[SPARK-10330] Add Scalastyle rule to require use of SparkHadoopUtil JobContext methods

core/src/main/scala/org/apache/spark/SparkContext.scala

@@ -858,7 +858,7 @@ class SparkContext(config: SparkConf) extends Logging with ExecutorAllocationCli
     // Use setInputPaths so that wholeTextFiles aligns with hadoopFile/textFile in taking
     // comma separated files as input. (see SPARK-7155)
     NewFileInputFormat.setInputPaths(job, path)
-    val updateConf = job.getConfiguration
+    val updateConf = SparkHadoopUtil.get.getConfigurationFromJobContext(job)
     new WholeTextFileRDD(
       this,
       classOf[WholeTextFileInputFormat],
@@ -910,7 +910,7 @@ class SparkContext(config: SparkConf) extends Logging with ExecutorAllocationCli
     // Use setInputPaths so that binaryFiles aligns with hadoopFile/textFile in taking
     // comma separated files as input. (see SPARK-7155)
     NewFileInputFormat.setInputPaths(job, path)
-    val updateConf = job.getConfiguration
+    val updateConf = SparkHadoopUtil.get.getConfigurationFromJobContext(job)
     new BinaryFileRDD(
       this,
       classOf[StreamInputFormat],
@@ -1092,7 +1092,7 @@ class SparkContext(config: SparkConf) extends Logging with ExecutorAllocationCli
     // Use setInputPaths so that newAPIHadoopFile aligns with hadoopFile/textFile in taking
     // comma separated files as input. (see SPARK-7155)
     NewFileInputFormat.setInputPaths(job, path)
-    val updatedConf = job.getConfiguration
+    val updatedConf = SparkHadoopUtil.get.getConfigurationFromJobContext(job)
     new NewHadoopRDD(this, fClass, kClass, vClass, updatedConf).setName(path)
   }
 

core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala

@@ -192,7 +192,9 @@ class SparkHadoopUtil extends Logging {
    * while it's interface in Hadoop 2.+.
    */
   def getConfigurationFromJobContext(context: JobContext): Configuration = {
+    // scalastyle:off jobconfig
     val method = context.getClass.getMethod("getConfiguration")
+    // scalastyle:on jobconfig
     method.invoke(context).asInstanceOf[Configuration]
   }
 
@@ -204,7 +206,9 @@ class SparkHadoopUtil extends Logging {
    */
   def getTaskAttemptIDFromTaskAttemptContext(
       context: MapReduceTaskAttemptContext): MapReduceTaskAttemptID = {
+    // scalastyle:off jobconfig
     val method = context.getClass.getMethod("getTaskAttemptID")
+    // scalastyle:on jobconfig
     method.invoke(context).asInstanceOf[MapReduceTaskAttemptID]
   }
 

core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala

@@ -934,8 +934,9 @@ class PairRDDFunctions[K, V](self: RDD[(K, V)])
     job.setOutputKeyClass(keyClass)
     job.setOutputValueClass(valueClass)
     job.setOutputFormatClass(outputFormatClass)
-    job.getConfiguration.set("mapred.output.dir", path)
-    saveAsNewAPIHadoopDataset(job.getConfiguration)
+    val jobConfiguration = SparkHadoopUtil.get.getConfigurationFromJobContext(job)
+    jobConfiguration.set("mapred.output.dir", path)
+    saveAsNewAPIHadoopDataset(jobConfiguration)
   }
 
   /**
@@ -1002,7 +1003,8 @@ class PairRDDFunctions[K, V](self: RDD[(K, V)])
     val formatter = new SimpleDateFormat("yyyyMMddHHmm")
     val jobtrackerID = formatter.format(new Date())
     val stageId = self.id
-    val wrappedConf = new SerializableConfiguration(job.getConfiguration)
+    val jobConfiguration = SparkHadoopUtil.get.getConfigurationFromJobContext(job)
+    val wrappedConf = new SerializableConfiguration(jobConfiguration)
     val outfmt = job.getOutputFormatClass
     val jobFormat = outfmt.newInstance
 

core/src/main/scala/org/apache/spark/rdd/SqlNewHadoopRDD.scala

@@ -86,7 +86,7 @@ private[spark] class SqlNewHadoopRDD[V: ClassTag](
     if (isDriverSide) {
       initDriverSideJobFuncOpt.map(f => f(job))
     }
-    job.getConfiguration
+    SparkHadoopUtil.get.getConfigurationFromJobContext(job)
   }
 
   private val jobTrackerId: String = {

core/src/test/scala/org/apache/spark/FileSuite.scala

@@ -19,6 +19,7 @@ package org.apache.spark
 
 import java.io.{File, FileWriter}
 
+import org.apache.spark.deploy.SparkHadoopUtil
 import org.apache.spark.input.PortableDataStream
 import org.apache.spark.storage.StorageLevel
 
