7bfb6 [Dan McClary] Map type added to SchemaRDD.toJSON 1b11980 [Dan McClary] Map and UserDefinedTypes partially done 11d2016 [Dan McClary] formatting and unicode deserialization default fixed 6af72d1 [Dan McClary] deleted extaneous comment 4d11c0c [Dan McClary] JsonFactory rewrite of toJSON for SchemaRDD 149dafd [Dan McClary] wrapped scala toJSON in sql.py 5e5eb1b [Dan McClary] switched to Jackson for JSON processing 6c94a54 [Dan McClary] added toJSON to pyspark SchemaRDD aaeba58 [Dan McClary] added toJSON to pyspark SchemaRDD 1d171aa [Dan McClary] upated missing brace on if statement 319e3ba [Dan McClary] updated to upstream master with merged SPARK-4228 424f130 [Dan McClary] tests pass, ready for pull and PR 626a5b1 [Dan McClary] added toJSON to SchemaRDD f7d166a [Dan McClary] added toJSON method 5d34e37 [Dan McClary] merge resolved d6d19e9 [Dan McClary] pr example
* [SPARK-3938][SQL] Names in-memory columnar RDD with corresponding table nameCheng Lian2014-11-206-16/+23
| | | | | | | | | | | | | | | | | | | | | | | | This PR enables the Web UI storage tab to show the in-memory table name instead of the mysterious query plan string as the name of the in-memory columnar RDD. Note that after #2501, a single columnar RDD can be shared by multiple in-memory tables, as long as their query results are the same. In this case, only the first cached table name is shown. For example: ```sql CACHE TABLE first AS SELECT * FROM src; CACHE TABLE second AS SELECT * FROM src; ``` The Web UI only shows "In-memory table first". <!-- Reviewable:start --> [<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/3383) <!-- Reviewable:end --> Author: Cheng Lian <lian@databricks.com> Closes #3383 from liancheng/columnar-rdd-name and squashes the following commits: 071907f [Cheng Lian] Fixes tests 12ddfa6 [Cheng Lian] Names in-memory columnar RDD with corresponding table name
* Bumping version to 1.3.0-SNAPSHOT.Marcelo Vanzin2014-11-181-1/+1
| | | | | | | | | | | | Author: Marcelo Vanzin <vanzin@cloudera.com> Closes #3277 from vanzin/version-1.3 and squashes the following commits: 7c3c396 [Marcelo Vanzin] Added temp repo to sbt build. 5f404ff [Marcelo Vanzin] Add another exclusion. 19457e7 [Marcelo Vanzin] Update old version to 1.2, add temporary 1.2 repo. 3c8d705 [Marcelo Vanzin] Workaround for MIMA checks. e940810 [Marcelo Vanzin] Bumping version to 1.3.0-SNAPSHOT.
* [SPARK-4468][SQL] Fixes Parquet filter creation for inequality predicates ↵Cheng Lian2014-11-182-4/+16
| | | | | | | | | | | | | | | | | | with literals on the left hand side For expressions like `10 < someVar`, we should create an `Operators.Gt` filter, but right now an `Operators.Lt` is created. This issue affects all inequality predicates with literals on the left hand side. (This bug existed before #3317 and affects branch-1.1. #3338 was opened to backport this to branch-1.1.) <!-- Reviewable:start --> [<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/3334) <!-- Reviewable:end --> Author: Cheng Lian <lian@databricks.com> Closes #3334 from liancheng/fix-parquet-comp-filter and squashes the following commits: 0130897 [Cheng Lian] Fixes Parquet comparison filter generation
* [SPARK-3721] [PySpark] broadcast objects larger than 2GDavies Liu2014-11-182-2/+2
| | | | | | | | | | | | | | | | | | | | | | | | | | | This patch will bring support for broadcasting objects larger than 2G. pickle, zlib, FrameSerializer and Array[Byte] all can not support objects larger than 2G, so this patch introduce LargeObjectSerializer to serialize broadcast objects, the object will be serialized and compressed into small chunks, it also change the type of Broadcast[Array[Byte]]] into Broadcast[Array[Array[Byte]]]]. Testing for support broadcast objects larger than 2G is slow and memory hungry, so this is tested manually, could be added into SparkPerf. Author: Davies Liu <davies@databricks.com> Author: Davies Liu <davies.liu@gmail.com> Closes #2659 from davies/huge and squashes the following commits: 7b57a14 [Davies Liu] add more tests for broadcast 28acff9 [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge a2f6a02 [Davies Liu] bug fix 4820613 [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge 5875c73 [Davies Liu] address comments 10a349b [Davies Liu] address comments 0c33016 [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge 6182c8f [Davies Liu] Merge branch 'master' into huge d94b68f [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge 2514848 [Davies Liu] address comments fda395b [Davies Liu] Merge branch 'master' of github.com:apache/spark into huge 1c2d928 [Davies Liu] fix scala style 091b107 [Davies Liu] broadcast objects larger than 2G
