1 下载: 首先需要下载 parcel。下载完成后，parcel 将驻留在 cloudera manager 主机的本地目录中。
2 分配: parcel 下载后，将分配到群集中的所有主机上并解压缩。
3 激活: 分配后，激活 parcel 为群集重启后使用做准备。激活前可能还需要升级。
2、同时下载manifest.json，并根据manifest.json文件中的hash值创建sha文件（注意：sha文件的名称与parcels包名一样）
3、命令行进入apache（如果没有安装，则需要安装）的网站根目录下，默认是/var/www/html,在此目录下创建lzo，并将这三个文件放在lzo目录中
4、启动httpd服务，在浏览器查看，如http://ip/lzo,则结果如下：
5、将发布的local parcels发布地址配置到远程 parcel 存储库 url地址中，见下图
6、在cloud manager的parcel页面的可下载parcel中，就可以看到lzo parcels, 点击并进行下载
7、根据parcels的部署步骤，进行分配、激活。结果如下图
修改hdfs的配置
将io.compression.codecs属性值中追加,org.apache.hadoop.io.compress.lz4codec,
com.hadoop.compression.lzo.lzopcodec
修改yarn配置
将mapreduce.application.classpath的属性值修改为：$hadoop_mapred_home/*,$hadoop_mapred_home/lib/*,$mr2_classpath,/opt/cloudera/parcels/hadoop_lzo/lib/hadoop/lib/*
将mapreduce.admin.user.env的属性值修改为：ld_library_path=$hadoop_common_home/lib/native:$java_library_path:/opt/cloudera/parcels/hadoop_lzo/lib/hadoop/lib/native
create external table lzo(id int,name string) row format delimited fields terminated by '#' stored as inputformat 'com.hadoop.mapred.deprecatedlzotextinputformat' outputformat 'org.apache.hadoop.hive.ql.io.hiveignorekeytextoutputformat' location '/test';
创建一个data.txt,内容如下：
然后使用lzop命令对此文件压缩，然后上传到hdfs的/test目录下
启动hive,建表并进行数据查询，结果如下：
hive> create external table lzo(id int,name string) row format delimited fields terminated by '#' stored as inputformat 'com.hadoop.mapred.deprecatedlzotextinputformat' outputformat 'org.apache.hadoop.hive.ql.io.hiveignorekeytextoutputformat' location '/test';
ok
time taken: 0.108 seconds
hive> select * from lzo where id>2;
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_1404206497656_0002, tracking url = http://hadoop01.kt:8088/proxy/application_1404206497656_0002/
kill command = /opt/cloudera/parcels/cdh-5.0.1-1.cdh5.0.1.p0.47/lib/hadoop/bin/hadoop job -kill job_1404206497656_0002
hadoop job information for stage-1: number of mappers: 1; number of reducers: 0
2014-07-01 17:30:27,547 stage-1 map = 0%, reduce = 0%
2014-07-01 17:30:37,403 stage-1 map = 100%, reduce = 0%, cumulative cpu 2.84 sec
2014-07-01 17:30:38,469 stage-1 map = 100%, reduce = 0%, cumulative cpu 2.84 sec
2014-07-01 17:30:39,527 stage-1 map = 100%, reduce = 0%, cumulative cpu 2.84 sec
mapreduce total cumulative cpu time: 2 seconds 840 msec
ended job = job_1404206497656_0002
mapreduce jobs launched:
job 0: map: 1 cumulative cpu: 2.84 sec hdfs read: 295 hdfs write: 15 success
total mapreduce cpu time spent: 2 seconds 840 msec
3 sz
4 sz
5 bx
time taken: 32.803 seconds, fetched: 3 row(s)
hive> set hive.exec.compress.output=true;
hive> set mapred.output.compression.codec=com.hadoop.compression.lzo.lzopcodec;
hive> create external table lzo2(id int,name string) row format delimited fields terminated by '#' stored as inputformat 'com.hadoop.mapred.deprecatedlzotextinputformat' outputformat 'org.apache.hadoop.hive.ql.io.hiveignorekeytextoutputformat' location '/test';
time taken: 0.092 seconds
hive> insert into table lzo2 select * from lzo;
total mapreduce jobs = 3
launching job 1 out of 3
starting job = job_1404206497656_0003, tracking url = http://hadoop01.kt:8088/proxy/application_1404206497656_0003/
kill command = /opt/cloudera/parcels/cdh-5.0.1-1.cdh5.0.1.p0.47/lib/hadoop/bin/hadoop job -kill job_1404206497656_0003
2014-07-01 17:33:47,351 stage-1 map = 0%, reduce = 0%
2014-07-01 17:33:57,114 stage-1 map = 100%, reduce = 0%, cumulative cpu 1.96 sec
2014-07-01 17:33:58,170 stage-1 map = 100%, reduce = 0%, cumulative cpu 1.96 sec
mapreduce total cumulative cpu time: 1 seconds 960 msec
ended job = job_1404206497656_0003
stage-4 is selected by condition resolver.
stage-3 is filtered out by condition resolver.
stage-5 is filtered out by condition resolver.
moving data to: hdfs://hadoop01.kt:8020/tmp/hive-hdfs/hive_2014-07-01_17-33-22_504_966970548620625440-1/-ext-10000
loading data to table default.lzo2
table default.lzo2 stats: [num_partitions: 0, num_files: 2, num_rows: 0, total_size: 171, raw_data_size: 0]
job 0: map: 1 cumulative cpu: 1.96 sec hdfs read: 295 hdfs write: 79 success
total mapreduce cpu time spent: 1 seconds 960 msec
time taken: 36.625 seconds