214293307  （期待与你一起学习，共同进步）

# Storm的体系结构

# Storm介绍

Storm为分布式实时计算提供了一组通用原语，可被用于“流处理”之中，实时处理消息并更新数据库。这是管理队列及工作者集群的另一种方式。 Storm也可被用于“连续计算”（continuous computation），对数据流做连续查询，在计算时就将结果以流的形式输出给用户。它还可被用于“分布式RPC”，以并行的方式运行昂贵的运算。 Storm的主工程师Nathan Marz表示：

Storm可以方便地在一个计算机集群中编写与扩展复杂的实时计算，Storm之于实时处理，就好比Hadoop之于批处理。Storm保证每个消息都会得到处理，而且它很快。在一个小集群中，每秒可以处理数以百万计的消息。更棒的是你可以使用任意编程语言来做开发。

Storm的主要特点如下：

简单的编程模型。类似于MapReduce降低了并行批处理复杂性，Storm降低了进行实时处理的复杂性。

可以使用各种编程语言。你可以在Storm之上使用各种编程语言。默认支持Clojure、Java、Ruby和Python。要增加对其他语言的支持，只需实现一个简单的Storm通信协议即可。

容错性。Storm会管理工作进程和节点的故障。

水平扩展。计算是在多个线程、进程和服务器之间并行进行的。

可靠的消息处理。Storm保证每个消息至少能得到一次完整处理。任务失败时，它会负责从消息源重试消息。

快速。系统的设计保证了消息能得到快速的处理，使用?MQ作为其底层消息队列。

本地模式。Storm有一个“本地模式”，可以在处理过程中完全模拟Storm集群。这让你可以快速进行开发和单元测试。

Storm集群由一个主节点和多个工作节点组成。主节点运行了一个名为“Nimbus”的守护进程，用于分配代码、布置任务及故障检测。每个工作节点都运行了一个名为“Supervisor”的守护进程，用于监听工作，开始并终止工作进程。Nimbus和Supervisor都能快速失败，而且是无状态的，这样一来它们就变得十分健壮，两者的协调工作是由ApacheZooKeeper来完成的。

Storm的术语包括Stream、Spout、Bolt、Task、Worker、Stream Grouping和Topology。Stream是被处理的数据。Spout是数据源。Bolt处理数据。Task是运行于Spout或Bolt中的线程。Worker是运行这些线程的进程。Stream Grouping规定了Bolt接收什么东西作为输入数据。数据可以随机分配（术语为Shuffle），或者根据字段值分配（术语为Fields），或者广播（术语为All），或者总是发给一个Task（术语为Global），也可以不关心该数据（术语为None），或者由自定义逻辑来决定（术语为 Direct）。Topology是由StreamGrouping连接起来的Spout和Bolt节点网络。在Storm Concepts页面里对这些术语有更详细的描述。

可以和Storm相提并论的系统有Esper、Streambase、HStreaming和Yahoo S4。其中和Storm最接近的就是S4。两者最大的区别在于Storm会保证消息得到处理。Storm，如果需要持久化，可以使用一个类似于Cassandra或Riak这样的外部数据库。Storm是分布式数据处理的框架，本身几乎不提供复杂事件计算，而Esper、Streambase属于CEP系统。

# Storm基本概念

Storm是一个开源的实时计算系统，它提供了一系列的基本元素用于进行计算：Topology、Stream、Spout、Bolt等等。

在Storm中，一个实时应用的计算任务被打包作为Topology发布，这同Hadoop的MapReduce任务相似。但是有一点不同的是：在Hadoop中，MapReduce任务最终会执行完成后结束；而在Storm中，Topology任务一旦提交后永远不会结束，除非你显示去停止任务。

计算任务Topology是由不同的Spouts和Bolts，通过数据流（Stream）连接起来的图。下面是一个Topology的结构示意图：

其中包含有：

Spout：Storm中的消息源，用于为Topology生产消息（数据），一般是从外部数据源（如Message Queue、RDBMS、NoSQL、Realtime Log）不间断地读取数据并发送给Topology消息（tuple元组）。

