By Tzu-Cheng Chuang 1-28-2011
Requires: Ubuntu10.04, hadoop0.20.2, zookeeper 3.3.2 HBase0.90.0
1. Download Ubuntu 10.04 desktop 32 bit from Ubuntu website.
2. Install Ubuntu 10.04 with username: hadoop, password: password, disk size: 20GB, memory: 2048MB, 1 processor, 2 cores
3. Install build-essential (for GNU C, C++ compiler) $ sudo apt-get install build-essential
4. Install sun-jave-6-jdk
(1) Add the Canonical Partner Repository to your apt repositories
$ sudo add-apt-repository "deb http://archive.canonical.com/ lucid partner"
(2) Update the source list
$ sudo apt-get update
(3) Install sun-java-6-jdk and make sure Sun’s java is the default jvm
$ sudo apt-get install sun-java6-jdk
(4) Set environment variable by modifying ~/.bashrc file, put the following two lines in the end of the file
export JAVA_HOME=/usr/lib/jvm/java-6-sun
export PATH=$PATH:$JAVA_HOME/bin
5. Configure SSH server so that ssh to localhost doesn’t need a passphrase
(1) Install openssh server
$ sudo apt-get install openssh-server
(2) Generate RSA pair key
$ ssh-keygen –t ras –P ""
(3) Enable SSH access to local machine
$ cat ~/.ssh/id_rsa.pub >> ~/.ssh/authorized_keys
6. Disable IPv6 by modifying /etc/sysctl.conf file, put the following two lines in the end of the file
#disable
ipv6 net.ipv6.conf.all.disable_ipv6 = 1
net.ipv6.conf.default.disable_ipv6 = 1
net.ipv6.conf.lo.disable_ipv6 = 1
7. Install hadoop
(1) Download hadoop-0.20.2.tar.gz(stable release on 1/25/2011) from Apache hadoop website
(2) Extract hadoop archive file to /usr/local/
(3) Make symbolic link
(4) Modify /usr/local/hadoop/conf/hadoop-env.sh
Change from # The java implementation to use. Required. # export JAVA_HOME=/usr/lib/j2sdk1.5-sun To # The java implementation to use. Required. export JAVA_HOME=/usr/lib/jvm/java-6-sun
(5)Create /usr/local/hadoop-datastore folder
$ sudo mkdir /usr/local/hadoop-datastore
$ sudo chown hadoop:hadoop /usr/local/hadoop-datastore
$ sudo chmod 750 /usr/local/hadoop-datastore
(6)Put the following code in /usr/local/hadoop/conf/core-site.xml
hadoop.tmp.dir/usr/local/hadoop/tmp/dir/hadoop-${user.name}A base for other temporary directories.fs.default.namehdfs://master:54310The name of the default file system. A URI whose scheme and authority determine the FileSystem implementation. The uri's scheme determines the config property (fs.SCHEME.impl) naming the FileSystem implementation class. The uri's authority is used to determine the host, port, etc. for a filesystem.
(7) Put the following code in /usr/local/hadoop/conf/mapred-site.xml
mapred.job.trackermaster:54311The host and port that the MapReduce job tracker runs at. If "local", then jobs are run in-process as a single map and reduce task.
(8) Put the following code in /usr/local/hadoop/conf/hdfs-site.xml
dfs.replication1Default block replication. The actual number of replications can be specified when the file is created. The default is used if replication is not specified in create time.
(9) Add hadoop to environment variable by modifying ~/.bashrc
export HADOOP_HOME=/usr/local/hadoop export PATH=$HADOOP_HOME/bin:$PATH
8. Restart Ubuntu Linux
9. Copy this virtual machine to another folder. At least we have 2 copies of Ubuntu linux
10. Modify /etc/hosts on both Linux Virtual Image machines, add in the following lines in the file. The IP address depends on each machine. We can use (ifconfig) to find out IP address.
# /etc/hosts (for master AND slave) 192.168.0.1 master 192.168.0.2 slave Modify the following line, because it might cause Hbase to find out wrong ip.
192.168.0.1 ubuntu
11. Check hadoop user access on both machines.
The hadoop user on the master (aka hadoop@master) must be able to connect a) to its own user account on the master – i.e. ssh master in this context and not necessarily ssh localhost – and b) to the hadoop user account on the slave (aka hadoop@slave) via a password-less SSH login. On both machines, make sure each one can connect to master, slave without typing passwords.
