When a Hadoop deployment is used to process sensitive data, several security requirements arise that may be dictated by internal policies and/or government regulations. They may require strong authentication, selective authorization to access data/resources, and data confidentiality. This session covers in detail how different components in the Hadoop ecosystem and external applications can interact with each other in a secure manner providing authentication, authorization, and confidentiality when accessing services and transferring data to/from/between services. This session will cover Hive security and how Apache Sentry (incubating) can be used to implement a fine-grained role-based access control policy for Hive. In particular, we will talk about how Sentry can be used in a multi-tenant environment to secure access to different data warehouse objects – tables, schemas, views, partitions, UDFs, and SerDes as well as queries that comprise of sub-queries and involve cross database joins. Finally, the session will cover topics like Kerberos authentication, Web UI authentication, File System permissions, delegation tokens, MR/YARN Access Control Lists, ProxyUser impersonation and network encryption.
Aaron T. Myers is a Software Engineer at Cloudera and an Apache Hadoop Committer. Aaron’s work is primarily focused on HDFS. Prior to joining Cloudera, Aaron was a Software Engineer and VP of Engineering at Amie Street, where he worked on all components of the software stack, including operations, infrastructure, and customer-facing feature development. Aaron holds both an Sc.B. and Sc.M. in Computer Science from Brown University.
Shreepadma Venugopalan is a software engineer in the Platform Team at Cloudera. Prior to Cloudera, Shreepadma was a member of the Server Technologies group at Oracle where she focused on the relational engine, query optimizer, and unstructured data management. She holds a Master’s degree in Computer Science from the University of Wisconsin-Madison.
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