Apache Griffin安装

02/11 17:33
阅读数 305

介绍

1.原理:

从hive metadata中加载数据源
根据用户指定的数据质量检查的规则,将规则转换为Spark程序,利用Spark这种强大的计算能力,为数据质量做出检测分析。

2.程序设计模块

measure:
计算层,使用spark计算用户制定的数据质量校验规则,由scala开发。
service:
服务层,对接ui的后端接口,定时调度、向livy提交spark程序的角色。
ui:
展现层,由angular2开发

安装

一、集群基础环境

1.JDK (1.8 or later versions)

2.PostgreSQL(version 10.4) or MySQL(version 8.0.11)

3.Hadoop (2.6.0 or later)

4.Hive (version 2.x),安装参考 :https://www.cnblogs.com/caoxb/p/11333741.html

5.Spark (version 2.2.1) 安装参考: https://blog.csdn.net/k393393/article/details/92440892

6.Livy 安装参考:https://www.cnblogs.com/students/p/11400940.html

7.ElasticSearch (5.0 or later versions). 参考https://blog.csdn.net/fiery_heart/article/details/85265585

8.Scala

二、安装Grigffin

1、MySQL:

1)在MySQL中创建数据库quartz,

2)然后执行Init_quartz_mysql_innodb.sql脚本初始化表信息:

mysql -u <username> -p <password> quartz < Init_quartz_mysql_innodb.sql

2、Hadoop和Hive:

从Hadoop服务器拷贝配置文件到Livy服务器上,这里假设将配置文件放在/usr/data/conf目录下。

在Hadoop服务器上创建/home/spark_conf目录,并将Hive的配置文件hive-site.xml上传到该目录下:

#创建/home/spark_conf目录
hadoop fs -mkdir -p /home/spark_conf
#上传hive-site.xml
hadoop fs -put hive-site.xml /home/spark_conf/

3、设置环境变量:

#!/bin/bash
export JAVA_HOME=/data/jdk1.8.0_192

#spark目录 export SPARK_HOME=/usr/data/spark-2.1.1-bin-2.6.3 #livy命令目录 export LIVY_HOME=/usr/data/livy/bin #hadoop配置文件目录 export HADOOP_CONF_DIR=/usr/data/conf 

4、Livy配置:

更新livy/conf下的livy.conf配置文件:

livy.server.host = 127.0.0.1
livy.spark.master = yarn
livy.spark.deployMode = cluster
livy.repl.enable-hive-context = true

启动livy:

livy-server start

5、Elasticsearch配置:

在ES里创建griffin索引:

curl -H "Content-Type: application/json" -XPUT http://es:9200/griffin?include_type_name=true '
{
    "aliases": {},
    "mappings": {
        "accuracy": {
            "properties": {
                "name": {
                    "fields": {
                        "keyword": {
                            "ignore_above": 256,
                            "type": "keyword"
                        }
                    },
                    "type": "text"
                },
                "tmst": {
                    "type": "date"
                }
            }
        }
    },
    "settings": {
        "index": {
            "number_of_replicas": "2",
            "number_of_shards": "5"
        }
    }
}'

源码打包部署

在这里我使用源码编译打包的方式来部署Griffin,Griffin的源码地址是:https://github.com/apache/griffin.git,这里我使用的源码tag是griffin-0.4.0

 

Griffin的源码结构很清晰,主要包括griffin-doc、measure、service和ui四个模块,其中griffin-doc负责存放Griffin的文档,measure负责与spark交互,执行统计任务,service使用spring boot作为服务实现,负责给ui模块提供交互所需的restful api,保存统计任务,展示统计结果。

源码导入构建完毕后,需要修改配置文件,具体修改的配置文件如下:

1、service/src/main/resources/application.properties:

# Apache Griffin应用名称
spring.application.name=griffin_service
# MySQL数据库配置信息
spring.datasource.url=jdbc:mysql://10.xxx.xx.xxx:3306/griffin_quartz?useSSL=false
spring.datasource.username=xxxxx
spring.datasource.password=xxxxx
spring.jpa.generate-ddl=true
spring.datasource.driver-class-name=com.mysql.jdbc.Driver
spring.jpa.show-sql=true
# Hive metastore配置信息
hive.metastore.uris=thrift://namenode.test01.xxx:9083
hive.metastore.dbname=default
hive.hmshandler.retry.attempts=15
hive.hmshandler.retry.interval=2000ms
# Hive cache time
cache.evict.hive.fixedRate.in.milliseconds=900000
# Kafka schema registry,按需配置
kafka.schema.registry.url=http://namenode.test01.xxx:8081
# Update job instance state at regular intervals
jobInstance.fixedDelay.in.milliseconds=60000
# Expired time of job instance which is 7 days that is 604800000 milliseconds.Time unit only supports milliseconds
jobInstance.expired.milliseconds=604800000
# schedule predicate job every 5 minutes and repeat 12 times at most
#interval time unit s:second m:minute h:hour d:day,only support these four units
predicate.job.interval=5m
predicate.job.repeat.count=12
# external properties directory location
external.config.location=
# external BATCH or STREAMING env
external.env.location=
# login strategy ("default" or "ldap")
login.strategy=default
# ldap,登录策略为ldap时配置
ldap.url=ldap://hostname:port
ldap.email=@example.com
ldap.searchBase=DC=org,DC=example
ldap.searchPattern=(sAMAccountName={0})
# hdfs default name
fs.defaultFS=
# elasticsearch配置
elasticsearch.host=griffindq02-test1-rgtj1-tj1
elasticsearch.port=9200
elasticsearch.scheme=http
# elasticsearch.user = user
# elasticsearch.password = password
# livy配置
livy.uri=http://10.104.xxx.xxx:8998/batches
# yarn url配置
yarn.uri=http://10.104.xxx.xxx:8088
# griffin event listener
internal.event.listeners=GriffinJobEventHook

