Accelerate MySQL for Demanding OLAP and OLTP Use Cases

mysql®是一种非常流行和广泛使用的RDBMS。Apache®Ignite™是领先的开放源码内存计算平台,可为基于RDBMS的应用程序提供速度和规模。ApacheIgnite插入到现有的应用程序和数据层之间,并与所有常见的RDBMS、NoSQL和Hadoop®数据库一起工作。
加入GridGain首席技术官兼联合创始人Nikita Ivanov和Percona首席执行官兼联合创始人Peter Zaitsev,讨论如何用Apache Ignite补充MySQL。你会学到:
如何利用ApacheIgnite的并行分布式计算和ANSISQL-99功能来克服MySQL架构对大数据分析的局限性
如何将ApacheIgnite用作高级高性能的热数据缓存平台
使用Apache Ignite而不是Memcache、Redis、Elastic®或Apache®Spark™的战略优势
在本次网络研讨会结束时,您将了解如何将ApacheIgnite集成到您的体系结构中,从而在扩展您当前的MySQL基础架构时,大大加快分析和事务处理速度。

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1. Accelerate MySQL® for Demanding OLAP and OLTP Use Case with Apache®Ignite™ December 7, 2016 Nikita Ivanov Peter Zaitsev CTO and Co-Founder CEO and Co-Founder GridGain Systems Percona

2.About the Presentation Problems Existing Solutions Nikita Ivanov will show the power of Apache Ignite 2 © 2016 Percona

3.About Percona We Exist to help you to succeed with MySQL and MongoDB 3 © 2016 Percona

4.Support Broad Ecosystem Percona Server for MySQL MariaDB MySQL AWS for Percona MySQL and MongoDB Server for Aurora MongoDB Google CloudSQL 4 © 2016 Percona

5.Percona Software – 100% Open Source Percona Server Percona Server Percona XtraDB for MySQL for MongoDB Cluster Percona Percona Percona Toolkit Monitoring and Xtrabackup Management 5 © 2016 Percona

6.Services • Support • More than Support (Percona Care) • Managed Services (Percona Care Ultimate) • Consulting, Training 6 © 2016 Percona

7.My Conviction There is no silver bullet in technology! 7 © 2016 Percona

8.Why ? All design decisions comes with their own benefits and drawbacks 8 © 2016 Percona

9.Technologies not Technology Large Scale applications tend to use more than one technology on data layer 9 © 2016 Percona

10.Works especially well with Open Source! Additional Components do not require hefty license fees Easy to prototype and test out Open Source Community is good at building bridges 10 © 2016 Percona

11.Balance is Needed Use as many technologies as you need, but no more 11 © 2016 Percona

12.MySQL MySQL is no Exception. It is not Great for Everything. 12 © 2016 Percona

13.Some of the Problems Hot Data Highly Volatile Data Large Data Volume Analytical Processing Full Text Search 13 © 2016 Percona

14.Hot Data For example “Cache” Large volume of simple requests High overhead due to SQL No good Memory focused Engine Not Designed for very high Concurrency 14 © 2016 Percona

15.Solutions MySQL External ••MemcacheD ••MemcacheD interface ••Redis ••Thread Pool 15 © 2016 Percona

16.Highly Volatile Data Lots of updates, especially to a single row Design around full Transactional ACID semantics Disk Log based durability Pessimistic Logging 16 © 2016 Percona

17.Solutions MySQL External ••Data Design ••MemcacheD ••Configuration ••Redis Tuning ••Parallel Replication 17 © 2016 Percona

18.Large Data Volume MySQL is designed as single node system Limited in CPU, Memory Manual “Sharding” solutions are painful Especially with complex queries 18 © 2016 Percona

19.Solutions MySQL External ••Manual ••Shading for Sharding MemcacheD and ••Vitess Redis ••ProxySQL ••MongoDB ••Cassandra 19 © 2016 Percona

20.Analytics (OLAP) MySQL does not support column based storage MySQL optimizer is limited for complex queries MySQL does not do parallel query execution MySQL does not do distributed query execution 20 © 2016 Percona

21.Solutions MySQL External ••Configuration ••Hadoop & and Schema Spark Design ••Vertica (Limited) ••ClickHouse 21 © 2016 Percona

22.Full Text Search Can handle basic Full Text Search Does not scale well with data volume No parallel processing Limited search relevance options Hard To do GIS searches; Facets No language processing 22 © 2016 Percona

23.Solutions MySQL External ••Small Scale search ••Elastic applications only ••Solr ••Supported with ••Sphinx Innodb tables since MySQL 5.6 23 © 2016 Percona

24.New Solutions constantly appear Always be on lookout for a better solutions! 24 © 2016 Percona

25.Apache Ignite Nikita Ivanov will show what you can do with Apache Ignite! 25 © 2016 Percona

26.Accelerate MySQL® for Demanding OLAP and OLTP Use Cases with Apache® Ignite™ December 7, 2016 Nikita Ivanov Founder & CTO, GridGain Systems Apache Ignite PMC

27.Why In-Memory Computing Now? Declining DRAM Cost Data Growth Driving Demand Growth of Global Data 35 30 Zettabytes of Data 25 20 15 10 DRAM 5 Flash 0 Disk 2009 2010 2015 2020 8 zettabytes in 2015 growing to 35 in 2020 Cost drops 30% every 12 months

28. In-Memory Data Fabric Ideal accelerator for SQL data stores and apps Apache Ignite is a leading open-source, cloud-ready distributed software delivering 100x performance and scalability by storing and processing data in memory across scale out or scale up infrastructure. © 2014 GridGain Systems, Inc.

29. In-Memory Data Fabric Main components © 2014 GridGain Systems, Inc.