Bolt：Storm中的消息处理者，用于为Topology进行消息的处理，Bolt可以执行过滤， 聚合， 查询数据库等操作，而且可以一级一级的进行处理。

最终，Topology会被提交到storm集群中运行；也可以通过命令停止Topology的运行，将Topology占用的计算资源归还给Storm集群。

# Storm数据流模型

数据流（Stream）是Storm中对数据进行的抽象，它是时间上无界的tuple元组序列。在Topology中，Spout是Stream的源头，负责为Topology从特定数据源发射Stream；Bolt可以接收任意多个Stream作为输入，然后进行数据的加工处理过程，如果需要，Bolt还可以发射出新的Stream给下级Bolt进行处理。

下面是一个Topology内部Spout和Bolt之间的数据流关系：

Topology中每一个计算组件（Spout和Bolt）都有一个并行执行度，在创建Topology时可以进行指定，Storm会在集群内分配对应并行度个数的线程来同时执行这一组件。

那么，有一个问题：既然对于一个Spout或Bolt，都会有多个task线程来运行，那么如何在两个组件（Spout和Bolt）之间发送tuple元组呢？

Storm提供了若干种数据流分发（StreamGrouping）策略用来解决这一问题。在Topology定义时，需要为每个Bolt指定接收什么样的Stream作为其输入（注：Spout并不需要接收Stream，只会发射Stream）。

目前Storm中提供了以下7种Stream Grouping策略：ShuffleGrouping、Fields Grouping、AllGrouping、Global Grouping、NonGrouping、Direct Grouping、Localor shuffle grouping，具体策略可以参考这里。

# Storm两种安装方式

# Storm本地安装

请看Storm集群安装，只要在一台服务器上同时运行Nimbus，Supervisor，UI就行了

# Storm集群安装

# Storm集群架构图

注意：该集群结构图是根据 Hadoop-2.2.0+Hbase-0.96.2 +Hive-0.13.1这篇博文来的，如果不明白可以看看刚刚那篇博文

一个Nimbus，UI，多个Supervisor

# Zookeeper集群的安装

这个Zookeeper集群的搭建在Hadoop-2.2.0 +Hbase-0.96.2+Hive-0.13.1分布式环境搭建博文中有，可以参考，这里不再叙述了。

# Storm的依赖JDK，Python的安装

这里也不再叙述了，下面是官网原文推荐版本

Next you need to install Storm’s dependencies on Nimbus and the workermachines. These are:

1. Java 6
2. Python 2.6.6

These are the versions of the dependencies that have been tested withStorm. Storm may or may not work with different versions of Java and/or Python.

