Mark Grover

Mark is a committer on Apache Bigtop and a committer and PMC member on Apache Sentry (incubating) and a contributor to Apache Hadoop, Apache Hive, Apache Sqoop and Apache Flume projects. He is also a section author of O’Reilly’s book on Apache Hive – Programming Hive.

Content

Shared nothing architectures: Giving Hadoop’s data processing frameworks scalability and fault tolerance

October 7, 2016

A look at the tools and patterns for accessing and processing data in Hadoop.

Best practices for streaming applications

August 11, 2016

Mark Grover and Ted Malaska offer an overview of projects for streaming applications, including Kafka, Flume, and Spark Streaming, and discuss the architectural schemas available, such as Lambda and Kappa.

Architecting Hadoop Applications

October 27, 2015

In this O'Reilly training video, the "Hadoop Application Architectures" authors present an end-to-end case study of a clickstream analytics engine to provide a concrete example of how to architect and implement a complete solution with Hadoop. In this segment, they provide an overview of the complete architecture. Presenters: Mark Grover, Gwen Shapira, Jonathan Seidman, Ted Malaska

Processing frameworks for Hadoop

February 15, 2015

How to decide which framework is best for your particular use case.