585ee48dc7
This change breaks out runtime filter memory consumption from the query-wide tracker to improve debuggability of memory limit exceeded errors. Testing: ran exhaustive tests, ran local and cluster stress tests. Change-Id: I9f28f3b55b5c62e6f0f9838c5947c9446d444d20 Reviewed-on: http://gerrit.cloudera.org:8080/3247 Reviewed-by: Tim Armstrong <tarmstrong@cloudera.com> Reviewed-by: Michael Ho <kwho@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.
Building Impala
This Apache Incubator repository is currently not buildable but has the complete source code for Impala minus some third-party dependences. See https://github.com/cloudera/Impala for the buildable Impala source and https://issues.cloudera.org/browse/IMPALA-3223 to track progress on making this repository buildable.