课程费用

6800.00 /人

课程时长

50分钟以下及更短时间

成为教练

课程简介

案例背景:
An important characteristic of Twitter is its real-time nature. Consequently, many of Twitter’s projects need real time analytics as a platform service. During recent years, a number of teams are adopting Presto and Druid as real time analytics engines.

解决思路:
In this talk, We start with Twitter’s big data architecture, followed by a detail introduction of Presto and Druid. We will focus on our design and implementation of Presto Druid Connector, which provides real time query latency with full SQL functionality. Leveraging Presto Connectors, users are able to join data between a variety of data sources, without data copy, including Hadoop, Druid, MySQL, Elasticsearch, etc. With predicate and aggregation pushdown, we achieved sub second query latency with Presto Druid Connector. We will also share our production experience, and roadmaps.

成果:
通过开源项目Presto和Druid的研发,我们实现了大数据分析的实时处理,绝大多数的查询可以做到一秒之内完成,很好的支持了Twitter业务

目标收益

听众可以了解大数据系统设计
听众可以了解大数据架构的演进
听众可以了解数据中台的设计和实现

培训对象

课程内容

案例方向


智能数据分析/企业级大数据架构演进/流式计算系统设计/数据库的未来

案例背景


An important characteristic of Twitter is its real-time nature. Consequently, many of Twitter’s projects need real time analytics as a platform service. During recent years, a number of teams are adopting Presto and Druid as real time analytics engines.

收益


听众可以了解大数据系统设计
听众可以了解大数据架构的演进
听众可以了解数据中台的设计和实现

解决思路


In this talk, We start with Twitter’s big data architecture, followed by a detail introduction of Presto and Druid. We will focus on our design and implementation of Presto Druid Connector, which provides real time query latency with full SQL functionality. Leveraging Presto Connectors, users are able to join data between a variety of data sources, without data copy, including Hadoop, Druid, MySQL, Elasticsearch, etc. With predicate and aggregation pushdown, we achieved sub second query latency with Presto Druid Connector. We will also share our production experience, and roadmaps.

结果


通过开源项目Presto和Druid的研发,我们实现了大数据分析的实时处理,绝大多数的查询可以做到一秒之内完成,很好的支持了Twitter业务

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