get up to speed with Apache drill, an extensible distributed SQL query engine that reads massive datasets in many popular file formats such as parquet, JSON, and CSV. Drill reads data in HDFS or in cloud-native storage such as S3 and works with Hive metastores along with distributed databases such as base, MongoDB, and relational databases. Drill works everywhere: on your laptop or in your largest cluster.
In this practical book, drill committers Charles givre and Paul Rogers show analysts and data scientists how to query and analyze raw data using this powerful tool. Data scientists today spend about 80% of their time just gathering and cleaning data. With this book, you’ll learn how drill helps you analyze data more effectively to drive down time to insight.
Use drill to clean, prepare, and summaries delimited data for further analysis Query file types including logfiles, parquet, JSON, and other complex formats Query Hadoop, relational databases, MongoDB, and Kafka with standard SQL

Paul Rogers

Paul Rogers is an Apache Drill committer at MapR where he focuses on Drill’s execution engine. Paul has worked as a software architect at a number database and BI companies such as Oracle, Actuate and Informix. Paul was the early architect of the Eclipse BIRT project. His interests include making Drill even easier to use for end-users and plug-in developers.

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