12. Cluster configuration
(1) Modify /usr/local/hadoop/conf/masters
only on master machine master
(2) Modify /usr/local/hadoop/conf/slaves
only on master machine master slave
(3) Change “localhost” to “master” in /usr/local/conf/hadoop/conf/core-site.xml and /usr/local/hadoop/conf/mapred-site.xml
only on master machine
(4) Change dfs.replication to “1” in /usr/local/conf/hadoop/conf/hdfs-site.xml
only on master machine
13. Format the namenode only once and only on master machine
$ /usr/local/hadoop/bin/hadoop namenode –format
14. Later on, start the multi-node cluster by typing following code only on master. So far, please don’t start hadoop yet.
$ /usr/local/hadoop/bin/start-dfs.sh $ /usr/local/hadoop/bin/start-mapred.sh
15. Install zookeeper only on master node
(1) download zookeeper-3.3.2.tar.gz from Apache hadoop website
(2) Extract zookeeper-3.3.2.tar.gz $ tar –xzf zookeeper-3-3.2.tar.gz
(3) Move folder zookeeper-3.3.2 to /home/hadoop/ and create a symbloink link
$ mv zookeeper-3.3.2 /home/hadoop/ ; ln –s /home/hadoop/zookeeper-3.3.2 /home/hadoop/zookeeper
(4) copy conf/zoo_sample.cfg to conf/zoo.cfg
$ cp conf/zoo_sample.cfg confg/zoo.cfg
(5) Modify conf/zoo.cfg dataDir=/home/hadoop/zookeeper/snapshot
16. Install Hbase on both master and slave nodes, configure it as fully-distributed
(1) Download hbase-0.90.0.tar.gz from Apache hadoop website
(2) Extract hbase-0.90.0.tar.gz $ tar –xzf hbase-0.90.0.tar.gz
(3) Move folder hbase-0.90.0 to /home/hadoop/ and create a symbloink link $ mv hbase-0.90.0 /home/hadoop/ ; ln –s /home/hadoop/hbase-0.90.0 /home/hadoop/hbase
(4) Edit /home/hadoop/hbase/conf/hbase-site.xml, put the following in between and hbase.rootdirhdfs://master:54310/hbase The directory shared by region servers. Should be fully-qualified to include the filesystem to use. E.g: hdfs://NAMENODE_SERVER:PORT/HBASE_ROOTDIR hbase.cluster.distributedtrueThe mode the cluster will be in. Possible values are false: standalone and pseudo-distributed setups with managed Zookeeper true: fully-distributed with unmanaged Zookeeper Quorum (see hbase-env.sh) hbase.zookeeper.quorummasterComma separated list of servers in the ZooKeeper Quorum. If HBASE_MANAGES_ZK is set in hbase-env.sh this is the list of servers which we will start/stop ZooKeeper on.
(5) modify environment variables in /home/hadoop/hbase/conf/hbase-env.sh
export JAVA_HOME=/usr/lib/jvm/java-6-sun/
export HBASE_IDENT_STRING=$HOSTNAME
export HBASE_MANAGES_ZK=false
(6)Overwrite /home/hadoop/hbase/conf/regionservers
on both machines master slave
(7)copy /usr/local/hadoop-0.20.2/haoop-0.20.2-core.jar to /home/hadoop/hbase/lib/ on both machines.
This is very important to fix version difference issue. Pay attention to its ownership and mode(755).
17. Start zookeeper. It seems the zookeeper bundled with Hbase is not set up correctly.
$ /home/hadoop/zookeeper/bin/zkServer.sh start (Optional)We can test if zookeeper is running correctly by typing $ /home/hadoop/zookeeper/bin/zkCli.sh –server 127.0.0.1:2181
18. Start hadoop cluster
$ /usr/local/hadoop/bin/start-dfs.sh $ /usr/local/hadoop/bin/start-mapred.sh
19. Start Hbase
$ /home/hadoop/hbase/bin/start-hbase.sh
20. Use Hbase shell
$ /home/hadoop/hbase/bin/hbase shell Check if hbase is running smoothly
Open your browser, and type in the following.
