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Real-time Query for Hadoop
C++ Java Python C Thrift Shell Other
Latest commit 7167950 May 16, 2016 @abehm abehm committed with Internal Jenkins Remove redundant test in
Change-Id: I7123cd5e19d79122af3b4fef2c092442b7a098f1
Reviewed-by: Alex Behm <>
Tested-by: Internal Jenkins
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be IMPALA-3163: Fix Decimal to Timestamp casting May 27, 2016
bin IMPALA-3619: disable IR symbols by default May 27, 2016
cmake_modules IMPALA-3223: Relocate squeasel and mustache directories May 27, 2016
common IMPALA-3369: Add ALTER TABLE SET COLUMN STATS statement. May 27, 2016
ext-data-source IMPALA-3384: add missing frontend -> ext-data-source dependency. May 2, 2016
fe IMPALA-3092: Set default value to NULL in AvroSchemaConverter May 27, 2016
infra IMPALA-3501: ee tests: detect build type and support different timeou… May 26, 2016
llvm-ir Misc. codegen utilties Feb 10, 2016
shell IMPALA-2336: Ignore trailing comments in non-interactive mode May 27, 2016
ssh_keys Move ssh keys from bin directory to fix packaging build break Jan 8, 2014
testdata Remove redundant test in May 28, 2016
tests Remove redundant test in May 28, 2016
thirdparty IMPALA-3223: Relocate squeasel and mustache directories May 27, 2016
www IMPALA-2198: Differentiate queries in exceptional states in web UI May 4, 2016
.gitignore Add .impala_compiler_opts to .gitignore May 9, 2016
CMakeLists.txt IMPALA-3223: Relocate squeasel and mustache directories May 27, 2016
LICENSE.txt Add text of Apache license May 8, 2014 Consolidate test and cluster logs under a single directory. Mar 28, 2016
NOTICE.txt Add NOTICE.txt file to Impala repo Jul 2, 2014 Fix link syntax for Mar 23, 2015 IMPALA-3594: Fix -build_shared_libs switch in May 24, 2016

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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