spark-instrumented-optimizer/sql
hyukjinkwon 7f3c778fd0
[SPARK-18718][TESTS] Skip some test failures due to path length limitation and fix tests to pass on Windows
## What changes were proposed in this pull request?

There are some tests failed on Windows due to the wrong format of path and the limitation of path length as below:

This PR proposes both to fix the failed tests by fixing the path for the tests below:

- `InsertSuite`
  ```
  Exception encountered when attempting to run a suite with class name: org.apache.spark.sql.sources.InsertSuite *** ABORTED *** (12 seconds, 547 milliseconds)
      org.apache.spark.sql.AnalysisException: Path does not exist: file:/C:projectsspark	arget	mpspark-177945ef-9128-42b4-8c07-de31f78bbbd6;
      at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$14.apply(DataSource.scala:382)
      at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$14.apply(DataSource.scala:370)
      at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
  ```

- `PathOptionSuite`
  ```
  - path option also exist for write path *** FAILED *** (1 second, 93 milliseconds)
    "C:[projectsspark	arget	mp]spark-5ab34a58-df8d-..." did not equal "C:[\projects\spark\target\tmp\]spark-5ab34a58-df8d-..." (PathOptionSuite.scala:93)
    org.scalatest.exceptions.TestFailedException:
        at org.scalatest.Assertions$class.newAssertionFailedException(Assertions.scala:500)
        at org.scalatest.FunSuite.newAssertionFailedException(FunSuite.scala:1555)
    ...
  ```

- `UDFSuite`
  ```
  - SPARK-8005 input_file_name *** FAILED *** (2 seconds, 234 milliseconds)
    "file:///C:/projects/spark/target/tmp/spark-e4e5720a-2006-48f9-8b11-797bf59794bf/part-00001-26fb05e4-603d-471d-ae9d-b9549e0c7765.snappy.parquet" did not contain "C:\projects\spark\target\tmp\spark-e4e5720a-2006-48f9-8b11-797bf59794bf" (UDFSuite.scala:67)
    org.scalatest.exceptions.TestFailedException:
      at org.scalatest.Assertions$class.newAssertionFailedException(Assertions.scala:500)
      at org.scalatest.FunSuite.newAssertionFailedException(FunSuite.scala:1555)
    ...
  ```

and to skip the tests belows which are being failed on Windows due to path length limitation.

- `SparkLauncherSuite`
  ```
  Test org.apache.spark.launcher.SparkLauncherSuite.testChildProcLauncher failed: java.lang.AssertionError: expected:<0> but was:<1>, took 0.062 sec
    at org.apache.spark.launcher.SparkLauncherSuite.testChildProcLauncher(SparkLauncherSuite.java:177)
      ...
  ```

  The stderr from the process is `The filename or extension is too long` which is equivalent to the one below.

- `BroadcastJoinSuite`
  ```
  04:09:40.882 ERROR org.apache.spark.deploy.worker.ExecutorRunner: Error running executor
  java.io.IOException: Cannot run program "C:\Progra~1\Java\jdk1.8.0\bin\java" (in directory "C:\projects\spark\work\app-20161205040542-0000\51658"): CreateProcess error=206, The filename or extension is too long
      at java.lang.ProcessBuilder.start(ProcessBuilder.java:1048)
      at org.apache.spark.deploy.worker.ExecutorRunner.org$apache$spark$deploy$worker$ExecutorRunner$$fetchAndRunExecutor(ExecutorRunner.scala:167)
      at org.apache.spark.deploy.worker.ExecutorRunner$$anon$1.run(ExecutorRunner.scala:73)
  Caused by: java.io.IOException: CreateProcess error=206, The filename or extension is too long
      at java.lang.ProcessImpl.create(Native Method)
      at java.lang.ProcessImpl.<init>(ProcessImpl.java:386)
      at java.lang.ProcessImpl.start(ProcessImpl.java:137)
      at java.lang.ProcessBuilder.start(ProcessBuilder.java:1029)
      ... 2 more
  04:09:40.929 ERROR org.apache.spark.deploy.worker.ExecutorRunner: Error running executor

    (appearently infinite same error messages)

  ...
  ```

## How was this patch tested?

Manually tested via AppVeyor.

**Before**

`InsertSuite`: https://ci.appveyor.com/project/spark-test/spark/build/148-InsertSuite-pr
`PathOptionSuite`: https://ci.appveyor.com/project/spark-test/spark/build/139-PathOptionSuite-pr
`UDFSuite`: https://ci.appveyor.com/project/spark-test/spark/build/143-UDFSuite-pr
`SparkLauncherSuite`: https://ci.appveyor.com/project/spark-test/spark/build/141-SparkLauncherSuite-pr
`BroadcastJoinSuite`: https://ci.appveyor.com/project/spark-test/spark/build/145-BroadcastJoinSuite-pr

**After**

`PathOptionSuite`: https://ci.appveyor.com/project/spark-test/spark/build/140-PathOptionSuite-pr
`SparkLauncherSuite`: https://ci.appveyor.com/project/spark-test/spark/build/142-SparkLauncherSuite-pr
`UDFSuite`: https://ci.appveyor.com/project/spark-test/spark/build/144-UDFSuite-pr
`InsertSuite`: https://ci.appveyor.com/project/spark-test/spark/build/147-InsertSuite-pr
`BroadcastJoinSuite`: https://ci.appveyor.com/project/spark-test/spark/build/149-BroadcastJoinSuite-pr

Author: hyukjinkwon <gurwls223@gmail.com>

Closes #16147 from HyukjinKwon/fix-tests.
2016-12-08 23:02:05 +08:00
..
catalyst [SPARK-18654][SQL] Remove unreachable patterns in makeRootConverter 2016-12-07 16:52:05 -08:00
core [SPARK-18718][TESTS] Skip some test failures due to path length limitation and fix tests to pass on Windows 2016-12-08 23:02:05 +08:00
hive [SPARK-18572][SQL] Add a method listPartitionNames to ExternalCatalog 2016-12-06 11:33:35 +08:00
hive-thriftserver [SPARK-18695] Bump master branch version to 2.2.0-SNAPSHOT 2016-12-02 21:09:37 -08:00
README.md [SPARK-16557][SQL] Remove stale doc in sql/README.md 2016-07-14 19:24:42 -07:00

Spark SQL

This module provides support for executing relational queries expressed in either SQL or the DataFrame/Dataset API.

Spark SQL is broken up into four subprojects:

  • Catalyst (sql/catalyst) - An implementation-agnostic framework for manipulating trees of relational operators and expressions.
  • Execution (sql/core) - A query planner / execution engine for translating Catalyst's logical query plans into Spark RDDs. This component also includes a new public interface, SQLContext, that allows users to execute SQL or LINQ statements against existing RDDs and Parquet files.
  • Hive Support (sql/hive) - Includes an extension of SQLContext called HiveContext that allows users to write queries using a subset of HiveQL and access data from a Hive Metastore using Hive SerDes. There are also wrappers that allows users to run queries that include Hive UDFs, UDAFs, and UDTFs.
  • HiveServer and CLI support (sql/hive-thriftserver) - Includes support for the SQL CLI (bin/spark-sql) and a HiveServer2 (for JDBC/ODBC) compatible server.