Remove reflection, hard-code StorageLevels

The sc.StorageLevel -> StorageLevel pathway is a bit janky, but otherwise
the shell would have to call a private method of SparkContext. Having
StorageLevel available in sc also doesn't seem like the end of the world.
There may be a better solution, though.

As for creating the StorageLevel object itself, this seems to be the best
way in Python 2 for creating singleton, enum-like objects:
http://stackoverflow.com/questions/36932/how-can-i-represent-an-enum-in-python

1 files changed, 0 insertions, 11 deletions

diff --git a/core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala b/core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala
index c3b770a42c..ccd3833964 100644
--- a/core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala
+++ b/core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala
@@ -28,7 +28,6 @@ import org.apache.spark.broadcast.Broadcast
 import org.apache.spark._
 import org.apache.spark.rdd.RDD
 import org.apache.spark.rdd.PipedRDD
-import org.apache.spark.storage.StorageLevel
 import org.apache.spark.util.Utils
 
 
@@ -271,16 +270,6 @@ private[spark] object PythonRDD {
     JavaRDD.fromRDD(sc.sc.parallelize(objs, parallelism))
   }
 
-  /**
-   * Returns the StorageLevel with the given string name.
-   * Throws an exception if the name is not a valid StorageLevel.
-   */
-  def getStorageLevelByName(name: String) : StorageLevel = {
-    // In Scala, "val MEMORY_ONLY" produces a public getter by the same name.
-    val storageLevelGetter = StorageLevel.getClass().getDeclaredMethod(name)
-    return storageLevelGetter.invoke(StorageLevel).asInstanceOf[StorageLevel]
-  }
-
   def writeIteratorToPickleFile[T](items: java.util.Iterator[T], filename: String) {
     import scala.collection.JavaConverters._
     writeIteratorToPickleFile(items.asScala, filename)