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Real-time Query for Hadoop
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Latest commit 53cc3a3 @abehm abehm committed with Internal Jenkins Fix OOM when data loading with the new Hive SNAPSHOT.
This patch is required for upgrading thirdparty.

After upgrading thirdparty, Hive OOMs in data loading TPCDS.
This patch fixes the OOM, but I have no idea why exactly it works.
I had tried several other approaches like increasing the
mapred and JVM heap memory to no avail.

Change-Id: I3c69e4c3bf0f24e0c3b6272c946f71c17e312e01
Reviewed-on: http://gerrit.cloudera.org:8080/2145
Reviewed-by: Alex Behm <alex.behm@cloudera.com>
Tested-by: Internal Jenkins

README.md

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.

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