922443da46
On the first cut of creating the Calcite planner, the Calcite planner was standalone and ran its own JniFrontend. In the current version, the parsing, validating, and single node planning is called from the Impala framework. There is some code in the first cut regarding the "ImpalaTypeCoercionFactory" class which handles deriving the correct data type for various expressions, for instance (found in exprs.test): select count(*) from alltypesagg where 10.1 in (tinyint_col, smallint_col, int_col, bigint_col, float_col, double_col) Without this patch, the query returns the following error: UDF ERROR: Decimal expression overflowed This code can be found in CalciteValidator.java, but was accidentally omitted from CalciteAnalysisDriver. Change-Id: I74c4c714504400591d1ec6313f040191613c25d9 Reviewed-on: http://gerrit.cloudera.org:8080/23039 Tested-by: Impala Public Jenkins <impala-public-jenkins@cloudera.com> Reviewed-by: Steve Carlin <scarlin@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.