黄东旭解析 TiDB 的核心优势
605
2023-04-04
在最近的 v6.5.0 发布的新特性中(详见:release-6.5.0),我对一个特性特别感兴趣: 从 v6.5.0 开始,TiCDC 支持将行变更事件保存至存储服务,如 Amazon S3、Azure Blob Storage 和 NFS。参考:使用指南 简言之,这个特性能够通过 TiCDC 这一个组件,就能保存 CDC 日志到对象存储中。如果应用这个特性,我就没有必要部署 Kafka 集群了,简化了部署要求,降低了部署成本。 本文依托部署在 K8s 中的 TiDB ,测试 CDC 的新特性,OSS 采用 MinIO。
TiDB 在 k8s 上的部署详见:快速上手 TiDB Operator,部署个测试集群即可,官方文档已经很详细了,可以参考我的 tidb-cluster.yml 如下:
# IT IS NOT SUITABLE FOR PRODUCTION USE. # This YAML describes a basic TiDB cluster with minimum resource requirements, # which should be able to run in any Kubernetes cluster with storage support. apiVersion: pingcap.com/v1alpha1 kind: TidbCluster metadata: name: basic spec: version: v6.5.0 timezone: UTC pvReclaimPolicy: Retain enableDynamicConfiguration: true configUpdateStrategy: RollingUpdate discovery: {} helper: image: alpine:3.16.0 pd: baseImage: uhub.service.ucloud.cn/pingcap/pd maxFailoverCount: 0 replicas: 3 # if storageClassName is not set, the default Storage Class of the Kubernetes cluster will be used # storageClassName: local-storage requests: storage: "1Gi" config: {} tikv: baseImage: uhub.service.ucloud.cn/pingcap/tikv maxFailoverCount: 0 # If only 1 TiKV is deployed, the TiKV region leader # cannot be transferred during upgrade, so we have # to configure a short timeout evictLeaderTimeout: 1m replicas: 3 # if storageClassName is not set, the default Storage Class of the Kubernetes cluster will be used # storageClassName: local-storage requests: storage: "1Gi" config: storage: # In basic examples, we set this to avoid using too much storage. reserve-space: "0MB" rocksdb: # In basic examples, we set this to avoid the following error in some Kubernetes clusters: # "the maximum number of open file descriptors is too small, got 1024, expect greater or equal to 82920" max-open-files: 256 raftdb: max-open-files: 256 tidb: baseImage: uhub.service.ucloud.cn/pingcap/tidb maxFailoverCount: 0 replicas: 1 service: type: ClusterIP config: {} ticdc: baseImage: uhub.service.ucloud.cn/pingcap/ticdc replicas: 3 config: logLevel: info部署后集群状态如下: 部署过程中,有点小波折,关于 6.5.0 版本中 TiDB-Dashboard 依赖包版本太高的问题,我最终采用了社区大佬的镜像,替换了官方镜像完成了部署。 替换步骤为,修改官方的 tidb-dashboard.yml:
apiVersion: pingcap.com/v1alpha1 kind: TidbDashboard metadata: name: basic spec: baseImage: sabaping/tidb-dashboard:v6.5.0 version: v6.5.0 clusters: - name: basic requests: storage: 10Gi修改完成后,执行:
kubectl apply -f tidb-dashboard.yml -n tidb-cluster即可完成更新。
MinIO 的在 k8s 上的部署详见:kubernetes 部署 minio 对象存储
官方参考文档:https://docs.pingcap.com/zh/tidb/stable/ticdc-sink-to-cloud-storage 我的目前是配置 TiCDC,同步 TiDB 的数据到同一个 k8s 集群的 MinIO 中,我配置中的地址都采用了 Service 地址。 我的配置如下:
./cdc cli changefeed create \ --server=http://basic-ticdc-peer:8301 \ --sink-uri="s3://tidbbinlog/?protocol=canal-json&endpoint=http://minio-headless.minio:9000&access-key=XXX&secret-access-key=XXX&force-path-style=true" \ --changefeed-id="oss-replication-task"各参数说明:
