Commit graph

244 commits

Author SHA1 Message Date
Michael Armbrust 90a6a46bd1 [SPARK-4522][SQL] Parse schema with missing metadata.
This is just a quick fix for 1.2.  SPARK-4523 describes a more complete solution.

Author: Michael Armbrust <michael@databricks.com>

Closes #3392 from marmbrus/parquetMetadata and squashes the following commits:

bcc6626 [Michael Armbrust] Parse schema with missing metadata.
2014-11-20 20:34:43 -08:00
Takuya UESHIN 2c2e7a44db [SPARK-4318][SQL] Fix empty sum distinct.
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.
2014-11-20 15:41:24 -08:00
ravipesala 98e9419784 [SPARK-4513][SQL] Support relational operator '<=>' in Spark SQL
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
2014-11-20 15:34:03 -08:00
Marcelo Vanzin 397d3aae5b Bumping version to 1.3.0-SNAPSHOT.
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.
2014-11-18 21:24:18 -08:00
Cheng Lian 36b0956a3e [SPARK-4453][SPARK-4213][SQL] Simplifies Parquet filter generation code
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](64c6b9bad5/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.

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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
2014-11-17 16:55:12 -08:00
Cheng Hao 69e858cc77 [SQL] Construct the MutableRow from an Array
Author: Cheng Hao <hao.cheng@intel.com>

Closes #3217 from chenghao-intel/mutablerow and squashes the following commits:

e8a10bd [Cheng Hao] revert the change of Row object
4681aea [Cheng Hao] Add toMutableRow method in object Row
a751838 [Cheng Hao] Construct the MutableRow from an existed row
2014-11-17 16:29:52 -08:00
Takuya UESHIN 566c791931 [SPARK-4425][SQL] Handle NaN or Infinity cast to Timestamp correctly.
`Cast` from `NaN` or `Infinity` of `Double` or `Float` to `TimestampType` throws `NumberFormatException`.

Author: Takuya UESHIN <ueshin@happy-camper.st>

Closes #3283 from ueshin/issues/SPARK-4425 and squashes the following commits:

14def0c [Takuya UESHIN] Fix Cast to be able to handle NaN or Infinity to TimestampType.
2014-11-17 16:28:07 -08:00
Takuya UESHIN 3a81a1c9e0 [SPARK-4420][SQL] Change nullability of Cast from DoubleType/FloatType to DecimalType.
This is follow-up of [SPARK-4390](https://issues.apache.org/jira/browse/SPARK-4390) (#3256).

Author: Takuya UESHIN <ueshin@happy-camper.st>

Closes #3278 from ueshin/issues/SPARK-4420 and squashes the following commits:

7fea558 [Takuya UESHIN] Add some tests.
cb2301a [Takuya UESHIN] Fix tests.
133bad5 [Takuya UESHIN] Change nullability of Cast from DoubleType/FloatType to DecimalType.
2014-11-17 16:26:48 -08:00
Kousuke Saruta 84468b2e20 [SPARK-4426][SQL][Minor] The symbol of BitwiseOr is wrong, should not be '&'
The symbol of BitwiseOr is defined as '&' but I think it's wrong. It should be '|'.

Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>

Closes #3284 from sarutak/bitwise-or-symbol-fix and squashes the following commits:

aff4be5 [Kousuke Saruta] Fixed symbol of BitwiseOr
2014-11-15 22:23:47 -08:00
kai cbddac2369 Added contains(key) to Metadata
Add contains(key) to org.apache.spark.sql.catalyst.util.Metadata to test the existence of a key. Otherwise, Class Metadata's get methods may throw NoSuchElement exception if the key does not exist.
Testcases are added to MetadataSuite as well.

Author: kai <kaizeng@eecs.berkeley.edu>

Closes #3273 from kai-zeng/metadata-fix and squashes the following commits:

74b3d03 [kai] Added contains(key) to Metadata
2014-11-14 23:44:23 -08:00
Cheng Lian 0c7b66bd44 [SPARK-4322][SQL] Enables struct fields as sub expressions of grouping fields
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.

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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
2014-11-14 15:09:36 -08:00
Michael Armbrust f805025e8e [SQL] Minor cleanup of comments, errors and override.
Author: Michael Armbrust <michael@databricks.com>

Closes #3257 from marmbrus/minorCleanup and squashes the following commits:

d8b5abc [Michael Armbrust] Use interpolation.
2fdf903 [Michael Armbrust] Better error message when coalesce can't be resolved.
f9fa6cf [Michael Armbrust] Methods in a final class do not also need to be final, use override.
199fd98 [Michael Armbrust] Fix typo
2014-11-14 15:00:42 -08:00
Michael Armbrust a0300ea32a [SPARK-4390][SQL] Handle NaN cast to decimal correctly
Author: Michael Armbrust <michael@databricks.com>

Closes #3256 from marmbrus/NanDecimal and squashes the following commits:

4c3ba46 [Michael Armbrust] fix style
d360f83 [Michael Armbrust] Handle NaN cast to decimal
2014-11-14 14:56:57 -08:00
DoingDone9 0cbdb01e1c [SPARK-4333][SQL] Correctly log number of iterations in RuleExecutor
When iterator of RuleExecutor breaks, the num of iterator should be (iteration - 1) not (iteration ).Because log looks like "Fixed point reached for batch ${batch.name} after 3 iterations.", but it did 2 iterations really!