# Storm的解压apache-storm-0.9.2-incubating.zip

[root@rs229 storm]# pwd

/usr/local/adsit/yting/apache/storm

[root@rs229 storm]# ll

total 19684

drwxr-xr-x 9 root root     4096 Apr 25 16:48apache-storm-0.9.1-incubating

-rw-r--r-- 1 root root 20151543 Jul  7 11:48 apache-storm-0.9.2-incubating.zip

[root@rs229 storm]# unzipapache-storm-0.9.2-incubating.zip

[root@rs229 storm]# ll

total 19688

drwxr-xr-x 9 root root     4096 Apr 25 16:48apache-storm-0.9.1-incubating

drwxrwxrwx 9 root root     4096 Jun 16 12:22apache-storm-0.9.2-incubating

-rw-r--r-- 1 root root 20151543 Jul  7 11:48 apache-storm-0.9.2-incubating.zip

[root@rs229 storm]# cd apache-storm-0.9.2-incubating

[root@rs229 apache-storm-0.9.2-incubating]# ll

total 112

drwxrwxrwx 2 root root  4096 Jun 16 12:22 bin

-rw-r--r-- 1 root root 34239 Jun 12 20:46CHANGELOG.md

drwxrwxrwx 2 root root  4096 Jun 16 12:22 conf

-rw-r--r-- 1 root root   538 Mar 12 23:17 DISCLAIMER

drwxrwxrwx 3 root root  4096 Jun 16 12:22 examples

drwxrwxrwx 3 root root  4096 Jun 16 12:22 external

drwxrwxrwx 2 root root  4096 Jun 16 12:22 lib

-rw-r--r-- 1 root root 22822 Jun 11 16:07 LICENSE

drwxrwxrwx 2 root root  4096 Jun 16 12:22 logback

-rw-r--r-- 1 root root   981 Jun 10 13:10 NOTICE

drwxrwxrwx 5 root root  4096 Jun 16 12:22 public

-rw-r--r-- 1 root root  7445 Jun 9 14:24 README.markdown

-rw-r--r-- 1 root root    17 Jun 16 12:22 RELEASE

-rw-r--r-- 1 root root  3581 May 29 12:20 SECURITY.md

[root@rs229 apache-storm-0.9.2-incubating]# cd conf

[root@rs229 conf]# ll

total 8

-rw-r--r-- 1 root root 1126 May 28 12:24storm_env.ini

-rw-r--r-- 1 root root 1613 May 28 12:24 storm.yaml

# 修改storm.yaml配置文件

### ldir

storm.local.dir: "/usr/local/adsit/yting/apache/storm/apache-storm-0.9.2-incubating/ldir"

### zookeeper

storm.zookeeper.servers:

     -"rs229"

     -"rs227"

     -"rs226"

     -"rs198"

     -"rs197"

### nimbus host

nimbus.host: "rs229"

### ui.* configs are for the master

ui.port: 8081 # 我这里修改了storm的ui端口

# 官方默认的配置文件

# Licensed to the Apache Software Foundation (ASF)under one

# or more contributor license agreements.  See the NOTICE file

# distributed with this work for additionalinformation

# regarding copyright ownership.  The ASF licenses this file

# to you under the Apache License, Version 2.0 (the

# "License"); you may not use this fileexcept 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 inwriting, 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 governingpermissions and

# limitations under the License.

########### These all have default values as shown

########### Additional configuration goes intostorm.yaml

java.library.path: "/usr/local/lib:/opt/local/lib:/usr/lib"

### storm.* configs are general configurations

# the local dir is where jars are kept

storm.local.dir: "storm-local"

storm.zookeeper.servers:

    -"localhost"

storm.zookeeper.port: 2181

storm.zookeeper.root: "/storm"

storm.zookeeper.session.timeout: 20000

storm.zookeeper.connection.timeout: 15000

storm.zookeeper.retry.times: 5

storm.zookeeper.retry.interval: 1000

storm.zookeeper.retry.intervalceiling.millis: 30000

storm.cluster.mode: "distributed" # can bedistributed or local

storm.local.mode.zmq: false

storm.thrift.transport:"backtype.storm.security.auth.SimpleTransportPlugin"

storm.messaging.transport:"backtype.storm.messaging.netty.Context"

### nimbus.* configs are for the master

nimbus.host: "localhost"

nimbus.thrift.port: 6627

nimbus.thrift.max_buffer_size: 1048576

nimbus.childopts: "-Xmx1024m"

nimbus.task.timeout.secs: 30

nimbus.supervisor.timeout.secs: 60

nimbus.monitor.freq.secs: 10

nimbus.cleanup.inbox.freq.secs: 600

nimbus.inbox.jar.expiration.secs: 3600

nimbus.task.launch.secs: 120

nimbus.reassign: true

nimbus.file.copy.expiration.secs: 600

nimbus.topology.validator:"backtype.storm.nimbus.DefaultTopologyValidator"

