Protect your private data in your Hadoop clusters with ORC column encryption
Who is this presentation for?
- Data engineers and software engineers
Fine-grained data protection at a column level in data lake environments has become a mandatory requirement to demonstrate compliance with multiple local and international regulations across many industries today. ORC is a self-describing type-aware columnar file format designed for Hadoop workloads that provides optimized streaming reads but with integrated support for finding required rows quickly.
Owen O’Malley dives into the progress the Apache community made for adding fine-grained column-level encryption natively into ORC format, which also provides capabilities to mask or redact data on write while protecting sensitive column metadata such as statistics to avoid information leakage. The column encryption capabilities will be fully compatible with Hadoop Key Management Server (KMS) and use the KMS to manage master keys, providing the additional flexibility to use and manage keys per column centrally. Owen also demonstrates an end-to-end scenario that shows how to leverage this capability.
- Experience with either Hive or Spark to process big data
What you'll learn
- Learn how to use ORC column encryption to protect your sensitive data
Owen O’Malley is a cofounder and technical fellow at Cloudera, formerly Hortonworks. Cloudera’s software includes Hadoop and the large ecosystem of big data tools that enterprises need for their data analytics. Owen has been working on Hadoop since the beginning of 2006 at Yahoo, was the first committer added to the project, and used Hadoop to set the Gray sort benchmark in 2008 and 2009. Previously, he was the architect of MapReduce, Security, and now Hive. He’s driving the development of the ORC file format and adding ACID transactions to Hive.
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