1.下载tez的依赖包:http://tez.apache.org
apache-tez-0.9.1-bin.tar.gz
2.上传tez的tar包到linux
3.将apache-tez-0.9.1-bin.tar.gz上传到HDFS的/tez目录下
hadoop fs -mkdir /tez
hadoop fs -put /opt/software/apache-tez-0.9.1-bin.tar.gz/ /tez
4.解压缩apache-tez-0.9.1-bin.tar.gz
tar -zxvf apache-tez-0.9.1-bin.tar.gz -C /opt
5.修改名称
mv apache-tez-0.9.1-bin/ tez-0.9.1
6.进入到Hive的配置目录:/opt/hive-2.3.7/conf
cd /opt/hive-2.3.7/conf
pwd
/opt/hive-2.3.7/conf
7.在Hive的/opt/hive-2.3.7/conf下面创建一个tez-site.xml文件
vim tez-site.xml
添加如下内容
tez.lib.uris
${fs.defaultFS}/tez/apache-tez-0.9.1-bin.tar.gz
tez.use.cluster.hadoop-libs
true
tez.history.logging.service.class
org.apache.tez.dag.history.logging.ats.ATSHistoryLoggingService
8.在hive-env.sh文件中添加tez环境变量配置和依赖包环境变量配置
vim hive-env.sh
添加如下配置
# Folder containing extra libraries required for hive compilation/execution can be controlled by:
export TEZ_HOME=/opt/tez-0.9.1 #是你的tez的解压目录
export TEZ_JARS=""
for jar in `ls $TEZ_HOME |grep jar`; do
export TEZ_JARS=$TEZ_JARS:$TEZ_HOME/$jar
done
for jar in `ls $TEZ_HOME/lib`;
do
export TEZ_JARS=$TEZ_JARS:$TEZ_HOME/lib/$jar
done
export HIVE_AUX_JARS_PATH=/opt/hadoop-2.7.2/share/hadoop/common/hadoop-lzo-0.4.20.jar$TEZ_JARS
9.在hive-site.xml文件中添加如下配置,更改hive计算引擎
hive.metastore.schema.verification
false
hive.execution.engine
tez
10.测试
启动Hive
bin/hive
创建表
create table student(id int,name string);
向表中插入数据
insert into student values(1,"zhangsan");
如果没有报错就表示成功了
select * from student;
1 zhangsan
运行Tez时检查到用过多内存而被NodeManager杀死进程问题:
Caused by: org.apache.tez.dag.api.SessionNotRunning: TezSession has already shutdown. Application application_1546781144082_0005 failed 2 times due to AM Container for appattempt_1546781144082_0005_000002 exited with exitCode: -103For more detailed output, check application tracking page:http://hadoop103:8088/cluster/app/application_1546781144082_0005Then, click on links to logs of each attempt.Diagnostics: Container [pid=11116,containerID=container_1546781144082_0005_02_000001] is running beyond virtual memory limits. Current usage: 216.3 MB of 1 GB physical memory used; 2.6 GB of 2.1 GB virtual memory used. Killing container. |
这种问题是从机上运行的Container试图使用过多的内存,而被NodeManager kill掉了
[摘录] The NodeManager is killing your container. It sounds like you are trying to use hadoop streaming which is running as a child process of the map-reduce task. The NodeManager monitors the entire process tree of the task and if it eats up more memory than the maximum set in mapreduce.map.memory.mb or mapreduce.reduce.memory.mb respectively, we would expect the Nodemanager to kill the task, otherwise your task is stealing memory belonging to other containers, which you don’t want. |
解决方法:
关掉虚拟内存检查,修改yarn-site.xml
yarn.nodemanager.vmem-check-enabled
false
修改后一定要分发,并重新启动hadoop集群
rsync -r yarn-site.xml node2:`pwd`