CDH5: 使用parcels配置lzo

1、Parcel 部署步骤

    1 下载: 首先须要下载 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，将分配到群集中的全部主机上并解压缩。
    3 激活: 分配后，激活 Parcel 为群集重启后使用作准备。激活前可能还须要升级。

2、lzo parcels本地化

    一、到http://archive-primary.cloudera.com/gplextras/parcels/latest/下载最新lzo parcels包，根据安装hadoop集群的服务器操做系统版本下载，我使用的是rhel6.2, 因此下载的是HADOOP_LZO-0.4.15-1.gplextras.p0.64-el6.parcel

    二、同时下载manifest.json，并根据manifest.json文件中的hash值建立sha文件（注意：sha文件的名称与parcels包名同样）

    三、命令行进入Apache（若是没有安装，则须要安装）的网站根目录下，默认是/var/www/html,在此目录下建立lzo，并将这三个文件放在lzo目录中

    四、启动httpd服务，在浏览器查看，如http://ip/lzo,则结果以下：

        

    五、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

        

 六、在cloud manager的parcel页面的可下载parcel中，就能够看到lzo parcels, 点击并进行下载

七、根据parcels的部署步骤，进行分配、激活。结果以下图

3、修改配置

    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的属性值修改成：$HADOOP_MAPRED_HOME/*,$HADOOP_MAPRED_HOME/lib/*,$MR2_CLASSPATH,/opt/cloudera/parcels/HADOOP_LZO/lib/hadoop/lib/*

    将mapreduce.admin.user.env的属性值修改成：LD_LIBRARY_PATH=$HADOOP_COMMON_HOME/lib/native:$JAVA_LIBRARY_PATH:/opt/cloudera/parcels/HADOOP_LZO/lib/hadoop/lib/native

4、验证

    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';

    建立一个data.txt,内容以下：  

1#tianhe
2#gz
3#sz
4#sz
5#bx

    而后使用lzop命令对此文件压缩，而后上传到hdfs的/test目录下

    启动hive,建表并进行数据查询，结果以下：

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
OK
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';
OK
Time taken: 0.092 seconds
hive> insert into table lzo2 select * from lzo; Total MapReduce jobs = 3 Launching Job 1 out of 3 Number of reduce tasks is set to 0 since there's no reduce operator 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 Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 0 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] MapReduce Jobs Launched:  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 OK Time taken: 36.625 seconds