Get fresh updates from Hortonworks by email

Once a month, receive latest insights, trends, analytics information and knowledge of Big Data.


Sign up for the Developers Newsletter

Once a month, receive latest insights, trends, analytics information and knowledge of Big Data.


Get Started


Ready to Get Started?

Download sandbox

How can we help you?

* I understand I can unsubscribe at any time. I also acknowledge the additional information found in Hortonworks Privacy Policy.
closeClose button
November 24, 2014
prev slideNext slide

Announcing Apache Hive 0.14

While YARN has allowed new engines to emerge for Hadoop, the most popular integration point with Hadoop continues to be SQL and Apache Hive is still the defacto standard. Although many SQL engines for Hadoop have emerged, their differentiation is being rendered obsolete as the open source community surrounds and advances this key engine at an accelerated rate.

Screen Shot 2014-11-24 at 8.40.21 AMLast week, the Apache Hive community released Apache Hive 0.14, which includes the results of the first phase in the initiative and takes Hive beyond its read-only roots and extends it with ACID transactions. Thirty developers collaborated on this version and resolved more than 1,015 JIRA issues.

Although there are many new features in Hive 0.14, there are a few highlights we’d like to highlight. For the complete list of features, improvements, and bug fixes, see the release notes.

Transactions with ACID semantics (HIVE-5317)

Allows users to modify data using insert, update and delete SQL statements. This provides snapshot isolation and uses locking for writes. Now users can make corrections to fact tables and changes to dimension tables.

Cost Base Optimizer (CBO) (HIVE-5775)

Now the query compiler uses a more sophisticated cost based optimizer that generates query plans based on statistics on data distribution. This works really well with complex joins and joins with multiple large fact tables. The CBO generates bushy plans that execute much faster.

SQL Temporary Tables (HIVE-7090)

Temporary tables exist in scratch space that goes away when the user session disconnects. This allows users and BI tools to store temporary results and further process that data with multiple queries.

Coming Next in Sub-Second Queries

After Hive 0.14, we’re planning on working with the community to deliver sub-second queries and SQL:2011 Analytics coverage in Hive. We also plan to work on Hive-Spark integration for machine learning and operational reporting with Hive streaming ingest and transactions.

Download Hive and Learn More


Leave a Reply

Your email address will not be published. Required fields are marked *

If you have specific technical questions, please post them in the Forums