标签：android style http os 使用 io strong 文件 for
环境：
Centos6.4 64位
Hadoop2.2.0
Sun JDK1.7.0_45
hive-0.12.0
准备工作：
yum -y install lzo-devel zlib-devel gcc autoconf automake libtool
开始了哦！
（1）安装LZO
wget http://www.oberhumer.com/opensource/lzo/download/lzo-2.06.tar.gz
tar -zxvf lzo-2.06.tar.gz
./configure -enable-shared -prefix=/usr/local/hadoop/lzo/
make && make test && make install
（2）安装LZOP
wget http://www.lzop.org/download/lzop-1.03.tar.gz
tar -zxvf lzop-1.03.tar.gz
export C_INCLUDE_PATH=/usr/local/hadoop/lzo/include/
./configure -enable-shared -prefix=/usr/local/hadoop/lzop
make && make install
（3）把lzop复制到/usr/bin/
ln -s /usr/local/hadoop/lzop/bin/lzop /usr/bin/lzop
（4）测试lzop
lzop /home/hadoop/data/access_20131219.log
报错：lzop: error while loading shared libraries: liblzo2.so.2: cannot open shared object file: No such file or directory
会在生成一个lzo后缀的压缩文件： /home/hadoop/data/access_20131219.log.lzo即表示前述几个步骤正确哦。
（5）安装Hadoop-LZO
当然的还有一个前提，就是配置好maven和svn 或者Git（我使用的是SVN），这个就不说了，如果这些搞不定，其实也不必要进行下去了！
我这里使用https://github.com/twitter/hadoop-lzo
使用SVN从https://github.com/twitter/hadoop-lzo/trunk下载代码，修改pom.xml文件中的一部分。
从：
<properties>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
<hadoop.current.version>2.1.0-beta</hadoop.current.version>
<hadoop.old.version>1.0.4</hadoop.old.version>
</properties>
修改为：
<properties>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
<hadoop.current.version>2.2.0</hadoop.current.version>
<hadoop.old.version>1.0.4</hadoop.old.version>
</properties>
再依次执行:
mvn clean package -Dmaven.test.skip=true
tar -cBf - -C target/native/Linux-amd64-64/lib . | tar -xBvf - -C /home/hadoop/hadoop-2.2.0/lib/native/
cp target/hadoop-lzo-0.4.20-SNAPSHOT.jar /home/hadoop/hadoop-2.2.0/share/hadoop/common/
接下来就是将/home/hadoop/hadoop-2.2.0/share/hadoop/common/hadoop-lzo-0.4.20-SNAPSHOT.jar以及/home/hadoop/hadoop-2.2.0/lib/native/ 同步到其它所有的hadoop节点。注意，要保证目录/home/hadoop/hadoop-2.2.0/lib/native/ 下的jar包，你运行hadoop的用户都有执行权限。
（6）配置Hadoop
在文件$HADOOP_HOME/etc/hadoop/hadoop-env.sh中追加如下内容：
export LD_LIBRARY_PATH=/usr/local/hadoop/lzo/lib
在文件$HADOOP_HOME/etc/hadoop/core-site.xml中追加如下内容：
<property>
<name>io.compression.codecs</name>
<value>org.apache.hadoop.io.compress.GzipCodec,
org.apache.hadoop.io.compress.DefaultCodec,
com.hadoop.compression.lzo.LzoCodec,
com.hadoop.compression.lzo.LzopCodec,
org.apache.hadoop.io.compress.BZip2Codec
</value>
</property>
<property>
<name>io.compression.codec.lzo.class</name>
<value>com.hadoop.compression.lzo.LzoCodec</value>
</property>
在文件$HADOOP_HOME/etc/hadoop/mapred-site.xml中追加如下内容：
<property>
<name>mapred.compress.map.output</name>
<value>true</value>
</property>
<property>
<name>mapred.map.output.compression.codec</name>
<value>com.hadoop.compression.lzo.LzoCodec</value>
</property>
<property>
<name>mapred.child.env</name>
<value>LD_LIBRARY_PATH=/usr/local/hadoop/lzo/lib</value>
</property>
（7）在Hive中体验lzo
A：首先创建nginx_lzo的表
CREATE TABLE logs_app_nginx (
ip STRING,
user STRING,
time STRING,
request STRING,
status STRING,
size STRING,
rt STRING,
referer STRING,
agent STRING,
forwarded String
)
partitioned by (
date string,
host string
)
row format delimited
fields terminated by ‘\t‘
STORED AS INPUTFORMAT "com.hadoop.mapred.DeprecatedLzoTextInputFormat"
OUTPUTFORMAT "org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat";
B：导入数据
LOAD DATA Local INPATH ‘/home/hadoop/data/access_20131230_25.log.lzo‘ INTO TABLE logs_app_nginx PARTITION(date=20131229,host=25);
/home/hadoop/data/access_20131219.log文件的格式如下:
221.207.93.109 - [23/Dec/2013:23:22:38 +0800] "GET /ClientGetResourceDetail.action?id=318880&token=Ocm HTTP/1.1" 200 199 0.008 "xxx.com" "Android4.1.2/LENOVO/Lenovo A706/ch_lenovo/80" "-"
直接采用lzop /home/hadoop/data/access_20131219.log即可生成lzo格式压缩文件/home/hadoop/data/access_20131219.log.lzo
C：索引LZO文件
$HADOOP_HOME/bin/hadoop jar /home/hadoop/hadoop-2.2.0/share/hadoop/common/hadoop-lzo-0.4.20-SNAPSHOT.jar com.hadoop.compression.lzo.DistributedLzoIndexer /user/hive/warehouse/<span style="font-family: Arial, Helvetica, sans-serif;">logs_app_nginx</span>
D：开始跑利用hive来跑map/reduce任务了
set hive.exec.reducers.max=10;
set mapred.reduce.tasks=10;
select ip,rt from nginx_lzo limit 10;
在hive的控制台能看到类似如下格式输出，就表示正确了!
hive> set hive.exec.reducers.max=10;
hive> set mapred.reduce.tasks=10;
hive> select ip,rt from nginx_lzo limit 10;
Total MapReduce jobs = 1
Launching Job 1 out of 1
Number of reduce tasks is set to 0 since there‘s no reduce operator
Starting Job = job_1388065803340_0009, Tracking URL = http://lrts216:8088/proxy/application_1388065803340_0009/
Kill Command = /home/hadoop/hadoop-2.2.0/bin/hadoop job -kill job_1388065803340_0009
Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 0
2013-12-27 09:13:39,163 Stage-1 map = 0%, reduce = 0%
2013-12-27 09:13:45,343 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 1.22 sec
2013-12-27 09:13:46,369 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 1.22 sec
MapReduce Total cumulative CPU time: 1 seconds 220 msec
Ended Job = job_1388065803340_0009
MapReduce Jobs Launched:
Job 0: Map: 1 Cumulative CPU: 1.22 sec HDFS Read: 63570 HDFS Write: 315 SUCCESS
Total MapReduce CPU Time Spent: 1 seconds 220 msec
OK
221.207.93.109 "XXX.com"
Time taken: 17.498 seconds, Fetched: 10 row(s)
标签：android style http os 使用 io strong 文件 for
原文地址：http://www.cnblogs.com/luxiaorui/p/3931024.html
