Introduction to Apache Drill - Self-Service Data Exploration & Nested Data

Introduction to Apache Drill - Self-Service Data Exploration and Nested Data Analytics on Hadoop

SQL is one of the most widely used languages to access, enterprise data architectures across industries, the need for SQL for both structured and loosely-structured data on Hadoop is growing rapidly. Apache Drill started off with the audacious goal of delivering consistent, millisecond ANSI SQL query capability across wide range of data formats. At a high level, this translates to two key requirements – Schema Flexibility and Performance.

Apache Drill provides the users the ability to interact with big data on Hadoop much faster and far more easily using the familiar SQL language. Users are no longer dependent on central IT teams and DBAs to produce schemas and then maintain them when the structure changes for a few records. Drill alleviates the pain associated with structuring unstructured data before one gains any insights by providing a simple mechanism to query any dataset on Hadoop - be it flat files, parquet or JSON files or tables within an HBase table. This session will give you an overview of several different use cases that enterprises are testing Drill for as well as the latest news on the project.

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BIO ABOUT THE PRESENTER

Vince Gonzalez - Systems Engineer, MapRVince Gonzalez is a Systems Engineer for MapR. He has 20 years of experience designing, implementing and automating infrastructure and applications. Previously, he was an Field Application Engineer for AMD Data Center Server Solutions (formerly SeaMicro), where he supported customers in the eastern U.S. Prior to AMD/SeaMicro, Vince worked for BlueArc Corporation. Vince held a variety of roles at BlueArc, including Field Engineer, Sales Engineer, and Director of Technical Services, where he led the Eastern region field technical team. Earlier in his career, Vince was a UNIX/Linux administrator.