Cassandra Dev 1: Cassandra 入门
???? 最近， Cassandra 绝对是一个比较前端的话题，随着互联网的不断发展， Distributed Database 的广受重视是一种必然， Cassandra 在存取效率、分散管理、容错能力、稳定性等方面的优点是其他Distributed Database 无法比拟的，So， 研究Cassandra 是非常有必要的。我将从下列方面学习Cassandra ：
1. Cassandra目录结构
从http://cassandra.apache.org/download/下载最新Cassandra，解压后目录结构如下?：
?如图由上向下：
bin中存放这一些可操作Cassandra脚本，如cassandra.bat，点击可以启动Cassandra
conf中包含一些Cassandra配置信息
interface中存放Cassandra的Thrift接口定义文件，可以用于生成各种语言的接口代码
javadoc中为Cassandra帮助文档（API）
lib中为Cassandra运行时依赖的包
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2. Cassandra HelloWorld
从学C语言开始，HelloWorld是一种传统，所以先写个HelloWorld，在apache-cassandra-0.6.4\conf目录下storage-conf.xml文件中，该文件中包含Cassandra的所有配置，先列出简单一些：
<!-- A --><ClusterName>Test Cluster</ClusterName><!-- B --><Keyspaces><Keyspace Name="Keyspace1"> </Keyspace></Keyspaces><!-- C --><CommitLogDirectory>/var/lib/cassandra/commitlog</CommitLogDirectory> <DataFileDirectories><DataFileDirectory>/var/lib/cassandra/data</DataFileDirectory></DataFileDirectories><!-- D --><ThriftPort>9160</ThriftPort>
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?如上:
A处定义Cluster名字（也称结点名字），一个Cluster可以包含多个Keyspace;
B处定义了此Cluster中包含一个Keyspace，且名字为Keyspace1，Keyspace相当于与关系数据库中的database；
C处定义了Cassandra数据和Commitlog存放的位置，如不对其做修改，在Windows下启动Cassandra，在D盘根目录下产生如上面所示的文件夹；
D处定义了Thrift RPC 端口号为9160，
在默认配置文件下启动Cassandra，然后编写如下代码：
package com.tibco.cassandra;import java.io.UnsupportedEncodingException;import java.util.Date;import org.apache.cassandra.thrift.Cassandra;import org.apache.cassandra.thrift.Column;import org.apache.cassandra.thrift.ColumnOrSuperColumn;import org.apache.cassandra.thrift.ColumnPath;import org.apache.cassandra.thrift.ConsistencyLevel;import org.apache.cassandra.thrift.InvalidRequestException;import org.apache.cassandra.thrift.NotFoundException;import org.apache.cassandra.thrift.TimedOutException;import org.apache.cassandra.thrift.UnavailableException;import org.apache.thrift.TException;import org.apache.thrift.protocol.TBinaryProtocol;import org.apache.thrift.protocol.TProtocol;import org.apache.thrift.transport.TSocket;import org.apache.thrift.transport.TTransport;public class CassandraHelloWorld {public static void main(String[] args) throws UnsupportedEncodingException, InvalidRequestException, UnavailableException, TimedOutException, TException, NotFoundException {//Part OneTTransport trans = new TSocket("127.0.0.1", 9160);TProtocol proto = new TBinaryProtocol(trans);Cassandra.Client client = new Cassandra.Client(proto);trans.open();//Part TwoString keyspace = "Keyspace1";String cf = "Standard2";String key = "kylinsoong";long timestamp = new Date().getTime();ColumnPath path = new ColumnPath(cf);path.setColumn("id".getBytes("UTF-8"));client.insert(keyspace, key, path, "520".getBytes("UTF-8"), timestamp, ConsistencyLevel.ONE);path.setColumn("action".getBytes("UTF-8"));client.insert(keyspace, key, path, "Hello, World, Cassandra!".getBytes("UTF-8"), timestamp, ConsistencyLevel.ONE);//Part Threepath.setColumn("id".getBytes("UTF-8"));ColumnOrSuperColumn cc = client.get(keyspace, key, path, ConsistencyLevel.ONE);Column c = cc.getColumn();String value = new String(c.value, "UTF-8");System.out.println(value);path.setColumn("action".getBytes("UTF-8"));ColumnOrSuperColumn cc2 = client.get(keyspace, key, path, ConsistencyLevel.ONE);Column c2 = cc2.getColumn();String value2 = new String(c2.value, "UTF-8");System.out.println(value2);//Part fourtrans.close();}}?