http://localhost:60010
21. Later on, stop the multi-node cluster by typing following code only on master
(1) Stop Hbase $ /home/hadoop/hbase/bin/stop-hbase.sh
(2) Stop hadoop file system (HDFS)
$ /usr/local/hadoop/bin/stop-mapred.sh
$ /usr/local/hadoop/bin/stop-dfs.sh
(3) Stop zookeeper
$ /home/hadoop/zookeeper/bin/zkServer.sh stop
Reference
http://www.michael-noll.com/tutorials/running-hadoop-on-ubuntu-linux-single-node-cluster/
http://www.michael-noll.com/tutorials/running-hadoop-on-ubuntu-linux-multi-node-cluster/
http://wiki.apache.org/hadoop/Hbase/10Minutes
http://hbase.apache.org/book/quickstart.html
http://alans.se/blog/2010/hadoop-hbase-cygwin-windows-7-x64/
Author
Tzu-Cheng Chuang
Appendix- Install Pig and Hive
1. Install Pig 0.8.0 on this cluster
(1) Download pig-0.8.0.tar.gz from Apache pig project website. Then extract the file and move it to /home/hadoop/
$ tar –xzf pig-0.8.0.tar.gz ; mv pig-0.8.0 /home/hadoop/
(2) Make symbolink link under pig-0.8.0/conf/
$ ln -s /usr/local/hadoop/conf/core-site.xml /home/hadoop/pig-0.8.0/conf/core-site.xml
$ ln -s /usr/local/hadoop/conf/mapred-site.xml /home/hadoop/pig-0.8.0/conf/mapred-site.xml
$ ln -s /usr/local/hadoop/conf/hdfs-site.xml /home/hadoop/pig-0.8.0/conf/hdfs-site.xml
3) Start pig in map-reduce mode: $ /home/hadoop/pig-0.8.0/bin/pig
(4) Exit pig from grunt> quit
2. Install Hive on this cluster
(1) Download hive-0.6.0.tar.gz from Apache hive project website, and then extract the file and move it to /home/hadoop/ $ tar –xzf hive-0.6.0.tar.gz ; mv hive-0.6.0 ~/
(2) Modify java heap size in hive-0.6.0/bin/ext/execHiveCmd.sh Change 4096 to 1024
(3) Create /tmp and /user/hive/warehouse and set them chmod g+w in HDFS before a table can be created in Hive $ hadoop fs –mkdir /tmp $ hadoop fs –mkdir /user/hive/warehouse $ hadoop fs –chmod g+w /tmp $ hadoop fs –chmod g+w /user/hive/warehouse
(4) start Hive $ /home/hadoop/hive-0.6.0/bin/hive
3. (Optional)Load data by using Hive
Create a file /home/hadoop/customer.txt 1, Kevin 2, David 3, Brian 4, Jane 5, Alice After hive shell is started, type in > CREATE TABLE IF NOT EXISTS customer(id INT, name STRING) > ROW FORMAT delimited fields terminated by ',' > STORED AS TEXTFILE; >LOAD DATA INPATH '/home/hadoop/customer.txt' OVERWRITE INTO TABLE customer; >SELECT customer.id, customer.name from customer;
http://chuangtc.info/ParallelComputing/SetUpHadoopClusterOnVmwareWorkstation.htm
以前和數據庫打交道的標準INTERFACE是JDBC，放SQL語句，執行，就可以有結果。隨著近年ORM的興起，以對象的方式存取數據庫大行其道。于是產生了JPA。
也是一套INTERFACE，以ORM的方式提供，由廠商實現，如ECLIPSE LINK，HIBERNATE，OPENEJB等。
ENTITYMANAGERFACTORY：根據配置文件制造ENTITYMANAGER
ENTITYMANAGER：以ORM的方式提供操作數據庫的功能
TRANSACTION：事務保證
PERSISTENCE.XML：鏈接數據庫信息，事務類型，重定義JPA的實現廠商等的配置信息
在容器環境下使用：
如果事務是RESOURCE_LOCAL的方式，則合用端需干所有的事情，如構造ENTITYMANAGER，打開事務，關閉事務等。類似于BMT。
以下是在服務器環境中合用RESOURCE_LOCAL型的JPA
事先要在容器中添加數據源。
persistence.xml
<?xml version="1.0" encoding="UTF-8" ?>
<persistence xmlns="http://java.sun.com/xml/ns/persistence" version="1.0">
<!-- Tutorial "unit" -->
<persistence-unit name="Tutorial" transaction-type="RESOURCE_LOCAL">
<non-jta-data-source>myNonJtaDataSource</non-jta-data-source>
<class>org.superbiz.jpa.Account</class>
</persistence-unit>
</persistence>
import javax.persistence.EntityManagerFactory;
import javax.persistence.EntityManager;
import javax.persistence.EntityTransaction;
import javax.persistence.PersistenceUnit;
public class MyEjbOrServlet
{
@PersistenceUnit(unitName="Tutorial")
private EntityManagerFactory factory;
// Proper exception handling left out for simplicity
public void ejbMethodOrServletServiceMethod()
throws Exception {
EntityManager entityManager = factory.createEntityManager();
EntityTransaction entityTransaction = entityManager.getTransaction();
entityTransaction.begin();
Account account = entityManager.find(Account.