* [SPARK-4453][SPARK-4213][SQL] Simplifies Parquet filter generation codeCheng Lian2014-11-174-693/+160
| | | | | | | | | | | | | | | | | | | While reviewing PR #3083 and #3161, I noticed that Parquet record filter generation code can be simplified significantly according to the clue stated in [SPARK-4453](https://issues.apache.org/jira/browse/SPARK-4213). This PR addresses both SPARK-4453 and SPARK-4213 with this simplification. While generating `ParquetTableScan` operator, we need to remove all Catalyst predicates that have already been pushed down to Parquet. Originally, we first generate the record filter, and then call `findExpression` to traverse the generated filter to find out all pushed down predicates [[1](https://github.com/apache/spark/blob/64c6b9bad559c21f25cd9fbe37c8813cdab939f2/sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala#L213-L228)]. In this way, we have to introduce the `CatalystFilter` class hierarchy to bind the Catalyst predicates together with their generated Parquet filter, and complicate the code base a lot. The basic idea of this PR is that, we don't need `findExpression` after filter generation, because we already know a predicate can be pushed down if we can successfully generate its corresponding Parquet filter. SPARK-4213 is fixed by returning `None` for any unsupported predicate type. <!-- Reviewable:start --> [<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/3317) <!-- Reviewable:end --> Author: Cheng Lian <lian@databricks.com> Closes #3317 from liancheng/simplify-parquet-filters and squashes the following commits: d6a9499 [Cheng Lian] Fixes import styling issue 43760e8 [Cheng Lian] Simplifies Parquet filter generation logic
* [SQL] Makes conjunction pushdown more aggressive for in-memory tableCheng Lian2014-11-172-5/+11
| | | | | | | | | | | | | | This is inspired by the [Parquet record filter generation code](https://github.com/apache/spark/blob/64c6b9bad559c21f25cd9fbe37c8813cdab939f2/sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetFilters.scala#L387-L400). <!-- Reviewable:start --> [<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/3318) <!-- Reviewable:end --> Author: Cheng Lian <lian@databricks.com> Closes #3318 from liancheng/aggresive-conj-pushdown and squashes the following commits: 78b69d2 [Cheng Lian] Makes conjunction pushdown more aggressive
* [SPARK-4410][SQL] Add support for external sortMichael Armbrust2014-11-164-6/+59
| | | | | | | | | | | | Adds a new operator that uses Spark's `ExternalSort` class. It is off by default now, but we might consider making it the default if benchmarks show that it does not regress performance. Author: Michael Armbrust <michael@databricks.com> Closes #3268 from marmbrus/externalSort and squashes the following commits: 48b9726 [Michael Armbrust] comments b98799d [Michael Armbrust] Add test afd7562 [Michael Armbrust] Add support for external sort.
* [SPARK-4412][SQL] Fix Spark's control of Parquet logging.Jim Carroll2014-11-141-0/+15
| | | | | | | | | | | | | | The Spark ParquetRelation.scala code makes the assumption that the parquet.Log class has already been loaded. If ParquetRelation.enableLogForwarding executes prior to the parquet.Log class being loaded then the code in enableLogForwarding has no affect. ParquetRelation.scala attempts to override the parquet logger but, at least currently (and if your application simply reads a parquet file before it does anything else with Parquet), the parquet.Log class hasn't been loaded yet. Therefore the code in ParquetRelation.enableLogForwarding has no affect. If you look at the code in parquet.Log there's a static initializer that needs to be called prior to enableLogForwarding or whatever enableLogForwarding does gets undone by this static initializer. The "fix" would be to force the static initializer to get called in parquet.Log as part of enableForwardLogging. Author: Jim Carroll <jim@dontcallme.com> Closes #3271 from jimfcarroll/parquet-logging and squashes the following commits: 37bdff7 [Jim Carroll] Fix Spark's control of Parquet logging.
