diff options
Diffstat (limited to 'core/src/main/scala/org/apache/spark/api/java/JavaSparkContext.scala')
| -rw-r--r-- | core/src/main/scala/org/apache/spark/api/java/JavaSparkContext.scala | 60 |
1 files changed, 32 insertions, 28 deletions
diff --git a/core/src/main/scala/org/apache/spark/api/java/JavaSparkContext.scala b/core/src/main/scala/org/apache/spark/api/java/JavaSparkContext.scala index d362c40b7a..dfd91ae338 100644 --- a/core/src/main/scala/org/apache/spark/api/java/JavaSparkContext.scala +++ b/core/src/main/scala/org/apache/spark/api/java/JavaSparkContext.scala @@ -295,13 +295,14 @@ class JavaSparkContext(val sc: SparkContext) new JavaRDD(sc.binaryRecords(path, recordLength)) } - /** Get an RDD for a Hadoop SequenceFile with given key and value types. - * - * '''Note:''' Because Hadoop's RecordReader class re-uses the same Writable object for each - * record, directly caching the returned RDD will create many references to the same object. - * If you plan to directly cache Hadoop writable objects, you should first copy them using - * a `map` function. - * */ + /** + * Get an RDD for a Hadoop SequenceFile with given key and value types. + * + * '''Note:''' Because Hadoop's RecordReader class re-uses the same Writable object for each + * record, directly caching the returned RDD will create many references to the same object. + * If you plan to directly cache Hadoop writable objects, you should first copy them using + * a `map` function. + */ def sequenceFile[K, V](path: String, keyClass: Class[K], valueClass: Class[V], @@ -312,13 +313,14 @@ class JavaSparkContext(val sc: SparkContext) new JavaPairRDD(sc.sequenceFile(path, keyClass, valueClass, minPartitions)) } - /** Get an RDD for a Hadoop SequenceFile. - * - * '''Note:''' Because Hadoop's RecordReader class re-uses the same Writable object for each - * record, directly caching the returned RDD will create many references to the same object. - * If you plan to directly cache Hadoop writable objects, you should first copy them using - * a `map` function. - */ + /** + * Get an RDD for a Hadoop SequenceFile. + * + * '''Note:''' Because Hadoop's RecordReader class re-uses the same Writable object for each + * record, directly caching the returned RDD will create many references to the same object. + * If you plan to directly cache Hadoop writable objects, you should first copy them using + * a `map` function. + */ def sequenceFile[K, V](path: String, keyClass: Class[K], valueClass: Class[V]): JavaPairRDD[K, V] = { implicit val ctagK: ClassTag[K] = ClassTag(keyClass) @@ -411,13 +413,14 @@ class JavaSparkContext(val sc: SparkContext) new JavaHadoopRDD(rdd.asInstanceOf[HadoopRDD[K, V]]) } - /** Get an RDD for a Hadoop file with an arbitrary InputFormat. - * - * '''Note:''' Because Hadoop's RecordReader class re-uses the same Writable object for each - * record, directly caching the returned RDD will create many references to the same object. - * If you plan to directly cache Hadoop writable objects, you should first copy them using - * a `map` function. - */ + /** + * Get an RDD for a Hadoop file with an arbitrary InputFormat. + * + * '''Note:''' Because Hadoop's RecordReader class re-uses the same Writable object for each + * record, directly caching the returned RDD will create many references to the same object. + * If you plan to directly cache Hadoop writable objects, you should first copy them using + * a `map` function. + */ def hadoopFile[K, V, F <: InputFormat[K, V]]( path: String, inputFormatClass: Class[F], @@ -431,13 +434,14 @@ class JavaSparkContext(val sc: SparkContext) new JavaHadoopRDD(rdd.asInstanceOf[HadoopRDD[K, V]]) } - /** Get an RDD for a Hadoop file with an arbitrary InputFormat - * - * '''Note:''' Because Hadoop's RecordReader class re-uses the same Writable object for each - * record, directly caching the returned RDD will create many references to the same object. - * If you plan to directly cache Hadoop writable objects, you should first copy them using - * a `map` function. - */ + /** + * Get an RDD for a Hadoop file with an arbitrary InputFormat + * + * '''Note:''' Because Hadoop's RecordReader class re-uses the same Writable object for each + * record, directly caching the returned RDD will create many references to the same object. + * If you plan to directly cache Hadoop writable objects, you should first copy them using + * a `map` function. + */ def hadoopFile[K, V, F <: InputFormat[K, V]]( path: String, inputFormatClass: Class[F], |