运行代码，伟大的Hello，World将会出现在我们眼前，运行结果：
520Hello, World, Cassandra!
先对代码做个简单分析，我将代码分为四个部分：
Part One，连接到数据库，相当于JDBC，具体这里是通过RPC通信协议连接到Cassandra的；
Part Two，向数据库中插入数据；
Part Three，读出刚才插入的数据；
Part four， 关闭数据库连接。
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3. 和关系数据库从存储效率上做个比较：
我们先不说Cassandra的数据模型及它的集群，首先我们从实验的角度比较它与Mysql的存储效率，比较之前先做个解释;
关系数据库最小的存储单元是row，而Cassandra是grid（此说法只是为了形象比喻）如下图;
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所示为一个row包含4个grid；
对关系数据库，可以一次插入或读取一行，而Cassandra只能一次插入或读取一个格，也就是说要插入此行信息关系数据库只需一个插入语句，而Cassandra需要四个，看上去关系数据库更有效率，实际上结果将会使你为之Shocking；
开始我们的实验，在本地开启Cassandra服务器：
在Mysql中创建一个数据库，在数据库中创建下表：
create table test(parseTime varchar(40)primary key,id varchar(40),creationTime varchar(40),globalInstanceId varchar(255),msg varchar(255),severity varchar(20),modelName varchar(255),rComponent varchar(255),rExecutionEnvironment varchar(255),sExecutionEnvironment varchar(255),sLocation varchar(255),msgId varchar(255));
?此表中包含12 column，为了简单索引column对应类型都是字符串，
向此表中插入68768 * 2 条数据，查看记录测试时间，如下为测试程序输出Log
create table time(id varchar(20));
?是的，此表只有一个字段，目的是让Cassandra与Mysql更有可比性。
同样先看Mysql输出日志：
<Storage><ClusterName>Kylin-PC</ClusterName><Keyspaces><Keyspace Name="Twitter"><ColumnFamily CompareWith="UTF8Type" Name="Statuses" /><ColumnFamily CompareWith="UTF8Type" Name="StatusAudits" /><ColumnFamily CompareWith="UTF8Type" Name="StatusRelationships" CompareSubcolumnsWith="TimeUUIDType" ColumnType="Super" /> <ColumnFamily CompareWith="UTF8Type" Name="Users" /><ColumnFamily CompareWith="UTF8Type" Name="UserRelationships" CompareSubcolumnsWith="TimeUUIDType" ColumnType="Super" /></Keyspace> </Keyspaces></Storage>
?上面Keyspace就是真实的Twitter存储数据的模型的定义，它里面包含5个ColumnFamily，对照Mysql，Keyspace相当于一个数据库，ColumnFamily 相当于数据库中一张表；
上面配置文件中ClusterName表示Cassandra的一个节点实例（逻辑上的一个Cassandra Server，一般为一台PC），名字为Kylin-PC，一个节点实例可以包括多个Keyspace；
下面我分别结合实例从以下几个方面说明Cassandra的数据模型：
（一）、ColumnFamily
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?如图，ColumnFamily 包含多个Row，上面说过ColumnFamily 相当于关系数据库中的一个Table，每一个Row都包含有Client提供的Key以及和该Key相关的一系列Column，每个Column都包括name,value,timestamp，值得注意每个Row中包含的Column不一定相同；
修改上面HelloWorld程序，修给后代码如下：
public static void main(String[] args) throws Exception {TTransport trans = new TSocket("127.0.0.1", 9160); TProtocol proto = new TBinaryProtocol(trans); Cassandra.Client client = new Cassandra.Client(proto); trans.open(); String keyspace = "Twitter"; String columnFamily = "Users"; ColumnPath path = new ColumnPath(columnFamily); String row1 = "kylin"; path.setColumn("id".getBytes()); client.insert(keyspace, row1, path,"101".getBytes(),new Date().getTime(),ConsistencyLevel.ONE); path.setColumn("name".getBytes()); client.insert(keyspace, row1, path,"Kylin Soong".getBytes(),new Date().getTime(),ConsistencyLevel.ONE); String row2 = "kobe"; path.setColumn("id".getBytes()); client.insert(keyspace, row2, path,"101".getBytes(),new