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Cheng Pan 6fbb301bbd [KYUUBI #6363] [INFRA] Increase CI concurrency
# 🔍 Description

Previously, we were asked to limit the job concurrency to 10, while the new policy is more relaxed.

> All workflows SHOULD have a job concurrency level less than or equal to 15. Just because 20 is the max, doesn't mean you should strive for 20.

https://infra.apache.org/github-actions-policy.html

## Types of changes 🔖

- [ ] Bugfix (non-breaking change which fixes an issue)
- [ ] New feature (non-breaking change which adds functionality)
- [ ] Breaking change (fix or feature that would cause existing functionality to change)

## Test Plan 🧪

Monitor CI

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# Checklist 📝

- [x] This patch was not authored or co-authored using [Generative Tooling](https://www.apache.org/legal/generative-tooling.html)

**Be nice. Be informative.**

Closes #6363 from pan3793/ci-con.

Closes #6363

101121aa9 [Cheng Pan] [INFRA] Increase CI concurrency

Authored-by: Cheng Pan <chengpan@apache.org>
Signed-off-by: Cheng Pan <chengpan@apache.org>
2024-05-06 04:45:36 +00:00
.github [KYUUBI #6363] [INFRA] Increase CI concurrency 2024-05-06 04:45:36 +00:00
.idea [KYUUBI #5252] [MINOR] Remove incubator link 2023-09-05 14:01:40 +08:00
bin [KYUUBI #6239] Rename beeline to kyuubi-beeline 2024-04-03 18:35:38 +08:00
build [KYUUBI #6297] Package Spark SQL engine both Scala 2.12 and 2.13 2024-04-15 09:44:44 +08:00
charts/kyuubi [KYUUBI #6312][HELM] Allow attaching annotations to service account 2024-04-17 00:05:56 +08:00
conf [KYUUBI #6268] Specify logDir for RollingFile filePattern 2024-04-09 17:27:56 +08:00
dev [KYUUBI #6294] Simplify Netty and gRPC dependency management 2024-04-17 15:41:07 +08:00
docker [KYUUBI #6323] Upgrade Spark 3.4.3 2024-04-24 16:07:14 +08:00
docs [KYUUBI #6338] Support connecting Kyuubi using Hive JDBC driver 4.0 2024-04-29 14:06:53 +08:00
extensions [KYUUBI #6315] Spark 3.5: MaxScanStrategy supports DSv2 2024-04-17 16:29:50 +08:00
externals [KYUUBI #6244][TEST] Fix test logs upload error 2024-04-30 14:59:42 +08:00
integration-tests [KYUUBI #6253] Support running JDBC engine on YARN AM 2024-04-15 17:39:17 +08:00
kyuubi-assembly [RELEASE] Bump 1.10.0-SNAPSHOT 2024-03-13 14:24:49 +08:00
kyuubi-common [KYUUBI #6338] Support connecting Kyuubi using Hive JDBC driver 4.0 2024-04-29 14:06:53 +08:00
kyuubi-ctl [KYUUBI #6216] Support to deny some client ips to make connection 2024-04-07 16:32:00 +08:00
kyuubi-events [KYUUBI #6290] Add custom exception serialization for SparkOperationEvent 2024-04-11 19:29:41 +08:00
kyuubi-ha [KYUUBI #6244][TEST] Fix test logs upload error 2024-04-30 14:59:42 +08:00
kyuubi-hive-beeline [KYUUBI #6251] Improve kyuubi-beeline help message 2024-04-12 19:21:08 +08:00
kyuubi-hive-jdbc [KYUUBI #6221] Fix parameter replacement issue caused by incorrect sql split 2024-03-29 10:33:04 +08:00
kyuubi-hive-jdbc-shaded [KYUUBI #6293] Upgrade Arrow from 12.0.0 to 15.0.2 2024-04-15 16:20:36 +08:00
kyuubi-metrics [RELEASE] Bump 1.10.0-SNAPSHOT 2024-03-13 14:24:49 +08:00
kyuubi-rest-client [KYUUBI #6049] Support to filter sessions/operations with session type 2024-04-21 18:18:19 -07:00
kyuubi-server [KYUUBI #6244][TEST] Fix test logs upload error 2024-04-30 14:59:42 +08:00
kyuubi-util [RELEASE] Bump 1.10.0-SNAPSHOT 2024-03-13 14:24:49 +08:00
kyuubi-util-scala [RELEASE] Bump 1.10.0-SNAPSHOT 2024-03-13 14:24:49 +08:00
kyuubi-zookeeper [RELEASE] Bump 1.10.0-SNAPSHOT 2024-03-13 14:24:49 +08:00
licenses
licenses-binary [KYUUBI #5674][LICENSE][FOLLOWUP] Update license files 2024-01-30 13:47:33 +08:00
python [KYUUBI #5686][FOLLOWUP] Rename pyhive to python 2024-04-09 20:30:02 +08:00
.asf.yaml [KYUUBI #5342] Add label hacktoberfest to project 2023-09-28 12:13:16 +08:00
.dockerignore
.gitattributes [KYUUBI #5335] Set markdown file EOL 2023-09-27 22:02:09 +08:00
.gitignore [KYUUBI #6071] Add .java-version into git ignore 2024-02-22 06:09:18 +00:00
.rat-excludes [KYUUBI #5686][FOLLOWUP] Rename pyhive to python 2024-04-09 20:30:02 +08:00
.readthedocs.yaml
.scalafmt.conf [KYUUBI #5007] Bump Scalafmt from 3.7.4 to 3.7.5 2023-06-30 11:34:36 +08:00
codecov.yml [KYUUBI #5501] Update codecov token and fix codecov reporting on PRs 2023-10-26 14:57:36 +08:00
CONTRIBUTING.md [KYUUBI #6068] Remove community section from user docs 2024-02-21 05:20:42 +00:00
LICENSE [KYUUBI #5484] Remove legacy Web UI 2023-10-25 13:36:00 +08:00
LICENSE-binary [KYUUBI #6293] Upgrade Arrow from 12.0.0 to 15.0.2 2024-04-15 16:20:36 +08:00
NOTICE [KYUUBI #5953] [LICENSE] Update NOTICE 2024-01-10 19:29:01 +08:00
NOTICE-binary [KYUUBI #6293] Upgrade Arrow from 12.0.0 to 15.0.2 2024-04-15 16:20:36 +08:00
pom.xml [KYUUBI #6323] Upgrade Spark 3.4.3 2024-04-24 16:07:14 +08:00
README.md [KYUUBI #5432] Fix typo in README.md 2023-10-16 22:03:57 +08:00
scalastyle-config.xml

