注:将整个项目的数据处理过程,从数据采集到数据分析,再到结果数据的导出,一系列的任务分割成若干个oozie的工作流,并用coordinator进行协调。
1、工作流定义示例
Ooize配置片段示例。
1.1、日志预处理mr程序工作流定义
<workflow-app name="weblogpreprocess" xmlns="uri:oozie:workflow:0.4"> <start to="firstjob"/> <action name="firstjob"> <map-reduce> <job-tracker>${jobTracker}</job-tracker> <name-node>${nameNode}</name-node> <prepare> <delete path="${nameNode}/${outpath}"/> </prepare> <configuration> <property> <name>mapreduce.job.map.class</name> <value>com.learn.bigdata.hive.mr.WeblogPreProcess$WeblogPreProcessMapper</value> </property>
<property> <name>mapreduce.job.output.key.class</name> <value>org.apache.hadoop.io.Text</value> </property> <property> <name>mapreduce.job.output.value.class</name> <value>org.apache.hadoop.io.NullWritable</value> </property>
<property> <name>mapreduce.input.fileinputformat.inputdir</name> <value>${inpath}</value> </property> <property> <name>mapreduce.output.fileoutputformat.outputdir</name> <value>${outpath}</value> </property> <property> <name>mapred.mapper.new-api</name> <value>true</value> </property> <property> <name>mapred.reducer.new-api</name> <value>true</value> </property>
</configuration> </map-reduce> <ok to="end"/> <error to="kill"/> |
1.2、数据加载etl工作流定义:
<workflow-app xmlns="uri:oozie:workflow:0.5" name="hive2-wf"> <start to="hive2-node"/>
<action name="hive2-node"> <hive2 xmlns="uri:oozie:hive2-action:0.1"> <job-tracker>${jobTracker}</job-tracker> <name-node>${nameNode}</name-node> <configuration> <property> <name>mapred.job.queue.name</name> <value>${queueName}</value> </property> </configuration> <jdbc-url>jdbc:hive2://hdp-node-01:10000</jdbc-url> <script>script.q</script> <param>input=/weblog/outpre2</param> </hive2> <ok to="end"/> <error to="fail"/> </action>
<kill name="fail"> <message>Hive2 (Beeline) action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message> </kill> <end name="end"/> </workflow-app> |
1.3、数据加载工作流所用hive脚本:
create database if not exists dw_weblog;
use dw_weblog;
drop table if exists t_orgin_weblog;
create table t_orgin_weblog(valid string,remote_addr string,
remote_user string,
time_local string,
request string,
status string,
body_bytes_sent string,
http_referer string,
http_user_agent string)
row format delimited
fields terminated by '\001';
load data inpath '/weblog/preout' overwrite into table t_orgin_weblog;
drop table if exists t_ods_detail_tmp_referurl;
create table t_ods_detail_tmp_referurl as
SELECT a.*,b.*
FROM t_orgin_weblog a
LATERAL VIEW parse_url_tuple(regexp_replace(http_referer, "\"", ""), 'HOST', 'PATH','QUERY', 'QUERY:id') b as host, path, query, query_id;
drop table if exists t_ods_detail;
create table t_ods_detail as
select b.*,substring(time_local,0,11) as daystr,
substring(time_local,13) as tmstr,
substring(time_local,4,3) as month,
substring(time_local,0,2) as day,
substring(time_local,13,2) as hour
from t_ods_detail_tmp_referurl b;
drop table t_ods_detail_prt;
create table t_ods_detail_prt(
valid string,
remote_addr string,
remote_user string,
time_local string,
request string,
status string,
body_bytes_sent string,
http_referer string,
http_user_agent string,
host string,
path string,
query string,
query_id string,
daystr string,