Author: DoingDone9 <799203320@qq.com>

Closes #3180 from DoingDone9/issue_01 and squashes the following commits:

571e2ed [DoingDone9] Update RuleExecutor.scala
46514b6 [DoingDone9] When iterator of RuleExecutor breaks, the num of iterator should be iteration - 1 not iteration.
2014-11-14 14:28:06 -08:00
Sandy Ryza f5f757e4ed SPARK-4375. no longer require -Pscala-2.10
It seems like the winds might have moved away from this approach, but wanted to post the PR anyway because I got it working and to show what it would look like.

Author: Sandy Ryza <sandy@cloudera.com>

Closes #3239 from sryza/sandy-spark-4375 and squashes the following commits:

0ffbe95 [Sandy Ryza] Enable -Dscala-2.11 in sbt
cd42d94 [Sandy Ryza] Update doc
f6644c3 [Sandy Ryza] SPARK-4375 take 2
2014-11-14 14:21:57 -08:00
Takuya UESHIN bbd8f5bee8 [SPARK-4245][SQL] Fix containsNull of the result ArrayType of CreateArray expression.
The `containsNull` of the result `ArrayType` of `CreateArray` should be `true` only if the children is empty or there exists nullable child.

Author: Takuya UESHIN <ueshin@happy-camper.st>

Closes #3110 from ueshin/issues/SPARK-4245 and squashes the following commits:

6f64746 [Takuya UESHIN] Move equalsIgnoreNullability method into DataType.
5a90e02 [Takuya UESHIN] Refine InsertIntoHiveType and add some comments.
cbecba8 [Takuya UESHIN] Fix a test title.
884ec37 [Takuya UESHIN] Merge branch 'master' into issues/SPARK-4245
3c5274b [Takuya UESHIN] Add tests to insert data of types ArrayType / MapType / StructType with nullability is false into Hive table.
41a94a9 [Takuya UESHIN] Replace InsertIntoTable with InsertIntoHiveTable if data types ignoring nullability are same.
43e6ef5 [Takuya UESHIN] Fix containsNull for empty array.
778e997 [Takuya UESHIN] Fix containsNull of the result ArrayType of CreateArray expression.
2014-11-14 14:21:16 -08:00
Michael Armbrust 77e845ca77 [SPARK-4394][SQL] Data Sources API Improvements
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.
2014-11-14 12:00:08 -08:00
Prashant Sharma daaca14c16 Support cross building for Scala 2.11
Let's give this another go using a version of Hive that shades its JLine dependency.

Author: Prashant Sharma <prashant.s@imaginea.com>
Author: Patrick Wendell <pwendell@gmail.com>

Closes #3159 from pwendell/scala-2.11-prashant and squashes the following commits:

