Commit graph

4834 commits

Author SHA1 Message Date
wangzhenhua a615513569 [SPARK-19149][SQL] Unify two sets of statistics in LogicalPlan
## What changes were proposed in this pull request?

Currently we have two sets of statistics in LogicalPlan: a simple stats and a stats estimated by cbo, but the computing logic and naming are quite confusing, we need to unify these two sets of stats.

## How was this patch tested?

Just modify existing tests.

Author: wangzhenhua <wangzhenhua@huawei.com>
Author: Zhenhua Wang <wzh_zju@163.com>

Closes #16529 from wzhfy/unifyStats.
2017-01-10 22:34:44 -08:00
Wenchen Fan 3b19c74e71 [SPARK-19157][SQL] should be able to change spark.sql.runSQLOnFiles at runtime
## What changes were proposed in this pull request?

The analyzer rule that supports to query files directly will be added to `Analyzer.extendedResolutionRules` when SparkSession is created, according to the `spark.sql.runSQLOnFiles` flag. If the flag is off when we create `SparkSession`, this rule is not added and we can not query files directly even we turn on the flag later.

This PR fixes this bug by always adding that rule to `Analyzer.extendedResolutionRules`.

## How was this patch tested?

new regression test

Author: Wenchen Fan <wenchen@databricks.com>

Closes #16531 from cloud-fan/sql-on-files.
2017-01-10 21:33:44 -08:00
Shixiong Zhu bc6c56e940 [SPARK-19140][SS] Allow update mode for non-aggregation streaming queries
## What changes were proposed in this pull request?

This PR allow update mode for non-aggregation streaming queries. It will be same as the append mode if a query has no aggregations.

## How was this patch tested?

Jenkins

Author: Shixiong Zhu <shixiong@databricks.com>

Closes #16520 from zsxwing/update-without-agg.
2017-01-10 17:58:11 -08:00
Dongjoon Hyun d5b1dc934a [SPARK-19137][SQL] Fix withSQLConf to reset OptionalConfigEntry correctly
## What changes were proposed in this pull request?

`DataStreamReaderWriterSuite` makes test files in source folder like the followings. Interestingly, the root cause is `withSQLConf` fails to reset `OptionalConfigEntry` correctly. In other words, it resets the config into `Some(undefined)`.

```bash
$ git status
Untracked files:
  (use "git add <file>..." to include in what will be committed)

        sql/core/%253Cundefined%253E/
        sql/core/%3Cundefined%3E/
```

## How was this patch tested?

Manual.
```
build/sbt "project sql" test
git status
```

Author: Dongjoon Hyun <dongjoon@apache.org>

Closes #16522 from dongjoon-hyun/SPARK-19137.
2017-01-10 10:49:44 -08:00
Shixiong Zhu 3ef183a941
[SPARK-19113][SS][TESTS] Set UncaughtExceptionHandler in onQueryStarted to ensure catching fatal errors during query initialization
## What changes were proposed in this pull request?

StreamTest sets `UncaughtExceptionHandler` after starting the query now. It may not be able to catch fatal errors during query initialization. This PR uses `onQueryStarted` callback to fix it.

## How was this patch tested?

Jenkins

Author: Shixiong Zhu <shixiong@databricks.com>

Closes #16492 from zsxwing/SPARK-19113.
2017-01-10 14:24:45 +00:00
Dongjoon Hyun a2c6adcc5d
[SPARK-18857][SQL] Don't use Iterator.duplicate for incrementalCollect in Thrift Server
## What changes were proposed in this pull request?

To support `FETCH_FIRST`, SPARK-16563 used Scala `Iterator.duplicate`. However,
Scala `Iterator.duplicate` uses a **queue to buffer all items between both iterators**,
this causes GC and hangs for queries with large number of rows. We should not use this,
especially for `spark.sql.thriftServer.incrementalCollect`.

https://github.com/scala/scala/blob/2.12.x/src/library/scala/collection/Iterator.scala#L1262-L1300

## How was this patch tested?

Pass the existing tests.

Author: Dongjoon Hyun <dongjoon@apache.org>

Closes #16440 from dongjoon-hyun/SPARK-18857.
2017-01-10 13:27:55 +00:00
hyukjinkwon 2cfd41ac02
[SPARK-19117][TESTS] Skip the tests using script transformation on Windows
## What changes were proposed in this pull request?

This PR proposes to skip the tests for script transformation failed on Windows due to fixed bash location.

```
SQLQuerySuite:
 - script *** FAILED *** (553 milliseconds)
   org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 56.0 failed 1 times, most recent failure: Lost task 0.0 in stage 56.0 (TID 54, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified

 - Star Expansion - script transform *** FAILED *** (2 seconds, 375 milliseconds)
   org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 389.0 failed 1 times, most recent failure: Lost task 0.0 in stage 389.0 (TID 725, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified

 - test script transform for stdout *** FAILED *** (2 seconds, 813 milliseconds)
   org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 391.0 failed 1 times, most recent failure: Lost task 0.0 in stage 391.0 (TID 726, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified

 - test script transform for stderr *** FAILED *** (2 seconds, 407 milliseconds)
   org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 393.0 failed 1 times, most recent failure: Lost task 0.0 in stage 393.0 (TID 727, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified

 - test script transform data type *** FAILED *** (171 milliseconds)
   org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 395.0 failed 1 times, most recent failure: Lost task 0.0 in stage 395.0 (TID 728, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified
```

```
HiveQuerySuite:
 - transform *** FAILED *** (359 milliseconds)
   Failed to execute query using catalyst:
   Error: Job aborted due to stage failure: Task 0 in stage 1347.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1347.0 (TID 2395, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified

 - schema-less transform *** FAILED *** (344 milliseconds)
   Failed to execute query using catalyst:
   Error: Job aborted due to stage failure: Task 0 in stage 1348.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1348.0 (TID 2396, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified

 - transform with custom field delimiter *** FAILED *** (296 milliseconds)
   Failed to execute query using catalyst:
   Error: Job aborted due to stage failure: Task 0 in stage 1349.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1349.0 (TID 2397, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified

 - transform with custom field delimiter2 *** FAILED *** (297 milliseconds)
   Failed to execute query using catalyst:
   Error: Job aborted due to stage failure: Task 0 in stage 1350.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1350.0 (TID 2398, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified

 - transform with custom field delimiter3 *** FAILED *** (312 milliseconds)
   Failed to execute query using catalyst:
   Error: Job aborted due to stage failure: Task 0 in stage 1351.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1351.0 (TID 2399, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified

 - transform with SerDe2 *** FAILED *** (437 milliseconds)
   org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1355.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1355.0 (TID 2403, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified
```

```
LogicalPlanToSQLSuite:
 - script transformation - schemaless *** FAILED *** (78 milliseconds)
   ...
   Cause: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1968.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1968.0 (TID 3932, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified
  - script transformation - alias list *** FAILED *** (94 milliseconds)
   ...
   Cause: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1969.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1969.0 (TID 3933, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified

 - script transformation - alias list with type *** FAILED *** (93 milliseconds)
   ...
   Cause: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1970.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1970.0 (TID 3934, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified

 - script transformation - row format delimited clause with only one format property *** FAILED *** (78 milliseconds)
   ...
   Cause: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1971.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1971.0 (TID 3935, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified

 - script transformation - row format delimited clause with multiple format properties *** FAILED *** (94 milliseconds)
   ...
   Cause: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1972.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1972.0 (TID 3936, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified

 - script transformation - row format serde clauses with SERDEPROPERTIES *** FAILED *** (78 milliseconds)
   ...
   Cause: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1973.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1973.0 (TID 3937, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified

 - script transformation - row format serde clauses without SERDEPROPERTIES *** FAILED *** (78 milliseconds)
   ...
   Cause: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1974.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1974.0 (TID 3938, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified
```

```
ScriptTransformationSuite:
 - cat without SerDe *** FAILED *** (156 milliseconds)
   ...
   Caused by: java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified

 - cat with LazySimpleSerDe *** FAILED *** (63 milliseconds)
    ...
    org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 2383.0 failed 1 times, most recent failure: Lost task 0.0 in stage 2383.0 (TID 4819, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified

 - script transformation should not swallow errors from upstream operators (no serde) *** FAILED *** (78 milliseconds)
    ...
    org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 2384.0 failed 1 times, most recent failure: Lost task 0.0 in stage 2384.0 (TID 4820, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified

 - script transformation should not swallow errors from upstream operators (with serde) *** FAILED *** (47 milliseconds)
    ...
    org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 2385.0 failed 1 times, most recent failure: Lost task 0.0 in stage 2385.0 (TID 4821, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified

 - SPARK-14400 script transformation should fail for bad script command *** FAILED *** (47 milliseconds)
   "Job aborted due to stage failure: Task 0 in stage 2386.0 failed 1 times, most recent failure: Lost task 0.0 in stage 2386.0 (TID 4822, localhost, executor driver): java.io.IOException: Cannot run program "/bin/bash": CreateProcess error=2, The system cannot find the file specified
```

## How was this patch tested?

AppVeyor as below:

```
SQLQuerySuite:
  - script !!! CANCELED !!! (63 milliseconds)
  - Star Expansion - script transform !!! CANCELED !!! (0 milliseconds)
  - test script transform for stdout !!! CANCELED !!! (0 milliseconds)
  - test script transform for stderr !!! CANCELED !!! (0 milliseconds)
  - test script transform data type !!! CANCELED !!! (0 milliseconds)
```

```
HiveQuerySuite:
  - transform !!! CANCELED !!! (31 milliseconds)
  - schema-less transform !!! CANCELED !!! (0 milliseconds)
  - transform with custom field delimiter !!! CANCELED !!! (0 milliseconds)
  - transform with custom field delimiter2 !!! CANCELED !!! (0 milliseconds)
  - transform with custom field delimiter3 !!! CANCELED !!! (0 milliseconds)
  - transform with SerDe2 !!! CANCELED !!! (0 milliseconds)
```

```
LogicalPlanToSQLSuite:
  - script transformation - schemaless !!! CANCELED !!! (78 milliseconds)
  - script transformation - alias list !!! CANCELED !!! (0 milliseconds)
  - script transformation - alias list with type !!! CANCELED !!! (0 milliseconds)
  - script transformation - row format delimited clause with only one format property !!! CANCELED !!! (15 milliseconds)
  - script transformation - row format delimited clause with multiple format properties !!! CANCELED !!! (0 milliseconds)
  - script transformation - row format serde clauses with SERDEPROPERTIES !!! CANCELED !!! (0 milliseconds)
  - script transformation - row format serde clauses without SERDEPROPERTIES !!! CANCELED !!! (0 milliseconds)
```

```
ScriptTransformationSuite:
  - cat without SerDe !!! CANCELED !!! (62 milliseconds)
  - cat with LazySimpleSerDe !!! CANCELED !!! (0 milliseconds)
  - script transformation should not swallow errors from upstream operators (no serde) !!! CANCELED !!! (0 milliseconds)
  - script transformation should not swallow errors from upstream operators (with serde) !!! CANCELED !!! (0 milliseconds)
  - SPARK-14400 script transformation should fail for bad script command !!! CANCELED !!! (0 milliseconds)
```

Jenkins tests

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #16501 from HyukjinKwon/windows-bash.
2017-01-10 13:22:35 +00:00
hyukjinkwon 4e27578faa
[SPARK-18922][SQL][CORE][STREAMING][TESTS] Fix all identified tests failed due to path and resource-not-closed problems on Windows
## What changes were proposed in this pull request?

This PR proposes to fix all the test failures identified by testing with AppVeyor.

**Scala - aborted tests**

```
WindowQuerySuite:
  Exception encountered when attempting to run a suite with class name: org.apache.spark.sql.hive.execution.WindowQuerySuite *** ABORTED *** (156 milliseconds)
   org.apache.spark.sql.AnalysisException: LOAD DATA input path does not exist: C:projectssparksqlhive   argetscala-2.11   est-classesdatafilespart_tiny.txt;

OrcSourceSuite:
 Exception encountered when attempting to run a suite with class name: org.apache.spark.sql.hive.orc.OrcSourceSuite *** ABORTED *** (62 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

ParquetMetastoreSuite:
 Exception encountered when attempting to run a suite with class name: org.apache.spark.sql.hive.ParquetMetastoreSuite *** ABORTED *** (4 seconds, 703 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

ParquetSourceSuite:
 Exception encountered when attempting to run a suite with class name: org.apache.spark.sql.hive.ParquetSourceSuite *** ABORTED *** (3 seconds, 907 milliseconds)
   org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark  arget mpspark-581a6575-454f-4f21-a516-a07f95266143;

KafkaRDDSuite:
 Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka.KafkaRDDSuite *** ABORTED *** (5 seconds, 212 milliseconds)
   java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-4722304d-213e-4296-b556-951df1a46807

DirectKafkaStreamSuite:
 Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka.DirectKafkaStreamSuite *** ABORTED *** (7 seconds, 127 milliseconds)
   java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-d0d3eba7-4215-4e10-b40e-bb797e89338e
   at org.apache.spark.util.Utils$.deleteRecursively(Utils.scala:1010)

ReliableKafkaStreamSuite
 Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka.ReliableKafkaStreamSuite *** ABORTED *** (5 seconds, 498 milliseconds)
   java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-d33e45a0-287e-4bed-acae-ca809a89d888

KafkaStreamSuite:
 Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka.KafkaStreamSuite *** ABORTED *** (2 seconds, 892 milliseconds)
   java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-59c9d169-5a56-4519-9ef0-cefdbd3f2e6c

KafkaClusterSuite:
 Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka.KafkaClusterSuite *** ABORTED *** (1 second, 690 milliseconds)
   java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-3ef402b0-8689-4a60-85ae-e41e274f179d

DirectKafkaStreamSuite:
 Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka010.DirectKafkaStreamSuite *** ABORTED *** (59 seconds, 626 milliseconds)
   java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-426107da-68cf-4d94-b0d6-1f428f1c53f6

KafkaRDDSuite:
Exception encountered when attempting to run a suite with class name: org.apache.spark.streaming.kafka010.KafkaRDDSuite *** ABORTED *** (2 minutes, 6 seconds)
   java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-b9ce7929-5dae-46ab-a0c4-9ef6f58fbc2
```

