© 2018 Percona. 1 Peter Zaitsev Using MySQL for Distributed Database Architectures CEO, Percona PingCAP Infra Meetup, Shanghai, China, May 26, 2018 © 2018 Percona. 2 About Percona Solutions enterprises © 2018 Percona. 3 Presentation Cover Basics Why Going Distributed How to do it © 2018 Percona. 4 Distributed ? MySQL Deployment on More than one System © 2018 Percona. 5 Modern Active Users Possible 15M of Daily Active Users counting time of day skew © 2018 Percona. 8 Distributed Systems Tend To be More Complicated to Develop Against More Complicated to Operate Have

be synchronous? • If sharding across multiple instances: – Will you have distributed transactions? – Do you require distributed consistency? – What isolation level is being used? • Will there be a node OLAP • OLTP write and read scalability • Custer-wide ACID properties • Can also act as distributed key-value store • Currently based on PostgreSQL 9.5 Postgres Conference China 2016 中国用户大会 cannot be parallelized and pushed-down, must take place at originating PostgreSQL instance • No distributed consistency Postgres-XL can do all of the above It may be difficult to build a scalability solution

Implementation Principle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Elastic Distributed Implementation . . . . . . . . . . . . . . . . . . . . . . . . . 10 Registry Data Structure . . 58 Common Listener Configuration . . . . . . . . . . . . . . . . . . . . . . . . . . . 58 Distributed Listener Configuration . . . . . . . . . . . . . . . . . . . . . . . . . 58 ii 6.2.4 Event Tracing . . . . . . . . 91 10.6 What should you do if you suspect that ElasticJob has a problem in a distributed envi‐ ronment, but it cannot be reproduced and cannot be debugged in the online environment? 91

1.8 Appendix with SQL operator . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 3.2 Distributed Transaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 3.2.1 Background Implementation classes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 317 5.10 Distributed Transaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 317 5.10.1 can not cast to Long exception occurs. . . . . . . . . 458 8.3.6 Sharding Why is the default distributed auto‐augment key strategy provided by ShardingSphere not continuous and most of them end with

1.0 Documentation Introduction to Apache Cassandra Apache Cassandra is a free, open-source, distributed database system for managing large amounts of structured, semi-structured, and unstructured data in Cassandra 10 If you do not calculate partitioner tokens so that the data ranges are evenly distributed for each data center, you could end up with uneven data distribution within a data center. is that once your tokens are set appropriately, data from all of your column families is evenly distributed across the cluster with no further effort. For example, one column family could be using user names

1.8 Appendix with SQL operator . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 3.2 Distributed Transaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 3.2.1 Background Implementation classes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 344 5.10 Distributed Transaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 344 5.10.1 can not cast to Long exception occurs. . . . . . . . . 497 8.3.6 Sharding Why is the default distributed auto‐augment key strategy provided by ShardingSphere not continuous and most of them end with

manage traffic flow, optimize energy usage, enhance public safety, and improve urban planning. Technology platforms require real-time monitoring and analytics to personalize experiences and ensure performance full-text, and vector data. Built-in indexing and search to make data instantly searchable across distributed systems. High-performance querying for analytics, search, and AI workloads at scale. SQL simplicity simplicity to unify access across divers data types, reducing complexity in querying distributed datasets. Horizontal scalability across hybrid environments, supporting cloud, on- prem, and edge deployments

26 Inline Expression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 Distributed Primary Key . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Hint Sharding Route Pagination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 4.3 Distributed Transaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 4.3.1 Background 165 Governance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166 Distributed Transaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 DistSQL . . .

Deployment Topology· · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · 577 5.3.6 Geo-Distributed Deployment Topology· · · · · · · · · · · · · · · · · · · · · · · · · · · · 580 5.3.7 Hybrid Deployment · · · · · · · · 3913 15.9.2 What’s the recommended solution for the deployment of three geo- distributed data centers?· · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · · 3913 About TiDB 2.1 TiDB Introduction TiDB (/’ta￿di￿bi:/, “Ti” stands for Titanium) is an open-source distributed SQL database that supports Hybrid Transactional and Analytical Processing (HTAP) workloads. It

30 Inline Expression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Distributed Primary Key . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 Hint Sharding Route Pagination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 4.4 Distributed Transaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 4.4.1 Background DatabaseDiscoveryType . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 234 6.10 Distributed Transaction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 234 6.10.1