e93aa3e [Patrick Wendell] Restoring -Phive-thriftserver profile and cleaning up build script.
f65d17d [Patrick Wendell] Fixing build issue due to merge conflict
a8c41eb [Patrick Wendell] Reverting dev/run-tests back to master state.
7a6eb18 [Patrick Wendell] Merge remote-tracking branch 'apache/master' into scala-2.11-prashant
583aa07 [Prashant Sharma] REVERT ME: removed hive thirftserver
3680e58 [Prashant Sharma] Revert "REVERT ME: Temporarily removing some Cli tests."
935fb47 [Prashant Sharma] Revert "Fixed by disabling a few tests temporarily."
925e90f [Prashant Sharma] Fixed by disabling a few tests temporarily.
2fffed3 [Prashant Sharma] Exclude groovy from sbt build, and also provide a way for such instances in future.
8bd4e40 [Prashant Sharma] Switched to gmaven plus, it fixes random failures observer with its predecessor gmaven.
5272ce5 [Prashant Sharma] SPARK_SCALA_VERSION related bugs.
2121071 [Patrick Wendell] Migrating version detection to PySpark
b1ed44d [Patrick Wendell] REVERT ME: Temporarily removing some Cli tests.
1743a73 [Patrick Wendell] Removing decimal test that doesn't work with Scala 2.11
f5cad4e [Patrick Wendell] Add Scala 2.11 docs
210d7e1 [Patrick Wendell] Revert "Testing new Hive version with shaded jline"
48518ce [Patrick Wendell] Remove association of Hive and Thriftserver profiles.
e9d0a06 [Patrick Wendell] Revert "Enable thritfserver for Scala 2.10 only"
67ec364 [Patrick Wendell] Guard building of thriftserver around Scala 2.10 check
8502c23 [Patrick Wendell] Enable thritfserver for Scala 2.10 only
e22b104 [Patrick Wendell] Small fix in pom file
ec402ab [Patrick Wendell] Various fixes
0be5a9d [Patrick Wendell] Testing new Hive version with shaded jline
4eaec65 [Prashant Sharma] Changed scripts to ignore target.
5167bea [Prashant Sharma] small correction
a4fcac6 [Prashant Sharma] Run against scala 2.11 on jenkins.
80285f4 [Prashant Sharma] MAven equivalent of setting spark.executor.extraClasspath during tests.
034b369 [Prashant Sharma] Setting test jars on executor classpath during tests from sbt.
d4874cb [Prashant Sharma] Fixed Python Runner suite. null check should be first case in scala 2.11.
6f50f13 [Prashant Sharma] Fixed build after rebasing with master. We should use ${scala.binary.version} instead of just 2.10
e56ca9d [Prashant Sharma] Print an error if build for 2.10 and 2.11 is spotted.
937c0b8 [Prashant Sharma] SCALA_VERSION -> SPARK_SCALA_VERSION
cb059b0 [Prashant Sharma] Code review
0476e5e [Prashant Sharma] Scala 2.11 support with repl and all build changes.
2014-11-11 21:36:48 -08:00
Takuya UESHIN a6405c5ddc [SPARK-4270][SQL] Fix Cast from DateType to DecimalType.
`Cast` from `DateType` to `DecimalType` throws `NullPointerException`.

Author: Takuya UESHIN <ueshin@happy-camper.st>

Closes #3134 from ueshin/issues/SPARK-4270 and squashes the following commits:

7394e4b [Takuya UESHIN] Fix Cast from DateType to DecimalType.
2014-11-07 12:30:47 -08:00
Jacky Li 68609c51ad [SQL] Modify keyword val location according to ordering
'DOUBLE' should be moved before 'ELSE' according to the ordering convension

Author: Jacky Li <jacky.likun@gmail.com>

Closes #3080 from jackylk/patch-5 and squashes the following commits:

3c11df7 [Jacky Li] [SQL] Modify keyword val location according to ordering
2014-11-07 11:52:08 -08:00
Michael Armbrust 8154ed7df6 [SQL] Support ScalaReflection of schema in different universes
Author: Michael Armbrust <michael@databricks.com>

Closes #3096 from marmbrus/reflectionContext and squashes the following commits:

adc221f [Michael Armbrust] Support ScalaReflection of schema in different universes
2014-11-07 11:51:20 -08:00
Michael Armbrust 515abb9afa [SQL] Add String option for DSL AS
Author: Michael Armbrust <michael@databricks.com>

Closes #3097 from marmbrus/asString and squashes the following commits:

6430520 [Michael Armbrust] Add String option for DSL AS
2014-11-04 18:14:28 -08:00
Xiangrui Meng 04450d1154 [SPARK-4192][SQL] Internal API for Python UDT
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
2014-11-03 19:29:11 -08:00
Michael Armbrust 15b58a2234 [SQL] Convert arguments to Scala UDFs
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
2014-11-03 18:04:51 -08:00
Cheng Hao e83f13e8d3 [SPARK-4152] [SQL] Avoid data change in CTAS while table already existed
CREATE TABLE t1 (a String);
CREATE TABLE t1 AS SELECT key FROM src; – throw exception
CREATE TABLE if not exists t1 AS SELECT key FROM src; – expect do nothing, currently it will overwrite the t1, which is incorrect.

Author: Cheng Hao <hao.cheng@intel.com>

Closes #3013 from chenghao-intel/ctas_unittest and squashes the following commits:

194113e [Cheng Hao] fix bug in CTAS when table already existed
2014-11-03 13:59:43 -08:00
Cheng Lian c238fb423d [SPARK-4202][SQL] Simple DSL support for Scala UDF
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
2014-11-03 13:20:33 -08:00
Davies Liu 24544fbce0 [SPARK-3594] [PySpark] [SQL] take more rows to infer schema or sampling
This patch will try to infer schema for RDD which has empty value (None, [], {}) in the first row. It will try first 100 rows and merge the types into schema, also merge fields of StructType together. If there is still NullType in schema, then it will show an warning, tell user to try with sampling.

If sampling is presented, it will infer schema from all the rows after sampling.

