This PR might have some issues with #3732 ,
and this would have merge conflicts with #3820 so the review can be delayed till that 2 were merged.
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#3822 from adrian-wang/parquetdate and squashes the following commits:
2c5d54d [Daoyuan Wang] add a test case
faef887 [Daoyuan Wang] parquet support for primitive date
97e9080 [Daoyuan Wang] parquet support for date type
Author: vinodkc <vinod.kc.in@gmail.com>
Closes#5112 from vinodkc/spark_1.3_doc_fixes and squashes the following commits:
2c6aee6 [vinodkc] Spark 1.3 doc fixes
Author: Reynold Xin <rxin@databricks.com>
Closes#5108 from rxin/hive-public-type and squashes the following commits:
a320328 [Reynold Xin] [SPARK-6428][SQL] Added explicit type for all public methods for Hive module.
This PR creates a trait `DataTypeParser` used to parse data types. This trait aims to be single place to provide the functionality of parsing data types' string representation. It is currently mixed in with `DDLParser` and `SqlParser`. It is also used to parse the data type for `DataFrame.cast` and to convert Hive metastore's data type string back to a `DataType`.
JIRA: https://issues.apache.org/jira/browse/SPARK-6250
Author: Yin Huai <yhuai@databricks.com>
Closes#5078 from yhuai/ddlKeywords and squashes the following commits:
0e66097 [Yin Huai] Special handle struct<>.
fea6012 [Yin Huai] Style.
c9733fb [Yin Huai] Create a trait to parse data types.
SELECT sum('a'), avg('a'), variance('a'), std('a') FROM src;
Should give output as
0.0 NULL NULL NULL
This fixes hive udaf_number_format.q
Author: Venkata Ramana G <ramana.gollamudihuawei.com>
Author: Venkata Ramana Gollamudi <ramana.gollamudi@huawei.com>
Closes#4466 from gvramana/sum_fix and squashes the following commits:
42e14d1 [Venkata Ramana Gollamudi] Added comments
39415c0 [Venkata Ramana Gollamudi] Handled the partitioned Sum expression scenario
df66515 [Venkata Ramana Gollamudi] code style fix
4be2606 [Venkata Ramana Gollamudi] Add udaf_number_format to whitelist and golden answer
330fd64 [Venkata Ramana Gollamudi] fix sum function for all null data
Because of no statistics override, in spute of super class say 'LeafNode must override'.
fix issue
[SPARK-5320: Joins on simple table created using select gives error](https://issues.apache.org/jira/browse/SPARK-5320)
Author: x1- <viva008@gmail.com>
Closes#5105 from x1-/SPARK-5320 and squashes the following commits:
e561aac [x1-] Add statistics method at NoRelation (override super).
When using "CREATE TEMPORARY TABLE AS SELECT" to create JSON table, we first delete the path file or directory and then generate a new directory with the same name. But if only read permission was granted, the delete failed.
Here we just throwing an error message to let users know what happened.
ParquetRelation2 may also hit this problem. I think to restrict JSONRelation and ParquetRelation2 must base on directory is more reasonable for access control. Maybe I can do it in follow up works.
Author: Yanbo Liang <ybliang8@gmail.com>
Author: Yanbo Liang <yanbohappy@gmail.com>
Closes#4610 from yanboliang/jsonInsertImprovements and squashes the following commits:
c387fce [Yanbo Liang] fix typos
42d7fb6 [Yanbo Liang] add unittest & fix output format
46f0d9d [Yanbo Liang] Update JSONRelation.scala
e2df8d5 [Yanbo Liang] check path exisit when write
79f7040 [Yanbo Liang] Update JSONRelation.scala
e4bc229 [Yanbo Liang] Update JSONRelation.scala
5a42d83 [Yanbo Liang] JSONRelation CTAS should check if delete is successful
When writing Parquet files, Spark 1.1.x persists the schema string into Parquet metadata with the result of `StructType.toString`, which was then deprecated in Spark 1.2 by a schema string in JSON format. But we still need to take the old schema format into account while reading Parquet files.
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Author: Cheng Lian <lian@databricks.com>
Closes#5034 from liancheng/spark-6315 and squashes the following commits:
a182f58 [Cheng Lian] Adds a regression test
b9c6dbe [Cheng Lian] Also tries the case class string parser while reading Parquet schema
Do the same check as #4610 for ParquetRelation2.
