Apache Hive 1.2.0, although not a major release, contains significant improvements.
Recently, the Apache Hive community moved to a more frequent, incremental release schedule. So, a little while ago, we covered the Apache Hive 1.0.0 release and explained how it was renamed from 0.14.1 with only minor feature additions since 0.14.0.
Shortly thereafter, Apache Hive 1.1.0 was released (renamed from Apache Hive 0.15.0), which included more significant features—including Hive-on-Spark.
Learn how to read FIX message files directly with Hive, create a view to simplify user queries, and use a flattened Apache Parquet table to enable fast user queries with Impala.
The Financial Information eXchange (FIX) protocol is used widely by the financial services industry to communicate various trading-related activities. Each FIX message is a record that represents an action by a financial party, such as a new order or an execution report.
A Hive-on-Spark beta is now available via CDH parcel. Give it a try!
The Hive-on-Spark project (HIVE-7292) is one of the most watched projects in Apache Hive history. It has attracted developers from across the ecosystem, including from organizations such as Intel, MapR, IBM, and Cloudera, and gained critical help from the Spark community.
Many anxious users have inquired about its availability in the last few months.
The Apache Hive PMC has recently voted to release Hive 1.0.0 (formerly known as Hive 0.14.1).
This release is recognition of the work the Apache Hive community has done over the past nine years and is continuing to do. The Apache Hive 1.0.0 release is a codebase that was expected to be released as 0.14.1 but the community felt it was time to move to a 1.x.y release naming structure.
Interested in Hive-on-Spark progress? This new AMI gives you a hands-on experience.
Nearly one year ago, the Apache Hadoop community began to embrace Apache Spark as a powerful batch-processing engine. Today, many organizations and projects are augmenting their Hadoop capabilities with Spark. As part of this shift, the Apache Hive community is working to add Spark as an execution engine for Hive. The Hive-on-Spark work is being tracked by HIVE-7292 which is one of the most popular JIRAs in the Hadoop ecosystem.