a41c5cbfdd
JniFrontend.getDbs() returns the thrift representation of all the dbs. This might trigger multiple getPartialCatalogObject requests to catalogd and could fail in InconsistentMetadataFetchException, e.g. if a db is removed after coordinator fetching the db name list and before coordinator fetching the msDb of that db. This patch fixes the issue by retrying the above steps when hitting InconsistentMetadataFetchException, similar to what other methods in Frontend do. Adds getThriftDbs() in Frontend to directly return the thrift db list so JniFrontend can use it directly and the retry can be added inside Frontend.java. TestAuthorization.test_local_catalog_show_dbs_with_transient_db is an existing test to verify a similar problem. Running this test with authorization disabled can reproduce the current bug. So this patch extracts the test code into TestLocalCatalogRetries._run_show_dbs_with_transient_db() and share it in both authz enabled and disabled tests. Tests - Ran TestLocalCatalogRetries.test_show_dbs_retry 60 times. Without the fix, it fails in about a dozen times. Change-Id: Ib337f88a2ac0f35142417f6cee51d30497f12845 Reviewed-on: http://gerrit.cloudera.org:8080/23402 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.