Author: Yanbo Liang <ybliang8@gmail.com>
Closes#5107 from yanboliang/spark-5821-parquet and squashes the following commits:
7092c8d [Yanbo Liang] ParquetRelation2 CTAS should check if delete is successful
Also implemented equals/hashCode when they are missing.
This is done in order to enable automatic public method type checking.
Author: Reynold Xin <rxin@databricks.com>
Closes#5104 from rxin/sql-hashcode-explicittype and squashes the following commits:
ffce6f3 [Reynold Xin] Code review feedback.
8b36733 [Reynold Xin] [SPARK-6428][SQL] Added explicit type for all public methods.
Use `Utils.createTempDir()` to replace other temp file mechanisms used in some tests, to further ensure they are cleaned up, and simplify
Author: Sean Owen <sowen@cloudera.com>
Closes#5029 from srowen/SPARK-6338 and squashes the following commits:
27b740a [Sean Owen] Fix hive-thriftserver tests that don't expect an existing dir
4a212fa [Sean Owen] Standardize a bit more temp dir management
9004081 [Sean Owen] Revert some added recursive-delete calls
57609e4 [Sean Owen] Use Utils.createTempDir() to replace other temp file mechanisms used in some tests, to further ensure they are cleaned up, and simplify
We need to handle ambiguous `exprId`s that are produced by new aliases as well as those caused by leaf nodes (`MultiInstanceRelation`).
Attempting to fix this revealed a bug in `equals` for `Alias` as these objects were comparing equal even when the expression ids did not match. Additionally, `LocalRelation` did not correctly provide statistics, and some tests in `catalyst` and `hive` were not using the helper functions for comparing plans.
Based on #4991 by chenghao-intel
Author: Michael Armbrust <michael@databricks.com>
Closes#5062 from marmbrus/selfJoins and squashes the following commits:
8e9b84b [Michael Armbrust] check qualifier too
8038a36 [Michael Armbrust] handle aggs too
0b9c687 [Michael Armbrust] fix more tests
c3c574b [Michael Armbrust] revert change.
725f1ab [Michael Armbrust] add statistics
a925d08 [Michael Armbrust] check for conflicting attributes in join resolution
b022ef7 [Michael Armbrust] Handle project aliases.
d8caa40 [Michael Armbrust] test case: SPARK-6247
f9c67c2 [Michael Armbrust] Check for duplicate attributes in join resolution.
898af73 [Michael Armbrust] Fix Alias equality.
Now spark version is only support
```create table table_in_database_creation.test1 as select * from src limit 1;``` in HiveContext.
This patch is used to support
```create table `table_in_database_creation.test2` as select * from src limit 1;``` in HiveContext.
Author: watermen <qiyadong2010@gmail.com>
Author: q00251598 <qiyadong@huawei.com>
Closes#4427 from watermen/SPARK-5651 and squashes the following commits:
c5c8ed1 [watermen] add the generated golden files
1f0e42e [q00251598] add input64 in blacklist and add test suit
By default, the statistic for logical plan with multiple children is quite aggressive, and those statistic are quite critical for the join optimization, hence we need to estimate the statistics as accurate as possible.
For `Union`, which has 2 children, and overwrite the default implementation by `adding` its children `byteInSize` instead of `multiplying`.
For `Expand`, which only has a single child, but it will grows the size, and we need to multiply its inflating factor.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#4914 from chenghao-intel/statistic and squashes the following commits:
d466bbc [Cheng Hao] Update the default statistic
`ResolveUdtfsAlias` in `hiveUdfs` only considers the `HiveGenericUdtf` with multiple alias. When only single alias is used with `HiveGenericUdtf`, the alias is not working.
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#4692 from viirya/udft_alias and squashes the following commits:
8a3bae4 [Liang-Chi Hsieh] No need to test selected column from DataFrame since DataFrame API is updated.
160a379 [Liang-Chi Hsieh] Merge remote-tracking branch 'upstream/master' into udft_alias
e6531cc [Liang-Chi Hsieh] Selected column from DataFrame should not re-analyze logical plan.
a45cc2a [Liang-Chi Hsieh] Resolve UdtfsAlias when only single Alias is used.