2、service/src/main/resources/quartz.properties

#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
# 
#   http://www.apache.org/licenses/LICENSE-2.0
# 
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.
#
org.quartz.scheduler.instanceName=spring-boot-quartz
org.quartz.scheduler.instanceId=AUTO
org.quartz.threadPool.threadCount=5
org.quartz.jobStore.class=org.quartz.impl.jdbcjobstore.JobStoreTX
# If you use postgresql as your database,set this property value to org.quartz.impl.jdbcjobstore.PostgreSQLDelegate
# If you use mysql as your database,set this property value to org.quartz.impl.jdbcjobstore.StdJDBCDelegate
# If you use h2 as your database, it's ok to set this property value to StdJDBCDelegate, PostgreSQLDelegate or others
org.quartz.jobStore.driverDelegateClass=org.quartz.impl.jdbcjobstore.StdJDBCDelegate
org.quartz.jobStore.useProperties=true
org.quartz.jobStore.misfireThreshold=60000
org.quartz.jobStore.tablePrefix=QRTZ_
org.quartz.jobStore.isClustered=true
org.quartz.jobStore.clusterCheckinInterval=20000

3、service/src/main/resources/sparkProperties.json:

{
  "file": "hdfs:///griffin/griffin-measure.jar",
  "className": "org.apache.griffin.measure.Application",
  "name": "griffin",
  "queue": "default",
  "numExecutors": 2,
  "executorCores": 1,
  "driverMemory": "1g",
  "executorMemory": "1g",
  "conf": {
    "spark.yarn.dist.files": "hdfs:///home/spark_conf/hive-site.xml"
  },
  "files": [
  ]
}

4、service/src/main/resources/env/env_batch.json:

{
  "spark": {
    "log.level": "INFO"
  },
  "sinks": [
    {
      "type": "CONSOLE",
      "config": {
        "max.log.lines": 10
      }
    },
    {
      "type": "HDFS",
      "config": {
        "path": "hdfs://namenodetest01.xx.xxxx.com:9001/griffin/persist",
        "max.persist.lines": 10000,
        "max.lines.per.file": 10000
      }
    },
    {
      "type": "ELASTICSEARCH",
      "config": {
        "method": "post",
        "api": "http://10.xxx.xxx.xxx:9200/griffin/accuracy",
        "connection.timeout": "1m",
        "retry": 10
      }
    }
  ],
  "griffin.checkpoint": []
}

配置文件修改好后,在idea里的terminal里执行如下maven命令进行编译打包:

mvn -Dmaven.test.skip=true clean install

命令执行完成后,会在service和measure模块的target目录下分别看到service-0.4.0.jar和measure-0.4.0.jar两个jar,将这两个jar分别拷贝到服务器目录下。这两个jar的使用方式如下:

1、使用如下命令将measure-0.4.0.jar这个jar上传到HDFS的/griffin文件目录里:

#改变jar名称
mv measure-0.4.0.jar griffin-measure.jar
mv service-0.4.0.jar griffin-service.jar #上传griffin-measure.jar到HDFS文件目录里 hadoop fs -put measure-0.4.0.jar /griffin/

这样做的目的主要是因为spark在yarn集群上执行任务时,需要到HDFS的/griffin目录下加载griffin-measure.jar,避免发生类org.apache.griffin.measure.Application找不到的错误。

2、运行service-0.4.0.jar,启动Griffin管理后台:

nohup java -jar service-0.4.0.jar>service.out 2>&1 &

几秒钟后,我们可以访问Apache Griffin的默认UI(默认情况下,spring boot的端口是8080)。

http://IP:8080

基于Apache Griffin Kafka源数据计算

http://griffin.apache.org/docs/usecases.html

实时数据检测目前未有界面配置,可以通过api的方式提交实时数据监控

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