编译hadoop-lzo组件

1）hadoop本身并不支持lzo压缩，故需要使用twitter提供的hadoop-lzo开源组件。hadoop-lzo需依赖hadoop和lzo进行编译，编译步骤如下。

0. 环境准备

maven（下载安装，配置环境变量，修改sitting.xml加阿里云镜像）

gcc-c++

zlib-devel

autoconf

automake

libtool

通过yum安装即可，yum -y install gcc-c++ lzo-devel zlib-devel autoconf automake libtool

1. 下载、安装并编译LZO

wget http://www.oberhumer.com/opensource/lzo/download/lzo-2.10.tar.gz

tar -zxvf lzo-2.10.tar.gz

cd lzo-2.10

./configure -prefix=/usr/local/hadoop/lzo/

make

make install

2. 编译hadoop-lzo源码

2.1 下载hadoop-lzo的源码，下载地址：https://github.com/twitter/hadoop-lzo/archive/master.zip

2.2 解压之后，修改pom.xml

<hadoop.current.version>3.1.3</hadoop.current.version>

2.3 声明两个临时环境变量

export C_INCLUDE_PATH=/usr/local/hadoop/lzo/include

export LIBRARY_PATH=/usr/local/hadoop/lzo/lib

2.4 编译

进入hadoop-lzo-master，执行maven编译命令

mvn package -Dmaven.test.skip=true

2.5 进入target，hadoop-lzo-0.4.21-SNAPSHOT.jar 即编译成功的hadoop-lzo组件

配置hadoop

2）将编译好后的hadoop-lzo-0.4.20.jar 放入hadoop-3.1.3/share/hadoop/common/

3）同步hadoop-lzo-0.4.20.jar到hadoop103、hadoop104

4）core-site.xml增加配置支持LZO压缩

<configuration>

<property>

<name>io.compression.codecs</name>

<value>

org.apache.hadoop.io.compress.GzipCodec,

org.apache.hadoop.io.compress.DefaultCodec,

org.apache.hadoop.io.compress.BZip2Codec,

org.apache.hadoop.io.compress.SnappyCodec,

com.hadoop.compression.lzo.LzoCodec,

com.hadoop.compression.lzo.LzopCodec

</value>

</property>

<property>

<name>io.compression.codec.lzo.class</name>

<value>com.hadoop.compression.lzo.LzoCodec</value>

</property>

</configuration>

5）同步core-site.xml到hadoop103、hadoop104

LZO创建索引

1）创建LZO文件的索引，LZO压缩文件的可切片特性依赖于其索引，故我们需要手动为LZO压缩文件创建索引。若无索引，则LZO文件的切片只有一个。

对上传的LZO文件建索引

[zy@hadoop102module]$ hadoop jar/opt/module/hadoop-3.1.3/share/hadoop/common/hadoop-lzo-0.4.20.jar com.hadoop.compression.lzo.DistributedLzoIndexer /input/bigtable.lzo

（4）再次执行WordCount程序

Hadoop原生不支持lzo 要手动指定jar包sonnpy原生支持不用指定

[zy@hadoop102module]$ hadoop jar

/opt/module/hadoop-3.1.3/share/hadoop/mapreduce/hadoop-mapreduce-examples-3.1.3.jar

wordcount -Dmapreduce.job.inputformat.class=com.hadoop.mapreduce.LzoTextInputFormat /input

/output2

3）注意：如果以上任务，在运行过程中报如下异常

Container

[pid=8468,containerID=container_1594198338753_0001_01_000002] is running

318740992B beyond the 'VIRTUAL' memory limit. Current usage: 111.5 MB of 1 GB physical memory

used; 2.4 GB of 2.1 GB

virtual memory used. Killing container.

Dump of the process-tree for container_1594198338753_0001_01_000002 :

解决办法：在hadoop102的/opt/module/hadoop-3.1.3/etc/hadoop/yarn-site.xml文件中增加如下配置，然后分发到hadoop103、hadoop104服务器上，并重新启动集群。

<property>

  yarn.nodemanager.pmem-check-enabled

   false

</property>



<property>

  yarn.nodemanager.vmem-check-enabled

   false

</property>