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OAP: Optimized Analytics Package for Spark Platform

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Spark SQL is one of the most popular components in big data warehouse for SQL queries in batch mode, and it allows user to process data from various data sources in a highly efficient way. However, Spark SQL is a general purpose SQL engine and not well designed for ad hoc queries. Intel invented an Apache Spark data source plugin called Spinach for fulfilling such requirements, by leveraging user-customized indices and fine-grained data cache mechanisms.

To be more specific, Spinach defines a new Parquet-like data storage format, offering a fine-grained hierarchical cache mechanism in the unit of “Fiber” in memory. Even existing Parquet or ORC data files can be loaded using corresponding adaptors. Data can be cached in off-heap memory to boost data loading. What’s more, Spinach has extended the Spark SQL DDL, to allow users to define the customized indices based on relation. Currently, B+ tree and bloom filter are the first two types of indices supported. Last but not least, since Spinach resides in the process of Spark executor, there’s no extra effort in deployment. All you need to do is to pick Spinach from Spark packages when launching the Spark SQL.
sing corresponding adaptors. Data can be cached in off-heap memory to boost data loading. What’s more, Spinach has extended the Spark SQL DDL, to allow user to define the customized indices based on relation. Currently B+ tree and bloom filter are the first 2 types of index we’ve supported. Last but not least, since Spinach resides in the process of Spark executor, there’s no extra effort in deployment, all we need to do is to pick Spinach from Spark packages when launch the Spark SQL.

Spinach has been imported in Baidu’s production environment since Q4 2016. It helps several teams migrating their regular data analysis tasks from Hive or MR jobs to ad-hoc queries. In Baidu search ads system FengChao, data engineers analyze advertising effectiveness based on several TBs data of display and click logs every day. Spinach brings a 5x boost compared to original Spark SQL (version 2.1), especially in the scenario of complex search and large data volume. It optimizes the average search cost from minutes to seconds, while brings only 3% data size increase for adding a single index.

Session hashtag: #SFexp3

Daoyuan Wang, Senior Software Engineer at Intel

About Daoyuan

Daoyuan Wang is a senior software engineer in Intel, and an Apache Spark active contributor. He graduated from Zhejiang University and joined Intel in 2013.

Yuanjian Li, Senior Engineer and Team Leader at Baidu

About Yuanjian

Yuanjian is a senior engineer and team leader of Baidu internal spark platform. He is also a Spark SQL contributor. Prior of that, He worked on real time computing and distributed tracing system in Baidu.