| commit | 653e5388dd34252c3c6357172a4b81f030b4651f | [log] [tgz] |
|---|---|---|
| author | Andrew Sherman <asherman@cloudera.com> | Mon Sep 30 13:53:12 2024 -0700 |
| committer | Impala Public Jenkins <impala-public-jenkins@cloudera.com> | Wed Oct 09 21:46:47 2024 +0000 |
| tree | a2869dc0840269dc1c21e2c97d1097cda81ec296 | |
| parent | b6b953b48e05b64e7f0c9d1cb2623148671ffce2 [diff] |
IMPALA-13408: use a specific flag for the topic prefix cluster identifier. The cluster_id flag was introduced in IMPALA-12426 to identify Impala clusters in systems where a single query_log table could be shared. In IMPALA-13208 the cluster_id flag was reused as a prefix to topic names for backend membership, to allow sub-clusters of backends within a Statestore service. There have been some problems with the interaction of these two usages. An important difference is that the query_log cluster_id must be set only on coordinators, whereas the topic prefix cluster_id must be set simultaneously on coordinators, executors, and admission daemons (if present). If a system is started with cluster_id set only on coordinators then there are split-brain problems where coordinators and executors are tracked in different topics. In addition, the query_log cluster_id is more likely to be user-settable as it is used for data in query_log which will be read by humans, who may want to write queries selecting data from their ‘production’ or ‘dev’ clusters. Avoid these problems by using a separate flag for the topic prefix cluster_id ‘cluster_membership_topic_id’. Change-Id: Icd3f7e1c73c00a7aaeee79ecb461209e3939c422 Reviewed-on: http://gerrit.cloudera.org:8080/21867 Reviewed-by: Impala Public Jenkins <impala-public-jenkins@cloudera.com> Tested-by: Impala Public Jenkins <impala-public-jenkins@cloudera.com>
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:
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.
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.
Impala runs on Linux systems only. The supported distros are
Other systems, e.g. SLES12, may also be supported but are not tested by the community.
This distribution uses cryptographic software and may be subject to export controls. Please refer to EXPORT_CONTROL.md for more information.
See Impala's developer documentation to get started.
Detailed build notes has some detailed information on the project layout and build.