@@ -506,8 +507,9 @@ class FileSuite extends SparkFunSuite with LocalSparkContext {
     job.setOutputKeyClass(classOf[String])
     job.setOutputValueClass(classOf[String])
     job.setOutputFormatClass(classOf[NewTextOutputFormat[String, String]])
-    job.getConfiguration.set("mapred.output.dir", tempDir.getPath + "/outputDataset_new")
-    randomRDD.saveAsNewAPIHadoopDataset(job.getConfiguration)
+    val jobConfig = SparkHadoopUtil.get.getConfigurationFromJobContext(job)
+    jobConfig.set("mapred.output.dir", tempDir.getPath + "/outputDataset_new")
+    randomRDD.saveAsNewAPIHadoopDataset(jobConfig)
     assert(new File(tempDir.getPath + "/outputDataset_new/part-r-00000").exists() === true)
   }
 

examples/src/main/scala/org/apache/spark/examples/CassandraCQLTest.scala

@@ -16,6 +16,7 @@
  */
 
  // scalastyle:off println
+ // scalastyle:off jobcontext
 package org.apache.spark.examples
 
 import java.nio.ByteBuffer
@@ -81,6 +82,7 @@ object CassandraCQLTest {
 
     val job = new Job()
     job.setInputFormatClass(classOf[CqlPagingInputFormat])
+    val configuration = job.getConfiguration
     ConfigHelper.setInputInitialAddress(job.getConfiguration(), cHost)
     ConfigHelper.setInputRpcPort(job.getConfiguration(), cPort)
     ConfigHelper.setInputColumnFamily(job.getConfiguration(), KeySpace, InputColumnFamily)
@@ -135,3 +137,4 @@ object CassandraCQLTest {
   }
 }
 // scalastyle:on println
+// scalastyle:on jobcontext

examples/src/main/scala/org/apache/spark/examples/CassandraTest.scala

@@ -16,6 +16,7 @@
  */
 
 // scalastyle:off println
+// scalastyle:off jobcontext
 package org.apache.spark.examples
 
 import java.nio.ByteBuffer
@@ -130,6 +131,7 @@ object CassandraTest {
   }
 }
 // scalastyle:on println
+// scalastyle:on jobcontext
 
 /*
 create keyspace casDemo;

scalastyle-config.xml

@@ -168,6 +168,14 @@ This file is divided into 3 sections:
     scala.collection.JavaConverters._ and use .asScala / .asJava methods</customMessage>
   </check>
 
+  <!-- As of SPARK-10330 JobContext methods should not be called directly -->
+  <check customId="jobcontext" level="error" class="org.scalastyle.scalariform.TokenChecker" enabled="true">
+    <parameters><parameter name="regex">^getConfiguration$|^getTaskAttemptID$</parameter></parameters>
+    <customMessage>Instead of calling .getConfiguration() or .getTaskAttemptID() directly,
+    use SparkHadoopUtil's getConfigurationFromJobContext() and getTaskAttemptIDFromTaskAttemptContext() methods.
+    </customMessage>
+  </check>
+
   <!-- ================================================================================ -->
   <!--       rules we'd like to enforce, but haven't cleaned up the codebase yet        -->
   <!-- ================================================================================ -->

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

@@ -47,7 +47,8 @@ private[sql] abstract class BaseWriterContainer(
 
   protected val dataSchema = relation.dataSchema
 
-  protected val serializableConf = new SerializableConfiguration(job.getConfiguration)
+  protected val serializableConf =
+    new SerializableConfiguration(SparkHadoopUtil.get.getConfigurationFromJobContext(job))
 
   // This UUID is used to avoid output file name collision between different appending write jobs.
   // These jobs may belong to different SparkContext instances. Concrete data source implementations
@@ -89,7 +90,8 @@ private[sql] abstract class BaseWriterContainer(
     // This UUID is sent to executor side together with the serialized `Configuration` object within
     // the `Job` instance.  `OutputWriters` on the executor side should use this UUID to generate
     // unique task output files.
-    job.getConfiguration.set("spark.sql.sources.writeJobUUID", uniqueWriteJobId.toString)
+    SparkHadoopUtil.get.getConfigurationFromJobContext(job).
+      set("spark.sql.sources.writeJobUUID", uniqueWriteJobId.toString)
 
     // Order of the following two lines is important.  For Hadoop 1, TaskAttemptContext constructor
     // clones the Configuration object passed in.  If we initialize the TaskAttemptContext first,
@@ -182,7 +184,9 @@ private[sql] abstract class BaseWriterContainer(
   private def setupIDs(jobId: Int, splitId: Int, attemptId: Int): Unit = {
     this.jobId = SparkHadoopWriter.createJobID(new Date, jobId)
     this.taskId = new TaskID(this.jobId, true, splitId)
+    // scalastyle:off jobcontext
     this.taskAttemptId = new TaskAttemptID(taskId, attemptId)
+    // scalastyle:on jobcontext
   }
 
   private def setupConf(): Unit = {

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

@@ -81,7 +81,7 @@ private[sql] class JSONRelation(
 
   private def createBaseRdd(inputPaths: Array[FileStatus]): RDD[String] = {
     val job = new Job(sqlContext.sparkContext.hadoopConfiguration)
-    val conf = job.getConfiguration
+    val conf = SparkHadoopUtil.get.getConfigurationFromJobContext(job)
 
     val paths = inputPaths.map(_.getPath)
 

