mirror of
https://github.com/apache/impala.git
synced 2026-01-04 09:00:56 -05:00
19b6bf0201
This only enforced the defaults in Hive. Users how manually choose to change the schema in Hive may trigger these new analysis exceptions in this commit unnecessarily. The Hive issue tracking the length restrictions is https://issues.apache.org/jira/browse/HIVE-9815 Change-Id: Ia30f286193fe63e51a10f0c19f12b848c4b02f34 Reviewed-on: http://gerrit.cloudera.org:8080/721 Reviewed-by: Jim Apple <jbapple@cloudera.com> Tested-by: Internal Jenkins
Welcome to Impala
Lightning-fast, distributed SQL queries for petabytes of data stored in Apache Hadoop clusters.
Impala is a modern, massively-distributed, massively-parallel, C++ query engine that lets you analyze, transform and combine data from a variety of data sources:
- Best of breed performance and scalability.
- Support for data stored in HDFS, Apache HBase and Amazon S3.
- Wide analytic SQL support, including window functions and subqueries.
- On-the-fly code generation using LLVM to generate CPU-efficient code tailored specifically to each individual query.
- Support for the most commonly-used Hadoop file formats, including the Apache Parquet (incubating) project.
- Apache-licensed, 100% open source.
More about Impala
To learn more about Impala as a business user, or to try Impala live or in a VM, please visit the Impala homepage.
If you are interested in contributing to Impala as a developer, or learning more about Impala's internals and architecture, visit the Impala wiki.