Also, add samplingRatio for jsonFile() and jsonRDD()

Author: Davies Liu <davies.liu@gmail.com>
Author: Davies Liu <davies@databricks.com>

Closes #2716 from davies/infer and squashes the following commits:

e678f6d [Davies Liu] Merge branch 'master' of github.com:apache/spark into infer
34b5c63 [Davies Liu] Merge branch 'master' of github.com:apache/spark into infer
567dc60 [Davies Liu] update docs
9767b27 [Davies Liu] Merge branch 'master' into infer
e48d7fb [Davies Liu] fix tests
29e94d5 [Davies Liu] let NullType inherit from PrimitiveType
ee5d524 [Davies Liu] Merge branch 'master' of github.com:apache/spark into infer
540d1d5 [Davies Liu] merge fields for StructType
f93fd84 [Davies Liu] add more tests
3603e00 [Davies Liu] take more rows to infer schema, or infer the schema by sampling the RDD
2014-11-03 13:17:09 -08:00
ravipesala 2b6e1ce6ee [SPARK-4207][SQL] Query which has syntax like 'not like' is not working in 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
2014-11-03 13:07:41 -08:00
Joseph K. Bradley ebd6480587 [SPARK-3572] [SQL] Internal API for User-Defined Types
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.
2014-11-02 17:56:00 -08:00
Michael Armbrust 9c0eb57c73 [SPARK-3247][SQL] An API for adding data sources to Spark SQL
This PR introduces a new set of APIs to Spark SQL to allow other developers to add support for reading data from new sources in `org.apache.spark.sql.sources`.

New sources must implement the interface `BaseRelation`, which is responsible for describing the schema of the data.  BaseRelations have three `Scan` subclasses, which are responsible for producing an RDD containing row objects.  The [various Scan interfaces](https://github.com/marmbrus/spark/blob/foreign/sql/core/src/main/scala/org/apache/spark/sql/sources/package.scala#L50) allow for optimizations such as column pruning and filter push down, when the underlying data source can handle these operations.

By implementing a class that inherits from RelationProvider these data sources can be accessed using using pure SQL.  I've used the functionality to update the JSON support so it can now be used in this way as follows:

```sql
CREATE TEMPORARY TABLE jsonTableSQL
USING org.apache.spark.sql.json
OPTIONS (
  path '/home/michael/data.json'
)
```

Further example usage can be found in the test cases: https://github.com/marmbrus/spark/tree/foreign/sql/core/src/test/scala/org/apache/spark/sql/sources

There is also a library that uses this new API to read avro data available here:
https://github.com/marmbrus/sql-avro

Author: Michael Armbrust <michael@databricks.com>

Closes #2475 from marmbrus/foreign and squashes the following commits:

1ed6010 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into foreign
ab2c31f [Michael Armbrust] fix test
1d41bb5 [Michael Armbrust] unify argument names
5b47901 [Michael Armbrust] Remove sealed, more filter types
fab154a [Michael Armbrust] Merge remote-tracking branch 'origin/master' into foreign
e3e690e [Michael Armbrust] Add hook for extraStrategies
a70d602 [Michael Armbrust] Fix style, more tests, FilteredSuite => PrunedFilteredSuite
70da6d9 [Michael Armbrust] Modify API to ease binary compatibility and interop with Java
7d948ae [Michael Armbrust] Fix equality of AttributeReference.
5545491 [Michael Armbrust] Address comments
5031ac3 [Michael Armbrust] Merge remote-tracking branch 'origin/master' into foreign
22963ef [Michael Armbrust] package objects compile wierdly...
b069146 [Michael Armbrust] traits => abstract classes
34f836a [Michael Armbrust] Make @DeveloperApi
0d74bcf [Michael Armbrust] Add documention on object life cycle
3e06776 [Michael Armbrust] remove line wraps
de3b68c [Michael Armbrust] Remove empty file
360cb30 [Michael Armbrust] style and java api
2957875 [Michael Armbrust] add override
0fd3a07 [Michael Armbrust] Draft of data sources API
2014-11-02 15:08:35 -08:00
Matei Zaharia 23f966f475 [SPARK-3930] [SPARK-3933] Support fixed-precision decimal in SQL, and some optimizations
- Adds optional precision and scale to Spark SQL's decimal type, which behave similarly to those in Hive 13 (https://cwiki.apache.org/confluence/download/attachments/27362075/Hive_Decimal_Precision_Scale_Support.pdf)
- Replaces our internal representation of decimals with a Decimal class that can store small values in a mutable Long, saving memory in this situation and letting some operations happen directly on Longs

This is still marked WIP because there are a few TODOs, but I'll remove that tag when done.