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

@@ -71,7 +71,11 @@ private[parquet] class CatalystReadSupport extends ReadSupport[InternalRow] with
 
   // Called before `prepareForRead()` when initializing Parquet record reader.
   override def init(context: InitContext): ReadContext = {
-    val conf = context.getConfiguration
+    val conf = {
+      // scalastyle:off jobcontext
+      context.getConfiguration
+      // scalastyle:on jobcontext
+    }
 
     // If the target file was written by Spark SQL, we should be able to find a serialized Catalyst
     // schema of this file from its metadata.

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

@@ -53,7 +53,11 @@ private[parquet] class DirectParquetOutputCommitter(outputPath: Path, context: T
   override def setupTask(taskContext: TaskAttemptContext): Unit = {}
 
   override def commitJob(jobContext: JobContext) {
-    val configuration = ContextUtil.getConfiguration(jobContext)
+    val configuration = {
+      // scalastyle:off jobcontext
+      ContextUtil.getConfiguration(jobContext)
+      // scalastyle:on jobcontext
+    }
     val fileSystem = outputPath.getFileSystem(configuration)
 
     if (configuration.getBoolean(ParquetOutputFormat.ENABLE_JOB_SUMMARY, true)) {

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

@@ -211,7 +211,11 @@ private[sql] class ParquetRelation(
   override def sizeInBytes: Long = metadataCache.dataStatuses.map(_.getLen).sum
 
   override def prepareJobForWrite(job: Job): OutputWriterFactory = {
-    val conf = ContextUtil.getConfiguration(job)
+    val conf = {
+      // scalastyle:off jobcontext
+      ContextUtil.getConfiguration(job)
+      // scalastyle:on jobcontext
+    }
 
     // SPARK-9849 DirectParquetOutputCommitter qualified name should be backward compatible
     val committerClassname = conf.get(SQLConf.PARQUET_OUTPUT_COMMITTER_CLASS.key)
@@ -528,7 +532,7 @@ private[sql] object ParquetRelation extends Logging {
       assumeBinaryIsString: Boolean,
       assumeInt96IsTimestamp: Boolean,
       followParquetFormatSpec: Boolean)(job: Job): Unit = {
-    val conf = job.getConfiguration
+    val conf = SparkHadoopUtil.get.getConfigurationFromJobContext(job)
     conf.set(ParquetInputFormat.READ_SUPPORT_CLASS, classOf[CatalystReadSupport].getName)
 
     // Try to push down filters when filter push-down is enabled.
@@ -572,7 +576,7 @@ private[sql] object ParquetRelation extends Logging {
       FileInputFormat.setInputPaths(job, inputFiles.map(_.getPath): _*)
     }
 
-    overrideMinSplitSize(parquetBlockSize, job.getConfiguration)
+    overrideMinSplitSize(parquetBlockSize, SparkHadoopUtil.get.getConfigurationFromJobContext(job))
   }
 
   private[parquet] def readSchema(

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

@@ -123,7 +123,11 @@ private[parquet] object ParquetTypesConverter extends Logging {
       throw new IllegalArgumentException("Unable to read Parquet metadata: path is null")
     }
     val job = new Job()
-    val conf = configuration.getOrElse(ContextUtil.getConfiguration(job))
+    val conf = {
+      // scalastyle:off jobcontext
+      configuration.getOrElse(ContextUtil.getConfiguration(job))
+      // scalastyle:on jobcontext
+    }
     val fs: FileSystem = origPath.getFileSystem(conf)
     if (fs == null) {
       throw new IllegalArgumentException(s"Incorrectly formatted Parquet metadata path $origPath")

sql/hive/src/main/scala/org/apache/spark/sql/hive/orc/OrcRelation.scala

@@ -203,7 +203,7 @@ private[sql] class OrcRelation(
   }
 
   override def prepareJobForWrite(job: Job): OutputWriterFactory = {
-    job.getConfiguration match {
+    SparkHadoopUtil.get.getConfigurationFromJobContext(job) match {
       case conf: JobConf =>
         conf.setOutputFormat(classOf[OrcOutputFormat])
       case conf =>
@@ -284,7 +284,7 @@ private[orc] case class OrcTableScan(
 
   def execute(): RDD[InternalRow] = {
     val job = new Job(sqlContext.sparkContext.hadoopConfiguration)
-    val conf = job.getConfiguration
+    val conf = SparkHadoopUtil.get.getConfigurationFromJobContext(job)
 
     // Tries to push down filters if ORC filter push-down is enabled
     if (sqlContext.conf.orcFilterPushDown) {