**Java - failed tests**

```
Test org.apache.spark.streaming.kafka.JavaKafkaRDDSuite.testKafkaRDD failed: java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-1cee32f4-4390-4321-82c9-e8616b3f0fb0, took 9.61 sec

Test org.apache.spark.streaming.kafka.JavaKafkaStreamSuite.testKafkaStream failed: java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-f42695dd-242e-4b07-847c-f299b8e4676e, took 11.797 sec

Test org.apache.spark.streaming.kafka.JavaDirectKafkaStreamSuite.testKafkaStream failed: java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-85c0d062-78cf-459c-a2dd-7973572101ce, took 1.581 sec

Test org.apache.spark.streaming.kafka010.JavaKafkaRDDSuite.testKafkaRDD failed: java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-49eb6b5c-8366-47a6-83f2-80c443c48280, took 17.895 sec

org.apache.spark.streaming.kafka010.JavaDirectKafkaStreamSuite.testKafkaStream failed: java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-898cf826-d636-4b1c-a61a-c12a364c02e7, took 8.858 sec
```

**Scala - failed tests**

```
PartitionProviderCompatibilitySuite:
 - insert overwrite partition of new datasource table overwrites just partition *** FAILED *** (828 milliseconds)
   java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-bb6337b9-4f99-45ab-ad2c-a787ab965c09

 - SPARK-18635 special chars in partition values - partition management true *** FAILED *** (5 seconds, 360 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

 - SPARK-18635 special chars in partition values - partition management false *** FAILED *** (141 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
```

```
UtilsSuite:
 - reading offset bytes of a file (compressed) *** FAILED *** (0 milliseconds)
   java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-ecb2b7d5-db8b-43a7-b268-1bf242b5a491

 - reading offset bytes across multiple files (compressed) *** FAILED *** (0 milliseconds)
   java.io.IOException: Failed to delete: C:\projects\spark\target\tmp\spark-25cc47a8-1faa-4da5-8862-cf174df63ce0
```

```
StatisticsSuite:
 - MetastoreRelations fallback to HDFS for size estimation *** FAILED *** (110 milliseconds)
   org.apache.spark.sql.catalyst.analysis.NoSuchTableException: Table or view 'csv_table' not found in database 'default';
```

```
SQLQuerySuite:
 - permanent UDTF *** FAILED *** (125 milliseconds)
   org.apache.spark.sql.AnalysisException: Undefined function: 'udtf_count_temp'. This function is neither a registered temporary function nor a permanent function registered in the database 'default'.; line 1 pos 24

 - describe functions - user defined functions *** FAILED *** (125 milliseconds)
   org.apache.spark.sql.AnalysisException: Undefined function: 'udtf_count'. This function is neither a registered temporary function nor a permanent function registered in the database 'default'.; line 1 pos 7

 - CTAS without serde with location *** FAILED *** (16 milliseconds)
   java.lang.IllegalArgumentException: java.net.URISyntaxException: Relative path in absolute URI: file:C:projectsspark%09arget%09mpspark-ed673d73-edfc-404e-829e-2e2b9725d94e/c1

 - derived from Hive query file: drop_database_removes_partition_dirs.q *** FAILED *** (47 milliseconds)
   java.lang.IllegalArgumentException: java.net.URISyntaxException: Relative path in absolute URI: file:C:projectsspark%09arget%09mpspark-d2ddf08e-699e-45be-9ebd-3dfe619680fe/drop_database_removes_partition_dirs_table

 - derived from Hive query file: drop_table_removes_partition_dirs.q *** FAILED *** (0 milliseconds)
   java.lang.IllegalArgumentException: java.net.URISyntaxException: Relative path in absolute URI: file:C:projectsspark%09arget%09mpspark-d2ddf08e-699e-45be-9ebd-3dfe619680fe/drop_table_removes_partition_dirs_table2

 - SPARK-17796 Support wildcard character in filename for LOAD DATA LOCAL INPATH *** FAILED *** (109 milliseconds)
   java.nio.file.InvalidPathException: Illegal char <:> at index 2: /C:/projects/spark/sql/hive/projectsspark	arget	mpspark-1a122f8c-dfb3-46c4-bab1-f30764baee0e/*part-r*
```

```
HiveDDLSuite:
 - drop external tables in default database *** FAILED *** (16 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

 - add/drop partitions - external table *** FAILED *** (16 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

 - create/drop database - location without pre-created directory *** FAILED *** (16 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

 - create/drop database - location with pre-created directory *** FAILED *** (32 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

 - drop database containing tables - CASCADE *** FAILED *** (94 milliseconds)
   CatalogDatabase(db1,,file:/C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be/db1.db,Map()) did not equal CatalogDatabase(db1,,file:C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be\db1.db,Map()) (HiveDDLSuite.scala:675)

 - drop an empty database - CASCADE *** FAILED *** (63 milliseconds)
   CatalogDatabase(db1,,file:/C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be/db1.db,Map()) did not equal CatalogDatabase(db1,,file:C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be\db1.db,Map()) (HiveDDLSuite.scala:675)

 - drop database containing tables - RESTRICT *** FAILED *** (47 milliseconds)
   CatalogDatabase(db1,,file:/C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be/db1.db,Map()) did not equal CatalogDatabase(db1,,file:C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be\db1.db,Map()) (HiveDDLSuite.scala:675)

 - drop an empty database - RESTRICT *** FAILED *** (47 milliseconds)
   CatalogDatabase(db1,,file:/C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be/db1.db,Map()) did not equal CatalogDatabase(db1,,file:C:/projects/spark/target/tmp/warehouse-d0665ee0-1e39-4805-b471-0b764f7838be\db1.db,Map()) (HiveDDLSuite.scala:675)

 - CREATE TABLE LIKE an external data source table *** FAILED *** (140 milliseconds)
   org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget	mpspark-c5eba16d-07ae-4186-95bb-21c5811cf888;

 - CREATE TABLE LIKE an external Hive serde table *** FAILED *** (16 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

 - desc table for data source table - no user-defined schema *** FAILED *** (125 milliseconds)
   org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget	mpspark-e8bf5bf5-721a-4cbe-9d6	at scala.collection.immutable.List.foreach(List.scala:381)d-5543a8301c1d;
```

```
MetastoreDataSourcesSuite
 - CTAS: persisted bucketed data source table *** FAILED *** (16 milliseconds)
   java.lang.IllegalArgumentException: Can not create a Path from an empty string
```

```
ShowCreateTableSuite:
 - simple external hive table *** FAILED *** (0 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
```

```
PartitionedTablePerfStatsSuite:
 - hive table: partitioned pruned table reports only selected files *** FAILED *** (313 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

 - datasource table: partitioned pruned table reports only selected files *** FAILED *** (219 milliseconds)
   org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget	mpspark-311f45f8-d064-4023-a4bb-e28235bff64d;

 - hive table: lazy partition pruning reads only necessary partition data *** FAILED *** (203 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

 - datasource table: lazy partition pruning reads only necessary partition data *** FAILED *** (187 milliseconds)
   org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget	mpspark-fde874ca-66bd-4d0b-a40f-a043b65bf957;

 - hive table: lazy partition pruning with file status caching enabled *** FAILED *** (188 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

 - datasource table: lazy partition pruning with file status caching enabled *** FAILED *** (187 milliseconds)
   org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget	mpspark-e6d20183-dd68-4145-acbe-4a509849accd;

 - hive table: file status caching respects refresh table and refreshByPath *** FAILED *** (172 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

 - datasource table: file status caching respects refresh table and refreshByPath *** FAILED *** (203 milliseconds)
   org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget	mpspark-8b2c9651-2adf-4d58-874f-659007e21463;

 - hive table: file status cache respects size limit *** FAILED *** (219 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

 - datasource table: file status cache respects size limit *** FAILED *** (171 milliseconds)
   org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget	mpspark-7835ab57-cb48-4d2c-bb1d-b46d5a4c47e4;

 - datasource table: table setup does not scan filesystem *** FAILED *** (266 milliseconds)
   org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget	mpspark-20598d76-c004-42a7-8061-6c56f0eda5e2;

 - hive table: table setup does not scan filesystem *** FAILED *** (266 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

 - hive table: num hive client calls does not scale with partition count *** FAILED *** (2 seconds, 281 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

 - datasource table: num hive client calls does not scale with partition count *** FAILED *** (2 seconds, 422 milliseconds)
   org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget	mpspark-4cfed321-4d1d-4b48-8d34-5c169afff383;

 - hive table: files read and cached when filesource partition management is off *** FAILED *** (234 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

 - datasource table: all partition data cached in memory when partition management is off *** FAILED *** (203 milliseconds)
   org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget	mpspark-4bcc0398-15c9-4f6a-811e-12d40f3eec12;

 - SPARK-18700: table loaded only once even when resolved concurrently *** FAILED *** (1 second, 266 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
```

```
HiveSparkSubmitSuite:
 - temporary Hive UDF: define a UDF and use it *** FAILED *** (2 seconds, 94 milliseconds)
   java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified

 - permanent Hive UDF: define a UDF and use it *** FAILED *** (281 milliseconds)
   java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified

 - permanent Hive UDF: use a already defined permanent function *** FAILED *** (718 milliseconds)
   java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified

 - SPARK-8368: includes jars passed in through --jars *** FAILED *** (3 seconds, 521 milliseconds)
   java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified

 - SPARK-8020: set sql conf in spark conf *** FAILED *** (0 milliseconds)
   java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified

 - SPARK-8489: MissingRequirementError during reflection *** FAILED *** (94 milliseconds)
   java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified

 - SPARK-9757 Persist Parquet relation with decimal column *** FAILED *** (16 milliseconds)
   java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified

 - SPARK-11009 fix wrong result of Window function in cluster mode *** FAILED *** (16 milliseconds)
   java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified

 - SPARK-14244 fix window partition size attribute binding failure *** FAILED *** (78 milliseconds)
   java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified

 - set spark.sql.warehouse.dir *** FAILED *** (16 milliseconds)
   java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified

 - set hive.metastore.warehouse.dir *** FAILED *** (15 milliseconds)
   java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified

 - SPARK-16901: set javax.jdo.option.ConnectionURL *** FAILED *** (16 milliseconds)
   java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified

 - SPARK-18360: default table path of tables in default database should depend on the location of default database *** FAILED *** (15 milliseconds)
   java.io.IOException: Cannot run program "./bin/spark-submit" (in directory "C:\projects\spark"): CreateProcess error=2, The system cannot find the file specified
```

```
UtilsSuite:
 - resolveURIs with multiple paths *** FAILED *** (0 milliseconds)
   ".../jar3,file:/C:/pi.py[%23]py.pi,file:/C:/path%..." did not equal ".../jar3,file:/C:/pi.py[#]py.pi,file:/C:/path%..." (UtilsSuite.scala:468)
```

```
CheckpointSuite:
 - recovery with file input stream *** FAILED *** (10 seconds, 205 milliseconds)
   The code passed to eventually never returned normally. Attempted 660 times over 10.014272499999999 seconds. Last failure message: Unexpected internal error near index 1
   \
    ^. (CheckpointSuite.scala:680)
```

## How was this patch tested?

Manually via AppVeyor as below:

**Scala - aborted tests**

```
WindowQuerySuite - all passed
OrcSourceSuite:
- SPARK-18220: read Hive orc table with varchar column *** FAILED *** (4 seconds, 417 milliseconds)
  org.apache.spark.sql.execution.QueryExecutionException: FAILED: Execution Error, return code -101 from org.apache.hadoop.hive.ql.exec.mr.MapRedTask. org.apache.hadoop.io.nativeio.NativeIO$Windows.access0(Ljava/lang/String;I)Z
  at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$runHive$1.apply(HiveClientImpl.scala:625)
ParquetMetastoreSuite - all passed
ParquetSourceSuite - all passed
KafkaRDDSuite - all passed
DirectKafkaStreamSuite - all passed
ReliableKafkaStreamSuite - all passed
KafkaStreamSuite - all passed
KafkaClusterSuite - all passed
DirectKafkaStreamSuite - all passed
KafkaRDDSuite - all passed
```

**Java - failed tests**

```
org.apache.spark.streaming.kafka.JavaKafkaRDDSuite - all passed
org.apache.spark.streaming.kafka.JavaDirectKafkaStreamSuite - all passed
org.apache.spark.streaming.kafka.JavaKafkaStreamSuite - all passed
org.apache.spark.streaming.kafka010.JavaDirectKafkaStreamSuite - all passed
org.apache.spark.streaming.kafka010.JavaKafkaRDDSuite - all passed
```