Author: Matei Zaharia <matei@databricks.com>

Closes #2983 from mateiz/decimal-1 and squashes the following commits:

35e6b02 [Matei Zaharia] Fix issues after merge
227f24a [Matei Zaharia] Review comments
31f915e [Matei Zaharia] Implement Davies's suggestions in Python
eb84820 [Matei Zaharia] Support reading/writing decimals as fixed-length binary in Parquet
4dc6bae [Matei Zaharia] Fix decimal support in PySpark
d1d9d68 [Matei Zaharia] Fix compile error and test issues after rebase
b28933d [Matei Zaharia] Support decimal precision/scale in Hive metastore
2118c0d [Matei Zaharia] Some test and bug fixes
81db9cb [Matei Zaharia] Added mutable Decimal that will be more efficient for small precisions
7af0c3b [Matei Zaharia] Add optional precision and scale to DecimalType, but use Unlimited for now
ec0a947 [Matei Zaharia] Make the result of AVG on Decimals be Decimal, not Double
2014-11-01 19:29:14 -07:00
Xiangrui Meng 1d4f355203 [SPARK-3569][SQL] Add metadata field to StructField
Add `metadata: Metadata` to `StructField` to store extra information of columns. `Metadata` is a simple wrapper over `Map[String, Any]` with value types restricted to Boolean, Long, Double, String, Metadata, and arrays of those types. SerDe is via JSON.

Metadata is preserved through simple operations like `SELECT`.

marmbrus liancheng

Author: Xiangrui Meng <meng@databricks.com>
Author: Michael Armbrust <michael@databricks.com>

Closes #2701 from mengxr/structfield-metadata and squashes the following commits:

dedda56 [Xiangrui Meng] merge remote
5ef930a [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into structfield-metadata
c35203f [Xiangrui Meng] Merge pull request #1 from marmbrus/pr/2701
886b85c [Michael Armbrust] Expose Metadata and MetadataBuilder through the public scala and java packages.
589f314 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into structfield-metadata
1e2abcf [Xiangrui Meng] change default value of metadata to None in python
611d3c2 [Xiangrui Meng] move metadata from Expr to NamedExpr
ddfcfad [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into structfield-metadata
a438440 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into structfield-metadata
4266f4d [Xiangrui Meng] add StructField.toString back for backward compatibility
3f49aab [Xiangrui Meng] remove StructField.toString
24a9f80 [Xiangrui Meng] Merge remote-tracking branch 'apache/master' into structfield-metadata
473a7c5 [Xiangrui Meng] merge master
c9d7301 [Xiangrui Meng] organize imports
1fcbf13 [Xiangrui Meng] change metadata type in StructField for Scala/Java
60cc131 [Xiangrui Meng] add doc and header
60614c7 [Xiangrui Meng] add metadata
e42c452 [Xiangrui Meng] merge master
93518fb [Xiangrui Meng] support metadata in python
905bb89 [Xiangrui Meng] java conversions
618e349 [Xiangrui Meng] make tests work in scala
61b8e0f [Xiangrui Meng] merge master
7e5a322 [Xiangrui Meng] do not output metadata in StructField.toString
c41a664 [Xiangrui Meng] merge master
d8af0ed [Xiangrui Meng] move tests to SQLQuerySuite
67fdebb [Xiangrui Meng] add test on join
d65072e [Xiangrui Meng] remove Map.empty
367d237 [Xiangrui Meng] add test
c194d5e [Xiangrui Meng] add metadata field to StructField and Attribute
2014-11-01 14:37:00 -07:00
Cheng Lian 23468e7e96 [SPARK-2220][SQL] Fixes remaining Hive commands
This PR adds support for the `ADD FILE` Hive command, and removes `ShellCommand` and `SourceCommand`. The reason is described in [this SPARK-2220 comment](https://issues.apache.org/jira/browse/SPARK-2220?focusedCommentId=14191841&page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#comment-14191841).

Author: Cheng Lian <lian.cs.zju@gmail.com>

Closes #3038 from liancheng/hive-commands and squashes the following commits:

6db61e0 [Cheng Lian] Fixes remaining Hive commands
2014-10-31 11:34:51 -07:00
ravipesala ea465af12d [SPARK-4154][SQL] Query does not work if it has "not between " in Spark SQL and HQL
if the query contains "not between" does not work like.
SELECT * FROM src where key not between 10 and 20'

Author: ravipesala <ravindra.pesala@huawei.com>

Closes #3017 from ravipesala/SPARK-4154 and squashes the following commits:

65fc89e [ravipesala] Handled admin comments
32e6d42 [ravipesala] 'not between' is not working
2014-10-31 11:33:20 -07:00
Anant d31517a3cd [SPARK-4108][SQL] Fixed usage of deprecated in sql/catalyst/types/datatypes
Fixed usage of deprecated in sql/catalyst/types/datatypes to have versio...n parameter