Date().getTime(),ConsistencyLevel.ONE); path.setColumn("name".getBytes()); client.insert(keyspace, row2, path,"Kobe Bryant".getBytes(),new Date().getTime(),ConsistencyLevel.ONE); path.setColumn("age".getBytes()); client.insert(keyspace, row2, path,"32".getBytes(),new Date().getTime(),ConsistencyLevel.ONE); path.setColumn("desc".getBytes()); client.insert(keyspace, row2, path,"Five NBA title, One regular season MVP, Two Final Games MVP".getBytes(),new Date().getTime(),ConsistencyLevel.ONE); path.setColumn("id".getBytes()); ColumnOrSuperColumn cos11 = client.get(keyspace, row1, path, ConsistencyLevel.ONE); path.setColumn("name".getBytes()); ColumnOrSuperColumn cos12 = client.get(keyspace, row1, path, ConsistencyLevel.ONE); Column c11 = cos11.getColumn(); Column c12 = cos12.getColumn(); System.out.println(new String(c11.getValue()) + " | " + new String(c12.getValue())); path.setColumn("id".getBytes()); ColumnOrSuperColumn cos21 = client.get(keyspace, row2, path, ConsistencyLevel.ONE); path.setColumn("name".getBytes()); ColumnOrSuperColumn cos22 = client.get(keyspace, row2, path, ConsistencyLevel.ONE); path.setColumn("age".getBytes()); ColumnOrSuperColumn cos23 = client.get(keyspace, row2, path, ConsistencyLevel.ONE); path.setColumn("desc".getBytes()); ColumnOrSuperColumn cos24 = client.get(keyspace, row2, path, ConsistencyLevel.ONE); Column c21 = cos21.getColumn(); Column c22 = cos22.getColumn(); Column c23 = cos23.getColumn(); Column c24 = cos24.getColumn(); System.out.println(new String(c21.getValue()) + " | " + new String(c22.getValue())+ " | " + new String(c23.getValue()) + " | " + new String(c24.getValue())); trans.close(); }上面代码所示：向名字为“Users”的columnFamily中添加2行，第一行包含2个Column，Column名字分别为：id、name；第二行包含4个Column，Column名字非别为id、name、age、desc；运行上述代码结果如下：
101 | Kylin Soong101 | Kobe Bryant | 32 | Five NBA title, One regular season MVP, Two Final Games MVP
?（二）SuperColumn
SuperColumn中包含多个Column，下面我们用程序实现向SuperColumn中添加，读取数据，先看下图：
?如上图所示ColumnFamily 包括2行，每行包括2个SuperColumn，每个SuperColumn中包含多个Column，下面我们用代码演示上图情景，为了简单，我们把两行，简化为一行；
修改HelloWorld代码，如下：
public static void main(String[] args) throws Exception {TTransport trans = new TSocket("127.0.0.1", 9160); TProtocol proto = new TBinaryProtocol(trans); Cassandra.Client client = new Cassandra.Client(proto); trans.open(); String keyspace = "Twitter"; String columnFamily = "UserRelationships"; String row = "row"; Map<String, List<ColumnOrSuperColumn>> cfmap = new HashMap<String, List<ColumnOrSuperColumn>>(); List<ColumnOrSuperColumn> cslist = new ArrayList<ColumnOrSuperColumn>(); ColumnOrSuperColumn cos = new ColumnOrSuperColumn(); List<Column> columnList = new ArrayList<Column>(); Column id = new Column(); id.setName("id".getBytes()); id.setValue("101".getBytes()); id.setTimestamp(new Date().getTime()); Column name = new Column(); name.setName("name".getBytes()); name.setValue("Kylin Soong".getBytes()); name.setTimestamp(new Date().getTime()); columnList.add(id); columnList.add(name); SuperColumn