commit | 9355c999d30aabe047e1f318bac295985557931e | [log] [tgz] |
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author | ulysses-you <ulyssesyou18@gmail.com> | Mon Apr 19 17:09:55 2021 +0800 |
committer | ulysses-you <ulyssesyou18@gmail.com> | Mon Apr 19 17:10:12 2021 +0800 |
tree | 4864db431f8a18a00b1b6a844ae2f0959463e8ff | |
parent | b15b42cadf2d9cf8bd5ffa3d4c30c443bd7596e3 [diff] |
[KYUUBI #543] [TESTS] Add test for scheduler pool <!-- Thanks for sending a pull request! Here are some tips for you: 1. If this is your first time, please read our contributor guidelines: https://kyuubi.readthedocs.io/en/latest/community/contributions.html 2. If the PR is related to an issue in https://github.com/NetEase/kyuubi/issues, add '[KYUUBI #XXXX]' in your PR title, e.g., '[KYUUBI #XXXX] Your PR title ...'. 3. If the PR is unfinished, add '[WIP]' in your PR title, e.g., '[WIP][KYUUBI #XXXX] Your PR title ...'. --> ### _Why are the changes needed?_ <!-- Please clarify why the changes are needed. For instance, 1. If you add a feature, you can talk about the use case of it. 2. If you fix a bug, you can clarify why it is a bug. --> Improve test coverage. ### _How was this patch tested?_ Pass `org.apache.kyuubi.engine.spark.SchedulerPoolSuite`. Closes #543 from ulysses-you/add-scheduler-pool-test. Closes #543 f5563b1 [ulysses-you] trait 57938a1 [ulysses-you] init Authored-by: ulysses-you <ulyssesyou18@gmail.com> Signed-off-by: ulysses-you <ulyssesyou18@gmail.com> (cherry picked from commit cacc2b05b344d99ade1c5d2f37f4ce27a556373e) Signed-off-by: ulysses-you <ulyssesyou18@gmail.com>
Kyuubi is a high-performance universal JDBC and SQL execution engine, built on top of Apache Spark. The goal of Kyuubi is to facilitate users to handle big data like ordinary data.
It provides a standardized JDBC interface with easy-to-use data access in big data scenarios. End-users can focus on developing their own business systems and mining data value without having to be aware of the underlying big data platform (compute engines, storage services, metadata management, etc.).
Kyuubi relies on Apache Spark to provide high-performance data query capabilities, and every improvement in the engine‘s capabilities can help Kyuubi’s performance make a qualitative leap. In addition, Kyuubi improves ad-hoc responsiveness through the engine caching, and enhances concurrency through horizontal scaling and load balancing. It provides complete authentication and authentication services to ensure data and metadata security. It provides robust high availability and load balancing to help you guarantee the SLA commitments. It provides a two-level elastic resource management architecture to effectively improve resource utilization while covering the performance and response requirements of all scenarios including interactive, or batch processing and point queries, or full table scans. It embraces Spark and builds an ecosystem on top of it, which allows Kyuubi to quickly expand its existing ecosystem and introduce new features, such as cloud-native support and Data Lake/Lake House
support.
The vision of Kyuubi is to build on top of Apache Spark and Data Lake technologies to unify the portal and become an ideal data lake management platform. It can support data processing e.g. ETL, and analytics e.g. BI in a pure SQL way. All workloads can be done on one platform, using one copy of data, with one SQL interface.
Since Kyuubi 1.0.0, the Kyuubi online documentation is hosted by https://readthedocs.org/. You can find the specific version of Kyuubi documentation as listed below.
For 0.8 and earlier versions, please check the Github Pages directly.
Ready? Getting Started with Kyuubi.
All bits of help are welcome. You can make various types of contributions to Kyuubi, including the following but not limited to,
Before you start, we recommend that you check the Contribution Guidelines first.
The project took its name from a character of a popular Japanese manga - Naruto
. The character is named Kyuubi Kitsune/Kurama
, which is a nine-tailed fox in mythology. Kyuubi
spread the power and spirit of fire, which is used here to represent the powerful Apache Spark. Its nine tails stands for end-to-end multi-tenancy support of this project.
This project is licensed under the Apache 2.0 License. See the LICENSE file for details.