Author: Anant <anant.asty@gmail.com>

Closes #2970 from anantasty/SPARK-4108 and squashes the following commits:

e92cb01 [Anant] Fixed usage of deprecated in sql/catalyst/types/datatypes to have version parameter
2014-10-30 23:02:42 -07:00
ravipesala 9b6ebe33db [SPARK-4120][SQL] Join of multiple tables with syntax like SELECT .. FROM T1,T2,T3.. does not work in SparkSQL
Right now it works for only 2 tables like below query.
sql("SELECT * FROM records1 as a,records2 as b where a.key=b.key ")

But it does not work for more than 2 tables like below query
sql("SELECT * FROM records1 as a,records2 as b,records3 as c where a.key=b.key and a.key=c.key").

Author: ravipesala <ravindra.pesala@huawei.com>

Closes #2987 from ravipesala/multijoin and squashes the following commits:

429b005 [ravipesala] Support multiple joins
2014-10-30 17:15:45 -07:00
Cheng Hao 4b55482abf [SPARK-3343] [SQL] Add serde support for CTAS
Currently, `CTAS` (Create Table As Select) doesn't support specifying the `SerDe` in HQL. This PR will pass down the `ASTNode` into the physical operator `execution.CreateTableAsSelect`, which will extract the `CreateTableDesc` object via Hive `SemanticAnalyzer`. In the meantime, I also update the `HiveMetastoreCatalog.createTable` to optionally support the `CreateTableDesc` for table creation.

Author: Cheng Hao <hao.cheng@intel.com>

Closes #2570 from chenghao-intel/ctas_serde and squashes the following commits:

e011ef5 [Cheng Hao] shim for both 0.12 & 0.13.1
cfb3662 [Cheng Hao] revert to hive 0.12
c8a547d [Cheng Hao] Support SerDe properties within CTAS
2014-10-28 14:36:06 -07:00
Daoyuan Wang 47a40f60d6 [SPARK-3988][SQL] add public API for date type
Add json and python api for date type.
By using Pickle, `java.sql.Date` was serialized as calendar, and recognized in python as `datetime.datetime`.

Author: Daoyuan Wang <daoyuan.wang@intel.com>

Closes #2901 from adrian-wang/spark3988 and squashes the following commits:

c51a24d [Daoyuan Wang] convert datetime to date
5670626 [Daoyuan Wang] minor line combine
f760d8e [Daoyuan Wang] fix indent
444f100 [Daoyuan Wang] fix a typo
1d74448 [Daoyuan Wang] fix scala style
8d7dd22 [Daoyuan Wang] add json and python api for date type
2014-10-28 13:43:25 -07:00
ravipesala 5807cb40ae [SPARK-3814][SQL] Support for Bitwise AND(&), OR(|) ,XOR(^), NOT(~) in Spark HQL and SQL
Currently there is no support of Bitwise & , | in Spark HiveQl and Spark SQL as well. So this PR support the same.
I am closing https://github.com/apache/spark/pull/2926 as it has conflicts to merge. And also added support for Bitwise AND(&), OR(|) ,XOR(^), NOT(~) And I handled all review comments in that PR

Author: ravipesala <ravindra.pesala@huawei.com>

Closes #2961 from ravipesala/SPARK-3814-NEW4 and squashes the following commits:

a391c7a [ravipesala] Rebase with master
2014-10-28 13:36:06 -07:00
Cheng Hao 418ad83fe1 [SPARK-3911] [SQL] HiveSimpleUdf can not be optimized in constant folding
```
explain extended select cos(null) from src limit 1;
```
outputs:
```
 Project [HiveSimpleUdf#org.apache.hadoop.hive.ql.udf.UDFCos(null) AS c_0#5]
  MetastoreRelation default, src, None

== Optimized Logical Plan ==
Limit 1
 Project [HiveSimpleUdf#org.apache.hadoop.hive.ql.udf.UDFCos(null) AS c_0#5]
  MetastoreRelation default, src, None

== Physical Plan ==
Limit 1
 Project [HiveSimpleUdf#org.apache.hadoop.hive.ql.udf.UDFCos(null) AS c_0#5]
  HiveTableScan [], (MetastoreRelation default, src, None), None
```
After patching this PR it outputs
```
== Parsed Logical Plan ==
Limit 1
 Project ['cos(null) AS c_0#0]
  UnresolvedRelation None, src, None

== Analyzed Logical Plan ==
Limit 1
 Project [HiveSimpleUdf#org.apache.hadoop.hive.ql.udf.UDFCos(null) AS c_0#0]
  MetastoreRelation default, src, None

== Optimized Logical Plan ==
Limit 1
 Project [null AS c_0#0]
  MetastoreRelation default, src, None

== Physical Plan ==
Limit 1
 Project [null AS c_0#0]
  HiveTableScan [], (MetastoreRelation default, src, None), None
```