When getting file statuses, create file system from each path instead of a single one from hadoop configuration.
Author: Pei-Lun Lee <pllee@appier.com>
Closes#5039 from ypcat/spark-6351 and squashes the following commits:
a19a3fe [Pei-Lun Lee] [SPARK-6330] [SQL] fix test
506f5a0 [Pei-Lun Lee] [SPARK-6351] [SQL] fix test
fa2290e [Pei-Lun Lee] [SPARK-6330] [SQL] Rename test case and add comment
606c967 [Pei-Lun Lee] Merge branch 'master' of https://github.com/apache/spark into spark-6351
896e80a [Pei-Lun Lee] [SPARK-6351] [SQL] Add test case
2ae0916 [Pei-Lun Lee] [SPARK-6351] [SQL] ParquetRelation2 supporting multiple file systems
Error in the code sample of the `implicits` object in `SQLContext`.
Author: Lomig Mégard <lomig.megard@gmail.com>
Closes#5051 from tarfaa/simple and squashes the following commits:
5a88acc [Lomig Mégard] [docs][minor] Fixed sample code in SQLContext scaladoc
---- comment;
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#4500 from adrian-wang/semicolon and squashes the following commits:
70b8abb [Daoyuan Wang] use mkstring instead of reduce
2d49738 [Daoyuan Wang] remove outdated golden file
317346e [Daoyuan Wang] only skip comment with semicolon at end of line, to avoid golden file outdated
d3ae01e [Daoyuan Wang] fix error
a11602d [Daoyuan Wang] fix comment with semicolon at end
If I'm running this locally and my path points to S3, this would currently error out because of incorrect FS.
I tested this in a scenario that previously didn't work, this change seemed to fix the issue.
Author: Volodymyr Lyubinets <vlyubin@gmail.com>
Closes#5020 from vlyubin/parquertbug and squashes the following commits:
a645ad5 [Volodymyr Lyubinets] Fix filesystem bug in newParquet relation
Still, we keep only a single HiveContext within ThriftServer, and we also create a object called `SQLSession` for isolating the different user states.
Developers can obtain/release a new user session via `openSession` and `closeSession`, and `SQLContext` and `HiveContext` will also provide a default session if no `openSession` called, for backward-compatibility.
Author: Cheng Hao <hao.cheng@intel.com>
Closes#4885 from chenghao-intel/multisessions_singlecontext and squashes the following commits:
1c47b2a [Cheng Hao] rename the tss => tlSession
815b27a [Cheng Hao] code style issue
57e3fa0 [Cheng Hao] openSession is not compatible between Hive0.12 & 0.13.1
4665b0d [Cheng Hao] thriftservice with single context
This is a following clean up PR for #5010
This will resolve issues when launching `hive/console` like below:
```
<console>:20: error: object ParquetTestData is not a member of package org.apache.spark.sql.parquet
import org.apache.spark.sql.parquet.ParquetTestData
```
Author: OopsOutOfMemory <victorshengli@126.com>
Closes#5032 from OopsOutOfMemory/SPARK-6285 and squashes the following commits:
2996aeb [OopsOutOfMemory] remove ParquetTestData
This PR adds a specialized in-memory column type for fixed-precision decimals.
For all other column types, a single integer column type ID is enough to determine which column type to use. However, this doesn't apply to fixed-precision decimal types with different precision and scale parameters. Moreover, according to the previous design, there seems no trivial way to encode precision and scale information into the columnar byte buffer. On the other hand, considering we always know the data type of the column to be built / scanned ahead of time. This PR no longer use column type ID to construct `ColumnBuilder`s and `ColumnAccessor`s, but resorts to the actual column data type. In this way, we can pass precision / scale information along the way.
The column type ID is now not used anymore and can be removed in a future PR.