class, 12345);
account.setBalance(5000);
entityTransaction.commit();
}
}
以下是JTA方式的JPA，容器+EJB+JPA+JTA，容器會在EJB的方法調用前打開一個事務，在方法退出后，提交事務，并且如果是多個數據源的，即有多個ENTITYMANAGER的
可以保證一致性，即全局事務。相當于之前的先調用USERTRANSACTION，BEGIN，COMMIT。
事先要在容器中添加數據源。
persistence.xml
<?xml version="1.0" encoding="UTF-8" ?>
<persistence xmlns="http://java.sun.com/xml/ns/persistence" version="1.0">
<!-- Tutorial "unit" -->
<persistence-unit name="Tutorial" transaction-type="JTA">
<jta-data-source>myJtaDataSource</jta-data-source>
<non-jta-data-source>myNonJtaDataSource</non-jta-data-source>
<class>org.superbiz.jpa.Account</class>
</persistence-unit>
</persistence>
EJB
import javax.ejb.Stateless;
import javax.ejb.TransactionAttribute;
import javax.ejb.TransactionAttributeType;
import javax.persistence.EntityManager;
import javax.persistence.PersistenceContext;
@Stateless
public class MyEjb implements MyEjbInterface {
@PersistenceContext(unitName = "Tutorial")
private EntityManager entityManager;
// Proper exception handling left out for simplicity
@TransactionAttribute(TransactionAttributeType.REQUIRED)
public void ejbMethod() throws Exception {
Account account = entityManager.find(Account.class, 12345);
account.setBalance(5000);
}
}
如果是J2SE環境下使用JPA，則又是不一樣的。
persistence.xml
<?xml version="1.0" encoding="UTF-8"?>
<persistence xmlns="http://java.sun.com/xml/ns/persistence" version="1.0">
<persistence-unit name="SimplePU" transaction-type="RESOURCE_LOCAL">
<provider>org.hibernate.ejb.HibernatePersistence</provider>
<class>com.someone.jmail.valueobject.CallActivity</class>
<class>com.someone.jmail.valueobject.Email</class>
<properties>
<property name="hibernate.connection.driver_class" value="com.mysql.jdbc.Driver" />
<property name="hibernate.connection.url" value="jdbc:mysql://localhost:3306/test" />
<property name="hibernate.connection.username" value="root" />
<property name="hibernate.connection.password" value="12345" />
<property name="hibernate.dialect" value="org.hibernate.dialect.MySQL5Dialect" />
<property name="hibernate.show_sql" value="false"/>
<property name="hibernate.format_sql" value="true"/>
<property name="hibernate.use_sql_comments" value="false"/>
<property name="hibernate.hbm2ddl.auto" value="none"/>
</properties>
</persistence-unit>
</persistence>
Dao:
public class UserDaoImpl implements UserDao {
public AccountInfo save(AccountInfo accountInfo) {
EntityManagerFactory emf =
Persistence.createEntityManagerFactory("SimplePU");
EntityManager em = emf.createEntityManager();
em.getTransaction().begin();
em.persist(accountInfo);
em.getTransaction().commit();
emf.close();
return accountInfo;
}
}