* [SPARK-4365][SQL] Remove unnecessary filter call on records returned from ↵Yash Datta2014-11-141-1/+1
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | parquet library Since parquet library has been updated , we no longer need to filter the records returned from parquet library for null records , as now the library skips those : from parquet-hadoop/src/main/java/parquet/hadoop/InternalParquetRecordReader.java public boolean nextKeyValue() throws IOException, InterruptedException { boolean recordFound = false; while (!recordFound) { // no more records left if (current >= total) { return false; } try { checkRead(); currentValue = recordReader.read(); current ++; if (recordReader.shouldSkipCurrentRecord()) { // this record is being filtered via the filter2 package if (DEBUG) LOG.debug("skipping record"); continue; } if (currentValue == null) { // only happens with FilteredRecordReader at end of block current = totalCountLoadedSoFar; if (DEBUG) LOG.debug("filtered record reader reached end of block"); continue; } recordFound = true; if (DEBUG) LOG.debug("read value: " + currentValue); } catch (RuntimeException e) { throw new ParquetDecodingException(format("Can not read value at %d in block %d in file %s", current, currentBlock, file), e); } } return true; } Author: Yash Datta <Yash.Datta@guavus.com> Closes #3229 from saucam/remove_filter and squashes the following commits: 8909ae9 [Yash Datta] SPARK-4365: Remove unnecessary filter call on records returned from parquet library
* [SPARK-4386] Improve performance when writing Parquet files.Jim Carroll2014-11-141-6/+8
| | | | | | | | | | | | If you profile the writing of a Parquet file, the single worst time consuming call inside of org.apache.spark.sql.parquet.MutableRowWriteSupport.write is actually in the scala.collection.AbstractSequence.size call. This is because the size call actually ends up COUNTING the elements in a scala.collection.LinearSeqOptimized.length ("optimized?"). This doesn't need to be done. "size" is called repeatedly where needed rather than called once at the top of the method and stored in a 'val'. Author: Jim Carroll <jim@dontcallme.com> Closes #3254 from jimfcarroll/parquet-perf and squashes the following commits: 30cc0b5 [Jim Carroll] Improve performance when writing Parquet files.
* [SPARK-4322][SQL] Enables struct fields as sub expressions of grouping fieldsCheng Lian2014-11-141-1/+11
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | While resolving struct fields, the resulted `GetField` expression is wrapped with an `Alias` to make it a named expression. Assume `a` is a struct instance with a field `b`, then `"a.b"` will be resolved as `Alias(GetField(a, "b"), "b")`. Thus, for this following SQL query: ```sql SELECT a.b + 1 FROM t GROUP BY a.b + 1 ``` the grouping expression is ```scala Add(GetField(a, "b"), Literal(1, IntegerType)) ``` while the aggregation expression is ```scala Add(Alias(GetField(a, "b"), "b"), Literal(1, IntegerType)) ``` This mismatch makes the above SQL query fail during the both analysis and execution phases. This PR fixes this issue by removing the alias when substituting aggregation expressions. <!-- Reviewable:start --> [<img src="https://reviewable.io/review_button.png" height=40 alt="Review on Reviewable"/>](https://reviewable.io/reviews/apache/spark/3248) <!-- Reviewable:end --> Author: Cheng Lian <lian@databricks.com> Closes #3248 from liancheng/spark-4322 and squashes the following commits: 23a46ea [Cheng Lian] Code simplification dd20a79 [Cheng Lian] Should only trim aliases around `GetField`s 7f46532 [Cheng Lian] Enables struct fields as sub expressions of grouping fields