### ui.* configs are for the master

ui.port: 8080

ui.childopts: "-Xmx768m"

logviewer.port: 8000

logviewer.childopts: "-Xmx128m"

logviewer.appender.name: "A1"

drpc.port: 3772

drpc.worker.threads: 64

drpc.queue.size: 128

drpc.invocations.port: 3773

drpc.request.timeout.secs: 600

drpc.childopts: "-Xmx768m"

transactional.zookeeper.root:"/transactional"

transactional.zookeeper.servers: null

transactional.zookeeper.port: null

### supervisor.* configs are for node supervisors

# Define the amount of workers that can be run onthis machine. Each worker is assigned a port to use for communication

supervisor.slots.ports:

    - 6700

    - 6701

    - 6702

    - 6703

supervisor.childopts: "-Xmx256m"

#how long supervisor will wait to ensure that aworker process is started

supervisor.worker.start.timeout.secs: 120

#how long between heartbeats until supervisorconsiders that worker dead and tries to restart it

supervisor.worker.timeout.secs: 30

#how frequently the supervisor checks on the statusof the processes it‘s monitoring and restarts if necessary

supervisor.monitor.frequency.secs: 3

#how frequently the supervisor heartbeats to thecluster state (for nimbus)

supervisor.heartbeat.frequency.secs: 5

supervisor.enable: true

### worker.* configs are for task workers

worker.childopts: "-Xmx768m"

worker.heartbeat.frequency.secs: 1

# control how many worker receiver threads we needper worker

topology.worker.receiver.thread.count: 1

task.heartbeat.frequency.secs: 3

task.refresh.poll.secs: 10

zmq.threads: 1

zmq.linger.millis: 5000

zmq.hwm: 0

storm.messaging.netty.server_worker_threads: 1

storm.messaging.netty.client_worker_threads: 1

storm.messaging.netty.buffer_size: 5242880 #5MBbuffer

storm.messaging.netty.max_retries: 30

storm.messaging.netty.max_wait_ms: 1000

storm.messaging.netty.min_wait_ms: 100

# If the Netty messaging layer is busy(netty internalbuffer not writable), the Netty client will try to batch message as more aspossible up to the size of storm.messaging.netty.transfer.batch.size bytes,otherwise it will try to flush message as soon as possible to reduce latency.

storm.messaging.netty.transfer.batch.size: 262144

# We check with this interval that whether the Nettychannel is writable and try to write pending messages if it is.

storm.messaging.netty.flush.check.interval.ms: 10

### topology.* configs are for specific executingstorms

topology.enable.message.timeouts: true

topology.debug: false

topology.workers: 1

topology.acker.executors: null

topology.tasks: null

# maximum amount of time a message has to completebefore it‘s considered failed

topology.message.timeout.secs: 30

topology.multilang.serializer:"backtype.storm.multilang.JsonSerializer"

topology.skip.missing.kryo.registrations: false

topology.max.task.parallelism: null

topology.max.spout.pending: null

topology.state.synchronization.timeout.secs: 60

topology.stats.sample.rate: 0.05

topology.builtin.metrics.bucket.size.secs: 60

topology.fall.back.on.java.serialization: true

topology.worker.childopts: null

topology.executor.receive.buffer.size: 1024 #batched

topology.executor.send.buffer.size: 1024 #individualmessages

topology.receiver.buffer.size: 8 # setting it toohigh causes a lot of problems (heartbeat thread gets starved, throughputplummets)

topology.transfer.buffer.size: 1024 # batched

topology.tick.tuple.freq.secs: null

topology.worker.shared.thread.pool.size: 4

topology.disruptor.wait.strategy:"com.lmax.disruptor.BlockingWaitStrategy"

topology.spout.wait.strategy:"backtype.storm.spout.SleepSpoutWaitStrategy"

topology.sleep.spout.wait.strategy.time.ms: 1

topology.error.throttle.interval.secs: 10

topology.max.error.report.per.interval: 5

topology.kryo.factory:"backtype.storm.serialization.DefaultKryoFactory"

topology.tuple.serializer: "backtype.storm.serialization.types.ListDelegateSerializer"

topology.trident.batch.emit.interval.millis: 500

topology.classpath: null

topology.environment: null

dev.zookeeper.path:"/tmp/dev-storm-zookeeper"