server=http://basic-ticdc-peer:8301 ticdc 的服务地址
sink-uri=... 目标对象存储的配置
s3://tidbbinlog/ TiCDC 支持的对象存储包含 s3 协议,MinIO 支持 s3 协议,此处采用 s3 协议,tidbbinlog 为 bucket 名称
protocol=canal-json 存储到对象存储中内容的格式,v6.5.0 支持 CSV 和 Canal-JSON 格式,我惯用 canal-json
endpoint=http://minio-headless.minio:9000 对象存储访问地址
access-key=XXX 对象存储访问 access-key
secret-access-key=XXX 对象存储访问 secret-access-key
force-path-style=true 采用路径访问的方式访问对象存储,访问 MinIO 必须设置
changefeed-id="oss-replication-task" CDC 的任务 ID
在命令行执行:
kubectl exec basic-ticdc-0 -it -n tidb-cluster -- /bin/bash进入 pod 的命令行窗口,执行命令:
./cdc cli changefeed create \ --server=http://basic-ticdc-peer:8301 \ --sink-uri="s3://tidbbinlog/?protocol=canal-json&endpoint=http://minio-headless.minio:9000&access-key=XXX&secret-access-key=XXX&force-path-style=true" \ --changefeed-id="oss-replication-task"返回信息如下:
Create changefeed successfully! ID: oss-replication-task Info: {"upstream_id":7184751775799892803,"namespace":"default","id":"oss-replication-task","sink_uri":...}此时查询任务状态:
./cdc cli changefeed list --server=http://basic-ticdc-peer:8301 [ { "id": "oss-replication-task", "namespace": "default", "summary": { "state": "normal", "tso": 438588139028348953, "checkpoint": "2023-01-07 08:42:54.687", "error": null } } ]MinIO 上可以看到在对应的 bucket 下已经创建了一个文件: 文件内容为:
{"checkpoint-ts":438588195559702535}438588195559702535 为同步数据的 commit-ts,438588195559702535 之前的数据都已经同步到了 MinIO。
在 TiDB 中建表和插入数据:
CREATE TABLE test.student (id varchar(20) NULL, name varchar(20) NULL, age varchar(100) NULL, `desc` varchar(100) NULL ); INSERT INTO test.student (id,name,age,`desc`) VALUES (1,zhangsan,18,好学生); INSERT INTO test.student (id,name,age,`desc`) VALUES (2,lisi,19,也是个好学生); INSERT INTO test.student (id,name,age,`desc`) VALUES (3,wangwu,19,更是个好学生);检查 MinIO 并没有新的目录和文件产生,经检查日志:
2023-01-07T08:49:18.857903341Z [2023/01/07 08:49:18.857 +00:00] [WARN] [snapshot.go:849] ["this table is ineligible to replicate"] [tableName=student] [tableID=82]查找原因是因为 test.student 表没有主键,建主键,并插入数据:
ALTER TABLE test.student ADD CONSTRAINT student_PK PRIMARY KEY (id); INSERT INTO test.student (id,name,age,`desc`) VALUES (21,zhangsan,18,好学生); INSERT INTO test.student (id,name,age,`desc`) VALUES (22,lisi,19,也是个好学生); INSERT INTO test.student (id,name,age,`desc`) VALUES (23,wangwu,19,更是个好学生);其中,CDC000001.json:
