780e6683a2
This commit contains the simpler parts from https://gerrit.cloudera.org/#/c/20602 This mainly means accessors for the header of the binary format and bounding box check (st_envIntersects). New tests for not yet covered functions / overloads are also added. For details of the binary format see be/src/exprs/geo/shape-format.h Differences from the PR above: Only a subset of functions are added. The criteria was: 1. the native function must be fully compatible with the Java version* 2. must not rely on (de)serializing the full geometry 3. the function must be tested 1 implies 2 because (de)serialization is not implemented yet in the original patch for >2d geometries, which would break compatibility for the Java version for ZYZ/XYM/XYZM geometries. *: there are 2 known differences: 1. NULL handling: the Java functions return error instead of NULL when getting a NULL parameter 2. st_envIntersects() doesn't check if the SRID matches - the Java library looks inconsistant about this Because the native functions are fairly safe replacements for the Java ones, they are always used when geospatial_library=HIVE_ESRI. Change-Id: I0ff950a25320549290a83a3b1c31ce828dd68e3c Reviewed-on: http://gerrit.cloudera.org:8080/23700 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.