Presto + Druid : How Big Data Goes Real Time @ Twitter

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