BASE ACID • 分布式 NoSQL • SQL • ACID+BASE • 分布式 NewSQLNewSQL的分类 New Architecture Transparent Sharding Middleware Database-as-a-Service What's Really New with NewSQL?数据库中间层的优势 系统 •事务 运维 • DBA Sidecar的优势Database Mesh架构图Sharding-Sphere 核心功能 数据分片 分布式事务 数据库治理 弹性伸缩 管控界面 实现方案 Sharding-JDBC Sharding-Proxy Sharding-Sidecar Sharding -Sphere 云原生 无中心 零侵入Sharding-Sphere：数据分片Sharding-Sphere：分布式事务Sharding-Sphere：治理中心 理中心 核心功能 •配置集中化 &动态化 •数据库熔断 & 禁用 支持的注册中心 •ZooKeeper •Etcd 业务代码 Sharding- Sphere 业务代码 Sharding- Sphere 应用 应用 注册中心Sharding-Sphere：APM演进线路图 JDBC + 数据分片 版本：1.X 数据库治理 版本：2.X Proxy 版本：3.0.X 分布式事务

3、接入端需要实现数据库协议，对非开源数据库无法支持。 数据库中间件使用的约束： 3.分布式数据库 3.分布式数据库 类库/框架 数据库中间件 分布式数据库 数据网格 TDDL Sharding-JDBC DRDS Sharding-Proxy MyCAT DBLE KingShard Vitess ? Spanner Aurora GaussDB PolarDB OceanBase TiDB Cockroach 应用场景。 5.数据库解决方案 Level 3：Sharding-Proxy中间件（3.x+） Level 2：Sharding-JDBC框架（1.x+） Level 1：MySQL数据库提供的能力 Level 4：Sharding-Scaling（4.x+） Level 5：Sharding-Sidecar（5.x+） Level 6：Sharding-Engine（6.x+） We're Here

Fully-managed ● Scalable read Cons: ● Single point write (if you want to scale out writer, you still need sharding) ● SQL layer is not designed for complex query ● Reader is eventual consistency ● Memory size and JDBC/ODBC, Applications ... MySQL Wire Protocol heartbeat meta TiDB is not a database middleware Sharding middleware TiDB ACID Transaction Support Mostly Elastic Scaling Complex Query (Join, Sub query, Metadata TiDB architecture Pros: ● Scale-out well on both read and write, without manual sharding or specifying sharding rules ● Full-featured SQL layer which is designed for distributed computing ● ACID sementics

NewSQL - 数据库无限水平扩展的完美解决方案 DB Sharding NewSQL | Ti Project 大数据时代，当单机数据 库容量及处理能力达到瓶 颈时，由于没有完美的分 布式解决方案，业界普遍 采用妥协的数据库分库分 表（Sharding）方案 DB Sharding vs NewSQL DB Sharding NewSQL | TiDB 工作内容 工作量 工作内容 工作量

for Tables with Different Schema or Table Names · · · · · · · · 3220 13.11.3 Data Check in the Sharding Scenario · · · · · · · · · · · · · · · · · · · · · · · · · · · · · 3224 13.11.4 Data Check in the Lightning to quickly merge and import the sharded tables. Then, you can use DM to replicate incremental sharding data (binlog) based on your application needs. • Migrate and Merge MySQL Shards of Large Datasets occur during the merge. Therefore, before migration, you need to take a deep look at the current sharding scheme from the business point of view, and find a way to avoid the conflicts. For more details

for Tables with Different Schema or Table Names · · · · · · · · 3176 13.13.3 Data Check in the Sharding Scenario · · · · · · · · · · · · · · · · · · · · · · · · · · · · · 3180 13.13.4 Data Check in the INFORMATION_ �→ SCHEMA.PARTITIONS is incorrect #54173 @Defined2014 • Fix the issue that the TIDB_ROW_ID_SHARDING_INFO field in the INFORMATION_ �→ SCHEMA.TABLES table is incorrect #52330 @tangenta • Fix the Lightning to quickly merge and import the sharded tables. Then, you can use DM to replicate incremental sharding data (binlog) based on your application needs. • Migrate and Merge MySQL Shards of Large Datasets

for Tables with Different Schema or Table Names · · · · · · · · 3183 13.13.3 Data Check in the Sharding Scenario · · · · · · · · · · · · · · · · · · · · · · · · · · · · · 3187 13.13.4 Data Check in the Lightning to quickly merge and import the sharded tables. Then, you can use DM to replicate incremental sharding data (binlog) based on your application needs. • Migrate and Merge MySQL Shards of Large Datasets occur during the merge. Therefore, before migration, you need to take a deep look at the current sharding scheme from the business point of view, and find a way to avoid the conflicts. For more details

for Tables with Different Schema or Table Names · · · · · · · · 3204 13.12.3 Data Check in the Sharding Scenario · · · · · · · · · · · · · · · · · · · · · · · · · · · · · 3208 13.12.4 Data Check in the Lightning to quickly merge and import the sharded tables. Then, you can use DM to replicate incremental sharding data (binlog) based on your application needs. • Migrate and Merge MySQL Shards of Large Datasets occur during the merge. Therefore, before migration, you need to take a deep look at the current sharding scheme from the business point of view, and find a way to avoid the conflicts. For more details

for Tables with Different Schema or Table Names · · · · · · · · 3151 13.13.3 Data Check in the Sharding Scenario · · · · · · · · · · · · · · · · · · · · · · · · · · · · · 3155 13.13.4 Data Check in the Lightning to quickly merge and import the sharded tables. Then, you can use DM to replicate incremental sharding data (binlog) based on your application needs. • Migrate and Merge MySQL Shards of Large Datasets occur during the merge. Therefore, before migration, you need to take a deep look at the current sharding scheme from the business point of view, and find a way to avoid the conflicts. For more details

semanticPrometheus at scale ● In the old days… ○ one or more prometheus per cluster ○ hashmod sharding Node Node Node Node Node Node Node Node Node Hashmod = 0 Hashmod = 1 Hashmod = 2 prometheus2Prometheus at scale ● In the old days… ○ one or more prometheus per cluster ○ hashmod sharding Almost works... prometheus prometheus prometheus prometheus