Quick Start

Apache Griffin 入门指南

数据质量模块是大数据平台中必不可少的一个功能组件,Apache Griffin(以下简称Griffin)是一个开源的大数据数据质量解决方案,它支持批处理和流模式两种数据质量检测方式,可以从不同维度(比如离线任务执行完毕后检查源端和目标端的数据数量是否一致、源表的数据空值数量等)度量数据资产,从而提升数据的准确度、可信度。

在Griffin的架构中,主要分为Define、Measure和Analyze三个部分,如下图所示:

arch

各部分的职责如下:

  • Define:主要负责定义数据质量统计的维度,比如数据质量统计的时间跨度、统计的目标(源端和目标端的数据数量是否一致,数据源里某一字段的非空的数量、不重复值的数量、最大值、最小值、top5的值数量等)
  • Measure:主要负责执行统计任务,生成统计结果
  • Analyze:主要负责保存与展示统计结果

基于以上功能,我们大数据平台计划引入Griffin作为数据质量解决方案,实现数据一致性检查、空值统计等功能。以下是安装步骤总结:

安装部署

依赖准备

  • JDK (1.8 or later versions)
  • MySQL(version 5.6及以上)
  • Hadoop (2.6.0 or later)
  • Hive (version 2.x)
  • Spark (version 2.2.1)
  • Livy(livy-0.5.0-incubating)
  • ElasticSearch (5.0 or later versions)

初始化

初始化操作具体请参考Apache Griffin Deployment Guide,由于我的测试环境中Hadoop集群、Hive集群已搭好,故这里省略Hadoop、Hive安装步骤,只保留拷贝配置文件、配置Hadoop配置文件目录步骤。

1、MySQL:

在MySQL中创建数据库quartz,然后执行Init_quartz_mysql_innodb.sql脚本初始化表信息:

mysql -u <username> -p <password> < 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 -XPUT http://es:9200/griffin -d '
{
    "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,下载完成在idea中导入并展开源码的结构图如下:

project

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://10.104.20.126:3306/griffin_quartz?useSSL=false
spring.datasource.username=xnuser
spring.datasource.password=Xn20!@n0oLk
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://namenodetest01.bi: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://namenodetest01.bi: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://10.104.110.116:8998/batches
# yarn url配置
yarn.uri=http://10.104.110.116:8088
# 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.bi.10101111.com:9001/griffin/persist",
        "max.persist.lines": 10000,
        "max.lines.per.file": 10000
      }
    },
    {
      "type": "ELASTICSEARCH",
      "config": {
        "method": "post",
        "api": "http://10.104.110.119:9200/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
#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

UI操作文档链接:Apache Griffin User Guide。通过UI操作界面,我们可以创建自己的统计任务,部分结果展示界面如下:

dashboard

功能体验

1、在hive里创建表demo_src和demo_tgt:

--create hive tables here. hql script
--Note: replace hdfs location with your own path
CREATE EXTERNAL TABLE `demo_src`(
  `id` bigint,
  `age` int,
  `desc` string) 
PARTITIONED BY (
  `dt` string,
  `hour` string)
ROW FORMAT DELIMITED
  FIELDS TERMINATED BY '|'
LOCATION
  'hdfs:///griffin/data/batch/demo_src';

--Note: replace hdfs location with your own path
CREATE EXTERNAL TABLE `demo_tgt`(
  `id` bigint,
  `age` int,
  `desc` string) 
PARTITIONED BY (
  `dt` string,
  `hour` string)
ROW FORMAT DELIMITED
  FIELDS TERMINATED BY '|'
LOCATION
  'hdfs:///griffin/data/batch/demo_tgt';

2、生成测试数据:

http://griffin.apache.org/data/batch/地址下载所有文件到Hadoop服务器上,然后使用如下命令执行gen-hive-data.sh脚本:

nohup ./gen-hive-data.sh>gen.out 2>&1 &

注意观察gen.out日志文件,如果有错误,视情况进行调整。这里我的测试环境Hadoop和Hive安装在同一台服务器上,因此直接运行脚本。

3、通过UI界面创建统计任务,具体按照Apache Griffin User Guide 一步步操作。

踩坑过程

1、gen-hive-data.sh脚本生成数据失败,报no such file or directory错误。

错误原因:HDFS中的/griffin/data/batch/demo_src/和/griffin/data/batch/demo_tgt/目录下”dt=时间”目录不存在,如dt=20190113。

