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Cheng Pan fe5377e0fa
[KYUUBI #5957] Flink engine should not load kyuubi-defaults.conf
# 🔍 Description

This is the root cause of #5957. Which is accidentally introduced in b315123a6b, thus affects 1.8.0, 1.8.1, 1.8.2, 1.9.0, 1.9.1.

`kyuubi-defaults.conf` is kind of a server side configuration file, all Kyuubi confs engine required should be passed via CLI args to sub-process.

## Types of changes 🔖

- [x] 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 🧪

Pass GHA.

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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 #6455 from pan3793/flink-conf-load.

Closes #5957

2972fbc98 [Cheng Pan] Flink engine should not load kyuubi-defaults.conf

Authored-by: Cheng Pan <chengpan@apache.org>
Signed-off-by: Cheng Pan <chengpan@apache.org>
2024-06-06 16:06:51 +08:00
.github [KYUUBI #6452] Add cross test for Spark 4.0 2024-06-05 15:24:27 +08:00
.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 #6305][FOLLOWUP] Improve package Spark SQL engine both Scala 2.12 and 2.13 2024-05-15 12:43:09 +08:00
charts/kyuubi [KYUUBI #6430] livenessProbe uses absolute path based on KYUUBI_HOME 2024-05-30 12:11:25 +08:00
conf [KYUUBI #6268] Specify logDir for RollingFile filePattern 2024-04-09 17:27:56 +08:00
dev [KYUUBI #6419] Bump Jetty 9.4.54.v20240208 2024-05-24 18:23:26 +08:00
docker [KYUUBI #6323] Upgrade Spark 3.4.3 2024-04-24 16:07:14 +08:00
docs [KYUUBI #6440] Fix casing in kubectl commands for serviceaccount creation 2024-06-03 11:12:29 +08:00
extensions [KYUUBI #6427] Extract data lake artifact names as maven properties 2024-06-05 15:23:45 +08:00
externals [KYUUBI #5957] Flink engine should not load kyuubi-defaults.conf 2024-06-06 16:06:51 +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 #6439] kyuubi-util-scala test jar leaked to compile scope 2024-06-04 11:31:58 +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 #4847][FOLLOWUP] Exclude the alive probe sessions in terminating checker 2024-05-09 08:48:21 -07:00
kyuubi-hive-beeline [KYUUBI #6251] Improve kyuubi-beeline help message 2024-04-12 19:21:08 +08:00
kyuubi-hive-jdbc [KYUUBI #6396][FOLLOWUP] Avoid NPE 2024-05-27 06:31:39 +00:00
kyuubi-hive-jdbc-shaded [KYUUBI #6391] Bump Arrow from 15.0.2 to 16.0.0 2024-05-20 19:26:15 +08:00
kyuubi-metrics [KYUUBI #6392] Support javax.servlet and jakarta.servlet co-exist 2024-05-20 21:09:30 +08:00
kyuubi-rest-client [KYUUBI #6392] Support javax.servlet and jakarta.servlet co-exist 2024-05-20 21:09:30 +08:00
kyuubi-server [KYUUBI #6427] Extract data lake artifact names as maven properties 2024-06-05 15:23:45 +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 #6392] Support javax.servlet and jakarta.servlet co-exist 2024-05-20 21:09:30 +08:00
python [KYUUBI #6445] Normalize extra name for optional Python distribution dependencies 2024-06-06 15:06:37 +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 #6416] Generate flattened POM 2024-05-24 18:20:25 +08:00
.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 #6392] Support javax.servlet and jakarta.servlet co-exist 2024-05-20 21:09:30 +08:00
NOTICE [KYUUBI #5953] [LICENSE] Update NOTICE 2024-01-10 19:29:01 +08:00
NOTICE-binary [KYUUBI #6391] Bump Arrow from 15.0.2 to 16.0.0 2024-05-20 19:26:15 +08:00
pom.xml [KYUUBI #6427] Extract data lake artifact names as maven properties 2024-06-05 15:23:45 +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.