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DataX全量和增量mysqltomysql

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全量mysqltomysql

进入目录编写json

cd /usr/local/datax/job
vi zabbixmysql2mysql.json

写入的表结构要和reader的表结构一样,先建立好
编写json文件

{
    "job": {
        "content": [
            {
                "reader": {
                    "name": "mysqlreader",
                    "parameter": {
                        "username": "test",
                        "password": "123",
                        "column": [
                            "itemid",
                            "clock",
                            "timestamp",
                            "source",
                            "severity",
                            "value",
                            "logeventid",
                            "ns" 
                        ],
                        "splitPk": "itemid",
                        "connection": [
                            {
                                "table": [
                                    "history_log"
                                ],
                                "jdbcUrl": [
                                    "jdbc:mysql://172.16.3.89:3306/zabbix"
                                ]
                            }
                        ]
                    }
                },
                "writer": {
                    "name": "mysqlwriter",
                    "parameter": {
                        "writeMode": "insert",
                        "username": "test",
                        "password": "123",
                        "column": [
                            "itemid",
                            "clock",
                            "timestamp",
                            "source",
                            "severity",
                            "value",
                            "logeventid",
                            "ns"    
                        ],
                        "preSql": [
                            "truncate history_log_copy1"
                        ], 
                        "connection": [
                            {
                                "jdbcUrl": "jdbc:mysql://172.16.3.89:3306/chenzhenhua2?useUnicode=true&characterEncoding=utf8",
                                "table": [
                                    "history_log_copy1"
                                ]
                            }
                        ]
                    }
                }
            }
        ],
        "setting": {
            "speed": {
                "channel": 6
            }
        }
    }
}

注意:“writeMode”: “insert”,也可以为update,update更加稳妥一点
“preSql”: [ “truncate history_log_copy1” ], 在写入前提前清空表清空表

如果写入的数据库为mysql8以上版本,必须修改mysql-connector-java的插件

cd /usr/local/datax/plugin/writer/mysqlwriter/libs
mv mysql-connector-java-5.1.34.jar mysql-connector-java-5.1.34.jar-bak

我这边上传的为mysql-connector-java-8.0.16.jar,下载地址https://static.runoob.com/download/mysql-connector-java-8.0.16.jar

增量同步

Datax需要解决的另一个难题在于增量更新。

首先需要说明, Datax本身在大部分reader插件中提供了where配置项,用于做增量更新。例如mysqlerader md文件说明如下:

* **where**

	* 描述:筛选条件,MysqlReader根据指定的column、table、where条件拼接SQL,并根据这个SQL进行数据抽取。在实际业务场景中,往往会选择当天的数据进行同步,可以将where条件指定为gmt_create > $bizdate 。注意:不可以将where条件指定为limit 10,limit不是SQL的合法where子句。<br />

          where条件可以有效地进行业务增量同步。如果不填写where语句,包括不提供where的key或者value,DataX均视作同步全量数据。

	* 必选:否 <br />

	* 默认值:无 <br />

* **querySql**

	* 描述:在有些业务场景下,where这一配置项不足以描述所筛选的条件,用户可以通过该配置型来自定义筛选SQL。当用户配置了这一项之后,DataX系统就会忽略table,column这些配置型,直接使用这个配置项的内容对数据进行筛选,例如需要进行多表join后同步数据,使用select a,b from table_a join table_b on table_a.id = table_b.id <br />

	 `当用户配置querySql时,MysqlReader直接忽略table、column、where条件的配置`,querySql优先级大于table、column、where选项。

	* 必选:否 <br />

	* 默认值:无 <br />

示例:
新建json

vi  new.json
{
    "job": {
        "content": [
            {
                "reader": {
                    "name": "mysqlreader",
                    "parameter": {
                        "username": "root",
                        "password": "123",
                        "where": "created_at > FROM_UNIXTIME(${create_time}) and created_at  < FROM_UNIXTIME(${end_time})",
                        "column": [
                            "id",
                            "rpt_date",
                            "rpt_hour",
                            "unit_id",
                            "build_id",
                            "num",
                            "run_state",
                            "created_at"
                        ],
                        "splitPk": "id",
                        "connection": [
                            {
                                "table": [
                                    "rpt_warning_hour"
                                ],
                                "jdbcUrl": [
                                    "jdbc:mysql://172.16.5.11:3306/smart_fire"
                                ]
                            }
                        ]
                    }
                },
                "writer": {
                    "name": "mysqlwriter",
                    "parameter": {
                        "writeMode": "update",
                        "username": "test",
                        "password": "123",
                        "column": [
                            "id",
                            "rpt_date",
                            "rpt_hour",
                            "unit_id",
                            "build_id",
                            "num",
                            "run_state",
                            "created_at"
                        ],
                        "connection": [
                            {
                                "jdbcUrl": "jdbc:mysql://172.16.3.89:3306/chenzhenhua2?useUnicode=true&characterEncoding=utf8",
                                "table": [
                                    "rpt_warning_hour"
                                ]
                            }
                        ]
                    }
                }
            }
        ],
        "setting": {
            "speed": {
                "channel": 6
            }
        }
    }
}

上面需要注意的事情为FROM_UNIXTIME将表里面的时间格式转换为时间戳格式,如果表里默认为时间戳不需要转换。
${…}就是将变量传入,上次更新{create_time}上次更新时间,{end_time}为现在本地时间。

然后再编写一个python脚本可以将参数传入json即可,vi dataxScheduler.py

import time,os,sys

print "going to execute"

configFilePath = sys.argv[1]
logFilePath = sys.argv[2]
lastTimeExecuteRecord = sys.argv[3]
lastExecuteTime=""

try:
    fo = open(lastTimeExecuteRecord, "r")
    lastExecuteTime = fo.read()
    print lastExecuteTime
except IOError:
    lastExecuteTime = int(1)
lastExecuteTime = int(lastExecuteTime)

print("last time execute time:  " + str(lastExecuteTime))

currentTime = int(time.time())
print("currentTime is        :"+ str(currentTime))


#os.system("python /usr/local/datax/bin/datax.py " + configFilePath + " --lastTime" +  lastExecuteTime + " --currentTime" + currentTime + " >> " + logFilePath)

script2execute  = "python /usr/local/datax/bin/datax.py %s -p \"-Dcreate_time=%s -Dend_time=%s\" >> %s"%(configFilePath,lastExecuteTime,currentTime,logFilePath)
print("to be excute script:"+script2execute)
os.system(script2execute)

print("script execute ending")

# update timestamp to file
fo = open(lastTimeExecuteRecord, "w+")
fo.write(str(currentTime))
fo.close()

print("ending---",lastTimeExecuteRecord)

运行

python /usr/local/datax/job/dataxScheduler.py  '/usr/local/datax/job/new.json'  '/usr/local/datax/job/test_job.log'   '/usr/local/datax/job/test_job.record'

测试,增加数据后再次运行,数据对应增加了,加入到定时任务执行即可完成增量同步。
但这个写脚本的方式还是非常笨拙的,下一篇介绍的datax-web会更好的去解决增量同步的问题。

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