{"id":0,"database":"test","table":"student","pkNames":["id"],"isDdl":false,"type":"INSERT","es":1673227668037,"ts":1673227668465,"sql":"","sqlType":{"id":12,"name":12,"age":12,"desc":12},"mysqlType":{"id":"varchar","name":"varchar","age":"varchar","desc":"varchar"},"old":null,"data":[{"id":"21","name":"zhangsan","age":"18","desc":" 好学生 "}]} {"id":0,"database":"test","table":"student","pkNames":["id"],"isDdl":false,"type":"INSERT","es":1673227669537,"ts":1673227670111,"sql":"","sqlType":{"id":12,"name":12,"age":12,"desc":12},"mysqlType":{"id":"varchar","name":"varchar","age":"varchar","desc":"varchar"},"old":null,"data":[{"id":"22","name":"lisi","age":"19","desc":" 也是个好学生 "}]} {"id":0,"database":"test","table":"student","pkNames":["id"],"isDdl":false,"type":"INSERT","es":1673227670787,"ts":1673227671141,"sql":"","sqlType":{"id":12,"name":12,"age":12,"desc":12},"mysqlType":{"id":"varchar","name":"varchar","age":"varchar","desc":"varchar"},"old":null,"data":[{"id":"23","name":"wangwu","age":"19","desc":" 更是个好学生 "}]}schema.json:
{ "Table": "student", "Schema": "test", "Version": 1, "TableVersion": 438626581528444931, "Query": "","Type": 0,"TableColumns": [ { "ColumnName": "id", "ColumnType": "VARCHAR", "ColumnPrecision": "20", "ColumnNullable": "false", "ColumnIsPk": "true" }, { "ColumnName": "name", "ColumnType": "VARCHAR", "ColumnPrecision": "20" }, { "ColumnName": "age", "ColumnType": "VARCHAR", "ColumnPrecision": "100" }, { "ColumnName": "desc", "ColumnType": "VARCHAR", "ColumnPrecision": "100" } ], "TableColumnsTotal": 4 }详细的内容解释,官方有文档说明,在此不再赘述。 为表增加字段:
ALTER TABLE test.student ADD graduation CHAR(1) NULL;test/student 下面增加了一个目录,根据官方说明,这一层是表的版本,也就是说,如果对表执行 ddl,此处就会增加一个目录。
分区表建表并插入数据:
CREATE TABLE `student_partition` ( `id` INT NOT NULL, `name` varchar(20) DEFAULT NULL, `age` varchar(100) DEFAULT NULL, `desc` varchar(100) DEFAULT NULL, `graduation` char(1) DEFAULT NULL, PRIMARY KEY (`id`) )PARTITION BY HASH(id) PARTITIONS 6; INSERT INTO test.student_partition (id,name,age,`desc`) VALUES (21,zhangsan,18,好学生); INSERT INTO test.student_partition (id,name,age,`desc`) VALUES (22,lisi,19,也是个好学生); INSERT INTO test.student_partition (id,name,age,`desc`) VALUES (23,wangwu,19,更是个好学生);查看对象存储: 发现在默认情况下,分区表和非分区表存储结构是一致的,但分区表通常是因为数据量巨大,才分区的,在处理 cdc 日志时,通常也希望能按照分区处理。 通过修改参数设置按照分区存储,执行:
kubectl exec basic-ticdc-0 -it -n tidb-cluster -- /bin/bash vi config在 config 里面写入:
[sink] date-separator = day enable-partition-separator = true其中: enable-partition-separator:开启按照分区分割目录 date-separator:按照分区分割目录的下层按天分割目录 保存 config 文件,执行:
./cdc cli changefeed create \ --server=http://basic-ticdc-peer:8301 \ --sink-uri="s3://tidbbinlog-separator/?protocol=canal-json&endpoint=http://minio-headless.minio:9000&access-key=XXX&secret-access-key=XXX&force-path-style=true" \ --changefeed-id="oss-replication-task-separator" \ --config ./config实际情况如下: 目录为tidbbinlog-separator/test/student_partition/438627372744835072/86/2023-01-09/CDC000001.json 目录中,86 为分区的 ID,2023-01-09 为按时间分割的目录,这两种分区方式可以根据需要,分别使用和组合使用。
我们在 Mysql 的 binlog 日志上,对于类似的处理方式已经有一些应用于生产,对于 json 格式的 cdc 日志,我们团队也有一些应用心得,有时间会写一篇文章补充介绍。
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