解决办法:给脚本中增加hadoop fs -mkdir创建目录操作,修改完后如下:

#!/bin/bash

#create table
hive -f create-table.hql
echo "create table done"

#current hour
sudo ./gen_demo_data.sh
cur_date=`date +%Y%m%d%H`
dt=${cur_date:0:8}
hour=${cur_date:8:2}
partition_date="dt='$dt',hour='$hour'"
sed s/PARTITION_DATE/$partition_date/ ./insert-data.hql.template > insert-data.hql
hive -f insert-data.hql
src_done_path=/griffin/data/batch/demo_src/dt=${dt}/hour=${hour}/_DONE
tgt_done_path=/griffin/data/batch/demo_tgt/dt=${dt}/hour=${hour}/_DONE
hadoop fs -mkdir -p /griffin/data/batch/demo_src/dt=${dt}/hour=${hour}
hadoop fs -mkdir -p /griffin/data/batch/demo_tgt/dt=${dt}/hour=${hour}
hadoop fs -touchz ${src_done_path}
hadoop fs -touchz ${tgt_done_path}
echo "insert data [$partition_date] done"

#last hour
sudo ./gen_demo_data.sh
cur_date=`date -d '1 hour ago' +%Y%m%d%H`
dt=${cur_date:0:8}
hour=${cur_date:8:2}
partition_date="dt='$dt',hour='$hour'"
sed s/PARTITION_DATE/$partition_date/ ./insert-data.hql.template > insert-data.hql
hive -f insert-data.hql
src_done_path=/griffin/data/batch/demo_src/dt=${dt}/hour=${hour}/_DONE
tgt_done_path=/griffin/data/batch/demo_tgt/dt=${dt}/hour=${hour}/_DONE
hadoop fs -mkdir -p /griffin/data/batch/demo_src/dt=${dt}/hour=${hour}
hadoop fs -mkdir -p /griffin/data/batch/demo_tgt/dt=${dt}/hour=${hour}
hadoop fs -touchz ${src_done_path}
hadoop fs -touchz ${tgt_done_path}
echo "insert data [$partition_date] done"

#next hours
set +e
while true
do
  sudo ./gen_demo_data.sh
  cur_date=`date +%Y%m%d%H`
  next_date=`date -d "+1hour" '+%Y%m%d%H'`
  dt=${next_date:0:8}
  hour=${next_date:8:2}
  partition_date="dt='$dt',hour='$hour'"
  sed s/PARTITION_DATE/$partition_date/ ./insert-data.hql.template > insert-data.hql
  hive -f insert-data.hql
  src_done_path=/griffin/data/batch/demo_src/dt=${dt}/hour=${hour}/_DONE
  tgt_done_path=/griffin/data/batch/demo_tgt/dt=${dt}/hour=${hour}/_DONE
  hadoop fs -mkdir -p /griffin/data/batch/demo_src/dt=${dt}/hour=${hour}
  hadoop fs -mkdir -p /griffin/data/batch/demo_tgt/dt=${dt}/hour=${hour}
  hadoop fs -touchz ${src_done_path}
  hadoop fs -touchz ${tgt_done_path}
  echo "insert data [$partition_date] done"
  sleep 3600
done
set -e

2、HDFS的/griffin/persist目录下没有统计结果文件,检查该目录的权限,设置合适的权限即可。

3、ES中的metric数据为空,有两种可能:

  • service/src/main/resources/env/env_batch.json里的ES配置信息不正确
  • 执行spark任务的yarn服务器上没有配置ES服务器的hostname,连接异常

4、启动service-0.4.0.jar之后,访问不到UI界面,查看启动日志无异常。检查打包时是不是执行的mvn package命令,将该命令替换成mvn -Dmaven.test.skip=true clean install命令重新打包启动即可。

Apache Griffin is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
Copyright © 2018 The Apache Software Foundation, Licensed under the Apache License, Version 2.0.
Apache Griffin, Griffin, Apache, the Apache feather logo and the Apache Griffin logo are trademarks of The Apache Software Foundation.