数据传输|dtle使用初探

  • Z时代
  • 2024-01-10
  • 分类：综合

database

作者：马莹乐

爱可生研发团队成员，负责 mysql 中间件和数据库管理平台的测试。擅长找茬（测试技术爱好者），欢迎大家试用 dtle~

本文来源：原创投稿

*爱可生开源社区出品，原创内容未经授权不得随意使用，转载请联系小编并注明来源。

dtle 是一款爱可生 MySQL 开源数据传输中间件，此文简要介绍初步使用方法。

项目地址：https://github.com/actiontech/dtle

一、下载安装

环境说明：

  • 准备三台主机，主机名分别为：node4、node5、node6

  • 三台均为 agent，另将 node4 和 node5 作为 manager

1.1 下载

下载 dtle 最新的 release rpm 包

地址：https://github.com/actiontech/dtle/releases

dtle 安装包下载：

wget https://github.com/actiontech/dtle/releases/download/v2.19.11.0/dtle-2.19.11.0.x86_64.rpm

1.2 安装

安装步骤

https://actiontech.github.io/dtle-docs-cn/4/4.0_installation.html

分别将 node4，node5 和 node6 的 dtle 安装完成。

1.3 启动 dtle

dtle 安装完成后，并未启动，需要先配置 dtle 的 conf 文件，再启动。

1.4 配置 dtle.conf

配置相关说明

https://actiontech.github.io/dtle-docs-cn/4/4.1_node_configuration.html

dtle.conf 准备：以下配置文件替分别替换原有 dtle.conf（/opt/dtle/etc/dtle/dtle.conf）

node4 的 dtle.conf

# Setup data dir
data_dir = "/opt/dtle/data"
log_level = "DEBUG"
log_file = "/opt/dtle.log"
#log_to_stdout = true
bind_addr = "172.100.9.4"
# Modify our port to avoid a collision with server
ports {
    http = 8190
}
# Enable the manager
manager {
    enabled = true
    # Self-elect, should be 3 or 5 for production,
    # Addresses to attempt to join when the server starts.
    join = [ "172.100.9.4","172.100.9.5" ]
}
# Enable the agent
agent {
    enabled = true
    managers = ["172.100.9.4:8191","172.100.9.5:8191"]
}
metric{
   collection_interval = "15s"
   publish_allocation_metrics = "true"
   publish_node_metrics = "true"
}
addresses {
    http = "172.100.9.4"
    rpc = "172.100.9.4"
    serf = "172.100.9.4"
}
advertise {
    http = "172.100.9.4"
    rpc = "172.100.9.4"
    serf = "172.100.9.4"
}

node5 的 dtle.conf

# Setup data dir
data_dir = "/opt/dtle/data"
log_level = "DEBUG"
log_file = "/opt/dtle.log"
#log_to_stdout = true
bind_addr = "172.100.9.5"
# Modify our port to avoid a collision with server
ports {
    http = 8190
}
# Enable the manager
manager {
    enabled = true
    # Self-elect, should be 3 or 5 for production,
    # Addresses to attempt to join when the server starts.
    join = [ "172.100.9.4","172.100.9.5" ]
}
# Enable the agent
agent {
    enabled = true
    managers = ["172.100.9.4:8191","172.100.9.5:8191"]
}
metric{
   collection_interval = "15s"
   publish_allocation_metrics = "true"
   publish_node_metrics = "true"
}
addresses {
    http = "172.100.9.5"
    rpc = "172.100.9.5"
    serf = "172.100.9.5"
}
advertise {
    http = "172.100.9.5"
    rpc = "172.100.9.5"
    serf = "172.100.9.5"
}

node6 的 dtle.conf

# Setup data dir
data_dir = "/opt/dtle/data"
log_level = "DEBUG"
log_file = "/opt/dtle.log"
#log_to_stdout = true
bind_addr = "172.100.9.6"
# Modify our port to avoid a collision with server
ports {
    http = 8190
}
# Enable the manager
manager {
    enabled = false
    # Self-elect, should be 3 or 5 for production,
    # Addresses to attempt to join when the server starts.
    join = [ "172.100.9.4","172.100.9.5" ]
}
# Enable the agent
agent {
    enabled = true
    managers = ["172.100.9.4:8191","172.100.9.5:8191"]
}
metric{
   collection_interval = "15s"
   publish_allocation_metrics = "true"
   publish_node_metrics = "true"
}
addresses {
    http = "172.100.9.6"
    rpc = "172.100.9.6"
    serf = "172.100.9.6"
}
advertise {
    http = "172.100.9.6"
    rpc = "172.100.9.6"
    serf = "172.100.9.6"
}