* [SQL] Don't shuffle code generated rowsMichael Armbrust2014-11-142-2/+9
| | | | | | | | | | When sort based shuffle and code gen are on we were trying to ship the code generated rows during a shuffle. This doesn't work because the classes don't exist on the other side. Instead we now copy into a generic row before shipping. Author: Michael Armbrust <michael@databricks.com> Closes #3263 from marmbrus/aggCodeGen and squashes the following commits: f6ba8cf [Michael Armbrust] fix and test
* [SPARK-4391][SQL] Configure parquet filters using SQLConfMichael Armbrust2014-11-145-11/+21
| | | | | | | | | | | | | | This is more uniform with the rest of SQL configuration and allows it to be turned on and off without restarting the SparkContext. In this PR I also turn off filter pushdown by default due to a number of outstanding issues (in particular SPARK-4258). When those are fixed we should turn it back on by default. Author: Michael Armbrust <michael@databricks.com> Closes #3258 from marmbrus/parquetFilters and squashes the following commits: 5655bfe [Michael Armbrust] Remove extra line. 15e9a98 [Michael Armbrust] Enable filters for tests 75afd39 [Michael Armbrust] Fix comments 78fa02d [Michael Armbrust] off by default e7f9e16 [Michael Armbrust] First draft of correctly configuring parquet filter pushdown
* [SPARK-4394][SQL] Data Sources API ImprovementsMichael Armbrust2014-11-145-3/+21
| | | | | | | | | | | | | | | This PR adds two features to the data sources API: - Support for pushing down `IN` filters - The ability for relations to optionally provide information about their `sizeInBytes`. Author: Michael Armbrust <michael@databricks.com> Closes #3260 from marmbrus/sourcesImprovements and squashes the following commits: 9a5e171 [Michael Armbrust] Use method instead of configuration directly 99c0e6b [Michael Armbrust] Add support for sizeInBytes. 416f167 [Michael Armbrust] Support for IN in data sources API. 2a04ab3 [Michael Armbrust] Simplify implementation of InSet.
* [SPARK-4274] [SQL] Fix NPE in printing the details of the query planCheng Hao2014-11-101-1/+1
| | | | | | | | Author: Cheng Hao <hao.cheng@intel.com> Closes #3139 from chenghao-intel/comparison_test and squashes the following commits: f5d7146 [Cheng Hao] avoid exception in printing the codegen enabled
* [SPARK-4149][SQL] ISO 8601 support for json date time stringsDaoyuan Wang2014-11-103-2/+40
| | | | | | | | | | This implement the feature davies mentioned in https://github.com/apache/spark/pull/2901#discussion-diff-19313312 Author: Daoyuan Wang <daoyuan.wang@intel.com> Closes #3012 from adrian-wang/iso8601 and squashes the following commits: 50df6e7 [Daoyuan Wang] json data timestamp ISO8601 support
* [SQL] remove a decimal case branch that has no effect at runtimeXiangrui Meng2014-11-101-1/+0
| | | | | | | | | | it generates warnings at compile time marmbrus Author: Xiangrui Meng <meng@databricks.com> Closes #3192 from mengxr/dtc-decimal and squashes the following commits: 955e9fb [Xiangrui Meng] remove a decimal case branch that has no effect
* [SPARK-4319][SQL] Enable an ignored test "null count".Takuya UESHIN2014-11-102-9/+9
| | | | | | | | Author: Takuya UESHIN <ueshin@happy-camper.st> Closes #3185 from ueshin/issues/SPARK-4319 and squashes the following commits: a44a38e [Takuya UESHIN] Enable an ignored test "null count".