Kyuubi logo

Project - Documentation - Who's using

Apache Kyuubi

Apache Kyuubi™ is a distributed and multi-tenant gateway to provide serverless SQL on data warehouses and lakehouses.

What is Kyuubi?

Kyuubi provides a pure SQL gateway through Thrift JDBC/ODBC interface for end-users to manipulate large-scale data with pre-programmed and extensible Spark SQL engines. This "out-of-the-box" model minimizes the barriers and costs for end-users to use Spark at the client side. At the server-side, Kyuubi server and engines' multi-tenant architecture provides the administrators a way to achieve computing resource isolation, data security, high availability, high client concurrency, etc.

  • A HiveServer2-like API
  • Multi-tenant Spark Support
  • Running Spark in a serverless way

Target Users

Kyuubi's goal is to make it easy and efficient for anyone to use Spark(maybe other engines soon) and facilitate users to handle big data like ordinary data. Here, anyone means that users do not need to have a Spark technical background but a human language, SQL only. Sometimes, SQL skills are unnecessary when integrating Kyuubi with Apache Superset, which supports rich visualizations and dashboards.

In typical big data production environments with Kyuubi, there should be system administrators and end-users.

  • System administrators: A small group consists of Spark experts responsible for Kyuubi deployment, configuration, and tuning.
  • End-users: Focus on business data of their own, not where it stores, how it computes.

Additionally, the Kyuubi community will continuously optimize the whole system with various features, such as History-Based Optimizer, Auto-tuning, Materialized View, SQL Dialects, Functions, etc.

Usage scenarios

Port workloads from HiveServer2 to Spark SQL

In typical big data production environments, especially secured ones, all bundled services manage access control lists to restricting access to authorized users. For example, Hadoop YARN divides compute resources into queues. With Queue ACLs, it can identify and control which users/groups can take actions on particular queues. Similarly, HDFS ACLs control access of HDFS files by providing a way to set different permissions for specific users/groups.

Apache Spark is a unified analytics engine for large-scale data processing. It provides a Distributed SQL Engine, a.k.a, the Spark Thrift Server(STS), designed to be seamlessly compatible with HiveServer2 and get even better performance.

HiveServer2 can identify and authenticate a caller, and then if the caller also has permissions for the YARN queue and HDFS files, it succeeds. Otherwise, it fails. However, on the one hand, STS is a single Spark application. The user and queue to which STS belongs are uniquely determined at startup. Consequently, STS cannot leverage cluster managers such as YARN and Kubernetes for resource isolation and sharing or control the access for callers by the single user inside the whole system. On the other hand, the Thrift Server is coupled in the Spark driver's JVM process. This coupled architecture puts a high risk on server stability and makes it unable to handle high client concurrency or apply high availability such as load balancing as it is stateful.

Kyuubi extends the use of STS in a multi-tenant model based on a unified interface and relies on the concept of multi-tenancy to interact with cluster managers to finally gain the ability of resources sharing/isolation and data security. The loosely coupled architecture of the Kyuubi server and engine dramatically improves the client concurrency and service stability of the service itself.

DataLake/Lakehouse Support

The vision of Kyuubi is to unify the portal and become an easy-to-use data lake management platform. Different kinds of workloads, such as ETL processing and BI analytics, can be supported by one platform, using one copy of data, with one SQL interface.

  • Logical View support via Kyuubi DataLake Metadata APIs
  • Multiple Catalogs support
  • SQL Standard Authorization support for DataLake(coming)

Cloud Native Support

Kyuubi can deploy its engines on different kinds of Cluster Managers, such as, Hadoop YARN, Kubernetes, etc.

The Kyuubi Ecosystem(present and future)

The figure below shows our vision for the Kyuubi Ecosystem. Some of them have been realized, some in development, and others would not be possible without your help.

Online Documentation Documentation Status

Quick Start

Ready? Getting Started with Kyuubi.

Contributing

Project & Community Status

Aside

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 stand for end-to-end multi-tenancy support of this project.