Author: Cheng Hao <hao.cheng@intel.com>

Closes #2771 from chenghao-intel/hive_udf_constant_folding and squashes the following commits:

1379c73 [Cheng Hao] duplicate the PlanTest with catalyst/plans/PlanTest
1e52dda [Cheng Hao] add unit test for hive simple udf constant folding
01609ff [Cheng Hao] support constant folding for HiveSimpleUdf
2014-10-27 20:42:05 -07:00
Kousuke Saruta 3a9d66cf59 [SPARK-4061][SQL] We cannot use EOL character in the operand of LIKE predicate.
We cannot use EOL character like \n or \r in the operand of LIKE predicate.
So following condition is never true.

    -- someStr is 'hoge\nfuga'
    where someStr LIKE 'hoge_fuga'

Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>

Closes #2908 from sarutak/spark-sql-like-match-modification and squashes the following commits:

d15798b [Kousuke Saruta] Remove test setting for thriftserver
f99a2f4 [Kousuke Saruta] Fixed LIKE predicate so that we can use EOL character as in a operand
2014-10-26 16:54:07 -07:00
Kousuke Saruta ace41e8bf2 [SPARK-3959][SPARK-3960][SQL] SqlParser fails to parse literal -9223372036854775808 (Long.MinValue). / We can apply unary minus only to literal.
SqlParser fails to parse -9223372036854775808 (Long.MinValue) so we cannot write queries such like as follows.

    SELECT value FROM someTable WHERE value > -9223372036854775808

Additionally, because of the wrong syntax definition, we cannot apply unary minus only to literal. So, we cannot write such expressions.

    -(value1 + value2) // Parenthesized expressions
    -column // Columns
    -MAX(column) // Functions

Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>

Closes #2816 from sarutak/spark-sql-dsl-improvement2 and squashes the following commits:

32a5005 [Kousuke Saruta] Remove test setting for thriftserver
c2bab5e [Kousuke Saruta] Fixed SPARK-3959 and SPARK-3960
2014-10-26 16:40:29 -07:00
ravipesala 974d7b238b [SPARK-3483][SQL] Special chars in column names
Supporting special chars in column names by using back ticks. Closed https://github.com/apache/spark/pull/2804 and created this PR as it has merge conflicts

Author: ravipesala <ravindra.pesala@huawei.com>

Closes #2927 from ravipesala/SPARK-3483-NEW and squashes the following commits:

f6329f3 [ravipesala] Rebased with master
2014-10-26 16:36:11 -07:00
Yin Huai 05308426f0 [SPARK-4052][SQL] Use scala.collection.Map for pattern matching instead of using Predef.Map (it is scala.collection.immutable.Map)
Please check https://issues.apache.org/jira/browse/SPARK-4052 for cases triggering this bug.

Author: Yin Huai <huai@cse.ohio-state.edu>

Closes #2899 from yhuai/SPARK-4052 and squashes the following commits:

1188f70 [Yin Huai] Address liancheng's comments.
b6712be [Yin Huai] Use scala.collection.Map instead of Predef.Map (scala.collection.immutable.Map).
2014-10-26 16:30:15 -07:00
Kousuke Saruta d518bc24af [SPARK-3953][SQL][Minor] Confusable variable name.
In SqlParser.scala, there is following code.

    case d ~ p ~ r ~ f ~ g ~ h ~ o ~ l  =>
      val base = r.getOrElse(NoRelation)
      val withFilter = f.map(f => Filter(f, base)).getOrElse(base)

In the code above, there are 2 variables which have same name "f" in near place.
One is receiver "f" and other is bound variable "f".

Author: Kousuke Saruta <sarutak@oss.nttdata.co.jp>

Closes #2807 from sarutak/SPARK-3953 and squashes the following commits:

4957c32 [Kousuke Saruta] Improved variable name in SqlParser.scala
2014-10-26 16:28:33 -07:00
Cheng Lian 2838bf8aad [SPARK-3537][SPARK-3914][SQL] Refines in-memory columnar table statistics
This PR refines in-memory columnar table statistics:

1. adds 2 more statistics for in-memory table columns: `count` and `sizeInBytes`
1. adds filter pushdown support for `IS NULL` and `IS NOT NULL`.
1. caches and propagates statistics in `InMemoryRelation` once the underlying cached RDD is materialized.

   Statistics are collected to driver side with an accumulator.

This PR also fixes SPARK-3914 by properly propagating in-memory statistics.