### Micro benchmark result
The following micro benchmark builds a simple table with 2 million decimals (precision = 10, scale = 0), cache it in memory, then count all the rows. Code (simply paste it into Spark shell):
```scala
import sc._
import sqlContext._
import sqlContext.implicits._
import org.apache.spark.sql.types._
import com.google.common.base.Stopwatch
def benchmark(n: Int)(f: => Long) {
val stopwatch = new Stopwatch()
def run() = {
stopwatch.reset()
stopwatch.start()
f
stopwatch.stop()
stopwatch.elapsedMillis()
}
val records = (0 until n).map(_ => run())
(0 until n).foreach(i => println(s"Round $i: ${records(i)} ms"))
println(s"Average: ${records.sum / n.toDouble} ms")
}
// Explicit casting is required because ScalaReflection can't inspect decimal precision
parallelize(1 to 2000000)
.map(i => Tuple1(Decimal(i, 10, 0)))
.toDF("dec")
.select($"dec" cast DecimalType(10, 0))
.registerTempTable("dec")
sql("CACHE TABLE dec")
val df = table("dec")
// Warm up
df.count()
df.count()
benchmark(5) {
df.count()
}
```
With `FIXED_DECIMAL` column type:
- Round 0: 75 ms
- Round 1: 97 ms
- Round 2: 75 ms
- Round 3: 70 ms
- Round 4: 72 ms
- Average: 77.8 ms
Without `FIXED_DECIMAL` column type:
- Round 0: 1233 ms
- Round 1: 1170 ms
- Round 2: 1171 ms
- Round 3: 1141 ms
- Round 4: 1141 ms
- Average: 1171.2 ms
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Author: Cheng Lian <lian@databricks.com>
Closes#4938 from liancheng/decimal-column-type and squashes the following commits:
fef5338 [Cheng Lian] Updates fixed decimal column type related test cases
e08ab5b [Cheng Lian] Only resorts to FIXED_DECIMAL when the value can be held in a long
4db713d [Cheng Lian] Adds in-memory column type for fixed-precision decimals
Author: ArcherShao <ArcherShao@users.noreply.github.com>
Author: ArcherShao <shaochuan@huawei.com>
Closes#5007 from ArcherShao/20150313 and squashes the following commits:
ae422ae [ArcherShao] Updated
459efbd [ArcherShao] [SQL]Delete some dupliate code in HiveThriftServer2
use prettyString instead of toString() (which include id of expression) as column name in agg()
Author: Davies Liu <davies@databricks.com>
Closes#5006 from davies/prettystring and squashes the following commits:
cb1fdcf [Davies Liu] use prettyString as column name in agg()
Author: vinodkc <vinod.kc.in@gmail.com>
Author: Vinod K C <vinod.kc@huawei.com>
Closes#5011 from vinodkc/HIVE_console_startupError and squashes the following commits:
b43925f [vinodkc] Changed order of import
b4f5453 [Vinod K C] Fixed HIVE console startup issue
All the contents in this file are not referenced anywhere and should have been removed in #4116 when I tried to get rid of the old Parquet test suites.
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Author: Cheng Lian <lian@databricks.com>
Closes#5010 from liancheng/spark-6285 and squashes the following commits:
06ed057 [Cheng Lian] Removes unused ParquetTestData and duplicated TestGroupWriteSupport
Author: Volodymyr Lyubinets <vlyubin@gmail.com>
Closes#4988 from vlyubin/columncomp and squashes the following commits:
92d7c8f [Volodymyr Lyubinets] Added equals to Column
Avoid `UnsupportedOperationException` from JsonRDD.inferSchema on empty RDD.
Not sure if this is supposed to be an error (but a better one), but it seems like this case can come up if the input is down-sampled so much that nothing is sampled.
Now stuff like this:
```
sqlContext.jsonRDD(sc.parallelize(List[String]()))
```
just results in
```
org.apache.spark.sql.DataFrame = []
```
Author: Sean Owen <sowen@cloudera.com>
Closes#4971 from srowen/SPARK-6245 and squashes the following commits:
3699964 [Sean Owen] Set() -> Set.empty
3c619e1 [Sean Owen] Avoid UnsupportedOperationException from JsonRDD.inferSchema on empty RDD
Resolve javac, scalac warnings of various types -- deprecations, Scala lang, unchecked cast, etc.
Author: Sean Owen <sowen@cloudera.com>
Closes#4950 from srowen/SPARK-6225 and squashes the following commits:
3080972 [Sean Owen] Ordered imports: Java, Scala, 3rd party, Spark
c67985b [Sean Owen] Resolve javac, scalac warnings of various types -- deprecations, Scala lang, unchecked cast, etc.
Removed an repeated "from" in the comments.
