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pycanal
一.pycanal 简介
pycanal 是阿里巴巴开源项目 Canal是阿里巴巴mysql数据库binlog的增量订阅&消费组件 的 python 客户端。为 python 开发者提供一个更友好的使用 Canal 的方式。Canal 是mysql数据库binlog的增量订阅&消费组件。
基于日志增量订阅&消费支持的业务:
- 数据库镜像
- 数据库实时备份
- 多级索引 (卖家和买家各自分库索引)
- search build
- 业务cache刷新
- 价格变化等重要业务消息
关于 Canal 的更多信息请访问 https://github.com/alibaba/canal/wiki
二.应用场景
pycanal 作为Canal的客户端,其应用场景就是Canal的应用场景。关于应用场景在Canal介绍一节已有概述。举一些实际的使用例子:
1.代替使用轮询数据库方式来监控数据库变更,有效改善轮询耗费数据库资源。
2.根据数据库的变更实时更新搜索引擎,比如电商场景下商品信息发生变更,实时同步到商品搜索引擎 Elasticsearch、solr等
3.根据数据库的变更实时更新缓存,比如电商场景下商品价格、库存发生变更实时同步到redis
4.数据库异地备份、数据同步
5.根据数据库变更触发某种业务,比如电商场景下,创建订单超过xx时间未支付被自动取消,我们获取到这条订单数据的状态变更即可向用户推送消息。
6.将数据库变更整理成自己的数据格式发送到kafka等消息队列,供消息队列的消费者进行消费。
三.工作原理
pycanal 是 Canal 的 python 客户端,它与 Canal 是采用的Socket来进行通信的,传输协议是TCP,交互协议采用的是 Google Protocol Buffer 3.0。
四.工作流程
1.Canal连接到mysql数据库,模拟slave
2.pycanal 与 Canal 建立连接
2.数据库发生变更写入到binlog
5.Canal向数据库发送dump请求,获取binlog并解析
4.pycanal 向 Canal 请求数据库变更
4.Canal 发送解析后的数据给pycanal
5.pycanal收到数据,消费成功,发送回执。(可选)
6.Canal记录消费位置。
五.快速启动
安装Canal
Canal 的安装以及配置使用请查看 https://github.com/alibaba/canal/wiki/QuickStart
环境要求
python >= 3
构建canal python客户端
pip install py3canal
建立与Canal的连接
import time
from pycanal.client import CanalClient
from pycanal.protocol import EntryProtocol_pb2
from tornado.ioloop import IOLoop
async def main():
while True:
canal = CanalClient(host="10.88.190.151", port=21111)
await canal.connect()
await canal.check_valid()
await canal.subscribe(client_id=b"14001", destination=b"pandora")
while True:
try:
message = await canal.get(100)
entries = message["entries"]
for entry in entries:
entry_type = entry.entryType
if entry_type in [EntryProtocol_pb2.EntryType.TRANSACTIONBEGIN,
EntryProtocol_pb2.EntryType.TRANSACTIONEND]:
continue
row_change = EntryProtocol_pb2.RowChange()
row_change.MergeFromString(entry.storeValue)
header = entry.header
database = header.schemaName
table = header.tableName
event_type = header.eventType
for row in row_change.rowDatas:
if event_type == EntryProtocol_pb2.EventType.DELETE:
format_data = dict()
print("delete: {}".format(EntryProtocol_pb2.EventType.DELETE))
for column in row.beforeColumns:
format_data[column.name] = column.value
data = dict(
db=database,
table=table,
event_type=event_type,
data=format_data,
)
print(data)
elif event_type == EntryProtocol_pb2.EventType.INSERT:
format_data = dict()
print("insert: {}".format(EntryProtocol_pb2.EventType.INSERT))
for column in row.afterColumns:
format_data[column.name] = column.value
data = dict(
db=database,
table=table,
event_type=event_type,
data=format_data,
)
print(data)
else:
format_data = dict()
format_data["before"] = format_data["after"] = dict()
for column in row.beforeColumns:
format_data["before"][column.name] = column.value
for column in row.afterColumns:
format_data["after"][column.name] = column.value
data = dict(
db=database,
table=table,
event_type=event_type,
data=format_data,
)
print(data)
except Exception as e:
print(e)
break
time.sleep(1)
canal.disconnect()
time.sleep(2)
if __name__ == "__main__":
io_loop = IOLoop.current()
io_loop.run_sync(main)
更多详情请查看 Sample
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