0fe8de0f3f
Contains the following improvements to the Impala queries as OpenTelemetry traces custom cluster tests: 1. Supporting code for asserting traces was moved to 'tests/util/otel_trace.py'. The moved code was modified to remove all references to 'self'. Since this code used 'self.assert_impalad_log_contains', it had to be modified so the caller provides the correct log file path to search. The '__find_span_log' function was updated to call a new generic file grep function to run the necessary log file search regex. All other code was moved unmodified. 2. Classes 'TestOtelTraceSelectsDMLs' and 'TestOtelTraceDDLs' contained a total of 11 individual tests that used the 'unique_database' fixture. When this fixture is used in a test, it results in two DDLs being run before the test to drop/create the database and one DDL being run after the test to drop the database. These classes now create a test database once during 'setup_class' and drop it once during 'teardown_class' because creating a new database for each test was unnecessary. This change dropped test execution time from about 97 seconds to about 77 seconds. 3. Each test now has comments describing what the test is asserting. 4. The unnecessary sleep in 'test_query_exec_fail' was removed saving five seconds of test execution time. 5. New test 'test_dml_insert_fail' added. Previously, the situation where an insert DML failed was not tested. The test passed without any changes to backend code. 6. Test 'test_ddl_createtable_fail' is greatly simplified by using a debug action to fail the query instead of multiple parallel queries where one dropped the database the other was inserting into. The simplified setup eliminated test flakiness caused by timing differences and sped up test execution by about 5 seconds. 7. Fixed test flakiness was caused by timing issues. Depending on when the close process was initiated, span events are sometimes in the QueryExecution span and sometimes in the Close span. Test assertions cannot handle these situations. All span event assertions for the Close span were removed. IMPALA-14334 will fix these assertions. 8. The function 'query_id_from_ui' which retrieves the query profile using the Impala debug ui now makes multiple attempts to retrieve the query. In slower test situations, such as ASAN, the query may not yet be available when the function is called initially which used to cause tests to fail. This test flakiness is now eliminated through the addition of the retries. Testing accomplished by running tests in test_otel_trace.py both locally and in a full Jenkins build. Generated-by: Github Copilot (Claude Sonnet 3.7) Change-Id: I0c3e0075df688c7ae601c6f2e5743f56d6db100e Reviewed-on: http://gerrit.cloudera.org:8080/23385 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.