tmstr string,
month string,
day string,
hour string)
partitioned by (mm string,dd string);
insert into table t_ods_detail_prt partition(mm='Sep',dd='18')
select * from t_ods_detail where daystr='18/Sep/2013';
insert into table t_ods_detail_prt partition(mm='Sep',dd='19')
select * from t_ods_detail where daystr='19/Sep/2013';
2、工作流单元测试
2.1、工作流定义配置上传
[hadoop@hdp-node-01 wf-oozie]$ hadoop fs -put hive2-etl /user/hadoop/oozie/myapps/
[hadoop@hdp-node-01 wf-oozie]$ hadoop fs -put hive2-dw /user/hadoop/oozie/myapps/
[hadoop@hdp-node-01 wf-oozie]$ ll
total 12
drwxrwxr-x. 2 hadoop hadoop 4096 Nov 23 16:32 hive2-dw
drwxrwxr-x. 2 hadoop hadoop 4096 Nov 23 16:32 hive2-etl
drwxrwxr-x. 3 hadoop hadoop 4096 Nov 23 11:24 weblog
[hadoop@hdp-node-01 wf-oozie]$ export OOZIE_URL=http://localhost:11000/oozie
2.2、工作流单元提交启动
oozie job -D inpath=/weblog/input -D outpath=/weblog/outpre -config weblog/job.properties -run
启动etl的hive工作流
oozie job -config hive2-etl/job.properties -run
启动pvs统计的hive工作流
oozie job -config hive2-dw/job.properties -run
2.3、工作流coordinator配置(片段)
多个工作流job用coordinator组织协调:
[hadoop@hdp-node-01 hive2-etl]$ ll
total 28
-rw-rw-r--. 1 hadoop hadoop 265 Nov 13 16:39 config-default.xml
-rw-rw-r--. 1 hadoop hadoop 512 Nov 26 16:43 coordinator.xml
-rw-rw-r--. 1 hadoop hadoop 382 Nov 26 16:49 job.properties
drwxrwxr-x. 2 hadoop hadoop 4096 Nov 27 11:26 lib
-rw-rw-r--. 1 hadoop hadoop 1910 Nov 23 17:49 script.q
-rw-rw-r--. 1 hadoop hadoop 687 Nov 23 16:32 workflow.xml
- config-default.xml
<configuration>
<property>
<name>jobTracker</name>
<value>hdp-node-01:8032</value>
</property>
<property>
<name>nameNode</name>
<value>hdfs://hdp-node-01:9000</value>
</property>
<property>
<name>queueName</name>
<value>default</value>
</property>
</configuration>
- job.properties
user.name=hadoop
oozie.use.system.libpath=true
oozie.libpath=hdfs://hdp-node-01:9000/user/hadoop/share/lib
oozie.wf.application.path=hdfs://hdp-node-01:9000/user/hadoop/oozie/myapps/hive2-etl/
- workflow.xml
<workflow-app xmlns="uri:oozie:workflow:0.5" name="hive2-wf">
<start to="hive2-node"/>
<action name="hive2-node">
<hive2 xmlns="uri:oozie:hive2-action:0.1">
<job-tracker>${jobTracker}</job-tracker>
<name-node>${nameNode}</name-node>
<configuration>
<property>
<name>mapred.job.queue.name</name>
<value>${queueName}</value>
</property>
</configuration>
<jdbc-url>jdbc:hive2://hdp-node-01:10000</jdbc-url>
<script>script.q</script>
<param>input=/weblog/outpre2</param>
</hive2>
<ok to="end"/>
<error to="fail"/>
</action>
<kill name="fail">
<message>Hive2 (Beeline) action failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
</kill>
<end name="end"/>
</workflow-app>
- coordinator.xml
<coordinator-app name="cron-coord" frequency="${coord:minutes(5)}" start="${start}" end="${end}" timezone="Asia/Shanghai" xmlns="uri:oozie:coordinator:0.2">
<action>
<workflow>
<app-path>${workflowAppUri}</app-path>
<configuration>
<property>
<name>jobTracker</name>
<value>${jobTracker}</value>
</property>
<property>
<name>nameNode</name>
<value>${nameNode}</value>
</property>
<property>
<name>queueName</name>
<value>${queueName}</value>
</property>
</configuration>
</workflow>
</action>
</coordinator-app>