* SPARK-1209 [CORE] (Take 2) SparkHadoop{MapRed,MapReduce}Util should not use ↵Sean Owen2014-11-091-0/+1
| | | | | | | | | | | | | | | | | | | | package org.apache.hadoop andrewor14 Another try at SPARK-1209, to address https://github.com/apache/spark/pull/2814#issuecomment-61197619 I successfully tested with `mvn -Dhadoop.version=1.0.4 -DskipTests clean package; mvn -Dhadoop.version=1.0.4 test` I assume that is what failed Jenkins last time. I also tried `-Dhadoop.version1.2.1` and `-Phadoop-2.4 -Pyarn -Phive` for more coverage. So this is why the class was put in `org.apache.hadoop` to begin with, I assume. One option is to leave this as-is for now and move it only when Hadoop 1.0.x support goes away. This is the other option, which adds a call to force the constructor to be public at run-time. It's probably less surprising than putting Spark code in `org.apache.hadoop`, but, does involve reflection. A `SecurityManager` might forbid this, but it would forbid a lot of stuff Spark does. This would also only affect Hadoop 1.0.x it seems. Author: Sean Owen <sowen@cloudera.com> Closes #3048 from srowen/SPARK-1209 and squashes the following commits: 0d48f4b [Sean Owen] For Hadoop 1.0.x, make certain constructors public, which were public in later versions 466e179 [Sean Owen] Disable MIMA warnings resulting from moving the class -- this was also part of the PairRDDFunctions type hierarchy though? eb61820 [Sean Owen] Move SparkHadoopMapRedUtil / SparkHadoopMapReduceUtil from org.apache.hadoop to org.apache.spark
* [SPARK-4213][SQL] ParquetFilters - No support for LT, LTE, GT, GTE operatorsKousuke Saruta2014-11-072-11/+364
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Following description is quoted from JIRA: When I issue a hql query against a HiveContext where my predicate uses a column of string type with one of LT, LTE, GT, or GTE operator, I get the following error: scala.MatchError: StringType (of class org.apache.spark.sql.catalyst.types.StringType$) Looking at the code in org.apache.spark.sql.parquet.ParquetFilters, StringType is absent from the corresponding functions for creating these filters. To reproduce, in a Hive 0.13.1 shell, I created the following table (at a specified DB): create table sparkbug ( id int, event string ) stored as parquet; Insert some sample data: insert into table sparkbug select 1, '2011-06-18' from <some table> limit 1; insert into table sparkbug select 2, '2012-01-01' from <some table> limit 1; Launch a spark shell and create a HiveContext to the metastore where the table above is located. import org.apache.spark.sql._ import org.apache.spark.sql.SQLContext import org.apache.spark.sql.hive.HiveContext val hc = new HiveContext(sc) hc.setConf("spark.sql.shuffle.partitions", "10") hc.setConf("spark.sql.hive.convertMetastoreParquet", "true") hc.setConf("spark.sql.parquet.compression.codec", "snappy") import hc._ hc.hql("select * from <db>.sparkbug where event >= '2011-12-01'") A scala.MatchError will appear in the output. Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp> Closes #3083 from sarutak/SPARK-4213 and squashes the following commits: 4ab6e56 [Kousuke Saruta] WIP b6890c6 [Kousuke Saruta] Merge branch 'master' of git://git.apache.org/spark into SPARK-4213 9a1fae7 [Kousuke Saruta] Fixed ParquetFilters so that compare Strings
* [SPARK-4262][SQL] add .schemaRDD to JavaSchemaRDDXiangrui Meng2014-11-051-0/+3
| | | | | | | | | | marmbrus Author: Xiangrui Meng <meng@databricks.com> Closes #3125 from mengxr/SPARK-4262 and squashes the following commits: 307695e [Xiangrui Meng] add .schemaRDD to JavaSchemaRDD
* [SPARK-3886] [PySpark] simplify serializer, use AutoBatchedSerializer by ↵Davies Liu2014-11-031-6/+4
| | | | | | | | | | | | | | | | | | | | | | | | | | | default. This PR simplify serializer, always use batched serializer (AutoBatchedSerializer as default), even batch size is 1. Author: Davies Liu <davies@databricks.com> This patch had conflicts when merged, resolved by Committer: Josh Rosen <joshrosen@databricks.com> Closes #2920 from davies/fix_autobatch and squashes the following commits: e544ef9 [Davies Liu] revert unrelated change 6880b14 [Davies Liu] Merge branch 'master' of github.com:apache/spark into fix_autobatch 1d557fc [Davies Liu] fix tests 8180907 [Davies Liu] Merge branch 'master' of github.com:apache/spark into fix_autobatch 76abdce [Davies Liu] clean up 53fa60b [Davies Liu] Merge branch 'master' of github.com:apache/spark into fix_autobatch d7ac751 [Davies Liu] Merge branch 'master' of github.com:apache/spark into fix_autobatch 2cc2497 [Davies Liu] Merge branch 'master' of github.com:apache/spark into fix_autobatch b4292ce [Davies Liu] fix bug in master d79744c [Davies Liu] recover hive tests be37ece [Davies Liu] refactor eb3938d [Davies Liu] refactor serializer in scala 8d77ef2 [Davies Liu] simplify serializer, use AutoBatchedSerializer by default.