# 将storm的目录复制到其它发服务器下去

（不复制也行，直接在Nimbus的服务器启动3个进程都OK，一个服务器的集群 - -！）

饿这里的话启动了一个Nimbus，三个Supervisor，一个UI，其中Nimbus跟UI都是在一台服务器上面，三个Supervisor分别在不同的服务器上面

[root@rs229 storm]# scp -r/usr/local/adsit/yting/apache/storm/apache-storm-0.9.2-incubatina rs198:/usr/local/adsit/yting/apache/storm/

[root@rs229 storm]# scp -r/usr/local/adsit/yting/apache/storm/apache-storm-0.9.2-incubatina rs197:/usr/local/adsit/yting/apache/storm/

[root@rs229 storm]# scp -r/usr/local/adsit/yting/apache/storm/apache-storm-0.9.2-incubatinars196:/usr/local/adsit/yting/apache/storm/

# Nimbus的启动

后台启动，懒得开shell，下面也一样都是后台启动的，不解释 、、、

[root@rs229 apache-storm-0.9.2-incubating]# bin/storm nimbus &

[1] 16025

[root@rs229 apache-storm-0.9.2-incubating]# Running:/usr/local/adsit/yting/jdk/jdk1.7.0_60/bin/java -server -Dstorm.options=-Dstorm.home=/usr/local/adsit/yting/apache/storm/apache-storm-0.9.2-incubating-Djava.library.path=/usr/local/lib:/opt/local/lib:/usr/lib -Dstorm.conf.file=-cp /…:/usr/local/adsit/yting/apache/storm/apache-storm-0.9.2-incubating/conf-Xmx1024m -Dlogfile.name=nimbus.log-Dlogback.configurationFile=/usr/local/adsit/yting/apache/storm/apache-storm-0.9.2-incubating/logback/cluster.xmlbacktype.storm.daemon.nimbus

# Supervisor的启动

# rs198上启动Supervisor

[root@rs198 apache-storm-0.9.2-incubating]# bin/storm supervisor &

[1] 15273

[root@RS198 apache-storm-0.9.2-incubating]# Running:/usr/local/adsit/yting/jdk/jdk1.7.0_60/bin/java -server -Dstorm.options=-Dstorm.home=/usr/local/adsit/yting/apache/storm/apache-storm-0.9.2-incubating-Djava.library.path=/usr/local/lib:/opt/local/lib:/usr/lib -Dstorm.conf.file=-cp /…:/usr/local/adsit/yting/apache/storm/apache-storm-0.9.2-incubating/conf-Xmx256m -Dlogfile.name=supervisor.log -Dlogback.configurationFile=/usr/local/adsit/yting/apache/storm/apache-storm-0.9.2-incubating/logback/cluster.xmlbacktype.storm.daemon.supervisor

# rs197上启动Supervisor

[root@RS197 apache-storm-0.9.2-incubating]# bin/stormsupervisor &

[1] 25262

[root@RS197 apache-storm-0.9.2-incubating]# Running:/root/jdk1.6.0_26/bin/java -server -Dstorm.options=-Dstorm.home=/usr/local/adsit/yting/apache/storm/apache-storm-0.9.2-incubating-Djava.library.path=/usr/local/lib:/opt/local/lib:/usr/lib -Dstorm.conf.file=-cp /…:/usr/local/adsit/yting/apache/storm/apache-storm-0.9.2-incubating/conf-Xmx256m -Dlogfile.name=supervisor.log-Dlogback.configurationFile=/usr/local/adsit/yting/apache/storm/apache-storm-0.9.2-incubating/logback/cluster.xmlbacktype.storm.daemon.supervisor