Author: Hongbo Liu <liuhb86@gmail.com>
Closes#4976 from liuhb86/mine and squashes the following commits:
e280e7c [Hongbo Liu] [SQL][Minor] fix typo in comments
The extra blank line is preventing the first lines from showing up in the package summary page.
Author: Reynold Xin <rxin@databricks.com>
Closes#4955 from rxin/datatype-docs and squashes the following commits:
1621114 [Reynold Xin] Minor doc: Remove the extra blank line in data types javadoc.
Author: Michael Armbrust <michael@databricks.com>
Closes#4920 from marmbrus/openStrategies and squashes the following commits:
cbc35c0 [Michael Armbrust] [SQL] Make Strategies a public developer API
jira: https://issues.apache.org/jira/browse/SPARK-6163
Author: Yin Huai <yhuai@databricks.com>
Closes#4896 from yhuai/SPARK-6163 and squashes the following commits:
45e023e [Yin Huai] Address @chenghao-intel's comment.
2e8734e [Yin Huai] Use JSON data source for jsonFile.
92a4a33 [Yin Huai] Test.
Based on #4904 with style errors fixed.
`LogicalPlan#resolve` will not only produce `Attribute`, but also "`GetField` chain".
So in `ResolveSortReferences`, after resolve the ordering expressions, we should not just collect the `Attribute` results, but also `Attribute` at the bottom of "`GetField` chain".
Author: Wenchen Fan <cloud0fan@outlook.com>
Author: Michael Armbrust <michael@databricks.com>
Closes#4918 from marmbrus/pr/4904 and squashes the following commits:
997f84e [Michael Armbrust] fix style
3eedbfc [Wenchen Fan] fix 6145
Option 1 of 2: Convert spark-parent module name to spark-parent_2.10 / spark-parent_2.11
Author: Sean Owen <sowen@cloudera.com>
Closes#4912 from srowen/SPARK-6182.1 and squashes the following commits:
eff60de [Sean Owen] Convert spark-parent module name to spark-parent_2.10 / spark-parent_2.11
For package thriftserver, guava is used at runtime.
/cc pwendell
Author: Daoyuan Wang <daoyuan.wang@intel.com>
Closes#4884 from adrian-wang/test and squashes the following commits:
4600ae7 [Daoyuan Wang] only promote for thriftserver
44dda18 [Daoyuan Wang] promote guava dep for hive
In `CodeGenerator`, the casting on `FloatType` should use `FloatType` instead of `IntegerType`.
Besides, `defaultPrimitive` for `LongType` should be `-1L` instead of `1L`.
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#4870 from viirya/codegen_type and squashes the following commits:
76311dd [Liang-Chi Hsieh] Fix wrong datatype for casting on FloatType. Fix the wrong value for LongType in defaultPrimitive.
Integration test suites in the JDBC data source (`MySQLIntegration` and `PostgresIntegration`) depend on docker-client 2.7.5, which transitively depends on Guava 17.0. Unfortunately, Guava 17.0 is causing test runtime binary compatibility issues when Spark is compiled against Hive 0.12.0, or Hadoop 2.4.
Considering `MySQLIntegration` and `PostgresIntegration` are ignored right now, I'd suggest moving them from the Spark project to the [Spark integration tests] [1] project. This PR removes both the JDBC data source integration tests and the docker-client test dependency.
[1]: |https://github.com/databricks/spark-integration-tests
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Author: Cheng Lian <lian@databricks.com>
Closes#4872 from liancheng/remove-docker-client and squashes the following commits:
1f4169e [Cheng Lian] Removes DockerHacks
159b24a [Cheng Lian] Removed JDBC integration tests which depends on docker-client
- Various Fixes to docs
- Make data source traits actually interfaces
Based on #4862 but with fixed conflicts.
Author: Reynold Xin <rxin@databricks.com>
Author: Michael Armbrust <michael@databricks.com>
Closes#4868 from marmbrus/pr/4862 and squashes the following commits:
fe091ea [Michael Armbrust] Merge remote-tracking branch 'origin/master' into pr/4862
0208497 [Reynold Xin] Test fixes.
34e0a28 [Reynold Xin] [SPARK-5310][SQL] Various fixes to Spark SQL docs.
