Hadoop2.2.0+hive使用LZO壓縮那些事
廢話不多說，我在apache Hadoop2.2.0測試叢集上配置支援使用LZO進行壓縮的時候，遇到很多坑，不過最後到搞定了，這裡把具體過程記錄下來，以供參考。
環境：
Centos6.4 64位
Hadoop2.2.0
Sun JDK1.7.0_45
hive-0.12.0
準備工作：
yum -y install lzo-devel zlib-devel gcc autoconf automake libtool
開始了哦！
（1）安裝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）安裝LZOP
wget http://www.lzop.org/download/lzop-1.03.tar.gz
tar -zxvf lzop-1.03.tar.gz
./configure -enable-shared -prefix=/usr/local/hadoop/lzop
make && make install
（3）把lzop複製到/usr/bin/
ln -s /usr/local/hadoop/lzop/bin/lzop /usr/bin/lzop
（4）測試lzop
lzop /home/hadoop/data/access_20131219.log
會在生成一個lzo字尾的壓縮檔案： /home/hadoop/data/access_20131219.log.lzo即表示前述幾個步驟正確哦。
（5）安裝Hadoop-LZO
當然的還有一個前提，就是配置好maven和svn 或者Git（我使用的是SVN），這個就不說了，如果這些搞不定，其實也不必要進行下去了！
使用SVN從https://github.com/twitter/hadoop-lzo/trunk下載程式碼，修改pom.xml檔案中的一部分。
從：
<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>
修改為：
<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>再依次執行:
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/在檔案$HADOOP_HOME/etc/hadoop/hadoop-env.sh中追加如下內容：
export LD_LIBRARY_PATH=/usr/local/hadoop/lzo/lib在檔案$HADOOP_HOME/etc/hadoop/core-site.xml中追加如下內容：
<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>
在檔案$HADOOP_HOME/etc/hadoop/mapred-site.xml中追加如下內容：
<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中體驗lzo
A：首先建立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";
LOAD DATA Local INPATH '/home/hadoop/data/access_20131230_25.log.lzo' INTO TABLE logs_app_nginx PARTITION(date=20131229,host=25);
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" "-"
直接採用lzop /home/hadoop/data/access_20131219.log即可生成lzo格式壓縮檔案/home/hadoop/data/access_20131219.log.lzo
C：索引LZO檔案
$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/logs_app_nginxD：開始跑利用hive來跑map/reduce任務了
set hive.exec.reducers.max=10;
set mapred.reduce.tasks=10;
select ip,rt from nginx_lzo limit 10;在hive的控制檯能看到類似如下格式輸出，就表示正確了!
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)至今沒有找到任何一個BLOG可以直接參照著就能順利完成，我也是折騰了3個晚上才終於讓測試叢集跑了起來的。
參考：
https://github.com/kevinweil/hadoop-lzo
https://github.com/twitter/hadoop-lzo
http://blog.csdn.net/lalaguozhe/article/details/10912527
http://blog.csdn.net/xiaoping8411/article/details/7605039
http://share.blog.51cto.com/278008/549393
http://hadoop.apache.org/docs/r2.2.0/hadoop-project-dist/hadoop-common/NativeLibraries.html