# rs167上启动Supervisor

[root@RS196 apache-storm-0.9.2-incubating]# bin/stormsupervisor &

[1] 17330

[root@RS196 apache-storm-0.9.2-incubating]# Running:/root/jdk1.6.0_26/bin/java -server -Dstorm.options=-Dstorm.home=/usr/local/adsit/yting/apache/storm/apache-storm-0.9.2-incubating-Djava.library.path=/usr/local/lib:/opt/local/lib:/usr/lib -Dstorm.conf.file=-cp /…:/usr/local/adsit/yting/apache/storm/apache-storm-0.9.2-incubating/conf-Xmx256m -Dlogfile.name=supervisor.log-Dlogback.configurationFile=/usr/local/adsit/yting/apache/storm/apache-storm-0.9.2-incubating/logback/cluster.xmlbacktype.storm.daemon.supervisor

# UI的启动

[root@rs229 apache-storm-0.9.2-incubating]# bin/storm ui &

[2] 16145

[root@rs229 apache-storm-0.9.2-incubating]# Running:/usr/local/adsit/yting/jdk/jdk1.7.0_60/bin/java -server -Dstorm.options=-Dstorm.home=/usr/local/adsit/yting/apache/storm/apache-storm-0.9.2-incubating-Djava.library.path=/usr/local/lib:/opt/local/lib:/usr/lib -Dstorm.conf.file=-cp /…:/usr/local/adsit/yting/apache/storm/apache-storm-0.9.2-incubating/conf-Xmx768m -Dlogfile.name=ui.log-Dlogback.configurationFile=/usr/local/adsit/yting/apache/storm/apache-storm-0.9.2-incubating/logback/cluster.xmlbacktype.storm.ui.core

# 在浏览器上访问Storm UI（记得我们在配置文件中把Storm UI的端口改为了8081）

# Zookeeper下查看是否有对应storm的目录

[root@rs229 ldir]# zkCli.sh

Connecting to localhost:2181

WATCHER::

WatchedEvent state:SyncConnected type:None path:null

[zk: localhost:2181(CONNECTED) 0] ls /

[storm, hbase,hadoop-ha, zookeeper]

[zk: localhost:2181(CONNECTED) 1] ls /storm

[workerbeats, errors, supervisors, storms,assignments]

[zk: localhost:2181(CONNECTED) 2]

可以看出zookeeper已经管理storm了

# Storm集群环境已经搭建成功，下面请看Storm之入门案例一

# Storm之入门案例一（官网案例）

# 说明

这是一个单词统计的程序，Java版本，官网给的，想要看具体的源码的话就用Eclipse关联源代码吧！

# Java代码

package com.yting.cloud.storm.example;

import java.util.HashMap;

import java.util.Map;

import backtype.storm.Config;

import backtype.storm.LocalCluster;

import backtype.storm.StormSubmitter;

importbacktype.storm.generated.AlreadyAliveException;

importbacktype.storm.generated.InvalidTopologyException;

import backtype.storm.testing.TestGlobalCount;

import backtype.storm.testing.TestWordCounter;

import backtype.storm.testing.TestWordSpout;

import backtype.storm.topology.TopologyBuilder;

import backtype.storm.tuple.Fields;

import backtype.storm.utils.Utils;

/**

 * 官网给的代码，改了下并行数的大小

 *

 * @Author 王扬庭（妳那伊抹微笑）

 * @Time2014-07-07

 *

 */

public class Example {

       publicstatic void main(String[] args) throws Exception {

              stormLocal();

              //stormCluster();

       }

       /**

        * Local

        */

       privatestatic void stormLocal() {

              //并行大小全部改为1了，为了该程序可以适应Local

              TopologyBuilderbuilder = new TopologyBuilder();

              builder.setSpout("1",new TestWordSpout(true), 1);

              builder.setSpout("2",new TestWordSpout(true), 1);

              builder.setBolt("3",new TestWordCounter(), 1).fieldsGrouping("1", newFields("word")).fieldsGrouping("2", newFields("word"));

              builder.setBolt("4",new TestGlobalCount()).globalGrouping("1");