This PR contains the following changes:
1. Add a new method, `DataType.equalsIgnoreCompatibleNullability`, which is the middle ground between DataType's equality check and `DataType.equalsIgnoreNullability`. For two data types `from` and `to`, it does `equalsIgnoreNullability` as well as if the nullability of `from` is compatible with that of `to`. For example, the nullability of `ArrayType(IntegerType, containsNull = false)` is compatible with that of `ArrayType(IntegerType, containsNull = true)` (for an array without null values, we can always say it may contain null values). However, the nullability of `ArrayType(IntegerType, containsNull = true)` is incompatible with that of `ArrayType(IntegerType, containsNull = false)` (for an array that may have null values, we cannot say it does not have null values).
2. For the `resolved` field of `InsertIntoTable`, use `equalsIgnoreCompatibleNullability` to replace the equality check of the data types.
3. For our data source write path, when appending data, we always use the schema of existing table to write the data. This is important for parquet, since nullability direct impacts the way to encode/decode values. If we do not do this, we may see corrupted values when reading values from a set of parquet files generated with different nullability settings.
4. When generating a new parquet table, we always set nullable/containsNull/valueContainsNull to true. So, we will not face situations that we cannot append data because containsNull/valueContainsNull in an Array/Map column of the existing table has already been set to `false`. This change makes the whole data pipeline more robust.
5. Update the equality check of JSON relation. Since JSON does not really cares nullability, `equalsIgnoreNullability` seems a better choice to compare schemata from to JSON tables.
JIRA: https://issues.apache.org/jira/browse/SPARK-5950
Thanks viirya for the initial work in #4729.
cc marmbrus liancheng
Author: Yin Huai <yhuai@databricks.com>
Closes#4826 from yhuai/insertNullabilityCheck and squashes the following commits:
3b61a04 [Yin Huai] Revert change on equals.
80e487e [Yin Huai] asNullable in UDT.
587d88b [Yin Huai] Make methods private.
0cb7ea2 [Yin Huai] marmbrus's comments.
3cec464 [Yin Huai] Cheng's comments.
486ed08 [Yin Huai] Merge remote-tracking branch 'upstream/master' into insertNullabilityCheck
d3747d1 [Yin Huai] Remove unnecessary change.
8360817 [Yin Huai] Merge remote-tracking branch 'upstream/master' into insertNullabilityCheck
8a3f237 [Yin Huai] Use equalsIgnoreNullability instead of equality check.
0eb5578 [Yin Huai] Fix tests.
f6ed813 [Yin Huai] Update old parquet path.
e4f397c [Yin Huai] Unit tests.
b2c06f8 [Yin Huai] Ignore nullability in JSON relation's equality check.
8bd008b [Yin Huai] nullable, containsNull, and valueContainsNull will be always true for parquet data.
bf50d73 [Yin Huai] When appending data, we use the schema of the existing table instead of the schema of the new data.
0a703e7 [Yin Huai] Test failed again since we cannot read correct content.
9a26611 [Yin Huai] Make InsertIntoTable happy.
8f19fe5 [Yin Huai] equalsIgnoreCompatibleNullability
4ec17fd [Yin Huai] Failed test.
Constructs like Hive `TRANSFORM` may generate malformed rows (via badly authored external scripts for example). I'm a bit hesitant to have this feature, since it introduces per-tuple cost when caching tables. However, considering caching tables is usually a one-time cost, this is probably worth having.
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Author: Cheng Lian <lian@databricks.com>
Closes#4842 from liancheng/spark-6082 and squashes the following commits:
b05dbff [Cheng Lian] Provides better error message for malformed rows when caching tables
Author: Michael Armbrust <michael@databricks.com>
Closes#4855 from marmbrus/explodeBug and squashes the following commits:
a712249 [Michael Armbrust] [SPARK-6114][SQL] Avoid metastore conversions before plan is resolved
HiveQL expression like `select count(1) from src tablesample(1 percent);` means take 1% sample to select. But it means 100% in the current version of the Spark.
Author: q00251598 <qiyadong@huawei.com>
Closes#4789 from watermen/SPARK-6040 and squashes the following commits:
2453ebe [q00251598] check and adjust the fraction.
It should be `true` instead of `false`?
Author: Liang-Chi Hsieh <viirya@gmail.com>
Closes#4762 from viirya/doc_fix and squashes the following commits:
2e37482 [Liang-Chi Hsieh] Fix doc.