**Scala - failed tests**

```
PartitionProviderCompatibilitySuite:
- insert overwrite partition of new datasource table overwrites just partition (1 second, 953 milliseconds)
- SPARK-18635 special chars in partition values - partition management true (6 seconds, 31 milliseconds)
- SPARK-18635 special chars in partition values - partition management false (4 seconds, 578 milliseconds)
```

```
UtilsSuite:
- reading offset bytes of a file (compressed) (203 milliseconds)
- reading offset bytes across multiple files (compressed) (0 milliseconds)
```

```
StatisticsSuite:
- MetastoreRelations fallback to HDFS for size estimation (94 milliseconds)
```

```
SQLQuerySuite:
 - permanent UDTF (407 milliseconds)
 - describe functions - user defined functions (441 milliseconds)
 - CTAS without serde with location (2 seconds, 831 milliseconds)
 - derived from Hive query file: drop_database_removes_partition_dirs.q (734 milliseconds)
 - derived from Hive query file: drop_table_removes_partition_dirs.q (563 milliseconds)
 - SPARK-17796 Support wildcard character in filename for LOAD DATA LOCAL INPATH (453 milliseconds)
```

```
HiveDDLSuite:
 - drop external tables in default database (3 seconds, 5 milliseconds)
 - add/drop partitions - external table (2 seconds, 750 milliseconds)
 - create/drop database - location without pre-created directory (500 milliseconds)
 - create/drop database - location with pre-created directory (407 milliseconds)
 - drop database containing tables - CASCADE (453 milliseconds)
 - drop an empty database - CASCADE (375 milliseconds)
 - drop database containing tables - RESTRICT (328 milliseconds)
 - drop an empty database - RESTRICT (391 milliseconds)
 - CREATE TABLE LIKE an external data source table (953 milliseconds)
 - CREATE TABLE LIKE an external Hive serde table (3 seconds, 782 milliseconds)
 - desc table for data source table - no user-defined schema (1 second, 150 milliseconds)
```

```
MetastoreDataSourcesSuite
 - CTAS: persisted bucketed data source table (875 milliseconds)
```

```
ShowCreateTableSuite:
 - simple external hive table (78 milliseconds)
```

```
PartitionedTablePerfStatsSuite:
 - hive table: partitioned pruned table reports only selected files (1 second, 109 milliseconds)
- datasource table: partitioned pruned table reports only selected files (860 milliseconds)
 - hive table: lazy partition pruning reads only necessary partition data (859 milliseconds)
 - datasource table: lazy partition pruning reads only necessary partition data (1 second, 219 milliseconds)
 - hive table: lazy partition pruning with file status caching enabled (875 milliseconds)
 - datasource table: lazy partition pruning with file status caching enabled (890 milliseconds)
 - hive table: file status caching respects refresh table and refreshByPath (922 milliseconds)
 - datasource table: file status caching respects refresh table and refreshByPath (640 milliseconds)
 - hive table: file status cache respects size limit (469 milliseconds)
 - datasource table: file status cache respects size limit (453 milliseconds)
 - datasource table: table setup does not scan filesystem (328 milliseconds)
 - hive table: table setup does not scan filesystem (313 milliseconds)
 - hive table: num hive client calls does not scale with partition count (5 seconds, 431 milliseconds)
 - datasource table: num hive client calls does not scale with partition count (4 seconds, 79 milliseconds)
 - hive table: files read and cached when filesource partition management is off (656 milliseconds)
 - datasource table: all partition data cached in memory when partition management is off (484 milliseconds)
 - SPARK-18700: table loaded only once even when resolved concurrently (2 seconds, 578 milliseconds)
```

```
HiveSparkSubmitSuite:
 - temporary Hive UDF: define a UDF and use it (1 second, 745 milliseconds)
 - permanent Hive UDF: define a UDF and use it (406 milliseconds)
 - permanent Hive UDF: use a already defined permanent function (375 milliseconds)
 - SPARK-8368: includes jars passed in through --jars (391 milliseconds)
 - SPARK-8020: set sql conf in spark conf (156 milliseconds)
 - SPARK-8489: MissingRequirementError during reflection (187 milliseconds)
 - SPARK-9757 Persist Parquet relation with decimal column (157 milliseconds)
 - SPARK-11009 fix wrong result of Window function in cluster mode (156 milliseconds)
 - SPARK-14244 fix window partition size attribute binding failure (156 milliseconds)
 - set spark.sql.warehouse.dir (172 milliseconds)
 - set hive.metastore.warehouse.dir (156 milliseconds)
 - SPARK-16901: set javax.jdo.option.ConnectionURL (157 milliseconds)
 - SPARK-18360: default table path of tables in default database should depend on the location of default database (172 milliseconds)
```

```
UtilsSuite:
 - resolveURIs with multiple paths (0 milliseconds)
```

```
CheckpointSuite:
 - recovery with file input stream (4 seconds, 452 milliseconds)
```

Note: after resolving the aborted tests, there is a test failure identified as below:

```
OrcSourceSuite:
- SPARK-18220: read Hive orc table with varchar column *** FAILED *** (4 seconds, 417 milliseconds)
  org.apache.spark.sql.execution.QueryExecutionException: FAILED: Execution Error, return code -101 from org.apache.hadoop.hive.ql.exec.mr.MapRedTask. org.apache.hadoop.io.nativeio.NativeIO$Windows.access0(Ljava/lang/String;I)Z
  at org.apache.spark.sql.hive.client.HiveClientImpl$$anonfun$runHive$1.apply(HiveClientImpl.scala:625)
```

This does not look due to this problem so this PR does not fix it here.

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #16451 from HyukjinKwon/all-path-resource-fixes.
2017-01-10 13:19:21 +00:00
Liwei Lin acfc5f3543 [SPARK-16845][SQL] GeneratedClass$SpecificOrdering grows beyond 64 KB
## What changes were proposed in this pull request?

Prior to this patch, we'll generate `compare(...)` for `GeneratedClass$SpecificOrdering` like below, leading to Janino exceptions saying the code grows beyond 64 KB.

``` scala
/* 005 */ class SpecificOrdering extends o.a.s.sql.catalyst.expressions.codegen.BaseOrdering {
/* ..... */   ...
/* 10969 */   private int compare(InternalRow a, InternalRow b) {
/* 10970 */     InternalRow i = null;  // Holds current row being evaluated.
/* 10971 */
/* 1.... */     code for comparing field0
/* 1.... */     code for comparing field1
/* 1.... */     ...
/* 1.... */     code for comparing field449
/* 15012 */
/* 15013 */     return 0;
/* 15014 */   }
/* 15015 */ }
```

This patch would break `compare(...)` into smaller `compare_xxx(...)` methods when necessary; then we'll get generated `compare(...)` like:

``` scala
/* 001 */ public SpecificOrdering generate(Object[] references) {
/* 002 */   return new SpecificOrdering(references);
/* 003 */ }
/* 004 */
/* 005 */ class SpecificOrdering extends o.a.s.sql.catalyst.expressions.codegen.BaseOrdering {
/* 006 */
/* 007 */     ...
/* 1.... */
/* 11290 */   private int compare_0(InternalRow a, InternalRow b) {
/* 11291 */     InternalRow i = null;  // Holds current row being evaluated.
/* 11292 */
/* 11293 */     i = a;
/* 11294 */     boolean isNullA;
/* 11295 */     UTF8String primitiveA;
/* 11296 */     {
/* 11297 */
/* 11298 */       Object obj = ((Expression) references[0]).eval(null);
/* 11299 */       UTF8String value = (UTF8String) obj;
/* 11300 */       isNullA = false;
/* 11301 */       primitiveA = value;
/* 11302 */     }
/* 11303 */     i = b;
/* 11304 */     boolean isNullB;
/* 11305 */     UTF8String primitiveB;
/* 11306 */     {
/* 11307 */
/* 11308 */       Object obj = ((Expression) references[0]).eval(null);
/* 11309 */       UTF8String value = (UTF8String) obj;
/* 11310 */       isNullB = false;
/* 11311 */       primitiveB = value;
/* 11312 */     }
/* 11313 */     if (isNullA && isNullB) {
/* 11314 */       // Nothing
/* 11315 */     } else if (isNullA) {
/* 11316 */       return -1;
/* 11317 */     } else if (isNullB) {
/* 11318 */       return 1;
/* 11319 */     } else {
/* 11320 */       int comp = primitiveA.compare(primitiveB);
/* 11321 */       if (comp != 0) {
/* 11322 */         return comp;
/* 11323 */       }
/* 11324 */     }
/* 11325 */
/* 11326 */
/* 11327 */     i = a;
/* 11328 */     boolean isNullA1;
/* 11329 */     UTF8String primitiveA1;
/* 11330 */     {
/* 11331 */
/* 11332 */       Object obj1 = ((Expression) references[1]).eval(null);
/* 11333 */       UTF8String value1 = (UTF8String) obj1;
/* 11334 */       isNullA1 = false;
/* 11335 */       primitiveA1 = value1;
/* 11336 */     }
/* 11337 */     i = b;
/* 11338 */     boolean isNullB1;
/* 11339 */     UTF8String primitiveB1;
/* 11340 */     {
/* 11341 */
/* 11342 */       Object obj1 = ((Expression) references[1]).eval(null);
/* 11343 */       UTF8String value1 = (UTF8String) obj1;
/* 11344 */       isNullB1 = false;
/* 11345 */       primitiveB1 = value1;
/* 11346 */     }
/* 11347 */     if (isNullA1 && isNullB1) {
/* 11348 */       // Nothing
/* 11349 */     } else if (isNullA1) {
/* 11350 */       return -1;
/* 11351 */     } else if (isNullB1) {
/* 11352 */       return 1;
/* 11353 */     } else {
/* 11354 */       int comp = primitiveA1.compare(primitiveB1);
/* 11355 */       if (comp != 0) {
/* 11356 */         return comp;
/* 11357 */       }
/* 11358 */     }
/* 1.... */
/* 1.... */   ...
/* 1.... */
/* 12652 */     return 0;
/* 12653 */   }
/* 1.... */
/* 1.... */   ...
/* 15387 */
/* 15388 */   public int compare(InternalRow a, InternalRow b) {
/* 15389 */
/* 15390 */     int comp_0 = compare_0(a, b);
/* 15391 */     if (comp_0 != 0) {
/* 15392 */       return comp_0;
/* 15393 */     }
/* 15394 */
/* 15395 */     int comp_1 = compare_1(a, b);
/* 15396 */     if (comp_1 != 0) {
/* 15397 */       return comp_1;
/* 15398 */     }
/* 1.... */
/* 1.... */     ...
/* 1.... */
/* 15450 */     return 0;
/* 15451 */   }
/* 15452 */ }
```
## How was this patch tested?
- a new added test case which
  - would fail prior to this patch
  - would pass with this patch
- ordering correctness should already be covered by existing tests like those in `OrderingSuite`

## Acknowledgement

A major part of this PR - the refactoring work of `splitExpression()` - has been done by ueshin.

Author: Liwei Lin <lwlin7@gmail.com>
Author: Takuya UESHIN <ueshin@happy-camper.st>
Author: Takuya Ueshin <ueshin@happy-camper.st>

Closes #15480 from lw-lin/spec-ordering-64k-.
2017-01-10 19:35:46 +08:00
Wenchen Fan b0319c2ecb [SPARK-19107][SQL] support creating hive table with DataFrameWriter and Catalog
## What changes were proposed in this pull request?

After unifying the CREATE TABLE syntax in https://github.com/apache/spark/pull/16296, it's pretty easy to support creating hive table with `DataFrameWriter` and `Catalog` now.

This PR basically just removes the hive provider check in `DataFrameWriter.saveAsTable` and `Catalog.createExternalTable`, and add tests.

## How was this patch tested?

new tests in `HiveDDLSuite`

Author: Wenchen Fan <wenchen@databricks.com>

Closes #16487 from cloud-fan/hive-table.
2017-01-10 19:26:51 +08:00
Burak Yavuz faabe69cc0 [SPARK-18952] Regex strings not properly escaped in codegen for aggregations
## What changes were proposed in this pull request?

If I use the function regexp_extract, and then in my regex string, use `\`, i.e. escape character, this fails codegen, because the `\` character is not properly escaped when codegen'd.

Example stack trace:
```
/* 059 */     private int maxSteps = 2;
/* 060 */     private int numRows = 0;
/* 061 */     private org.apache.spark.sql.types.StructType keySchema = new org.apache.spark.sql.types.StructType().add("date_format(window#325.start, yyyy-MM-dd HH:mm)", org.apache.spark.sql.types.DataTypes.StringType)
/* 062 */     .add("regexp_extract(source#310.description, ([a-zA-Z]+)\[.*, 1)", org.apache.spark.sql.types.DataTypes.StringType);
/* 063 */     private org.apache.spark.sql.types.StructType valueSchema = new org.apache.spark.sql.types.StructType().add("sum", org.apache.spark.sql.types.DataTypes.LongType);
/* 064 */     private Object emptyVBase;

...

org.codehaus.commons.compiler.CompileException: File 'generated.java', Line 62, Column 58: Invalid escape sequence
	at org.codehaus.janino.Scanner.scanLiteralCharacter(Scanner.java:918)
	at org.codehaus.janino.Scanner.produce(Scanner.java:604)
	at org.codehaus.janino.Parser.peekRead(Parser.java:3239)
	at org.codehaus.janino.Parser.parseArguments(Parser.java:3055)
	at org.codehaus.janino.Parser.parseSelector(Parser.java:2914)
	at org.codehaus.janino.Parser.parseUnaryExpression(Parser.java:2617)
	at org.codehaus.janino.Parser.parseMultiplicativeExpression(Parser.java:2573)
	at org.codehaus.janino.Parser.parseAdditiveExpression(Parser.java:2552)
```

In the codegend expression, the literal should use `\\` instead of `\`

A similar problem was solved here: https://github.com/apache/spark/pull/15156.

## How was this patch tested?

Regression test in `DataFrameAggregationSuite`

Author: Burak Yavuz <brkyvz@gmail.com>

Closes #16361 from brkyvz/reg-break.
2017-01-09 14:25:38 -08:00
Zhenhua Wang 15c2bd01b0 [SPARK-19020][SQL] Cardinality estimation of aggregate operator
## What changes were proposed in this pull request?

Support cardinality estimation of aggregate operator

## How was this patch tested?

Add test cases

Author: Zhenhua Wang <wzh_zju@163.com>
Author: wangzhenhua <wangzhenhua@huawei.com>

Closes #16431 from wzhfy/aggEstimation.
2017-01-09 11:29:42 -08:00
Zhenhua Wang 3ccabdfb4d [SPARK-17077][SQL] Cardinality estimation for project operator
## What changes were proposed in this pull request?

Support cardinality estimation for project operator.

## How was this patch tested?

Add a test suite and a base class in the catalyst package.

Author: Zhenhua Wang <wzh_zju@163.com>

Closes #16430 from wzhfy/projectEstimation.
2017-01-08 21:15:52 -08:00
anabranch 19d9d4c855 [SPARK-19126][DOCS] Update Join Documentation Across Languages
## What changes were proposed in this pull request?