sc = new SuperColumn(); sc.setColumns(columnList); sc.setName("super1".getBytes()); cos.super_column = sc; cslist.add(cos); cfmap.put(columnFamily, cslist); Map<String, List<ColumnOrSuperColumn>> cfmap2 = new HashMap<String, List<ColumnOrSuperColumn>>(); List<ColumnOrSuperColumn> cslist2 = new ArrayList<ColumnOrSuperColumn>(); ColumnOrSuperColumn cos2 = new ColumnOrSuperColumn(); List<Column> columnList2 = new ArrayList<Column>(); Column id2 = new Column(); id2.setName("id".getBytes()); id2.setValue("101".getBytes()); id2.setTimestamp(new Date().getTime()); Column name2 = new Column(); name2.setName("name".getBytes()); name2.setValue("Kobe Bryant".getBytes()); name2.setTimestamp(new Date().getTime()); Column age = new Column(); age.setName("age".getBytes()); age.setValue("32".getBytes()); age.setTimestamp(new Date().getTime()); Column desc = new Column(); desc.setName("desc".getBytes()); desc.setValue("Five NBA title, One regular season MVP, Two Final Games MVP".getBytes()); desc.setTimestamp(new Date().getTime()); columnList2.add(id2); columnList2.add(name2); columnList2.add(age); columnList2.add(desc); SuperColumn sc2 = new SuperColumn(); sc2.setColumns(columnList2); sc2.setName("super2".getBytes()); cos2.super_column = sc2; cslist2.add(cos2); cfmap2.put(columnFamily, cslist2); client.batch_insert(keyspace, row, cfmap, ConsistencyLevel.ONE); client.batch_insert(keyspace, row, cfmap2, ConsistencyLevel.ONE); ColumnPath path = new ColumnPath(columnFamily); path.setSuper_column("super1".getBytes()); ColumnOrSuperColumn s = client.get(keyspace, row, path, ConsistencyLevel.ONE); System.out.println(new String(s.super_column.columns.get(0).value) + " | " + new String(s.super_column.columns.get(1).value)); path.setSuper_column("super2".getBytes()); ColumnOrSuperColumn s2 = client.get(keyspace, row, path, ConsistencyLevel.ONE); System.out.println(new String(s2.super_column.columns.get(2).value) + " | " + new String(s2.super_column.columns.get(3).value) + " | " + new String(s2.super_column.columns.get(0).value) + " | " + new String(s2.super_column.columns.get(1).value)); trans.close(); }?上述代码演示往名字叫“UserRelationships”的columnFamily中添加一行，这一行中包含两个SuperColumn，名字分别：super1和super2，super1包含2个Column，名字分别为id,name；super2包含4个Column，名字分别为id,name,age,desc，运行结果：
101 | Kylin Soong101 | Kobe Bryant | 32 | Five NBA title, One regular season MVP, Two Final Games MVP
（三）Column
从上面一、二可以看到Column是Cassandra的最小存储单位，它的结构如下：
struct Column { 1: binary name, 2: binary value, 3: i64 timestamp,}?（四）keyspace
如上面一二中 String keyspace = "Twitter"; 都定义了keyspace 是名字为“Twitter”，相当于干系数据库中的Schema或数据库。
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结束
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1 楼 weijinxian 2010-08-18 hi,为什么你要研究cassandra呢? 2 楼 kylinsoong 2010-08-18 weijinxian 写道hi,为什么你要研究cassandra呢?因为我们的一个软件运行时产生大量信息需要保持，之前保持在数据库，现在需要保持到Cassandra，因为Cassandra的扩展性，速度等