So I might be late in posting this article, but I want to publicize the changes in HDP 2.6.0 documentation and blog postings for Hive, Hive Views, and Ambari that were released in early April 2017. After all, I don't think all of you out there are upgraded to HDP 2.6.0 yet. To complement the G.A. release of Hive low-latency analytical processing (LLAP), the "Hive Performance Tuning Guide" has been completely rewritten to focus on how to optimize your environment and queries for interactive processing. While the guide is tailored to run a Hive data warehouse on the Tez framework, the new edition still has relevant tips and links to information for users who do batch processing on a MapReduce framework. A couple of LLAP blogs to consider reading are "Fast Analytics in the Cloud with Hive LLAP" and "Top 5 Performance Boosters with Apache Hive LLAP". Important debugging and optimization tools to get the most out of your Hive queries and your architecture are documented in Hive View 2.0 and Tez View, both of which introduce improvements over earlier versions of Ambari Views. You might also want to check out the "3 Great Reasons to Try Apache Hive View 2.0" blog. SQL-standard ACID MERGE support in HDP 2.6 raises the bar for Hive transactional data management by adding a helpful capability to ACID tables in HDP Hive, which already had supported record-level INSERT, UPDATE, and DELETE operations within tables. The current plan is to expand the documentation to include a step-by-step procedure for creating an ACID table with Apache Ambari. In the meantime, a good overview of why to use this functionality is in the "Apache Hive: Moving Beyond Analytics Offload with SQL MERGE" blog. ... View more

Hortonworks Data Platform 2.5 enhances your data access experience by redesigning and centralizing data access content, including providing you with content roadmaps for Apache Hive and Apache HBase. These content roadmaps help you find your way through the wider HDP and Apache libraries, with links to relevant sites and topics based on your task. Working with Hive? You might want to try the technical preview of Interactive and Sub-Second SQL Queries through LLAP. HDP 2.5 also includes improved security through row-level filtering and column masking. And by default, the Hive View now supports a JDBC connection. HBase users, you can now backup and restore datasets that run on production clusters by performing a single full backup and then capturing incremental changes to the dataset. HDP 2.5 also provides HBase Medium Object (MOB) Storage support. Using Apache Phoenix? HDP 2.5 supports Apache Phoenix version 4.7 including improved integration of HBase and Phoenix namespaces. And you can configure Phoenix Storage Handlers so that Hive queries can be run on Phoenix data. The newest version of HDP also helps users who want a more lightweight client for developing and running applications with Phoenix. The distro supports more Phoenix Query Server client driver options. To help secure your data application environment, you can enable native Kerberos authentication in the query server. Check out these updates and more in the HDP Data Access content and leave us some feedback in HCC! ... View more