* [SPARK-4192][SQL] Internal API for Python UDTXiangrui Meng2014-11-034-1/+71
| | | | | | | | | | | | | | | | | | | | | Following #2919, this PR adds Python UDT (for internal use only) with tests under "pyspark.tests". Before `SQLContext.applySchema`, we check whether we need to convert user-type instances into SQL recognizable data. In the current implementation, a Python UDT must be paired with a Scala UDT for serialization on the JVM side. A following PR will add VectorUDT in MLlib for both Scala and Python. marmbrus jkbradley davies Author: Xiangrui Meng <meng@databricks.com> Closes #3068 from mengxr/SPARK-4192-sql and squashes the following commits: acff637 [Xiangrui Meng] merge master dba5ea7 [Xiangrui Meng] only use pyClass for Python UDT output sqlType as well 2c9d7e4 [Xiangrui Meng] move import to global setup; update needsConversion 7c4a6a9 [Xiangrui Meng] address comments 75223db [Xiangrui Meng] minor update f740379 [Xiangrui Meng] remove UDT from default imports e98d9d0 [Xiangrui Meng] fix py style 4e84fce [Xiangrui Meng] remove local hive tests and add more tests 39f19e0 [Xiangrui Meng] add tests b7f666d [Xiangrui Meng] add Python UDT
* [SQL] Convert arguments to Scala UDFsMichael Armbrust2014-11-031-5/+13
| | | | | | | | | Author: Michael Armbrust <michael@databricks.com> Closes #3077 from marmbrus/udfsWithUdts and squashes the following commits: 34b5f27 [Michael Armbrust] style 504adef [Michael Armbrust] Convert arguments to Scala UDFs
* [SQL] More aggressive defaultsMichael Armbrust2014-11-032-8/+8
| | | | | | | | | | | | | | | | | | | | - Turns on compression for in-memory cached data by default - Changes the default parquet compression format back to gzip (we have seen more OOMs with production workloads due to the way Snappy allocates memory) - Ups the batch size to 10,000 rows - Increases the broadcast threshold to 10mb. - Uses our parquet implementation instead of the hive one by default. - Cache parquet metadata by default. Author: Michael Armbrust <michael@databricks.com> Closes #3064 from marmbrus/fasterDefaults and squashes the following commits: 97ee9f8 [Michael Armbrust] parquet codec docs e641694 [Michael Armbrust] Remote also a12866a [Michael Armbrust] Cache metadata. 2d73acc [Michael Armbrust] Update docs defaults. d63d2d5 [Michael Armbrust] document parquet option da373f9 [Michael Armbrust] More aggressive defaults
* [SPARK-4202][SQL] Simple DSL support for Scala UDFCheng Lian2014-11-031-4/+13
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This feature is based on an offline discussion with mengxr, hopefully can be useful for the new MLlib pipeline API. For the following test snippet ```scala case class KeyValue(key: Int, value: String) val testData = sc.parallelize(1 to 10).map(i => KeyValue(i, i.toString)).toSchemaRDD def foo(a: Int, b: String) => a.toString + b ``` the newly introduced DSL enables the following syntax ```scala import org.apache.spark.sql.catalyst.dsl._ testData.select(Star(None), foo.call('key, 'value) as 'result) ``` which is equivalent to ```scala testData.registerTempTable("testData") sqlContext.registerFunction("foo", foo) sql("SELECT *, foo(key, value) AS result FROM testData") ``` Author: Cheng Lian <lian@databricks.com> Closes #3067 from liancheng/udf-dsl and squashes the following commits: f132818 [Cheng Lian] Adds DSL support for Scala UDF
* [SPARK-4207][SQL] Query which has syntax like 'not like' is not working in ↵ravipesala2014-11-031-0/+5
| | | | | | | | | | | | | | | Spark SQL Queries which has 'not like' is not working spark sql. sql("SELECT * FROM records where value not like 'val%'") same query works in Spark HiveQL Author: ravipesala <ravindra.pesala@huawei.com> Closes #3075 from ravipesala/SPARK-4207 and squashes the following commits: 35c11e7 [ravipesala] Supported 'not like' syntax in sql
