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安装 Hama 之前，应该首先确保系统中已经安装了 Hadoop，本集群使用的版本为 hadoop-2.3.0
一、下载及解压 Hama 文件
下载地址：http://www.apache.org/dyn/closer.cgi/hama，选用的是目前最新版本：hama0.6.4。解压之后的存放位置自己设定。
二、修改配置文件
- 在 hama-env.sh 文件中加入 JAVA_HOME 变量（分布式情况下，设为机器的值）
- 配置 hama-site.xml（分布式情况下，所有机器的配置相同）
bsp.master.address 为 bsp master 地址。fs.default.name 参数设置成 hadoop 里 namenode 的地址。hama.zookeeper.quorum 和 hama.zookeeper.property.clientPort 两个参数和 zookeeper 有关，设置成为 zookeeper 的 quorum server 即可，单机伪分布式就是本机地址。
4. 配置 groomservers 文件。hama 与 hadoop 具有相似的主从结构，该文件存放从节点的 IP 地址，每个 IP 占一行。（分布式情况下只需要配置 BSPMaster 所在的机器即可）
5. hama0.6.4 自带的 hadoop 核心包为 1.2.0，与集群 hadoop2.3.0 不一致，需要进行替换，具体是在 hadoop 的 lib 文件夹下找到 hadoop-core-2.3.0*.jar 和 hadoop-test-2.3.0*.jar，拷贝到 hama 的 lib 目录下，并删除 hadoop-core-1.2.0.jar 和 hadoop-test-1.2.0.jar 两个文件。
6. 此时可能会报找不到类的错，需加入缺失的 jar 包。（把 hadoop 开头的 jar 包和 protobuf-java-2.5.0.jar 导入到 hama/lib 下）
三、编写 Hama job
在 eclipse 下新建 Java Project，将 hama 安装时需要的 jar 包全部导入工程。
官网中计算 PI 的例子：
package pi;
import java.io.IOException;
import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import org.apache.hadoop.fs.FSDataInputStream;
import org.apache.hadoop.fs.FileStatus;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.DoubleWritable;
import org.apache.hadoop.io.IOUtils;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hama.HamaConfiguration;
import org.apache.hama.bsp.BSP;
import org.apache.hama.bsp.BSPJob;
import org.apache.hama.bsp.BSPJobClient;
import org.apache.hama.bsp.BSPPeer;
import org.apache.hama.bsp.ClusterStatus;
import org.apache.hama.bsp.FileOutputFormat;
import org.apache.hama.bsp.NullInputFormat;
import org.apache.hama.bsp.TextOutputFormat;
import org.apache.hama.bsp.sync.SyncException;
public class PiEstimator {
private static Path TMP_OUTPUT = new Path(“/tmp/pi-“
+ System.currentTimeMillis());
public static class MyEstimator
extends
BSP<NullWritable, NullWritable, Text, DoubleWritable, DoubleWritable> {
public static final Log LOG = LogFactory.getLog(MyEstimator.class);
private String masterTask;
private static final int iterations = 100000;
@Override
public void bsp(
BSPPeer<NullWritable, NullWritable, Text, DoubleWritable, DoubleWritable> peer)
throws IOException, SyncException, InterruptedException {
int in = 0;
for (int i = 0; i < iterations; i++) {
double x = 2.0 * Math.random() – 1.0, y = 2.0 * Math.random() – 1.0;
if ((Math.sqrt(x * x + y * y) < 1.0)) {
in++;
}
}
double data = 4.0 * in / iterations;
peer.send(masterTask, new DoubleWritable(data));
peer.sync();
if (peer.getPeerName().equals(masterTask)) {
double pi = 0.0;
int numPeers = peer.getNumCurrentMessages();
DoubleWritable received;
while ((received = peer.getCurrentMessage()) != null) {
pi += received.get();
}
pi = pi / numPeers;
peer.write(new Text(“Estimated value1 of PI is”),
new DoubleWritable(pi));
}
peer.sync();
int in2 = 0;
for (int i = 0; i < iterations; i++) {
double x = 2.0 * Math.random() – 1.0, y = 2.0 * Math.random() – 1.0;
if ((Math.sqrt(x * x + y * y) < 1.0)) {
in2++;
}
}
double data2 = 4.0 * in2 / iterations;
peer.send(masterTask, new DoubleWritable(data2));
peer.sync();
if (peer.getPeerName().equals(masterTask)) {
double pi2 = 0.0;
int numPeers = peer.getNumCurrentMessages();
DoubleWritable received;
while ((received = peer.getCurrentMessage()) != null) {
pi2 += received.get();
