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/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.spark.mllib.impl
import org.apache.spark.SparkContext
import org.apache.spark.graphx.Graph
import org.apache.spark.storage.StorageLevel
/**
* This class helps with persisting and checkpointing Graphs.
* Specifically, it automatically handles persisting and (optionally) checkpointing, as well as
* unpersisting and removing checkpoint files.
*
* Users should call update() when a new graph has been created,
* before the graph has been materialized. After updating [[PeriodicGraphCheckpointer]], users are
* responsible for materializing the graph to ensure that persisting and checkpointing actually
* occur.
*
* When update() is called, this does the following:
* - Persist new graph (if not yet persisted), and put in queue of persisted graphs.
* - Unpersist graphs from queue until there are at most 3 persisted graphs.
* - If using checkpointing and the checkpoint interval has been reached,
* - Checkpoint the new graph, and put in a queue of checkpointed graphs.
* - Remove older checkpoints.
*
* WARNINGS:
* - This class should NOT be copied (since copies may conflict on which Graphs should be
* checkpointed).
* - This class removes checkpoint files once later graphs have been checkpointed.
* However, references to the older graphs will still return isCheckpointed = true.
*
* Example usage:
* {{{
* val (graph1, graph2, graph3, ...) = ...
* val cp = new PeriodicGraphCheckpointer(2, sc)
* graph1.vertices.count(); graph1.edges.count()
* // persisted: graph1
* cp.updateGraph(graph2)
* graph2.vertices.count(); graph2.edges.count()
* // persisted: graph1, graph2
* // checkpointed: graph2
* cp.updateGraph(graph3)
* graph3.vertices.count(); graph3.edges.count()
* // persisted: graph1, graph2, graph3
* // checkpointed: graph2
* cp.updateGraph(graph4)
* graph4.vertices.count(); graph4.edges.count()
* // persisted: graph2, graph3, graph4
* // checkpointed: graph4
* cp.updateGraph(graph5)
* graph5.vertices.count(); graph5.edges.count()
* // persisted: graph3, graph4, graph5
* // checkpointed: graph4
* }}}
*
* @param checkpointInterval Graphs will be checkpointed at this interval.
* If this interval was set as -1, then checkpointing will be disabled.
* @tparam VD Vertex descriptor type
* @tparam ED Edge descriptor type
*
* TODO: Move this out of MLlib?
*/
private[mllib] class PeriodicGraphCheckpointer[VD, ED](
checkpointInterval: Int,
sc: SparkContext)
extends PeriodicCheckpointer[Graph[VD, ED]](checkpointInterval, sc) {
override protected def checkpoint(data: Graph[VD, ED]): Unit = data.checkpoint()
override protected def isCheckpointed(data: Graph[VD, ED]): Boolean = data.isCheckpointed
override protected def persist(data: Graph[VD, ED]): Unit = {
if (data.vertices.getStorageLevel == StorageLevel.NONE) {
data.vertices.persist()
}
if (data.edges.getStorageLevel == StorageLevel.NONE) {
data.edges.persist()
}
}
override protected def unpersist(data: Graph[VD, ED]): Unit = data.unpersist(blocking = false)
override protected def getCheckpointFiles(data: Graph[VD, ED]): Iterable[String] = {
data.getCheckpointFiles
}
}
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