* [SPARK-3572] [SQL] Internal API for User-Defined TypesJoseph K. Bradley2014-11-0218-76/+413
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This PR adds User-Defined Types (UDTs) to SQL. It is a precursor to using SchemaRDD as a Dataset for the new MLlib API. Currently, the UDT API is private since there is incomplete support (e.g., no Java or Python support yet). Author: Joseph K. Bradley <joseph@databricks.com> Author: Michael Armbrust <michael@databricks.com> Author: Xiangrui Meng <meng@databricks.com> Closes #3063 from marmbrus/udts and squashes the following commits: 7ccfc0d [Michael Armbrust] remove println 46a3aee [Michael Armbrust] Slightly easier to read test output. 6cc434d [Michael Armbrust] Recursively convert rows. e369b91 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into udts 15c10a6 [Joseph K. Bradley] Merge remote-tracking branch 'upstream/master' into sql-udt2 f3c72fe [Joseph K. Bradley] Fixing merge e13cd8a [Joseph K. Bradley] Removed Vector UDTs 5817b2b [Joseph K. Bradley] style edits 30ce5b2 [Joseph K. Bradley] updates based on code review d063380 [Joseph K. Bradley] Cleaned up Java UDT Suite, and added warning about element ordering when creating schema from Java Bean a571bb6 [Joseph K. Bradley] Removed old UDT code (registry and Java UDTs). Cleaned up other code. Extended JavaUserDefinedTypeSuite 6fddc1c [Joseph K. Bradley] Made MyLabeledPoint into a Java Bean 20630bc [Joseph K. Bradley] fixed scalastyle fa86b20 [Joseph K. Bradley] Removed Java UserDefinedType, and made UDTs private[spark] for now 8de957c [Joseph K. Bradley] Modified UserDefinedType to store Java class of user type so that registerUDT takes only the udt argument. 8b242ea [Joseph K. Bradley] Fixed merge error after last merge. Note: Last merge commit also removed SQL UDT examples from mllib. 7f29656 [Joseph K. Bradley] Moved udt case to top of all matches. Small cleanups b028675 [Xiangrui Meng] allow any type in UDT 4500d8a [Xiangrui Meng] update example code 87264a5 [Xiangrui Meng] remove debug code 3143ac3 [Xiangrui Meng] remove unnecessary changes cfbc321 [Xiangrui Meng] support UDT in parquet db16139 [Joseph K. Bradley] Added more doc for UserDefinedType. Removed unused code in Suite 759af7a [Joseph K. Bradley] Added more doc to UserDefineType 63626a4 [Joseph K. Bradley] Updated ScalaReflectionsSuite per @marmbrus suggestions 51e5282 [Joseph K. Bradley] fixed 1 test f025035 [Joseph K. Bradley] Cleanups before PR. Added new tests 85872f6 [Michael Armbrust] Allow schema calculation to be lazy, but ensure its available on executors. dff99d6 [Joseph K. Bradley] Added UDTs for Vectors in MLlib, plus DatasetExample using the UDTs cd60cb4 [Joseph K. Bradley] Trying to get other SQL tests to run 34a5831 [Joseph K. Bradley] Added MLlib dependency on SQL. e1f7b9c [Joseph K. Bradley] blah 2f40c02 [Joseph K. Bradley] renamed UDT types 3579035 [Joseph K. Bradley] udt annotation now working b226b9e [Joseph K. Bradley] Changing UDT to annotation fea04af [Joseph K. Bradley] more cleanups 964b32e [Joseph K. Bradley] some cleanups 893ee4c [Joseph K. Bradley] udt finallly working 50f9726 [Joseph K. Bradley] udts 04303c9 [Joseph K. Bradley] udts 39f8707 [Joseph K. Bradley] removed old udt suite 273ac96 [Joseph K. Bradley] basic UDT is working, but deserialization has yet to be done 8bebf24 [Joseph K. Bradley] commented out convertRowToScala for debugging 53de70f [Joseph K. Bradley] more udts... 982c035 [Joseph K. Bradley] still working on UDTs 19b2f60 [Joseph K. Bradley] still working on UDTs 0eaeb81 [Joseph K. Bradley] Still working on UDTs 105c5a3 [Joseph K. Bradley] Adding UserDefinedType to SQL, not done yet.
generated by cgit v1.2.3 (git 2.39.1) at 2024-07-13 14:20:39 +0000