- [X] Make sure all join types are clearly mentioned
- [X] Make join labeling/style consistent
- [X] Make join label ordering docs the same
- [X] Improve join documentation according to above for Scala
- [X] Improve join documentation according to above for Python
- [X] Improve join documentation according to above for R

## How was this patch tested?
No tests b/c docs.

Please review http://spark.apache.org/contributing.html before opening a pull request.

Author: anabranch <wac.chambers@gmail.com>

Closes #16504 from anabranch/SPARK-19126.
2017-01-08 20:37:46 -08:00
anabranch 1f6ded6455 [SPARK-19127][DOCS] Update Rank Function Documentation
## What changes were proposed in this pull request?

- [X] Fix inconsistencies in function reference for dense rank and dense
- [X] Make all languages equivalent in their reference to `dense_rank` and `rank`.

## How was this patch tested?

N/A for docs.

Please review http://spark.apache.org/contributing.html before opening a pull request.

Author: anabranch <wac.chambers@gmail.com>

Closes #16505 from anabranch/SPARK-19127.
2017-01-08 17:53:53 -08:00
Dilip Biswal 4351e62207 [SPARK-19093][SQL] Cached tables are not used in SubqueryExpression
## What changes were proposed in this pull request?
Consider the plans inside subquery expressions while looking up cache manager to make
use of cached data. Currently CacheManager.useCachedData does not consider the
subquery expressions in the plan.

SQL
```
select * from rows where not exists (select * from rows)
```
Before the fix
```
== Optimized Logical Plan ==
Join LeftAnti
:- InMemoryRelation [_1#3775, _2#3776], true, 10000, StorageLevel(disk, memory, deserialized, 1 replicas)
:     +- *FileScan parquet [_1#3775,_2#3776] Batched: true, Format: Parquet, Location: InMemoryFileIndex[dbfs:/tmp/rows], PartitionFilters: [], PushedFilters: [], ReadSchema: struct<_1:string,_2:string>
+- Project [_1#3775 AS _1#3775#4001, _2#3776 AS _2#3776#4002]
   +- Relation[_1#3775,_2#3776] parquet
```

After
```
== Optimized Logical Plan ==
Join LeftAnti
:- InMemoryRelation [_1#256, _2#257], true, 10000, StorageLevel(disk, memory, deserialized, 1 replicas)
:     +- *FileScan parquet [_1#256,_2#257] Batched: true, Format: Parquet, Location: InMemoryFileIndex[file:/tmp/rows], PartitionFilters: [], PushedFilters: [], ReadSchema: struct<_1:string,_2:string>
+- Project [_1#256 AS _1#256#298, _2#257 AS _2#257#299]
   +- InMemoryRelation [_1#256, _2#257], true, 10000, StorageLevel(disk, memory, deserialized, 1 replicas)
         +- *FileScan parquet [_1#256,_2#257] Batched: true, Format: Parquet, Location: InMemoryFileIndex[file:/tmp/rows], PartitionFilters: [], PushedFilters: [], ReadSchema: struct<_1:string,_2:string>
```

Query2
```
 SELECT * FROM t1
 WHERE
 c1 IN (SELECT c1 FROM t2 WHERE c1 IN (SELECT c1 FROM t3 WHERE c1 = 1))
```
Before
```
== Analyzed Logical Plan ==
c1: int
Project [c1#3]
+- Filter predicate-subquery#47 [(c1#3 = c1#10)]
   :  +- Project [c1#10]
   :     +- Filter predicate-subquery#46 [(c1#10 = c1#17)]
   :        :  +- Project [c1#17]
   :        :     +- Filter (c1#17 = 1)
   :        :        +- SubqueryAlias t3, `t3`
   :        :           +- Project [value#15 AS c1#17]
   :        :              +- LocalRelation [value#15]
   :        +- SubqueryAlias t2, `t2`
   :           +- Project [value#8 AS c1#10]
   :              +- LocalRelation [value#8]
   +- SubqueryAlias t1, `t1`
      +- Project [value#1 AS c1#3]
         +- LocalRelation [value#1]

== Optimized Logical Plan ==
Join LeftSemi, (c1#3 = c1#10)
:- InMemoryRelation [c1#3], true, 10000, StorageLevel(disk, memory, deserialized, 1 replicas), t1
:     +- LocalTableScan [c1#3]
+- Project [value#8 AS c1#10]
   +- Join LeftSemi, (value#8 = c1#17)
      :- LocalRelation [value#8]
      +- Project [value#15 AS c1#17]
         +- Filter (value#15 = 1)
            +- LocalRelation [value#15]

```
After
```
== Analyzed Logical Plan ==
c1: int
Project [c1#3]
+- Filter predicate-subquery#47 [(c1#3 = c1#10)]
   :  +- Project [c1#10]
   :     +- Filter predicate-subquery#46 [(c1#10 = c1#17)]
   :        :  +- Project [c1#17]
   :        :     +- Filter (c1#17 = 1)
   :        :        +- SubqueryAlias t3, `t3`
   :        :           +- Project [value#15 AS c1#17]
   :        :              +- LocalRelation [value#15]
   :        +- SubqueryAlias t2, `t2`
   :           +- Project [value#8 AS c1#10]
   :              +- LocalRelation [value#8]
   +- SubqueryAlias t1, `t1`
      +- Project [value#1 AS c1#3]
         +- LocalRelation [value#1]

== Optimized Logical Plan ==
Join LeftSemi, (c1#3 = c1#10)
:- InMemoryRelation [c1#3], true, 10000, StorageLevel(disk, memory, deserialized, 1 replicas), t1
:     +- LocalTableScan [c1#3]
+- Join LeftSemi, (c1#10 = c1#17)
   :- InMemoryRelation [c1#10], true, 10000, StorageLevel(disk, memory, deserialized, 1 replicas), t2
   :     +- LocalTableScan [c1#10]
   +- Filter (c1#17 = 1)
      +- InMemoryRelation [c1#17], true, 10000, StorageLevel(disk, memory, deserialized, 1 replicas), t1
            +- LocalTableScan [c1#3]
```
## How was this patch tested?
Added new tests in CachedTableSuite.

Author: Dilip Biswal <dbiswal@us.ibm.com>

Closes #16493 from dilipbiswal/SPARK-19093.
2017-01-08 23:09:07 +01:00
Wenchen Fan b3d39620c5 [SPARK-19085][SQL] cleanup OutputWriterFactory and OutputWriter
## What changes were proposed in this pull request?

`OutputWriterFactory`/`OutputWriter` are internal interfaces and we can remove some unnecessary APIs:
1. `OutputWriterFactory.newWriter(path: String)`: no one calls it and no one implements it.
2. `OutputWriter.write(row: Row)`: during execution we only call `writeInternal`, which is weird as `OutputWriter` is already an internal interface. We should rename `writeInternal` to `write` and remove `def write(row: Row)` and it's related converter code. All implementations should just implement `def write(row: InternalRow)`

## How was this patch tested?

existing tests.

Author: Wenchen Fan <wenchen@databricks.com>

Closes #16479 from cloud-fan/hive-writer.
2017-01-08 00:42:09 +08:00
Tathagata Das b59cddaba0 [SPARK-19074][SS][DOCS] Updated Structured Streaming Programming Guide for update mode and source/sink options
## What changes were proposed in this pull request?

Updates
- Updated Late Data Handling section by adding a figure for Update Mode. Its more intuitive to explain late data handling with Update Mode, so I added the new figure before the Append Mode figure.
- Updated Output Modes section with Update mode
- Added options for all the sources and sinks

---------------------------
---------------------------

![image](https://cloud.githubusercontent.com/assets/663212/21665176/f150b224-d29f-11e6-8372-14d32da21db9.png)

---------------------------
---------------------------
<img width="931" alt="screen shot 2017-01-03 at 6 09 11 pm" src="https://cloud.githubusercontent.com/assets/663212/21629740/d21c9bb8-d1df-11e6-915b-488a59589fa6.png">
<img width="933" alt="screen shot 2017-01-03 at 6 10 00 pm" src="https://cloud.githubusercontent.com/assets/663212/21629749/e22bdabe-d1df-11e6-86d3-7e51d2f28dbc.png">

---------------------------
---------------------------
![image](https://cloud.githubusercontent.com/assets/663212/21665200/108e18fc-d2a0-11e6-8640-af598cab090b.png)
![image](https://cloud.githubusercontent.com/assets/663212/21665148/cfe414fa-d29f-11e6-9baa-4124ccbab093.png)
![image](https://cloud.githubusercontent.com/assets/663212/21665226/2e8f39e4-d2a0-11e6-85b1-7657e2df5491.png)

Author: Tathagata Das <tathagata.das1565@gmail.com>

Closes #16468 from tdas/SPARK-19074.
2017-01-06 11:29:01 -08:00
Michal Senkyr 903bb8e8a2 [SPARK-16792][SQL] Dataset containing a Case Class with a List type causes a CompileException (converting sequence to list)
## What changes were proposed in this pull request?

Added a `to` call at the end of the code generated by `ScalaReflection.deserializerFor` if the requested type is not a supertype of `WrappedArray[_]` that uses `CanBuildFrom[_, _, _]` to convert result into an arbitrary subtype of `Seq[_]`.

Care was taken to preserve the original deserialization where it is possible to avoid the overhead of conversion in cases where it is not needed

`ScalaReflection.serializerFor` could already be used to serialize any `Seq[_]` so it was not altered

`SQLImplicits` had to be altered and new implicit encoders added to permit serialization of other sequence types

Also fixes [SPARK-16815] Dataset[List[T]] leads to ArrayStoreException

## How was this patch tested?
```bash
./build/mvn -DskipTests clean package && ./dev/run-tests
```

Also manual execution of the following sets of commands in the Spark shell:
```scala
case class TestCC(key: Int, letters: List[String])

val ds1 = sc.makeRDD(Seq(
(List("D")),
(List("S","H")),
(List("F","H")),
(List("D","L","L"))
)).map(x=>(x.length,x)).toDF("key","letters").as[TestCC]

val test1=ds1.map{_.key}
test1.show
```

```scala
case class X(l: List[String])
spark.createDataset(Seq(List("A"))).map(X).show
```

```scala
spark.sqlContext.createDataset(sc.parallelize(List(1) :: Nil)).collect
```

After adding arbitrary sequence support also tested with the following commands:

```scala
case class QueueClass(q: scala.collection.immutable.Queue[Int])

spark.createDataset(Seq(List(1,2,3))).map(x => QueueClass(scala.collection.immutable.Queue(x: _*))).map(_.q.dequeue).collect
```

Author: Michal Senkyr <mike.senkyr@gmail.com>

Closes #16240 from michalsenkyr/sql-caseclass-list-fix.
2017-01-06 15:05:20 +08:00
Kevin Yu bcc510b021 [SPARK-18871][SQL] New test cases for IN/NOT IN subquery
## What changes were proposed in this pull request?
This PR extends the existing IN/NOT IN subquery test cases coverage, adds more test cases to the IN subquery test suite.

Based on the discussion, we will create  `subquery/in-subquery` sub structure under `sql/core/src/test/resources/sql-tests/inputs` directory.

This is the high level grouping for IN subquery:

`subquery/in-subquery/`
`subquery/in-subquery/simple-in.sql`
`subquery/in-subquery/in-group-by.sql (in parent side, subquery, and both)`
`subquery/in-subquery/not-in-group-by.sql`
`subquery/in-subquery/in-order-by.sql`
`subquery/in-subquery/in-limit.sql`
`subquery/in-subquery/in-having.sql`
`subquery/in-subquery/in-joins.sql`
`subquery/in-subquery/not-in-joins.sql`
`subquery/in-subquery/in-set-operations.sql`
`subquery/in-subquery/in-with-cte.sql`
`subquery/in-subquery/not-in-with-cte.sql`
subquery/in-subquery/in-multiple-columns.sql`

We will deliver it through multiple prs, this is the first pr for the IN subquery, it has

`subquery/in-subquery/simple-in.sql`
`subquery/in-subquery/in-group-by.sql (in parent side, subquery, and both)`

These are the results from running on DB2.
[Modified test file of in-group-by.sql used to run on DB2](https://github.com/apache/spark/files/683367/in-group-by.sql.db2.txt)
[Output of the run result on DB2](https://github.com/apache/spark/files/683362/in-group-by.sql.db2.out.txt)
[Modified test file of simple-in.sql used to run on DB2](https://github.com/apache/spark/files/683378/simple-in.sql.db2.txt)
[Output of the run result on DB2](https://github.com/apache/spark/files/683379/simple-in.sql.db2.out.txt)

## How was this patch tested?

This patch is adding tests.

Author: Kevin Yu <qyu@us.ibm.com>

Closes #16337 from kevinyu98/spark-18871.
2017-01-05 19:00:39 -08:00
Wenchen Fan cca945b6aa [SPARK-18885][SQL] unify CREATE TABLE syntax for data source and hive serde tables
## What changes were proposed in this pull request?

Today we have different syntax to create data source or hive serde tables, we should unify them to not confuse users and step forward to make hive a data source.

Please read https://issues.apache.org/jira/secure/attachment/12843835/CREATE-TABLE.pdf for  details.

TODO(for follow-up PRs):
1. TBLPROPERTIES is not added to the new syntax, we should decide if we wanna add it later.
2. `SHOW CREATE TABLE` should be updated to use the new syntax.
3. we should decide if we wanna change the behavior of `SET LOCATION`.

## How was this patch tested?

new tests

Author: Wenchen Fan <wenchen@databricks.com>

Closes #16296 from cloud-fan/create-table.
2017-01-05 17:40:27 -08:00
Wenchen Fan 30345c43b7 [SPARK-19058][SQL] fix partition related behaviors with DataFrameWriter.saveAsTable
## What changes were proposed in this pull request?

When we append data to a partitioned table with `DataFrameWriter.saveAsTable`, there are 2 issues:
1. doesn't work when the partition has custom location.
2. will recover all partitions

This PR fixes them by moving the special partition handling code from `DataSourceAnalysis` to `InsertIntoHadoopFsRelationCommand`, so that the `DataFrameWriter.saveAsTable` code path can also benefit from it.