Author: Cheng Lian <lian@databricks.com>

Closes #2860 from liancheng/propagates-in-mem-stats and squashes the following commits:

0cc5271 [Cheng Lian] Restricts visibility of o.a.s.s.c.p.l.Statistics
c5ff904 [Cheng Lian] Fixes test table name conflict
a8c818d [Cheng Lian] Refines tests
1d01074 [Cheng Lian] Bug fix: shouldn't call STRING.actualSize on null string value
7dc6a34 [Cheng Lian] Adds more in-memory table statistics and propagates them properly
2014-10-26 16:10:09 -07:00
Liang-Chi Hsieh 0af7e514c6 [SPARK-3925][SQL] Do not consider the ordering of qualifiers during comparison
The orderings should not be considered during the comparison between old qualifiers and new qualifiers.

Author: Liang-Chi Hsieh <viirya@gmail.com>

Closes #2783 from viirya/full_qualifier_comp and squashes the following commits:

89f652c [Liang-Chi Hsieh] modification for comment.
abb5762 [Liang-Chi Hsieh] More comprehensive comparison of qualifiers.
2014-10-26 14:29:13 -07:00
Josh Rosen bf589fc717 [SPARK-3616] Add basic Selenium tests to WebUISuite
This patch adds Selenium tests for Spark's web UI.  To avoid adding extra
dependencies to the test environment, the tests use Selenium's HtmlUnitDriver,
which is pure-Java, instead of, say, ChromeDriver.

I added new tests to try to reproduce a few UI bugs reported on JIRA, namely
SPARK-3021, SPARK-2105, and SPARK-2527.  I wasn't able to reproduce these bugs;
I suspect that the older ones might have been fixed by other patches.

In order to use HtmlUnitDriver, I added an explicit dependency on the
org.apache.httpcomponents version of httpclient in order to prevent jets3t's
older version from taking precedence on the classpath.

I also upgraded ScalaTest to 2.2.1.

Author: Josh Rosen <joshrosen@apache.org>
Author: Josh Rosen <joshrosen@databricks.com>

Closes #2474 from JoshRosen/webui-selenium-tests and squashes the following commits:

fcc9e83 [Josh Rosen] scalautils -> scalactic package rename
510e54a [Josh Rosen] [SPARK-3616] Add basic Selenium tests to WebUISuite.
2014-10-26 11:29:27 -07:00
Michael Armbrust 3a845d3c04 [SQL] Update Hive test harness for Hive 12 and 13
As part of the upgrade I also copy the newest version of the query tests, and whitelist a bunch of new ones that are now passing.

Author: Michael Armbrust <michael@databricks.com>

Closes #2936 from marmbrus/fix13tests and squashes the following commits:

d9cbdab [Michael Armbrust] Remove user specific tests
65801cd [Michael Armbrust] style and rat
8f6b09a [Michael Armbrust] Update test harness to work with both Hive 12 and 13.
f044843 [Michael Armbrust] Update Hive query tests and golden files to 0.13
2014-10-24 18:36:35 -07:00
Michael Armbrust 0e886610ee [SPARK-4050][SQL] Fix caching of temporary tables with projections.
Previously cached data was found by `sameResult` plan matching on optimized plans.  This technique however fails to locate the cached data when a temporary table with a projection is queried with a further reduced projection.  The failure is due to the fact that optimization will collapse the projections, producing a plan that no longer produces the sameResult as the cached data (though the cached data still subsumes the desired data).  For example consider the following previously failing test case.

```scala
sql("CACHE TABLE tempTable AS SELECT key FROM testData")
assertCached(sql("SELECT COUNT(*) FROM tempTable"))
```

In this PR I change the matching to occur after analysis instead of optimization, so that in the case of temporary tables, the plans will always match.  I think this should work generally, however, this error does raise questions about the need to do more thorough subsumption checking when locating cached data.

Another question is what sort of semantics we want to provide when uncaching data from temporary tables.  For example consider the following sequence of commands:

```scala
testData.select('key).registerTempTable("tempTable1")
testData.select('key).registerTempTable("tempTable2")
cacheTable("tempTable1")

// This obviously works.
assertCached(sql("SELECT COUNT(*) FROM tempTable1"))

// It seems good that this works ...
assertCached(sql("SELECT COUNT(*) FROM tempTable2"))

// ... but is this valid?
uncacheTable("tempTable2")

// Should this still be cached?
assertCached(sql("SELECT COUNT(*) FROM tempTable1"), 0)
```

Author: Michael Armbrust <michael@databricks.com>

Closes #2912 from marmbrus/cachingBug and squashes the following commits:

9c822d4 [Michael Armbrust] remove commented out code
5c72fb7 [Michael Armbrust] Add a test case / question about uncaching semantics.
63a23e4 [Michael Armbrust] Perform caching on analyzed instead of optimized plan.
03f1cfe [Michael Armbrust] Clean-up / add tests to SameResult suite.
2014-10-24 10:52:25 -07:00