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Diffstat (limited to 'streaming/src/main/scala/spark/streaming/DStreamCheckpointData.scala')
-rw-r--r-- | streaming/src/main/scala/spark/streaming/DStreamCheckpointData.scala | 93 |
1 files changed, 93 insertions, 0 deletions
diff --git a/streaming/src/main/scala/spark/streaming/DStreamCheckpointData.scala b/streaming/src/main/scala/spark/streaming/DStreamCheckpointData.scala new file mode 100644 index 0000000000..6b0fade7c6 --- /dev/null +++ b/streaming/src/main/scala/spark/streaming/DStreamCheckpointData.scala @@ -0,0 +1,93 @@ +package spark.streaming + +import org.apache.hadoop.fs.Path +import org.apache.hadoop.fs.FileSystem +import org.apache.hadoop.conf.Configuration +import collection.mutable.HashMap +import spark.Logging + + + +private[streaming] +class DStreamCheckpointData[T: ClassManifest] (dstream: DStream[T]) + extends Serializable with Logging { + protected val data = new HashMap[Time, AnyRef]() + + @transient private var fileSystem : FileSystem = null + @transient private var lastCheckpointFiles: HashMap[Time, String] = null + + protected[streaming] def checkpointFiles = data.asInstanceOf[HashMap[Time, String]] + + /** + * Updates the checkpoint data of the DStream. This gets called every time + * the graph checkpoint is initiated. Default implementation records the + * checkpoint files to which the generate RDDs of the DStream has been saved. + */ + def update() { + + // Get the checkpointed RDDs from the generated RDDs + val newCheckpointFiles = dstream.generatedRDDs.filter(_._2.getCheckpointFile.isDefined) + .map(x => (x._1, x._2.getCheckpointFile.get)) + + // Make a copy of the existing checkpoint data (checkpointed RDDs) + lastCheckpointFiles = checkpointFiles.clone() + + // If the new checkpoint data has checkpoints then replace existing with the new one + if (newCheckpointFiles.size > 0) { + checkpointFiles.clear() + checkpointFiles ++= newCheckpointFiles + } + + // TODO: remove this, this is just for debugging + newCheckpointFiles.foreach { + case (time, data) => { logInfo("Added checkpointed RDD for time " + time + " to stream checkpoint") } + } + } + + /** + * Cleanup old checkpoint data. This gets called every time the graph + * checkpoint is initiated, but after `update` is called. Default + * implementation, cleans up old checkpoint files. + */ + def cleanup() { + // If there is at least on checkpoint file in the current checkpoint files, + // then delete the old checkpoint files. + if (checkpointFiles.size > 0 && lastCheckpointFiles != null) { + (lastCheckpointFiles -- checkpointFiles.keySet).foreach { + case (time, file) => { + try { + val path = new Path(file) + if (fileSystem == null) { + fileSystem = path.getFileSystem(new Configuration()) + } + fileSystem.delete(path, true) + logInfo("Deleted checkpoint file '" + file + "' for time " + time) + } catch { + case e: Exception => + logWarning("Error deleting old checkpoint file '" + file + "' for time " + time, e) + } + } + } + } + } + + /** + * Restore the checkpoint data. This gets called once when the DStream graph + * (along with its DStreams) are being restored from a graph checkpoint file. + * Default implementation restores the RDDs from their checkpoint files. + */ + def restore() { + // Create RDDs from the checkpoint data + checkpointFiles.foreach { + case(time, file) => { + logInfo("Restoring checkpointed RDD for time " + time + " from file '" + file + "'") + dstream.generatedRDDs += ((time, dstream.context.sparkContext.checkpointFile[T](file))) + } + } + } + + override def toString() = { + "[\n" + checkpointFiles.size + " checkpoint files \n" + checkpointFiles.mkString("\n") + "\n]" + } +} + |