## How was this patch tested?

newly added regression tests

Author: Wenchen Fan <wenchen@databricks.com>

Closes #16460 from cloud-fan/append.
2017-01-05 14:11:05 +08:00
Herman van Hovell 4262fb0d55 [SPARK-19070] Clean-up dataset actions
## What changes were proposed in this pull request?
Dataset actions currently spin off a new `Dataframe` only to track query execution. This PR simplifies this code path by using the `Dataset.queryExecution` directly. This PR also merges the typed and untyped action evaluation paths.

## How was this patch tested?
Existing tests.

Author: Herman van Hovell <hvanhovell@databricks.com>

Closes #16466 from hvanhovell/SPARK-19070.
2017-01-04 23:47:58 +08:00
Niranjan Padmanabhan a1e40b1f5d
[MINOR][DOCS] Remove consecutive duplicated words/typo in Spark Repo
## What changes were proposed in this pull request?
There are many locations in the Spark repo where the same word occurs consecutively. Sometimes they are appropriately placed, but many times they are not. This PR removes the inappropriately duplicated words.

## How was this patch tested?
N/A since only docs or comments were updated.

Author: Niranjan Padmanabhan <niranjan.padmanabhan@gmail.com>

Closes #16455 from neurons/np.structure_streaming_doc.
2017-01-04 15:07:29 +00:00
Wenchen Fan 101556d0fa [SPARK-19060][SQL] remove the supportsPartial flag in AggregateFunction
## What changes were proposed in this pull request?

Now all aggregation functions support partial aggregate, we can remove the `supportsPartual` flag in `AggregateFunction`

## How was this patch tested?

existing tests.

Author: Wenchen Fan <wenchen@databricks.com>

Closes #16461 from cloud-fan/partial.
2017-01-04 12:46:30 +01:00
Wenchen Fan cbd11d2357 [SPARK-19072][SQL] codegen of Literal should not output boxed value
## What changes were proposed in this pull request?

In https://github.com/apache/spark/pull/16402 we made a mistake that, when double/float is infinity, the `Literal` codegen will output boxed value and cause wrong result.

This PR fixes this by special handling infinity to not output boxed value.

## How was this patch tested?

new regression test

Author: Wenchen Fan <wenchen@databricks.com>

Closes #16469 from cloud-fan/literal.
2017-01-03 22:40:14 -08:00
gatorsmile b67b35f76b [SPARK-19048][SQL] Delete Partition Location when Dropping Managed Partitioned Tables in InMemoryCatalog
### What changes were proposed in this pull request?
The data in the managed table should be deleted after table is dropped. However, if the partition location is not under the location of the partitioned table, it is not deleted as expected. Users can specify any location for the partition when they adding a partition.

This PR is to delete partition location when dropping managed partitioned tables stored in `InMemoryCatalog`.

### How was this patch tested?
Added test cases for both HiveExternalCatalog and InMemoryCatalog

Author: gatorsmile <gatorsmile@gmail.com>

Closes #16448 from gatorsmile/unsetSerdeProp.
2017-01-03 11:43:47 -08:00
Dongjoon Hyun 7a2b5f93bc [SPARK-18877][SQL] CSVInferSchema.inferField on DecimalType should find a common type with typeSoFar
## What changes were proposed in this pull request?

CSV type inferencing causes `IllegalArgumentException` on decimal numbers with heterogeneous precisions and scales because the current logic uses the last decimal type in a **partition**. Specifically, `inferRowType`, the **seqOp** of **aggregate**, returns the last decimal type. This PR fixes it to use `findTightestCommonType`.

**decimal.csv**
```
9.03E+12
1.19E+11
```

**BEFORE**
```scala
scala> spark.read.format("csv").option("inferSchema", true).load("decimal.csv").printSchema
root
 |-- _c0: decimal(3,-9) (nullable = true)

scala> spark.read.format("csv").option("inferSchema", true).load("decimal.csv").show
16/12/16 14:32:49 ERROR Executor: Exception in task 0.0 in stage 4.0 (TID 4)
java.lang.IllegalArgumentException: requirement failed: Decimal precision 4 exceeds max precision 3
```

**AFTER**
```scala
scala> spark.read.format("csv").option("inferSchema", true).load("decimal.csv").printSchema
root
 |-- _c0: decimal(4,-9) (nullable = true)

scala> spark.read.format("csv").option("inferSchema", true).load("decimal.csv").show
+---------+
|      _c0|
+---------+
|9.030E+12|
| 1.19E+11|
+---------+
```

## How was this patch tested?

Pass the newly add test case.

Author: Dongjoon Hyun <dongjoon@apache.org>

Closes #16320 from dongjoon-hyun/SPARK-18877.
2017-01-03 23:06:50 +08:00
Liang-Chi Hsieh 52636226dc [SPARK-18932][SQL] Support partial aggregation for collect_set/collect_list
## What changes were proposed in this pull request?

Currently collect_set/collect_list aggregation expression don't support partial aggregation. This patch is to enable partial aggregation for them.

## How was this patch tested?

Jenkins tests.

Please review http://spark.apache.org/contributing.html before opening a pull request.

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

Closes #16371 from viirya/collect-partial-support.
2017-01-03 22:11:54 +08:00
Zhenhua Wang ae83c21125 [SPARK-18998][SQL] Add a cbo conf to switch between default statistics and estimated statistics
## What changes were proposed in this pull request?

We add a cbo configuration to switch between default stats and estimated stats.
We also define a new statistics method `planStats` in LogicalPlan with conf as its parameter, in order to pass the cbo switch and other estimation related configurations in the future. `planStats` is used on the caller sides (i.e. in Optimizer and Strategies) to make transformation decisions based on stats.

## How was this patch tested?

Add a test case using a dummy LogicalPlan.

Author: Zhenhua Wang <wzh_zju@163.com>

Closes #16401 from wzhfy/cboSwitch.
2017-01-03 12:19:52 +08:00
gatorsmile a6cd9dbc60 [SPARK-19029][SQL] Remove databaseName from SimpleCatalogRelation
### What changes were proposed in this pull request?
Remove useless `databaseName ` from `SimpleCatalogRelation`.

### How was this patch tested?
Existing test cases.

Author: gatorsmile <gatorsmile@gmail.com>

Closes #16438 from gatorsmile/removeDBFromSimpleCatalogRelation.
2017-01-03 11:55:31 +08:00
hyukjinkwon 46b2126024
[SPARK-19002][BUILD][PYTHON] Check pep8 against all Python scripts
## What changes were proposed in this pull request?

This PR proposes to check pep8 against all other Python scripts and fix the errors as below:

```bash
./dev/create-release/generate-contributors.py
./dev/create-release/releaseutils.py
./dev/create-release/translate-contributors.py
./dev/lint-python
./python/docs/epytext.py
./examples/src/main/python/mllib/decision_tree_classification_example.py
./examples/src/main/python/mllib/decision_tree_regression_example.py
./examples/src/main/python/mllib/gradient_boosting_classification_example.py
./examples/src/main/python/mllib/gradient_boosting_regression_example.py
./examples/src/main/python/mllib/linear_regression_with_sgd_example.py
./examples/src/main/python/mllib/logistic_regression_with_lbfgs_example.py
./examples/src/main/python/mllib/naive_bayes_example.py
./examples/src/main/python/mllib/random_forest_classification_example.py
./examples/src/main/python/mllib/random_forest_regression_example.py
./examples/src/main/python/mllib/svm_with_sgd_example.py
./examples/src/main/python/streaming/network_wordjoinsentiments.py
./sql/hive/src/test/resources/data/scripts/cat.py
./sql/hive/src/test/resources/data/scripts/cat_error.py
./sql/hive/src/test/resources/data/scripts/doubleescapedtab.py
./sql/hive/src/test/resources/data/scripts/dumpdata_script.py
./sql/hive/src/test/resources/data/scripts/escapedcarriagereturn.py
./sql/hive/src/test/resources/data/scripts/escapednewline.py
./sql/hive/src/test/resources/data/scripts/escapedtab.py
./sql/hive/src/test/resources/data/scripts/input20_script.py
./sql/hive/src/test/resources/data/scripts/newline.py
```

## How was this patch tested?

- `./python/docs/epytext.py`

  ```bash
  cd ./python/docs $$ make html
  ```

- pep8 check (Python 2.7 / Python 3.3.6)

  ```
  ./dev/lint-python
  ```

- `./dev/merge_spark_pr.py` (Python 2.7 only / Python 3.3.6 not working)

  ```bash
  python -m doctest -v ./dev/merge_spark_pr.py
  ```

- `./dev/create-release/releaseutils.py` `./dev/create-release/generate-contributors.py` `./dev/create-release/translate-contributors.py` (Python 2.7 only / Python 3.3.6 not working)

  ```bash
  python generate-contributors.py
  python translate-contributors.py
  ```

- Examples (Python 2.7 / Python 3.3.6)

  ```bash
  ./bin/spark-submit examples/src/main/python/mllib/decision_tree_classification_example.py
  ./bin/spark-submit examples/src/main/python/mllib/decision_tree_regression_example.py
  ./bin/spark-submit examples/src/main/python/mllib/gradient_boosting_classification_example.py
  ./bin/spark-submit examples/src/main/python/mllib/gradient_boosting_regression_example.p
  ./bin/spark-submit examples/src/main/python/mllib/random_forest_classification_example.py
  ./bin/spark-submit examples/src/main/python/mllib/random_forest_regression_example.py
  ```

- Examples (Python 2.7 only / Python 3.3.6 not working)
  ```
  ./bin/spark-submit examples/src/main/python/mllib/linear_regression_with_sgd_example.py
  ./bin/spark-submit examples/src/main/python/mllib/logistic_regression_with_lbfgs_example.py
  ./bin/spark-submit examples/src/main/python/mllib/naive_bayes_example.py
  ./bin/spark-submit examples/src/main/python/mllib/svm_with_sgd_example.py
  ```

- `sql/hive/src/test/resources/data/scripts/*.py` (Python 2.7 / Python 3.3.6 within suggested changes)

  Manually tested only changed ones.

- `./dev/github_jira_sync.py` (Python 2.7 only / Python 3.3.6 not working)

  Manually tested this after disabling actually adding comments and links.

And also via Jenkins tests.

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #16405 from HyukjinKwon/minor-pep8.
2017-01-02 15:23:19 +00:00
hyukjinkwon f1330b1d9e
[SPARK-19022][TESTS] Fix tests dependent on OS due to different newline characters
## What changes were proposed in this pull request?

There are two tests failing on Windows due to the different newlines.

```
 - StreamingQueryProgress - prettyJson *** FAILED *** (0 milliseconds)
 "{
    "id" : "39788670-6722-48b7-a248-df6ba08722ac",
    "runId" : "422282f1-3b81-4b47-a15d-82dda7e69390",
    "name" : "myName",
    ...
  }" did not equal "{
    "id" : "39788670-6722-48b7-a248-df6ba08722ac",
    "runId" : "422282f1-3b81-4b47-a15d-82dda7e69390",
    "name" : "myName",
    ...
  }"
  ...
```

```
 - StreamingQueryStatus - prettyJson *** FAILED *** (0 milliseconds)
 "{
    "message" : "active",
    "isDataAvailable" : true,
    "isTriggerActive" : false
  }" did not equal "{
    "message" : "active",
    "isDataAvailable" : true,
    "isTriggerActive" : false
  }"
  ...
```

The reason is, `pretty` in `org.json4s.pretty` writes OS-dependent newlines but the string defined in the tests are `\n`. This ends up with test failures.

This PR proposes to compare these regardless of newline concerns.

## How was this patch tested?

Manually tested via AppVeyor.

**Before**
https://ci.appveyor.com/project/spark-test/spark/build/417-newlines-fix-before

**After**
https://ci.appveyor.com/project/spark-test/spark/build/418-newlines-fix

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #16433 from HyukjinKwon/tests-StreamingQueryStatusAndProgressSuite.
2017-01-02 15:17:02 +00:00
Shixiong Zhu 2394047370 [SPARK-19050][SS][TESTS] Fix EventTimeWatermarkSuite 'delay in months and years handled correctly'
## What changes were proposed in this pull request?

`monthsSinceEpoch` in this test is like `math.floor(num)`, so `monthDiff` has two possible values.

## How was this patch tested?

Jenkins.

Author: Shixiong Zhu <shixiong@databricks.com>

Closes #16449 from zsxwing/watermark-test-hotfix.
2017-01-01 13:25:44 -08:00
gatorsmile 35e974076d [SPARK-19028][SQL] Fixed non-thread-safe functions used in SessionCatalog
### What changes were proposed in this pull request?
Fixed non-thread-safe functions used in SessionCatalog:
- refreshTable
- lookupRelation

### How was this patch tested?
N/A

Author: gatorsmile <gatorsmile@gmail.com>

Closes #16437 from gatorsmile/addSyncToLookUpTable.
2016-12-31 19:40:28 +08:00
Dongjoon Hyun b85e29437d [SPARK-18123][SQL] Use db column names instead of RDD column ones during JDBC Writing
## What changes were proposed in this pull request?

Apache Spark supports the following cases **by quoting RDD column names** while saving through JDBC.
- Allow reserved keyword as a column name, e.g., 'order'.
- Allow mixed-case colume names like the following, e.g., `[a: int, A: int]`.

  ``` scala
  scala> val df = sql("select 1 a, 1 A")
  df: org.apache.spark.sql.DataFrame = [a: int, A: int]
  ...
  scala> df.write.mode("overwrite").format("jdbc").options(option).save()
  scala> df.write.mode("append").format("jdbc").options(option).save()
  ```

This PR aims to use **database column names** instead of RDD column ones in order to support the following additionally.
Note that this case succeeds with `MySQL`, but fails on `Postgres`/`Oracle` before.

``` scala
val df1 = sql("select 1 a")
val df2 = sql("select 1 A")
...
df1.write.mode("overwrite").format("jdbc").options(option).save()
df2.write.mode("append").format("jdbc").options(option).save()
```
## How was this patch tested?

Pass the Jenkins test with a new testcase.

