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liangbowen 2a39d697c0 [KYUUBI #5801] [DOC] Add spark-3.4 and spark-3.5 as supported Spark profiles to the docs of building from source
# 🔍 Description
## Issue References 🔗

## Describe Your Solution 🔧

Add docs for spark-3.4 and spark-3.5 as supported Spark profiles.

## 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 🧪

#### Behavior Without This Pull Request ⚰️

<img width="774" alt="image" src="https://github.com/apache/kyuubi/assets/1935105/29b0690d-574f-4b3c-ac70-50d5fb67a75e">

#### Behavior With This Pull Request 🎉

<img width="766" alt="image" src="https://github.com/apache/kyuubi/assets/1935105/58af356b-0f9c-4fe9-8f2b-8769ccebcc3a">

#### Related Unit Tests

---

# Checklists
## 📝 Author Self Checklist

- [x] My code follows the [style guidelines](https://kyuubi.readthedocs.io/en/master/contributing/code/style.html) of this project
- [x] I have performed a self-review
- [x] I have commented my code, particularly in hard-to-understand areas
- [x] I have made corresponding changes to the documentation
- [ ] My changes generate no new warnings
- [ ] I have added tests that prove my fix is effective or that my feature works
- [ ] New and existing unit tests pass locally with my changes
- [x] This patch was not authored or co-authored using [Generative Tooling](https://www.apache.org/legal/generative-tooling.html)

## 📝 Committer Pre-Merge Checklist

- [ ] Pull request title is okay.
- [ ] No license issues.
- [ ] Milestone correctly set?
- [ ] Test coverage is ok
- [ ] Assignees are selected.
- [ ] Minimum number of approvals
- [ ] No changes are requested

**Be nice. Be informative.**

Closes #5801 from bowenliang123/doc-spark-profiles.

Closes #5801

35254df09 [liangbowen] style
2b55824fd [liangbowen] add spark-3.4 and spark-3.5 to the docs of building from code

Authored-by: liangbowen <liangbowen@gf.com.cn>
Signed-off-by: Bowen Liang <liangbowen@gf.com.cn>
2023-12-04 08:46:17 +08:00
.github [KYUUBI #5779] [CI] Upgrade Github actions for Docker 2023-11-27 23:10:29 +08:00
.idea
bin
build [KYUUBI #5637] [INFRA] Add known contributor translation 2023-11-08 09:42:48 +08:00
charts/kyuubi [KYUUBI #5631] [K8S][HELM] Set session affinity if needed in helm chart 2023-11-22 12:14:27 +08:00
conf [KYUUBI #5729] Use G1GC as Java option example in kyuubi-env template 2023-11-22 15:44:14 +08:00
dev [KYUUBI #5395] Bump netty from 4.1.93.Final to 4.1.100.Final 2023-11-13 19:40:56 +08:00
docker [KYUUBI #5640] Upgrade playground to Kyuubi 1.8.0 and Spark 3.4.1 2023-11-08 10:44:20 +08:00
docs [KYUUBI #5801] [DOC] Add spark-3.4 and spark-3.5 as supported Spark profiles to the docs of building from source 2023-12-04 08:46:17 +08:00
extensions [KYUUBI #5780][AUTHZ][FOLLOWUP] Format PermanentViewMarker tree string 2023-12-01 13:09:37 +08:00
externals [KYUUBI #5807] Simple norm the use of kyuubi.operation.result.arrow.timestampAsString and kyuubi.operation.result.format 2023-12-03 20:16:24 +08:00
integration-tests [KYUUBI #5782] Flink Engine GetInfo support CLI_ODBC_KEYWORDS 2023-11-27 22:14:41 +08:00
kyuubi-assembly
kyuubi-common [KYUUBI #5767] Extract common utils for assembling key value pairs with config option prefix in processbuilder 2023-12-02 01:25:02 +08:00
kyuubi-ctl [KYUUBI #5717] Infer the proxy user automatically for delete batch operation 2023-11-17 20:52:40 +08:00
kyuubi-events
kyuubi-ha
kyuubi-hive-beeline
kyuubi-hive-jdbc [KYUUBI #5713] Backport HIVE-27271: Client connection to HS2 fails when transportMode=http, ssl=true, sslTrustStore specified without trustStorePassword in the JDBC URL 2023-11-17 19:31:59 +08:00
kyuubi-hive-jdbc-shaded
kyuubi-metrics
kyuubi-rest-client [KYUUBI #5717] Infer the proxy user automatically for delete batch operation 2023-11-17 20:52:40 +08:00
kyuubi-server [KYUUBI #5767] Extract common utils for assembling key value pairs with config option prefix in processbuilder 2023-12-02 01:25:02 +08:00
kyuubi-util
kyuubi-util-scala [KYUUBI #5767] Extract common utils for assembling key value pairs with config option prefix in processbuilder 2023-12-02 01:25:02 +08:00
kyuubi-zookeeper [KYUUBI #5412] Resolve the relative zk configuration dir based on KYUUBI_HOME 2023-10-27 10:48:22 +08:00
licenses
licenses-binary [KYUUBI #4152] Enhance LDAP authentication 2023-02-03 05:48:02 +00:00
tools/spark-block-cleaner
.asf.yaml
.dockerignore
.gitattributes
.gitignore [KYUUBI #5637] [INFRA] Add known contributor translation 2023-11-08 09:42:48 +08:00
.rat-excludes [KYUUBI #5484] Remove legacy Web UI 2023-10-25 13:36:00 +08:00
.readthedocs.yaml
.scalafmt.conf
codecov.yml [KYUUBI #5501] Update codecov token and fix codecov reporting on PRs 2023-10-26 14:57:36 +08:00
CONTRIBUTING.md
LICENSE [KYUUBI #5484] Remove legacy Web UI 2023-10-25 13:36:00 +08:00
LICENSE-binary [KYUUBI #5671] Bump axios from 0.27.2 to 1.6.0 in /kyuubi-server/web-ui 2023-11-13 19:32:54 +08:00
NOTICE
NOTICE-binary
pom.xml [KYUUBI #5464] JDBC Engine supports MySQL 2023-11-24 21:17:17 +08:00
README.md
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.