}
pi2 = pi2 / numPeers;
peer.write(new Text(“Estimated value2 of PI is”),
new DoubleWritable(pi2));
}
peer.sync();
}
@Override
public void setup(
BSPPeer<NullWritable, NullWritable, Text, DoubleWritable, DoubleWritable> peer)
throws IOException {
// Choose one as a master
this.masterTask = peer.getPeerName(peer.getNumPeers() / 2);
}
@Override
public void cleanup(
BSPPeer<NullWritable, NullWritable, Text, DoubleWritable, DoubleWritable> peer)
throws IOException {
// if (peer.getPeerName().equals(masterTask)) {
// double pi = 0.0;
// int numPeers = peer.getNumCurrentMessages();
// DoubleWritable received;
// while ((received = peer.getCurrentMessage()) != null) {
// pi += received.get();
// }
//
// pi = pi / numPeers;
// peer.write(new Text(“Estimated value of PI is”),
// new DoubleWritable(pi));
// }
}
}
static void printOutput(HamaConfiguration conf) throws IOException {
FileSystem fs = FileSystem.get(conf);
FileStatus[] files = fs.listStatus(TMP_OUTPUT);
for (int i = 0; i < files.length; i++) {
if (files[i].getLen() > 0) {
FSDataInputStream in = fs.open(files[i].getPath());
IOUtils.copyBytes(in, System.out, conf, false);
in.close();
break;
}
}
fs.delete(TMP_OUTPUT, true);
}
public static void main(String[] args) throws InterruptedException,
IOException, ClassNotFoundException {
// BSP job configuration
HamaConfiguration conf = new HamaConfiguration();
BSPJob bsp = new BSPJob(conf, PiEstimator.class);
// Set the job name
bsp.setJobName(“Pi Estimation Example”);
bsp.setBspClass(MyEstimator.class);
bsp.setInputFormat(NullInputFormat.class);
bsp.setOutputKeyClass(Text.class);
bsp.setOutputValueClass(DoubleWritable.class);
bsp.setOutputFormat(TextOutputFormat.class);
FileOutputFormat.setOutputPath(bsp, TMP_OUTPUT);
BSPJobClient jobClient = new BSPJobClient(conf);
ClusterStatus cluster = jobClient.getClusterStatus(true);
if (args.length > 0) {
bsp.setNumBspTask(Integer.parseInt(args[0]));
} else {
// Set to maximum
bsp.setNumBspTask(cluster.getMaxTasks());
}
long startTime = System.currentTimeMillis();
if (bsp.waitForCompletion(true)) {
printOutput(conf);
System.out.println(“Job Finished in “
+ (System.currentTimeMillis() – startTime) / 1000.0
+ ” seconds”);
}
}
}
将工程 Export 成 Jar 文件，发到集群上运行。运行命令:
$HAMA_HOME/bin/hama jar jarName.jar
输出：
Current supersteps number: 0（）
Current supersteps number: 4（）
The total number of supersteps: 4（总超级步数目）
Counters: 8（一共 8 个计数器，如下 8 个。所有计数器列表待完善）
org.apache.hama.bsp.JobInProgress$JobCounter
SUPERSTEPS=4（BSPMaster 超级步数目）
LAUNCHED_TASKS=3（共多少个 task）
org.apache.hama.bsp.BSPPeerImpl$PeerCounter
SUPERSTEP_SUM=12（总共的超级步数目，task 数目 *BSPMaster 超级步数目）
MESSAGE_BYTES_TRANSFERED=48（传输信息字节数）
TIME_IN_SYNC_MS=657（同步消耗时间）
TOTAL_MESSAGES_SENT=6（发送信息条数）
TOTAL_MESSAGES_RECEIVED=6（接收信息条数）
TASK_OUTPUT_RECORDS=2（任务输出记录数）
PageRank 例子：
package pi;
import java.io.IOException;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.DoubleWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hama.HamaConfiguration;
import org.apache.hama.bsp.HashPartitioner;
import org.apache.hama.bsp.TextOutputFormat;
import org.apache.hama.graph.AverageAggregator;
import org.apache.hama.graph.Edge;
import org.apache.hama.graph.GraphJob;
import org.apache.hama.graph.Vertex;
import org.apache.hama.graph.VertexInputReader;
/**
* Real pagerank with dangling node contribution.