Author: Dongjoon Hyun <dongjoon@apache.org>
Author: gatorsmile <gatorsmile@gmail.com>

Closes #15664 from dongjoon-hyun/SPARK-18123.
2016-12-30 10:27:14 -08:00
hyukjinkwon 852782b83c
[SPARK-18922][TESTS] Fix more path-related test failures on Windows
## What changes were proposed in this pull request?

This PR proposes to fix the test failures due to different format of paths on Windows.

Failed tests are as below:

```
ColumnExpressionSuite:
- input_file_name, input_file_block_start, input_file_block_length - FileScanRDD *** FAILED *** (187 milliseconds)
  "file:///C:/projects/spark/target/tmp/spark-0b21b963-6cfa-411c-8d6f-e6a5e1e73bce/part-00001-c083a03a-e55e-4b05-9073-451de352d006.snappy.parquet" did not contain "C:\projects\spark\target\tmp\spark-0b21b963-6cfa-411c-8d6f-e6a5e1e73bce" (ColumnExpressionSuite.scala:545)

- input_file_name, input_file_block_start, input_file_block_length - HadoopRDD *** FAILED *** (172 milliseconds)
  "file:/C:/projects/spark/target/tmp/spark-5d0afa94-7c2f-463b-9db9-2e8403e2bc5f/part-00000-f6530138-9ad3-466d-ab46-0eeb6f85ed0b.txt" did not contain "C:\projects\spark\target\tmp\spark-5d0afa94-7c2f-463b-9db9-2e8403e2bc5f" (ColumnExpressionSuite.scala:569)

- input_file_name, input_file_block_start, input_file_block_length - NewHadoopRDD *** FAILED *** (156 milliseconds)
  "file:/C:/projects/spark/target/tmp/spark-a894c7df-c74d-4d19-82a2-a04744cb3766/part-00000-29674e3f-3fcf-4327-9b04-4dab1d46338d.txt" did not contain "C:\projects\spark\target\tmp\spark-a894c7df-c74d-4d19-82a2-a04744cb3766" (ColumnExpressionSuite.scala:598)
```

```
DataStreamReaderWriterSuite:
- source metadataPath *** FAILED *** (62 milliseconds)
  org.mockito.exceptions.verification.junit.ArgumentsAreDifferent: Argument(s) are different! Wanted:
streamSourceProvider.createSource(
    org.apache.spark.sql.SQLContext3b04133b,
    "C:\projects\spark\target\tmp\streaming.metadata-b05db6ae-c8dc-4ce4-b0d9-1eb8c84876c0/sources/0",
    None,
    "org.apache.spark.sql.streaming.test",
    Map()
);
-> at org.apache.spark.sql.streaming.test.DataStreamReaderWriterSuite$$anonfun$12.apply$mcV$sp(DataStreamReaderWriterSuite.scala:374)
Actual invocation has different arguments:
streamSourceProvider.createSource(
    org.apache.spark.sql.SQLContext3b04133b,
    "/C:/projects/spark/target/tmp/streaming.metadata-b05db6ae-c8dc-4ce4-b0d9-1eb8c84876c0/sources/0",
    None,
    "org.apache.spark.sql.streaming.test",
    Map()
);
```

```
GlobalTempViewSuite:
- CREATE GLOBAL TEMP VIEW USING *** FAILED *** (110 milliseconds)
  org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark  arget mpspark-960398ba-a0a1-45f6-a59a-d98533f9f519;
```

```
CreateTableAsSelectSuite:
- CREATE TABLE USING AS SELECT *** FAILED *** (0 milliseconds)
  java.lang.IllegalArgumentException: Can not create a Path from an empty string

- create a table, drop it and create another one with the same name *** FAILED *** (16 milliseconds)
  java.lang.IllegalArgumentException: Can not create a Path from an empty string

- create table using as select - with partitioned by *** FAILED *** (0 milliseconds)
  java.lang.IllegalArgumentException: Can not create a Path from an empty string

- create table using as select - with non-zero buckets *** FAILED *** (0 milliseconds)
  java.lang.IllegalArgumentException: Can not create a Path from an empty string
```

```
HiveMetadataCacheSuite:
- partitioned table is cached when partition pruning is true *** FAILED *** (532 milliseconds)
  org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

- partitioned table is cached when partition pruning is false *** FAILED *** (297 milliseconds)
  org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
```

```
MultiDatabaseSuite:
- createExternalTable() to non-default database - with USE *** FAILED *** (954 milliseconds)
  org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark  arget mpspark-0839d9a7-5e29-467a-9e3e-3e4cd618ee09;

- createExternalTable() to non-default database - without USE *** FAILED *** (500 milliseconds)
  org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark  arget mpspark-c7e24d73-1d8f-45e8-ab7d-53a83087aec3;

 - invalid database name and table names *** FAILED *** (31 milliseconds)
   "Path does not exist: file:/C:projectsspark  arget mpspark-15a2a494-3483-4876-80e5-ec396e704b77;" did not contain "`t:a` is not a valid name for tables/databases. Valid names only contain alphabet characters, numbers and _." (MultiDatabaseSuite.scala:296)
```

```
OrcQuerySuite:
 - SPARK-8501: Avoids discovery schema from empty ORC files *** FAILED *** (15 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

 - Verify the ORC conversion parameter: CONVERT_METASTORE_ORC *** FAILED *** (78 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

 - converted ORC table supports resolving mixed case field *** FAILED *** (297 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
```

```
HadoopFsRelationTest - JsonHadoopFsRelationSuite, OrcHadoopFsRelationSuite, ParquetHadoopFsRelationSuite, SimpleTextHadoopFsRelationSuite:
 - Locality support for FileScanRDD *** FAILED *** (15 milliseconds)
   java.lang.IllegalArgumentException: Wrong FS: file://C:\projects\spark\target\tmp\spark-383d1f13-8783-47fd-964d-9c75e5eec50f, expected: file:///
```

```
HiveQuerySuite:
- CREATE TEMPORARY FUNCTION *** FAILED *** (0 milliseconds)
   java.net.MalformedURLException: For input string: "%5Cprojects%5Cspark%5Csql%5Chive%5Ctarget%5Cscala-2.11%5Ctest-classes%5CTestUDTF.jar"

 - ADD FILE command *** FAILED *** (500 milliseconds)
   java.net.URISyntaxException: Illegal character in opaque part at index 2: C:\projects\spark\sql\hive\target\scala-2.11\test-classes\data\files\v1.txt

 - ADD JAR command 2 *** FAILED *** (110 milliseconds)
   org.apache.spark.sql.AnalysisException: LOAD DATA input path does not exist: C:projectssparksqlhive  argetscala-2.11 est-classesdatafilessample.json;
```

```
PruneFileSourcePartitionsSuite:
 - PruneFileSourcePartitions should not change the output of LogicalRelation *** FAILED *** (15 milliseconds)
   org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
```

```
HiveCommandSuite:
 - LOAD DATA LOCAL *** FAILED *** (109 milliseconds)
   org.apache.spark.sql.AnalysisException: LOAD DATA input path does not exist: C:projectssparksqlhive  argetscala-2.11 est-classesdatafilesemployee.dat;

 - LOAD DATA *** FAILED *** (93 milliseconds)
   java.net.URISyntaxException: Illegal character in opaque part at index 15: C:projectsspark arget mpemployee.dat7496657117354281006.tmp

 - Truncate Table *** FAILED *** (78 milliseconds)
   org.apache.spark.sql.AnalysisException: LOAD DATA input path does not exist: C:projectssparksqlhive  argetscala-2.11 est-classesdatafilesemployee.dat;
```

```
HiveExternalCatalogBackwardCompatibilitySuite:
- make sure we can read table created by old version of Spark *** FAILED *** (0 milliseconds)
  "[/C:/projects/spark/target/tmp/]spark-0554d859-74e1-..." did not equal "[C:\projects\spark\target\tmp\]spark-0554d859-74e1-..." (HiveExternalCatalogBackwardCompatibilitySuite.scala:213)
  org.scalatest.exceptions.TestFailedException

- make sure we can alter table location created by old version of Spark *** FAILED *** (110 milliseconds)
  java.net.URISyntaxException: Illegal character in opaque part at index 15: C:projectsspark	arget	mpspark-0e9b2c5f-49a1-4e38-a32a-c0ab1813a79f
```

```
ExternalCatalogSuite:
- create/drop/rename partitions should create/delete/rename the directory *** FAILED *** (610 milliseconds)
  java.net.URISyntaxException: Illegal character in opaque part at index 2: C:\projects\spark\target\tmp\spark-4c24f010-18df-437b-9fed-990c6f9adece
```

```
SQLQuerySuite:
- describe functions - temporary user defined functions *** FAILED *** (16 milliseconds)
  java.net.URISyntaxException: Illegal character in opaque part at index 22: C:projectssparksqlhive	argetscala-2.11	est-classesTestUDTF.jar

- specifying database name for a temporary table is not allowed *** FAILED *** (125 milliseconds)
  org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget	mpspark-a34c9814-a483-43f2-be29-37f616b6df91;
```

```
PartitionProviderCompatibilitySuite:
- convert partition provider to hive with repair table *** FAILED *** (281 milliseconds)
  org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget	mpspark-ee5fc96d-8c7d-4ebf-8571-a1d62736473e;

- when partition management is enabled, new tables have partition provider hive *** FAILED *** (187 milliseconds)
  org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget	mpspark-803ad4d6-3e8c-498d-9ca5-5cda5d9b2a48;

- when partition management is disabled, new tables have no partition provider *** FAILED *** (172 milliseconds)
  org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget	mpspark-c9fda9e2-4020-465f-8678-52cd72d0a58f;

- when partition management is disabled, we preserve the old behavior even for new tables *** FAILED *** (203 milliseconds)
  org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget
mpspark-f4a518a6-c49d-43d3-b407-0ddd76948e13;

- insert overwrite partition of legacy datasource table *** FAILED *** (188 milliseconds)
  org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget	mpspark-f4a518a6-c49d-43d3-b407-0ddd76948e79;

- insert overwrite partition of new datasource table overwrites just partition *** FAILED *** (219 milliseconds)
  org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget	mpspark-6ba3a88d-6f6c-42c5-a9f4-6d924a0616ff;

- SPARK-18544 append with saveAsTable - partition management true *** FAILED *** (173 milliseconds)
  org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget	mpspark-cd234a6d-9cb4-4d1d-9e51-854ae9543bbd;

- SPARK-18635 special chars in partition values - partition management true *** FAILED *** (2 seconds, 967 milliseconds)
  org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

- SPARK-18635 special chars in partition values - partition management false *** FAILED *** (62 milliseconds)
  org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

- SPARK-18659 insert overwrite table with lowercase - partition management true *** FAILED *** (63 milliseconds)
  org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

- SPARK-18544 append with saveAsTable - partition management false *** FAILED *** (266 milliseconds)
  org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

- SPARK-18659 insert overwrite table files - partition management false *** FAILED *** (63 milliseconds)
  org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

- SPARK-18659 insert overwrite table with lowercase - partition management false *** FAILED *** (78 milliseconds)
  org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

- sanity check table setup *** FAILED *** (31 milliseconds)
  org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

- insert into partial dynamic partitions *** FAILED *** (47 milliseconds)
  org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

- insert into fully dynamic partitions *** FAILED *** (62 milliseconds)
  org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

- insert into static partition *** FAILED *** (78 milliseconds)
  org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

- overwrite partial dynamic partitions *** FAILED *** (63 milliseconds)
  org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

- overwrite fully dynamic partitions *** FAILED *** (47 milliseconds)
  org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

- overwrite static partition *** FAILED *** (63 milliseconds)
  org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
```

```
MetastoreDataSourcesSuite:
- check change without refresh *** FAILED *** (203 milliseconds)
  org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget	mpspark-00713fe4-ca04-448c-bfc7-6c5e9a2ad2a1;

- drop, change, recreate *** FAILED *** (78 milliseconds)
  org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget	mpspark-2030a21b-7d67-4385-a65b-bb5e2bed4861;

- SPARK-15269 external data source table creation *** FAILED *** (78 milliseconds)
  org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget	mpspark-4d50fd4a-14bc-41d6-9232-9554dd233f86;

- CTAS *** FAILED *** (109 milliseconds)
  java.lang.IllegalArgumentException: Can not create a Path from an empty string

- CTAS with IF NOT EXISTS *** FAILED *** (109 milliseconds)
  java.lang.IllegalArgumentException: Can not create a Path from an empty string

- CTAS: persisted partitioned bucketed data source table *** FAILED *** (0 milliseconds)
  java.lang.IllegalArgumentException: Can not create a Path from an empty string

- SPARK-15025: create datasource table with path with select *** FAILED *** (16 milliseconds)
  java.lang.IllegalArgumentException: Can not create a Path from an empty string

- CTAS: persisted partitioned data source table *** FAILED *** (47 milliseconds)
  java.lang.IllegalArgumentException: Can not create a Path from an empty string
```

```
HiveMetastoreCatalogSuite:
- Persist non-partitioned parquet relation into metastore as managed table using CTAS *** FAILED *** (16 milliseconds)
  java.lang.IllegalArgumentException: Can not create a Path from an empty string

- Persist non-partitioned orc relation into metastore as managed table using CTAS *** FAILED *** (16 milliseconds)
  java.lang.IllegalArgumentException: Can not create a Path from an empty string
```

```
HiveUDFSuite:
- SPARK-11522 select input_file_name from non-parquet table *** FAILED *** (16 milliseconds)
  org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
```

```
QueryPartitionSuite:
- SPARK-13709: reading partitioned Avro table with nested schema *** FAILED *** (250 milliseconds)
  org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
```

```
ParquetHiveCompatibilitySuite:
- simple primitives *** FAILED *** (16 milliseconds)
  org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

- SPARK-10177 timestamp *** FAILED *** (0 milliseconds)
  org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

- array *** FAILED *** (16 milliseconds)
  org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

- map *** FAILED *** (16 milliseconds)
  org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

- struct *** FAILED *** (0 milliseconds)
  org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);

- SPARK-16344: array of struct with a single field named 'array_element' *** FAILED *** (15 milliseconds)
  org.apache.spark.sql.AnalysisException: org.apache.hadoop.hive.ql.metadata.HiveException: MetaException(message:java.lang.IllegalArgumentException: Can not create a Path from an empty string);
```