1.5 启动 dtle

启动命令说明

https://actiontech.github.io/dtle-docs-cn/4/4.2_command.html

1.6 查看 3 个节点 dtle 进程

node 4

node 5

node 6

1.7 尝试查看 dtle 架构是否符合预期

命令说明

https://actiontech.github.io/dtle-docs-cn/4/4.2_command.html

其中，members 展示的是集群中 manager 节点的信息

HTTP API

https://actiontech.github.io/dtle-docs-cn/4/4.4_http_api.html

输出内容为 json 格式，可以安装 jq，使之格式化展示。

二、源端/目标端准备

MySQL 迁移用户准备

2.1 创建用户

源端用户创建

目标端用户创建

有关源端/目标端用户的最小权限说明

https://actiontech.github.io/dtle-docs-cn/4/4.5_mysql_user_privileges.html

2.2 数据准备

源端数据准备

目标端测试前库表情况

2.3 创建 job

创建全量 + 增量，表级别迁移 job，分别使用 node5 和 node6 节点的 dtle 作为源端和目标端迁移的 agent

job 配置相关参数

https://actiontech.github.io/dtle-docs-cn/4/4.3_job_configuration.html

2.3.1 准备 job.json

job.json

{
    "Name":"have_a_try",
    "Failover":false,
    "Orders":[],
    "Type":"synchronous",
    "Tasks":[
        {
            "Type":"Src",
            "NodeId":"ee97dc49-85ed-febc-4d3c-cfbfa87f46bd",
            "Config":{
                "Gtid":"",
                "DropTableIfExists":false,
                "SkipCreateDbTable":false,
                "ApproveHeterogeneous":true,
                "ReplChanBufferSize":"600",
                "ChunkSize":"2000",
                "ExpandSyntaxSupport":false,
                "MsgBytesLimit":"20480",
                "MsgsLimit":"65536",
                "BytesLimit":"67108864",
                "GroupMaxSize":"1",
                "GroupTimeout":"100",
                "SqlFilter":[],
                "ReplicateDoDb":[
                    {
                        "TableSchema":"test",
                        "Tables":[
                            {
                                "TableName":"test1"
                            }
                        ]
                    }
                ],
                "ConnectionConfig":{
                    "Host":"172.100.9.1",
                    "Port":"3306",
                    "User":"src_test",
                    "Password":"test"
                }
            }
        },
        {
            "Type":"Dest",
            "NodeId":"e623aedd-5c37-da67-4ddf-1a82ce1ac298",
            "Config":{
                "ParallelWorkers":"1",
                "ConnectionConfig":{
                    "Host":"172.100.9.2",
                    "Port":"3306",
                    "User":"dest_test",
                    "Password":"test"
                }
            }
        }
    ]
}

其中 NodeId 可通过命令或者 HTTP API 查询得知。

2.3.2 创建job

创建 job 试用 HTTP API

https://actiontech.github.io/dtle-docs-cn/4/4.4_http_api.html

创建完成后查询 job 状态为 running

job 详细信息可使用 HTTP API 查询，示例

[
    {
        "CreateIndex":109,
        "ID":"ba13f3e1-0630-f141-4c60-a1f36c61cdb3",
        "JobModifyIndex":2372,
        "JobSummary":{
            "Constraints":null,
            "CreateIndex":109,
            "Datacenters":[
                "dc1"
            ],
            "EnforceIndex":false,
            "Failover":false,
            "ID":"ba13f3e1-0630-f141-4c60-a1f36c61cdb3",
            "JobModifyIndex":2372,
            "ModifyIndex":2372,
            "Name":"have_a_try",
            "Orders":[
            ],
            "Region":"global",
            "Status":"running",
            "StatusDescription":"",
            "Tasks":[
                {
                    "Config":{
                        "GroupMaxSize":"1",
                        "ChunkSize":"2000",
                        "BinlogFile":"1.000002",
                        "MsgsLimit":"65536",
                        "GroupTimeout":"100",
                        "DropTableIfExists":false,
                        "ExpandSyntaxSupport":false,
                        "BytesLimit":"67108864",
                        "MsgBytesLimit":"20480",
                        "ReplChanBufferSize":"600",
                        "NatsAddr":"172.100.9.6:8193",
                        "ApproveHeterogeneous":true,
                        "SqlFilter":[
                        ],
                        "BinlogPos":4261,
                        "ConnectionConfig":{
                            "Host":"172.100.9.1",
                            "Port":"3306",
                            "User":"src_test",
                            "Password":"*"
                        },
                        "TrafficAgainstLimits":0,
                        "Gtid":"8868d98f-af5e-11e8-9aa9-0242ac110002:1-16",
                        "ReplicateDoDb":[
                            {
                                "TableSchema":"test",
                                "Tables":[
                                    {
                                        "TableName":"test1"
                                    }
                                ]
                            }
                        ],
                        "SkipCreateDbTable":false
                    },
                    "ConfigLock":{
                    },
                    "Constraints":null,
                    "Driver":"MySQL",
                    "Leader":false,
                    "NodeID":"ee97dc49-85ed-febc-4d3c-cfbfa87f46bd",
                    "NodeName":"",
                    "Type":"Src"
                },
                {
                    "Config":{
                        "BinlogFile":"1.000002",
                        "BinlogPos":4261,
                        "ConnectionConfig":{
                            "Host":"172.100.9.2",
                            "Port":"3306",
                            "User":"dest_test",
                            "Password":"*"
                        },
                        "Gtid":"8868d98f-af5e-11e8-9aa9-0242ac110002:1-16",
                        "ParallelWorkers":"1",
                        "NatsAddr":"172.100.9.6:8193"
                    },
                    "ConfigLock":{
                    },
                    "Constraints":null,
                    "Driver":"MySQL",
                    "Leader":true,
                    "NodeID":"e623aedd-5c37-da67-4ddf-1a82ce1ac298",
                    "NodeName":"",
                    "Type":"Dest"
                }
            ],
            "Type":"synchronous"
        },
        "ModifyIndex":2372,
        "Name":"have_a_try",
        "Status":"running",
        "StatusDescription":"",
        "Type":"synchronous"
    }
]

2.4 查询目标端迁移情况

目标端迁移前后对比：

新增两个库其中 test 库是我们 job 迁移的结果。

dtle 库相关说明

https://actiontech.github.io/dtle-docs-cn/3/3.3_impact_on_dest.html

2.5 在源端执行普通 DML 操作

2.6 在源端执行普通 DDL 操作

小结

更多用法，详见项目文档，欢迎试用~

https://actiontech.github.io/dtle-docs-cn/

以上是 数据传输|dtle使用初探 的全部内容， 来源链接： utcz.com/z/532908.html

回到顶部