*/
public class PageRank {
public static class PageRankVertex extends
Vertex<Text, NullWritable, DoubleWritable> {
static double DAMPING_FACTOR = 0.85;
static double MAXIMUM_CONVERGENCE_ERROR = 0.001;
@Override
public void setup(HamaConfiguration conf) {
String val = conf.get(“hama.pagerank.alpha”);
if (val != null) {
DAMPING_FACTOR = Double.parseDouble(val);
}
val = conf.get(“hama.graph.max.convergence.error”);
if (val != null) {
MAXIMUM_CONVERGENCE_ERROR = Double.parseDouble(val);
}
}
@Override
public void compute(Iterable<DoubleWritable> messages)
throws IOException {
// initialize this vertex to 1 / count of global vertices in this
// graph
if (this.getSuperstepCount() == 0) {
this.setValue(new DoubleWritable(1.0 / this.getNumVertices()));
} else if (this.getSuperstepCount() >= 1) {
double sum = 0;
for (DoubleWritable msg : messages) {
sum += msg.get();
}
double alpha = (1.0d – DAMPING_FACTOR) / this.getNumVertices();
this.setValue(new DoubleWritable(alpha + (sum * DAMPING_FACTOR)));
}
// if we have not reached our global error yet, then proceed.
DoubleWritable globalError = this.getAggregatedValue(0);
if (globalError != null && this.getSuperstepCount() > 2
&& MAXIMUM_CONVERGENCE_ERROR > globalError.get()) {
voteToHalt();
return;
}
// in each superstep we are going to send a new rank to our
// neighbours
sendMessageToNeighbors(new DoubleWritable(this.getValue().get()
/ this.getEdges().size()));
}
}
public static GraphJob createJob(String[] args, HamaConfiguration conf)
throws IOException {
GraphJob pageJob = new GraphJob(conf, PageRank.class);
pageJob.setJobName(“Pagerank”);
pageJob.setVertexClass(PageRankVertex.class);
pageJob.setInputPath(new Path(args[0]));
pageJob.setOutputPath(new Path(args[1]));
// set the defaults
pageJob.setMaxIteration(30);
pageJob.set(“hama.pagerank.alpha”, “0.85”);
// reference vertices to itself, because we don’t have a dangling node
// contribution here
pageJob.set(“hama.graph.self.ref”, “true”);
pageJob.set(“hama.graph.max.convergence.error”, “1”);
if (args.length == 3) {
pageJob.setNumBspTask(Integer.parseInt(args[2]));
}
// error
pageJob.setAggregatorClass(AverageAggregator.class);
// Vertex reader
pageJob.setVertexInputReaderClass(PagerankTextReader.class);
pageJob.setVertexIDClass(Text.class);
pageJob.setVertexValueClass(DoubleWritable.class);
pageJob.setEdgeValueClass(NullWritable.class);
pageJob.setPartitioner(HashPartitioner.class);
pageJob.setOutputFormat(TextOutputFormat.class);
pageJob.setOutputKeyClass(Text.class);
pageJob.setOutputValueClass(DoubleWritable.class);
return pageJob;
}
private static void printUsage() {
System.out.println(“Usage: <input> <output> [tasks]”);
System.exit(-1);
}
public static class PagerankTextReader
extends
VertexInputReader<LongWritable, Text, Text, NullWritable, DoubleWritable> {
@Override
public boolean parseVertex(LongWritable key, Text value,
Vertex<Text, NullWritable, DoubleWritable> vertex)
throws Exception {
String[] split = value.toString().split(“\t”);
for (int i = 0; i < split.length; i++) {
if (i == 0) {
vertex.setVertexID(new Text(split[i]));
} else {
vertex.addEdge(new Edge<Text, NullWritable>(new Text(
split[i]), null));
}
}
return true;
}
}
public static void main(String[] args) throws IOException,
InterruptedException, ClassNotFoundException {
if (args.length < 2)
printUsage();
HamaConfiguration conf = new HamaConfiguration(new Configuration());
GraphJob pageJob = createJob(args, conf);
long startTime = System.currentTimeMillis();
if (pageJob.waitForCompletion(true)) {
System.out.println(“Job Finished in “
+ (System.currentTimeMillis() – startTime) / 1000.0
+ ” seconds”);
}
}
}
输出：
本文永久更新链接地址 ：http://www.linuxidc.com/Linux/2016-04/130626.htm