              Mapconf = new HashMap();

              conf.put(Config.TOPOLOGY_WORKERS,4);

              conf.put(Config.TOPOLOGY_DEBUG,true);

              LocalClustercluster = new LocalCluster();

              cluster.submitTopology("mytopology",conf, builder.createTopology());

              Utils.sleep(10000);

              cluster.shutdown();

       }

       /**

        * Cluster

        *

        * @throws AlreadyAliveException

        * @throws InvalidTopologyException

        */

       privatestatic void stormCluster() throws AlreadyAliveException,InvalidTopologyException {

              TopologyBuilderbuilder = new TopologyBuilder();

              builder.setSpout("1",new TestWordSpout(true), 5);

              builder.setSpout("2",new TestWordSpout(true), 3);

              builder.setBolt("3",new TestWordCounter(), 3).fieldsGrouping("1", newFields("word")).fieldsGrouping("2", newFields("word"));

              builder.setBolt("4",new TestGlobalCount()).globalGrouping("1");

              Mapconf = new HashMap();

              conf.put(Config.TOPOLOGY_WORKERS,4);

              StormSubmitter.submitTopology("mytopology",conf, builder.createTopology());

       }

}

# 将上面的代码在Eclipse下打成jar包并上传到服务器上去，使用storm命令执行，然后看下面的日志输出

[root@rs229 yjar]# pwd

/usr/local/adsit/yting/apache/storm/apache-storm-0.9.2-incubating/yjar

[root@rs229 yjar]# ll

total 32

-rw-r--r-- 1 root root 15149 Jul  7 16:49 storm-wordcount-official-cluster.jar

-rw-r--r-- 1 root root 15195 Jul  7 16:50storm-wordcount-official-local.jar

[root@rs229 yjar]#

[root@rs229 yjar]# storm jar./storm-wordcount-official-local.jar com.yting.cloud.storm.example.Example

# 分析日志输出（只保留了有用的一部分，日志信息太多了）

14268 [Thread-26-2] INFO  backtype.storm.daemon.task - Emitting: 2default[jackson]

14269 [Thread-10-3] INFO  backtype.storm.daemon.executor - Processingreceived message source: 2:2, stream: default, id: {}, [jackson]

14269 [Thread-10-3] INFO  backtype.storm.daemon.task - Emitting: 3default[jackson, 32]

14291 [Thread-32-1] INFO  backtype.storm.daemon.task - Emitting: 1default [jackson]

14292 [Thread-10-3] INFO  backtype.storm.daemon.executor - Processingreceived message source: 1:1, stream: default, id: {}, [jackson]

14292 [Thread-9-4] INFO  backtype.storm.daemon.executor - Processingreceived message source: 1:1, stream: default, id: {}, [jackson]

14292 [Thread-10-3] INFO  backtype.storm.daemon.task - Emitting: 3default [jackson, 33]

14292 [Thread-9-4] INFO  backtype.storm.daemon.task - Emitting: 4default[80]

14368 [Thread-26-2] INFO  backtype.storm.daemon.task - Emitting: 2default [golda]

14369 [Thread-10-3] INFO  backtype.storm.daemon.executor - Processingreceived message source: 2:2, stream: default, id: {}, [golda]

这里是一部分日志信息，分析如下：

1：TestWordSpout 这个spout产生数据并emit（[jackson]）
2：TestWordCounter这个blot接受刚刚spout产生的数据，并统计每个单词出现的次数（[jackson, 32]）

3：TestGlobalCount全局统计一共产生了多少个档次（[80]）

#  师傅领进门，修行靠个人，哈哈 、、、

# 时间：2014-07-07 18:09:21