作者|白松
目的：科研中，需要分析在每次迭代过程中参与计算的顶点数目，来进一步优化系统。比如，在SSSP的compute()方法最后一行，都会把当前顶点voteToHalt，即变为InActive状态。所以每次迭代完成后，所有顶点都是InActive状态。在大同步后，收到消息的顶点会被激活，变为Active状态，然后调用顶点的compute()方法。本文的目的就是统计每次迭代过程中，参与计算的顶点数目。下面附上SSSP的compute()方法：
@Override
public void compute(Iterable messages) {
if (getSuperstep() == 0) {
setValue(new DoubleWritable(Double.MAX_VALUE));
}
double minDist = isSource() ? 0d : Double.MAX_VALUE;
for (DoubleWritable message : messages) {
minDist = Math.min(minDist, message.get());
}
if (minDist < getValue().get()) {
setValue(new DoubleWritable(minDist));
for (Edge edge : getEdges()) {
double distance = minDist + edge.getValue().get();
sendMessage(edge.getTargetVertexId(), new DoubleWritable(distance));
}
}
//把顶点置为InActive状态
voteToHalt();
}附：giraph中算法的终止条件是：没有活跃顶点且worker间没有消息传递。
hama-0.6.0中算法的终止条件只是：判断是否有活跃顶点。不是真正的pregel思想，半成品。
修改过程如下：
org.apache.giraph.partition. PartitionStats 类
添加变量和方法，用来统计每个Partition在每个超步中参与计算的顶点数目。添加的变量和方法如下：
/** computed vertices in this partition */
private long computedVertexCount=0;
/**
* Increment the computed vertex count by one.
*/
public void incrComputedVertexCount() {
++ computedVertexCount;
}
/**
* @return the computedVertexCount
*/
public long getComputedVertexCount() {
return computedVertexCount;
}修改readFields()和write()方法，每个方法追加最后一句。当每个Partition计算完成后，会把自己的computedVertexCount发送给Master，Mater再读取汇总。
@Override
public void readFields(DataInput input) throws IOException {
partitionId = input.readInt();
vertexCount = input.readLong();
finishedVertexCount = input.readLong();
edgeCount = input.readLong();
messagesSentCount = input.readLong();
//添加下条语句
computedVertexCount=input.readLong();
}
@Override
public void write(DataOutput output) throws IOException {
output.writeInt(partitionId);
output.writeLong(vertexCount);
output.writeLong(finishedVertexCount);
output.writeLong(edgeCount);
output.writeLong(messagesSentCount);
//添加下条语句
output.writeLong(computedVertexCount);
}-
org.apache.giraph.graph. GlobalStats 类
添加变量和方法，用来统计每个超步中参与计算的顶点总数目，包含每个Worker上的所有Partitions。
/** computed vertices in this partition
* Add by BaiSong
*/
private long computedVertexCount=0;
/**
* @return the computedVertexCount
*/
public long getComputedVertexCount() {
return computedVertexCount;
}修改addPartitionStats(PartitionStats partitionStats)方法，增加统计computedVertexCount功能。
/**
* Add the stats of a partition to the global stats.
*
* @param partitionStats Partition stats to be added.
*/
public void addPartitionStats(PartitionStats partitionStats) {
this.vertexCount += partitionStats.getVertexCount();
this.finishedVertexCount += partitionStats.getFinishedVertexCount();
this.edgeCount += partitionStats.getEdgeCount();
//Add by BaiSong，添加下条语句
this.computedVertexCount+=partitionStats.getComputedVertexCount();
}当然为了Debug方便，也可以修改该类的toString()方法（可选），修改后的如下：
public String toString() {
return "(vtx=" + vertexCount + ", computedVertexCount="
+ computedVertexCount + ",finVtx=" + finishedVertexCount
+ ",edges=" + edgeCount + ",msgCount=" + messageCount
+ ",haltComputation=" + haltComputation + ")";
}org.apache.giraph.graph. ComputeCallable
添加统计功能。在computePartition()方法中，添加下面一句。
if (!vertex.isHalted()) {
context.progress();
TimerContext computeOneTimerContext = computeOneTimer.time();
try {
vertex.compute(messages);
//添加下面一句，当顶点调用完compute()方法后，就把该Partition的computedVertexCount加1
partitionStats.incrComputedVertexCount();
} finally {
computeOneTimerContext.stop();
}
……添加Counters统计，和我的博客Giraph源码分析（七）—— 添加消息统计功能) 类似，此处不再详述。添加的类为：org.apache.giraph.counters.GiraphComputedVertex，下面附上该类的源码：
package org.apache.giraph.counters;
import java.util.Iterator;
import java.util.Map;
import org.apache.hadoop.mapreduce.Mapper.Context;
import com.google.common.collect.Maps;
/**
* Hadoop Counters in group "Giraph Messages" for counting every superstep
* message count.
*/
public class GiraphComputedVertex extends HadoopCountersBase {
/** Counter group name for the giraph Messages */
public static final String GROUP_NAME = "Giraph Computed Vertex";
/** Singleton instance for everyone to use */
private static GiraphComputedVertex INSTANCE;
/** superstep time in msec */
private final Map superstepVertexCount;
private GiraphComputedVertex(Context context) {
super(context, GROUP_NAME);
superstepVertexCount = Maps.newHashMap();
}
/**
* Instantiate with Hadoop Context.
*
* @param context
* Hadoop Context to use.
*/
public static void init(Context context) {
INSTANCE = new GiraphComputedVertex(context);
}
/**
* Get singleton instance.
*
* @return singleton GiraphTimers instance.
*/
public static GiraphComputedVertex getInstance() {
return INSTANCE;
}
/**
* Get counter for superstep messages
*
* @param superstep
* @return
*/
public GiraphHadoopCounter getSuperstepVertexCount(long superstep) {
GiraphHadoopCounter counter = superstepVertexCount.get(superstep);
if (counter == null) {
String counterPrefix = "Superstep: " + superstep+" ";
counter = getCounter(counterPrefix);
superstepVertexCount.put(superstep, counter);
}
return counter;
}
@Override
public Iterator iterator() {
return superstepVertexCount.values().iterator();
}
}实验结果，运行程序后。会在终端输出每次迭代参与计算的顶点总数目。 测试SSSP（SimpleShortestPathsVertex类），输入图中共有9个顶点和12条边。输出结果如下：
上图测试中，共有6次迭代。红色框中，显示出了每次迭代过冲参与计算的顶点数目，依次是：9,4,4,3,4,0
解释：在第0个超步，每个顶点都是活跃的，所有共有9个顶点参与计算。在第5个超步，共有0个顶点参与计算，那么就不会向外发送消息，加上每个顶点都是不活跃的，所以算法迭代终止。
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