## How was this patch tested?

Manually tested via AppVeyor.

```
ColumnExpressionSuite:
- input_file_name, input_file_block_start, input_file_block_length - FileScanRDD (234 milliseconds)
- input_file_name, input_file_block_start, input_file_block_length - HadoopRDD (235 milliseconds)
- input_file_name, input_file_block_start, input_file_block_length - NewHadoopRDD (203 milliseconds)
```

```
DataStreamReaderWriterSuite:
- source metadataPath (63 milliseconds)
```

```
GlobalTempViewSuite:
 - CREATE GLOBAL TEMP VIEW USING (436 milliseconds)
```

```
CreateTableAsSelectSuite:
- CREATE TABLE USING AS SELECT (171 milliseconds)
- create a table, drop it and create another one with the same name (422 milliseconds)
- create table using as select - with partitioned by (141 milliseconds)
- create table using as select - with non-zero buckets (125 milliseconds)
```

```
HiveMetadataCacheSuite:
- partitioned table is cached when partition pruning is true (3 seconds, 211 milliseconds)
- partitioned table is cached when partition pruning is false (1 second, 781 milliseconds)
```

```
MultiDatabaseSuite:
 - createExternalTable() to non-default database - with USE (797 milliseconds)
 - createExternalTable() to non-default database - without USE (640 milliseconds)
 - invalid database name and table names (62 milliseconds)
```

```
OrcQuerySuite:
 - SPARK-8501: Avoids discovery schema from empty ORC files (703 milliseconds)
 - Verify the ORC conversion parameter: CONVERT_METASTORE_ORC (750 milliseconds)
 - converted ORC table supports resolving mixed case field (625 milliseconds)
```

```
HadoopFsRelationTest - JsonHadoopFsRelationSuite, OrcHadoopFsRelationSuite, ParquetHadoopFsRelationSuite, SimpleTextHadoopFsRelationSuite:
 - Locality support for FileScanRDD (296 milliseconds)
```

```
HiveQuerySuite:
 - CREATE TEMPORARY FUNCTION (125 milliseconds)
 - ADD FILE command (250 milliseconds)
 - ADD JAR command 2 (609 milliseconds)
```

```
PruneFileSourcePartitionsSuite:
- PruneFileSourcePartitions should not change the output of LogicalRelation (359 milliseconds)
```

```
HiveCommandSuite:
 - LOAD DATA LOCAL (1 second, 829 milliseconds)
 - LOAD DATA (1 second, 735 milliseconds)
 - Truncate Table (1 second, 641 milliseconds)
```

```
HiveExternalCatalogBackwardCompatibilitySuite:
 - make sure we can read table created by old version of Spark (32 milliseconds)
 - make sure we can alter table location created by old version of Spark (125 milliseconds)
 - make sure we can rename table created by old version of Spark (281 milliseconds)
```

```
ExternalCatalogSuite:
- create/drop/rename partitions should create/delete/rename the directory (625 milliseconds)
```

```
SQLQuerySuite:
- describe functions - temporary user defined functions (31 milliseconds)
- specifying database name for a temporary table is not allowed (390 milliseconds)
```

```
PartitionProviderCompatibilitySuite:
 - convert partition provider to hive with repair table (813 milliseconds)
 - when partition management is enabled, new tables have partition provider hive (562 milliseconds)
 - when partition management is disabled, new tables have no partition provider (344 milliseconds)
 - when partition management is disabled, we preserve the old behavior even for new tables (422 milliseconds)
 - insert overwrite partition of legacy datasource table (750 milliseconds)
 - SPARK-18544 append with saveAsTable - partition management true (985 milliseconds)
 - SPARK-18635 special chars in partition values - partition management true (3 seconds, 328 milliseconds)
 - SPARK-18635 special chars in partition values - partition management false (2 seconds, 891 milliseconds)
 - SPARK-18659 insert overwrite table with lowercase - partition management true (750 milliseconds)
 - SPARK-18544 append with saveAsTable - partition management false (656 milliseconds)
 - SPARK-18659 insert overwrite table files - partition management false (922 milliseconds)
 - SPARK-18659 insert overwrite table with lowercase - partition management false (469 milliseconds)
 - sanity check table setup (937 milliseconds)
 - insert into partial dynamic partitions (2 seconds, 985 milliseconds)
 - insert into fully dynamic partitions (1 second, 937 milliseconds)
 - insert into static partition (1 second, 578 milliseconds)
 - overwrite partial dynamic partitions (7 seconds, 561 milliseconds)
 - overwrite fully dynamic partitions (1 second, 766 milliseconds)
 - overwrite static partition (1 second, 797 milliseconds)
```

```
MetastoreDataSourcesSuite:
 - check change without refresh (610 milliseconds)
 - drop, change, recreate (437 milliseconds)
 - SPARK-15269 external data source table creation (297 milliseconds)
 - CTAS with IF NOT EXISTS (437 milliseconds)
 - CTAS: persisted partitioned bucketed data source table (422 milliseconds)
 - SPARK-15025: create datasource table with path with select (265 milliseconds)
 - CTAS (438 milliseconds)
 - CTAS with IF NOT EXISTS (469 milliseconds)
 - CTAS: persisted partitioned bucketed data source table (406 milliseconds)
```

```
HiveMetastoreCatalogSuite:
 - Persist non-partitioned parquet relation into metastore as managed table using CTAS (406 milliseconds)
 - Persist non-partitioned orc relation into metastore as managed table using CTAS (313 milliseconds)
```

```
HiveUDFSuite:
 - SPARK-11522 select input_file_name from non-parquet table (3 seconds, 144 milliseconds)
```

```
QueryPartitionSuite:
 - SPARK-13709: reading partitioned Avro table with nested schema (1 second, 67 milliseconds)
```

```
ParquetHiveCompatibilitySuite:
 - simple primitives (745 milliseconds)
 - SPARK-10177 timestamp (375 milliseconds)
 - array (407 milliseconds)
 - map (409 milliseconds)
 - struct (437 milliseconds)
 - SPARK-16344: array of struct with a single field named 'array_element' (391 milliseconds)
```

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #16397 from HyukjinKwon/SPARK-18922-paths.
2016-12-30 11:16:03 +00:00
Dongjoon Hyun 752d9eeb9b [SPARK-19012][SQL] Fix createTempViewCommand to throw AnalysisException instead of ParseException
## What changes were proposed in this pull request?

Currently, `createTempView`, `createOrReplaceTempView`, and `createGlobalTempView` show `ParseExceptions` on invalid table names. We had better show better error message. Also, this PR also adds and updates the missing description on the API docs correctly.

**BEFORE**
```
scala> spark.range(10).createOrReplaceTempView("11111")
org.apache.spark.sql.catalyst.parser.ParseException:
mismatched input '11111' expecting {'SELECT', 'FROM', 'ADD', ...}(line 1, pos 0)

== SQL ==
11111
...
```

**AFTER**
```
scala> spark.range(10).createOrReplaceTempView("11111")
org.apache.spark.sql.AnalysisException: Invalid view name: 11111;
...
```

## How was this patch tested?

Pass the Jenkins with updated a test case.

Author: Dongjoon Hyun <dongjoon@apache.org>

Closes #16427 from dongjoon-hyun/SPARK-19012.
2016-12-29 21:22:13 +01:00
Wenchen Fan 7d19b6ab7d [SPARK-18567][SQL] Simplify CreateDataSourceTableAsSelectCommand
## What changes were proposed in this pull request?

The `CreateDataSourceTableAsSelectCommand` is quite complex now, as it has a lot of work to do if the table already exists:

1. throw exception if we don't want to ignore it.
2. do some check and adjust the schema if we want to append data.
3. drop the table and create it again if we want to overwrite.

The work 2 and 3 should be done by analyzer, so that we can also apply it to hive tables.

## How was this patch tested?

existing tests.

Author: Wenchen Fan <wenchen@databricks.com>

Closes #15996 from cloud-fan/append.
2016-12-28 21:50:21 -08:00
Kazuaki Ishizaki 93f35569fd [SPARK-16213][SQL] Reduce runtime overhead of a program that creates an primitive array in DataFrame
## What changes were proposed in this pull request?

This PR reduces runtime overhead of a program the creates an primitive array in DataFrame by using the similar approach to #15044. Generated code performs boxing operation in an assignment from InternalRow to an `Object[]` temporary array (at Lines 051 and 061 in the generated code before without this PR). If we know that type of array elements is primitive, we apply the following optimizations:
1. Eliminate a pair of `isNullAt()` and a null assignment
2. Allocate an primitive array instead of `Object[]` (eliminate boxing operations)
3. Create `UnsafeArrayData` by using `UnsafeArrayWriter` to keep a primitive array in a row format instead of doing non-lightweight operations in constructor of `GenericArrayData`
The PR also performs the same things for `CreateMap`.

Here are performance results of [DataFrame programs](6bf54ec5e2/sql/core/src/test/scala/org/apache/spark/sql/execution/benchmark/PrimitiveArrayBenchmark.scala (L83-L112)) by up to 17.9x over without this PR.

```
Without SPARK-16043
OpenJDK 64-Bit Server VM 1.8.0_91-b14 on Linux 4.4.11-200.fc22.x86_64
Intel Xeon E3-12xx v2 (Ivy Bridge)
Read a primitive array in DataFrame:     Best/Avg Time(ms)    Rate(M/s)   Per Row(ns)   Relative
------------------------------------------------------------------------------------------------
Int                                           3805 / 4150          0.0      507308.9       1.0X
Double                                        3593 / 3852          0.0      479056.9       1.1X

With SPARK-16043
Read a primitive array in DataFrame:     Best/Avg Time(ms)    Rate(M/s)   Per Row(ns)   Relative
------------------------------------------------------------------------------------------------
Int                                            213 /  271          0.0       28387.5       1.0X
Double                                         204 /  223          0.0       27250.9       1.0X
```
Note : #15780 is enabled for these measurements

An motivating example

``` java
val df = sparkContext.parallelize(Seq(0.0d, 1.0d), 1).toDF
df.selectExpr("Array(value + 1.1d, value + 2.2d)").show
```

Generated code without this PR

``` java
/* 005 */ final class GeneratedIterator extends org.apache.spark.sql.execution.BufferedRowIterator {
/* 006 */   private Object[] references;
/* 007 */   private scala.collection.Iterator[] inputs;
/* 008 */   private scala.collection.Iterator inputadapter_input;
/* 009 */   private UnsafeRow serializefromobject_result;
/* 010 */   private org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder serializefromobject_holder;
/* 011 */   private org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter serializefromobject_rowWriter;
/* 012 */   private Object[] project_values;
/* 013 */   private UnsafeRow project_result;
/* 014 */   private org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder project_holder;
/* 015 */   private org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter project_rowWriter;
/* 016 */   private org.apache.spark.sql.catalyst.expressions.codegen.UnsafeArrayWriter project_arrayWriter;
/* 017 */
/* 018 */   public GeneratedIterator(Object[] references) {
/* 019 */     this.references = references;
/* 020 */   }
/* 021 */
/* 022 */   public void init(int index, scala.collection.Iterator[] inputs) {
/* 023 */     partitionIndex = index;
/* 024 */     this.inputs = inputs;
/* 025 */     inputadapter_input = inputs[0];
/* 026 */     serializefromobject_result = new UnsafeRow(1);
/* 027 */     this.serializefromobject_holder = new org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder(serializefromobject_result, 0);
/* 028 */     this.serializefromobject_rowWriter = new org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter(serializefromobject_holder, 1);
/* 029 */     this.project_values = null;
/* 030 */     project_result = new UnsafeRow(1);
/* 031 */     this.project_holder = new org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder(project_result, 32);
/* 032 */     this.project_rowWriter = new org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter(project_holder, 1);
/* 033 */     this.project_arrayWriter = new org.apache.spark.sql.catalyst.expressions.codegen.UnsafeArrayWriter();
/* 034 */
/* 035 */   }
/* 036 */
/* 037 */   protected void processNext() throws java.io.IOException {
/* 038 */     while (inputadapter_input.hasNext()) {
/* 039 */       InternalRow inputadapter_row = (InternalRow) inputadapter_input.next();
/* 040 */       double inputadapter_value = inputadapter_row.getDouble(0);
/* 041 */
/* 042 */       final boolean project_isNull = false;
/* 043 */       this.project_values = new Object[2];
/* 044 */       boolean project_isNull1 = false;
/* 045 */
/* 046 */       double project_value1 = -1.0;
/* 047 */       project_value1 = inputadapter_value + 1.1D;
/* 048 */       if (false) {
/* 049 */         project_values[0] = null;
/* 050 */       } else {
/* 051 */         project_values[0] = project_value1;
/* 052 */       }
/* 053 */
/* 054 */       boolean project_isNull4 = false;
/* 055 */
/* 056 */       double project_value4 = -1.0;
/* 057 */       project_value4 = inputadapter_value + 2.2D;
/* 058 */       if (false) {
/* 059 */         project_values[1] = null;
/* 060 */       } else {
/* 061 */         project_values[1] = project_value4;
/* 062 */       }
/* 063 */
/* 064 */       final ArrayData project_value = new org.apache.spark.sql.catalyst.util.GenericArrayData(project_values);
/* 065 */       this.project_values = null;
/* 066 */       project_holder.reset();
/* 067 */
/* 068 */       project_rowWriter.zeroOutNullBytes();
/* 069 */
/* 070 */       if (project_isNull) {
/* 071 */         project_rowWriter.setNullAt(0);
/* 072 */       } else {
/* 073 */         // Remember the current cursor so that we can calculate how many bytes are
/* 074 */         // written later.
/* 075 */         final int project_tmpCursor = project_holder.cursor;
/* 076 */
/* 077 */         if (project_value instanceof UnsafeArrayData) {
/* 078 */           final int project_sizeInBytes = ((UnsafeArrayData) project_value).getSizeInBytes();
/* 079 */           // grow the global buffer before writing data.
/* 080 */           project_holder.grow(project_sizeInBytes);
/* 081 */           ((UnsafeArrayData) project_value).writeToMemory(project_holder.buffer, project_holder.cursor);
/* 082 */           project_holder.cursor += project_sizeInBytes;
/* 083 */
/* 084 */         } else {
/* 085 */           final int project_numElements = project_value.numElements();
/* 086 */           project_arrayWriter.initialize(project_holder, project_numElements, 8);
/* 087 */
/* 088 */           for (int project_index = 0; project_index < project_numElements; project_index++) {
/* 089 */             if (project_value.isNullAt(project_index)) {
/* 090 */               project_arrayWriter.setNullDouble(project_index);
/* 091 */             } else {
/* 092 */               final double project_element = project_value.getDouble(project_index);
/* 093 */               project_arrayWriter.write(project_index, project_element);
/* 094 */             }
/* 095 */           }
/* 096 */         }
/* 097 */
/* 098 */         project_rowWriter.setOffsetAndSize(0, project_tmpCursor, project_holder.cursor - project_tmpCursor);
/* 099 */       }
/* 100 */       project_result.setTotalSize(project_holder.totalSize());
/* 101 */       append(project_result);
/* 102 */       if (shouldStop()) return;
/* 103 */     }
/* 104 */   }
/* 105 */ }
```

