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LZ4 has a high compression mode that gets higher compression ratios (at the cost of higher compression time) while maintaining the fast decompression speed. This type of compression would be useful for workloads that write data once and read it many times. This adds support for specifying a compression level for the LZ4 codec. Compression level 1 is the current fast API. Compression levels between LZ4HC_CLEVEL_MIN (3) and LZ4HC_CLEVEL_MAX (12) use the high compression API. This lines up with the behavior of the lz4 commandline. TPC-H 42 scale comparison Compression codec | Avg Time (s) | Geomean Time (s) | Lineitem Size (GB) | Compression time for lineitem (s) ------------------+--------------+------------------+--------------------+------------------------------ Snappy | 2.75 | 2.08 | 8.76 | 7.436 LZ4 level 1 | 2.58 | 1.91 | 9.1 | 6.864 LZ4 level 3 | 2.58 | 1.93 | 7.9 | 43.918 LZ4 level 9 | 2.68 | 1.98 | 7.6 | 125.0 Zstd level 3 | 3.03 | 2.31 | 6.36 | 17.274 Zstd level 6 | 3.10 | 2.38 | 6.33 | 44.955 LZ4 level 3 is about 10% smaller in data size while being about as fast as regular LZ4. It compresses at about the same speed as Zstd level 6. Testing: - Ran perf-AB-test with lz4 high compression levels - Added test cases to decompress-test Change-Id: Ie7470ce38b8710c870cacebc80bc02cf5d022791 Reviewed-on: http://gerrit.cloudera.org:8080/23254 Reviewed-by: Impala Public Jenkins <impala-public-jenkins@cloudera.com> Tested-by: Impala Public Jenkins <impala-public-jenkins@cloudera.com>
Welcome to Impala
Lightning-fast, distributed SQL queries for petabytes of data stored in open data and table formats.
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 Apache Iceberg, HDFS, Apache HBase, Apache Kudu, Amazon S3, Azure Data Lake Storage, Apache Hadoop Ozone and more!
- Wide analytic SQL support, including window functions and subqueries.
- On-the-fly code generation using LLVM to generate lightning-fast code tailored specifically to each individual query.
- Support for the most commonly-used Hadoop file formats, including Apache Parquet and Apache ORC.
- Support for industry-standard security protocols, including Kerberos, LDAP and TLS.
- Apache-licensed, 100% open source.
More about Impala
The fastest way to try out Impala is a quickstart Docker container. You can try out running queries and processing data sets in Impala on a single machine without installing dependencies. It can automatically load test data sets into Apache Kudu and Apache Parquet formats and you can start playing around with Apache Impala SQL within minutes.
To learn more about Impala as a user or administrator, or to try Impala, please visit the Impala homepage. Detailed documentation for administrators and users is available at Apache Impala documentation.
If you are interested in contributing to Impala as a developer, or learning more about Impala's internals and architecture, visit the Impala wiki.
Supported Platforms
Impala only supports Linux at the moment. Impala supports x86_64 and has experimental support for arm64 (as of Impala 4.0). Impala Requirements contains more detailed information on the minimum CPU requirements.
Supported OS Distributions
Impala runs on Linux systems only. The supported distros are
- Ubuntu 16.04/18.04
- CentOS/RHEL 7/8
Other systems, e.g. SLES12, may also be supported but are not tested by the community.
Export Control Notice
This distribution uses cryptographic software and may be subject to export controls. Please refer to EXPORT_CONTROL.md for more information.
Build Instructions
See Impala's developer documentation to get started.
Detailed build notes has some detailed information on the project layout and build.