[SPARK-10063][SQL] Remove DirectParquetOutputCommitter

docs/sql-programming-guide.md

@@ -1466,37 +1466,6 @@ Configuration of Parquet can be done using the `setConf` method on `SQLContext`
     support.
   </td>
 </tr>
-<tr>
-  <td><code>spark.sql.parquet.output.committer.class</code></td>
-  <td><code>org.apache.parquet.hadoop.<br />ParquetOutputCommitter</code></td>
-  <td>
-    <p>
-      The output committer class used by Parquet. The specified class needs to be a subclass of
-      <code>org.apache.hadoop.<br />mapreduce.OutputCommitter</code>. Typically, it's also a
-      subclass of <code>org.apache.parquet.hadoop.ParquetOutputCommitter</code>.
-    </p>
-    <p>
-      <b>Note:</b>
-      <ul>
-        <li>
-          This option is automatically ignored if <code>spark.speculation</code> is turned on.
-        </li>
-        <li>
-          This option must be set via Hadoop <code>Configuration</code> rather than Spark
-          <code>SQLConf</code>.
-        </li>
-        <li>
-          This option overrides <code>spark.sql.sources.<br />outputCommitterClass</code>.
-        </li>
-      </ul>
-    </p>
-    <p>
-      Spark SQL comes with a builtin
-      <code>org.apache.spark.sql.<br />parquet.DirectParquetOutputCommitter</code>, which can be more
-      efficient then the default Parquet output committer when writing data to S3.
-    </p>
-  </td>
-</tr>
 <tr>
   <td><code>spark.sql.parquet.mergeSchema</code></td>
   <td><code>false</code></td>
@@ -2165,8 +2134,6 @@ options.
  - In the `sql` dialect, floating point numbers are now parsed as decimal. HiveQL parsing remains
    unchanged.
  - The canonical name of SQL/DataFrame functions are now lower case (e.g. sum vs SUM).
- - It has been determined that using the DirectOutputCommitter when speculation is enabled is unsafe
-   and thus this output committer will not be used when speculation is on, independent of configuration.
  - JSON data source will not automatically load new files that are created by other applications
    (i.e. files that are not inserted to the dataset through Spark SQL).
    For a JSON persistent table (i.e. the metadata of the table is stored in Hive Metastore),

sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/WriterContainer.scala

@@ -129,16 +129,17 @@ private[sql] abstract class BaseWriterContainer(
       outputWriterFactory.newInstance(path, bucketId, dataSchema, taskAttemptContext)
     } catch {
       case e: org.apache.hadoop.fs.FileAlreadyExistsException =>
-        if (outputCommitter.isInstanceOf[parquet.DirectParquetOutputCommitter]) {
-          // Spark-11382: DirectParquetOutputCommitter is not idempotent, meaning on retry
+        if (outputCommitter.getClass.getName.contains("Direct")) {
+          // SPARK-11382: DirectParquetOutputCommitter is not idempotent, meaning on retry
           // attempts, the task will fail because the output file is created from a prior attempt.
           // This often means the most visible error to the user is misleading. Augment the error
           // to tell the user to look for the actual error.
           throw new SparkException("The output file already exists but this could be due to a " +
             "failure from an earlier attempt. Look through the earlier logs or stage page for " +
-            "the first error.\n  File exists error: " + e)
+            "the first error.\n  File exists error: " + e.getLocalizedMessage, e)
+        } else {
+          throw e
         }
-        throw e
     }
   }
 
@@ -156,15 +157,6 @@ private[sql] abstract class BaseWriterContainer(
         s"Using default output committer ${defaultOutputCommitter.getClass.getCanonicalName} " +
           "for appending.")
       defaultOutputCommitter
-    } else if (speculationEnabled) {
-      // When speculation is enabled, it's not safe to use customized output committer classes,
-      // especially direct output committers (e.g. `DirectParquetOutputCommitter`).
-      //
-      // See SPARK-9899 for more details.
-      logInfo(
-        s"Using default output committer ${defaultOutputCommitter.getClass.getCanonicalName} " +
-          "because spark.speculation is configured to be true.")
-      defaultOutputCommitter
     } else {
       val configuration = context.getConfiguration
       val committerClass = configuration.getClass(

sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetRelation.scala

@@ -76,13 +76,6 @@ private[sql] class DefaultSource
 
     val conf = ContextUtil.getConfiguration(job)
 
-    // SPARK-9849 DirectParquetOutputCommitter qualified name should be backward compatible
-    val committerClassName = conf.get(SQLConf.PARQUET_OUTPUT_COMMITTER_CLASS.key)
-    if (committerClassName == "org.apache.spark.sql.parquet.DirectParquetOutputCommitter") {
-      conf.set(SQLConf.PARQUET_OUTPUT_COMMITTER_CLASS.key,
-        classOf[DirectParquetOutputCommitter].getCanonicalName)
-    }
-
     val committerClass =
       conf.getClass(
         SQLConf.PARQUET_OUTPUT_COMMITTER_CLASS.key,

sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetIOSuite.scala

@@ -445,55 +445,6 @@ class ParquetIOSuite extends QueryTest with ParquetTest with SharedSQLContext {
     }
   }
 
-  testQuietly("SPARK-6352 DirectParquetOutputCommitter") {
-    val clonedConf = new Configuration(hadoopConfiguration)
-
-    // Write to a parquet file and let it fail.
-    // _temporary should be missing if direct output committer works.
-    try {
-      hadoopConfiguration.set("spark.sql.parquet.output.committer.class",
-        classOf[DirectParquetOutputCommitter].getCanonicalName)
-      sqlContext.udf.register("div0", (x: Int) => x / 0)
-      withTempPath { dir =>
-        intercept[org.apache.spark.SparkException] {
-          sqlContext.sql("select div0(1) as div0").write.parquet(dir.getCanonicalPath)
-        }
-        val path = new Path(dir.getCanonicalPath, "_temporary")
-        val fs = path.getFileSystem(hadoopConfiguration)
-        assert(!fs.exists(path))
-      }
-    } finally {
-      // Hadoop 1 doesn't have `Configuration.unset`
-      hadoopConfiguration.clear()
-      clonedConf.asScala.foreach(entry => hadoopConfiguration.set(entry.getKey, entry.getValue))
-    }
-  }
-
-  testQuietly("SPARK-9849 DirectParquetOutputCommitter qualified name backwards compatibility") {
-    val clonedConf = new Configuration(hadoopConfiguration)
-
-    // Write to a parquet file and let it fail.
-    // _temporary should be missing if direct output committer works.
-    try {
-      hadoopConfiguration.set("spark.sql.parquet.output.committer.class",
-        "org.apache.spark.sql.parquet.DirectParquetOutputCommitter")
-      sqlContext.udf.register("div0", (x: Int) => x / 0)
-      withTempPath { dir =>
-        intercept[org.apache.spark.SparkException] {
-          sqlContext.sql("select div0(1) as div0").write.parquet(dir.getCanonicalPath)
-        }
-        val path = new Path(dir.getCanonicalPath, "_temporary")
-        val fs = path.getFileSystem(hadoopConfiguration)
-        assert(!fs.exists(path))
-      }
-    } finally {
-      // Hadoop 1 doesn't have `Configuration.unset`
-      hadoopConfiguration.clear()
-      clonedConf.asScala.foreach(entry => hadoopConfiguration.set(entry.getKey, entry.getValue))
-    }
-  }
-
-
   test("SPARK-8121: spark.sql.parquet.output.committer.class shouldn't be overridden") {
     withTempPath { dir =>
       val clonedConf = new Configuration(hadoopConfiguration)