Generated code with this PR

``` java
/* 005 */ final class GeneratedIterator extends org.apache.spark.sql.execution.BufferedRowIterator {
/* 006 */   private Object[] references;
/* 007 */   private scala.collection.Iterator[] inputs;
/* 008 */   private scala.collection.Iterator inputadapter_input;
/* 009 */   private UnsafeRow serializefromobject_result;
/* 010 */   private org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder serializefromobject_holder;
/* 011 */   private org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter serializefromobject_rowWriter;
/* 012 */   private UnsafeArrayData project_arrayData;
/* 013 */   private UnsafeRow project_result;
/* 014 */   private org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder project_holder;
/* 015 */   private org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter project_rowWriter;
/* 016 */   private org.apache.spark.sql.catalyst.expressions.codegen.UnsafeArrayWriter project_arrayWriter;
/* 017 */
/* 018 */   public GeneratedIterator(Object[] references) {
/* 019 */     this.references = references;
/* 020 */   }
/* 021 */
/* 022 */   public void init(int index, scala.collection.Iterator[] inputs) {
/* 023 */     partitionIndex = index;
/* 024 */     this.inputs = inputs;
/* 025 */     inputadapter_input = inputs[0];
/* 026 */     serializefromobject_result = new UnsafeRow(1);
/* 027 */     this.serializefromobject_holder = new org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder(serializefromobject_result, 0);
/* 028 */     this.serializefromobject_rowWriter = new org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter(serializefromobject_holder, 1);
/* 029 */
/* 030 */     project_result = new UnsafeRow(1);
/* 031 */     this.project_holder = new org.apache.spark.sql.catalyst.expressions.codegen.BufferHolder(project_result, 32);
/* 032 */     this.project_rowWriter = new org.apache.spark.sql.catalyst.expressions.codegen.UnsafeRowWriter(project_holder, 1);
/* 033 */     this.project_arrayWriter = new org.apache.spark.sql.catalyst.expressions.codegen.UnsafeArrayWriter();
/* 034 */
/* 035 */   }
/* 036 */
/* 037 */   protected void processNext() throws java.io.IOException {
/* 038 */     while (inputadapter_input.hasNext()) {
/* 039 */       InternalRow inputadapter_row = (InternalRow) inputadapter_input.next();
/* 040 */       double inputadapter_value = inputadapter_row.getDouble(0);
/* 041 */
/* 042 */       byte[] project_array = new byte[32];
/* 043 */       project_arrayData = new UnsafeArrayData();
/* 044 */       Platform.putLong(project_array, 16, 2);
/* 045 */       project_arrayData.pointTo(project_array, 16, 32);
/* 046 */
/* 047 */       boolean project_isNull1 = false;
/* 048 */
/* 049 */       double project_value1 = -1.0;
/* 050 */       project_value1 = inputadapter_value + 1.1D;
/* 051 */       if (false) {
/* 052 */         project_arrayData.setNullAt(0);
/* 053 */       } else {
/* 054 */         project_arrayData.setDouble(0, project_value1);
/* 055 */       }
/* 056 */
/* 057 */       boolean project_isNull4 = false;
/* 058 */
/* 059 */       double project_value4 = -1.0;
/* 060 */       project_value4 = inputadapter_value + 2.2D;
/* 061 */       if (false) {
/* 062 */         project_arrayData.setNullAt(1);
/* 063 */       } else {
/* 064 */         project_arrayData.setDouble(1, project_value4);
/* 065 */       }
/* 066 */       project_holder.reset();
/* 067 */
/* 068 */       // Remember the current cursor so that we can calculate how many bytes are
/* 069 */       // written later.
/* 070 */       final int project_tmpCursor = project_holder.cursor;
/* 071 */
/* 072 */       if (project_arrayData instanceof UnsafeArrayData) {
/* 073 */         final int project_sizeInBytes = ((UnsafeArrayData) project_arrayData).getSizeInBytes();
/* 074 */         // grow the global buffer before writing data.
/* 075 */         project_holder.grow(project_sizeInBytes);
/* 076 */         ((UnsafeArrayData) project_arrayData).writeToMemory(project_holder.buffer, project_holder.cursor);
/* 077 */         project_holder.cursor += project_sizeInBytes;
/* 078 */
/* 079 */       } else {
/* 080 */         final int project_numElements = project_arrayData.numElements();
/* 081 */         project_arrayWriter.initialize(project_holder, project_numElements, 8);
/* 082 */
/* 083 */         for (int project_index = 0; project_index < project_numElements; project_index++) {
/* 084 */           if (project_arrayData.isNullAt(project_index)) {
/* 085 */             project_arrayWriter.setNullDouble(project_index);
/* 086 */           } else {
/* 087 */             final double project_element = project_arrayData.getDouble(project_index);
/* 088 */             project_arrayWriter.write(project_index, project_element);
/* 089 */           }
/* 090 */         }
/* 091 */       }
/* 092 */
/* 093 */       project_rowWriter.setOffsetAndSize(0, project_tmpCursor, project_holder.cursor - project_tmpCursor);
/* 094 */       project_result.setTotalSize(project_holder.totalSize());
/* 095 */       append(project_result);
/* 096 */       if (shouldStop()) return;
/* 097 */     }
/* 098 */   }
/* 099 */ }
```
## How was this patch tested?

Added unit tests into `DataFrameComplexTypeSuite`

Author: Kazuaki Ishizaki <ishizaki@jp.ibm.com>
Author: Liang-Chi Hsieh <viirya@gmail.com>

Closes #13909 from kiszk/SPARK-16213.
2016-12-29 10:59:37 +08:00
Carson Wang 2a5f52a714
[MINOR][DOC] Fix doc of ForeachWriter to use writeStream
## What changes were proposed in this pull request?

Fix the document of `ForeachWriter` to use `writeStream` instead of `write` for a streaming dataset.

## How was this patch tested?
Docs only.

Author: Carson Wang <carson.wang@intel.com>

Closes #16419 from carsonwang/FixDoc.
2016-12-28 12:12:44 +00:00
uncleGen 76e9bd7488
[SPARK-18960][SQL][SS] Avoid double reading file which is being copied.
## What changes were proposed in this pull request?

In HDFS, when we copy a file into target directory, there will a temporary `._COPY_` file for a period of time. The duration depends on file size. If we do not skip this file, we will may read the same data for two times.

## How was this patch tested?
update unit test

Author: uncleGen <hustyugm@gmail.com>

Closes #16370 from uncleGen/SPARK-18960.
2016-12-28 10:42:47 +00:00
gatorsmile 5ac62043cf [SPARK-18992][SQL] Move spark.sql.hive.thriftServer.singleSession to SQLConf
### What changes were proposed in this pull request?

Since `spark.sql.hive.thriftServer.singleSession` is a configuration of SQL component, this conf can be moved from `SparkConf` to `StaticSQLConf`.

When we introduced `spark.sql.hive.thriftServer.singleSession`, all the SQL configuration are session specific. They can be modified in different sessions.

In Spark 2.1, static SQL configuration is added. It is a perfect fit for `spark.sql.hive.thriftServer.singleSession`. Previously, we did the same move for `spark.sql.warehouse.dir` from `SparkConf` to `StaticSQLConf`

### How was this patch tested?
Added test cases in HiveThriftServer2Suites.scala

Author: gatorsmile <gatorsmile@gmail.com>

Closes #16392 from gatorsmile/hiveThriftServerSingleSession.
2016-12-28 10:16:22 +08:00
Yin Huai 2404d8e54b Revert "[SPARK-18990][SQL] make DatasetBenchmark fairer for Dataset"
This reverts commit a05cc425a0.
2016-12-27 10:03:52 -08:00
Wenchen Fan a05cc425a0 [SPARK-18990][SQL] make DatasetBenchmark fairer for Dataset
## What changes were proposed in this pull request?

Currently `DatasetBenchmark` use `case class Data(l: Long, s: String)` as the record type of `RDD` and `Dataset`, which introduce serialization overhead only to `Dataset` and is unfair.

This PR use `Long` as the record type, to be fairer for `Dataset`

## How was this patch tested?

existing tests

Author: Wenchen Fan <wenchen@databricks.com>

Closes #16391 from cloud-fan/benchmark.
2016-12-27 22:42:28 +08:00
Dongjoon Hyun c2a2069dae [SPARK-19004][SQL] Fix JDBCWriteSuite.testH2Dialect by removing getCatalystType
## What changes were proposed in this pull request?

`JDBCSuite` and `JDBCWriterSuite` have their own `testH2Dialect`s for their testing purposes.

This PR fixes `testH2Dialect` in `JDBCWriterSuite` by removing `getCatalystType` implementation in order to return correct types. Currently, it always returns `Some(StringType)` incorrectly. Note that, for the `testH2Dialect` in `JDBCSuite`, it's intentional because of the test case `Remap types via JdbcDialects`.

## How was this patch tested?

This is a test only update.

Author: Dongjoon Hyun <dongjoon@apache.org>

Closes #16409 from dongjoon-hyun/SPARK-H2-DIALECT.
2016-12-27 06:26:56 -08:00
Wenchen Fan 6ddbf467b4 [SPARK-18999][SQL][MINOR] simplify Literal codegen
## What changes were proposed in this pull request?

`Literal` can use `CodegenContex.addReferenceObj` to implement codegen, instead of `CodegenFallback`.  This can also simplify the generated code a little bit, before we will generate: `((Expression) references[1]).eval(null)`, now it's just `references[1]`.

## How was this patch tested?

N/A

Author: Wenchen Fan <wenchen@databricks.com>

Closes #16402 from cloud-fan/minor.
2016-12-27 06:22:12 -08:00
Wenchen Fan dd724c84c8 [SPARK-18989][SQL] DESC TABLE should not fail with format class not found
## What changes were proposed in this pull request?

When we describe a table, we only wanna see the information of this table, not read it, so it's ok even if the format class is not present at the classpath.

## How was this patch tested?

new regression test

Author: Wenchen Fan <wenchen@databricks.com>

Closes #16388 from cloud-fan/hive.
2016-12-26 11:27:56 -08:00
Wenchen Fan 8a7db8a608 [SPARK-18980][SQL] implement Aggregator with TypedImperativeAggregate
## What changes were proposed in this pull request?

Currently we implement `Aggregator` with `DeclarativeAggregate`, which will serialize/deserialize the buffer object every time we process an input.

This PR implements `Aggregator` with `TypedImperativeAggregate` and avoids to serialize/deserialize buffer object many times. The benchmark shows we get about 2 times speed up.

For simple buffer object that doesn't need serialization, we still go with `DeclarativeAggregate`, to avoid performance regression.

## How was this patch tested?

N/A

Author: Wenchen Fan <wenchen@databricks.com>

Closes #16383 from cloud-fan/aggregator.
2016-12-26 22:10:20 +08:00
hyukjinkwon d6cbec7598 [SPARK-18943][SQL] Avoid per-record type dispatch in CSV when reading
## What changes were proposed in this pull request?

`CSVRelation.csvParser` does type dispatch for each value in each row. We can prevent this because the schema is already kept in `CSVRelation`.

So, this PR proposes that converters are created first according to the schema, and then apply them to each.

I just ran some small benchmarks as below after resembling the logics in 7c33b0fd05/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/CSVFileFormat.scala (L170-L178) to test the updated logics.

```scala
test("Benchmark for CSV converter") {
  var numMalformedRecords = 0
  val N = 500 << 12
  val schema = StructType(
    StructField("a", StringType) ::
    StructField("b", StringType) ::
    StructField("c", StringType) ::
    StructField("d", StringType) :: Nil)

  val row = Array("1.0", "test", "2015-08-20 14:57:00", "FALSE")
  val data = spark.sparkContext.parallelize(List.fill(N)(row))
  val parser = CSVRelation.csvParser(schema, schema.fieldNames, CSVOptions())

  val benchmark = new Benchmark("CSV converter", N)
  benchmark.addCase("cast CSV string tokens", 10) { _ =>
    data.flatMap { recordTokens =>
      parser(recordTokens, numMalformedRecords)
    }.collect()
  }
  benchmark.run()
}
```

**Before**

```
CSV converter:                           Best/Avg Time(ms)    Rate(M/s)   Per Row(ns)   Relative
------------------------------------------------------------------------------------------------
cast CSV string tokens                        1061 / 1130          1.9         517.9       1.0X
```

**After**

```
CSV converter:                           Best/Avg Time(ms)    Rate(M/s)   Per Row(ns)   Relative
------------------------------------------------------------------------------------------------
cast CSV string tokens                         940 / 1011          2.2         459.2       1.0X
```

## How was this patch tested?

Tests in `CSVTypeCastSuite` and `CSVRelation`

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #16351 from HyukjinKwon/type-dispatch.
2016-12-24 23:28:34 +08:00