Powering Interactive BI Analytics with Presto and Delta Lake

Описание: Presto, an open source distributed SQL engine, is widely recognized for its low-latency queries, high concurrency, and native ability to query multiple data sources. Proven at scale in a variety of use cases at Airbnb, Comcast, GrubHub, Facebook, FINRA, LinkedIn, Lyft, Netflix, Twitter, and Uber, in the last few years Presto experienced an unprecedented growth in popularity in both on-premises and cloud deployments over Object Stores, HDFS, NoSQL and RDBMS data stores. Delta Lake, a storage layer originally invented by Databricks and recently open sourced, brings ACID capabilities to big datasets held in Object Storage. While initially designed for Spark, Delta Lake now supports multiple query compute engines. In particular, Starburst, developed a native integration for Presto that leverages Delta-specific performance optimizations. In this talk we show how a combination of Presto, Spark Streaming, and Delta Lake into one architecture supports highly concurrent and interactive BI analytics. Furthermore Presto enables query-time correlations between S3-based IoT data, customer data in a legacy Oracle database, and web log data in Elasticsearch.

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