The API signatire for join requires the JoinType to be the third parameter. The code examples provided for join show JoinType being provided as the 2nd parater resuling in errors (i.e. "df1.join(df2, "outer", $"df1Key" === $"df2Key") ). The correct sample code is df1.join(df2, $"df1Key" === $"df2Key", "outer")
Author: Paul Power <paul.power@peerside.com>
Closes#4847 from peerside/master and squashes the following commits:
ebc1efa [Paul Power] Merge pull request #1 from peerside/peerside-patch-1
e353340 [Paul Power] Updated comments use correct sample code for Dataframe joins
When run ```select * from nzhang_part where hr = 'file,';```, it throws exception ```java.lang.IllegalArgumentException: Can not create a Path from an empty string```
. Because the path of hdfs contains comma, and FileInputFormat.setInputPaths will split path by comma.
### SQL
```
set hive.merge.mapfiles=true;
set hive.merge.mapredfiles=true;
set hive.input.format=org.apache.hadoop.hive.ql.io.HiveInputFormat;
set hive.exec.dynamic.partition=true;
set hive.exec.dynamic.partition.mode=nonstrict;
create table nzhang_part like srcpart;
insert overwrite table nzhang_part partition (ds='2010-08-15', hr) select key, value, hr from srcpart where ds='2008-04-08';
insert overwrite table nzhang_part partition (ds='2010-08-15', hr=11) select key, value from srcpart where ds='2008-04-08';
insert overwrite table nzhang_part partition (ds='2010-08-15', hr)
select * from (
select key, value, hr from srcpart where ds='2008-04-08'
union all
select '1' as key, '1' as value, 'file,' as hr from src limit 1) s;
select * from nzhang_part where hr = 'file,';
```
### Error Log
```
15/02/10 14:33:16 ERROR SparkSQLDriver: Failed in [select * from nzhang_part where hr = 'file,']
java.lang.IllegalArgumentException: Can not create a Path from an empty string
at org.apache.hadoop.fs.Path.checkPathArg(Path.java:127)
at org.apache.hadoop.fs.Path.<init>(Path.java:135)
at org.apache.hadoop.util.StringUtils.stringToPath(StringUtils.java:241)
at org.apache.hadoop.mapred.FileInputFormat.setInputPaths(FileInputFormat.java:400)
at org.apache.spark.sql.hive.HadoopTableReader$.initializeLocalJobConfFunc(TableReader.scala:251)
at org.apache.spark.sql.hive.HadoopTableReader$$anonfun$11.apply(TableReader.scala:229)
at org.apache.spark.sql.hive.HadoopTableReader$$anonfun$11.apply(TableReader.scala:229)
at org.apache.spark.rdd.HadoopRDD$$anonfun$getJobConf$6.apply(HadoopRDD.scala:172)
at org.apache.spark.rdd.HadoopRDD$$anonfun$getJobConf$6.apply(HadoopRDD.scala:172)
at scala.Option.map(Option.scala:145)
at org.apache.spark.rdd.HadoopRDD.getJobConf(HadoopRDD.scala:172)
at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:196)
Author: q00251598 <qiyadong@huawei.com>
Closes#4532 from watermen/SPARK-5741 and squashes the following commits:
9758ab1 [q00251598] fix bug
1db1a1c [q00251598] use setInputPaths(Job job, Path... inputPaths)
b788a72 [q00251598] change FileInputFormat.setInputPaths to jobConf.set and add test suite
Always set `containsNull = true` when infer the schema of JSON datasets. If we set `containsNull` based on records we scanned, we may miss arrays with null values when we do sampling. Also, because future data can have arrays with null values, if we convert JSON data to parquet, always setting `containsNull = true` is a more robust way to go.
JIRA: https://issues.apache.org/jira/browse/SPARK-6052
Author: Yin Huai <yhuai@databricks.com>
Closes#4806 from yhuai/jsonArrayContainsNull and squashes the following commits:
05eab9d [Yin Huai] Change containsNull to true.
JIRA: https://issues.apache.org/jira/browse/SPARK-6073
liancheng
Author: Yin Huai <yhuai@databricks.com>
Closes#4824 from yhuai/refreshCache and squashes the following commits:
b9542ef [Yin Huai] Refresh metadata cache in the Catalog in CreateMetastoreDataSourceAsSelect.
