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[KYUUBI #6840] Fix PodMonitor pods selection
### Why are the changes needed?

I am using the podminitor of kyuubi metrics, But I found using the podmonitor's selector.matchLabels can not select correct pods . So I fix it .

I also changed the values.yaml to add an example of podmonitor to improve the usability.

### How was this patch tested?

```
helm install kyuubi .
# kubectl get podmonitor kyuubi -oyaml
apiVersion: monitoring.coreos.com/v1
kind: PodMonitor
metadata:
  annotations:
    meta.helm.sh/release-name: kyuubi
    meta.helm.sh/release-namespace: default
  creationTimestamp: "2024-12-06T07:46:12Z"
  generation: 1
  labels:
    app.kubernetes.io/instance: kyuubi
    app.kubernetes.io/managed-by: Helm
    app.kubernetes.io/name: kyuubi
    app.kubernetes.io/version: 1.8.0
    helm.sh/chart: kyuubi-0.1.0
  name: kyuubi
  namespace: default
  resourceVersion: "7583800"
  uid: 0dd11e43-d126-434e-988a-7f1914586e2b
spec:
  podMetricsEndpoints:
  - path: /metrics
    port: prometheus
  selector:
    matchLabels:
      app.kubernetes.io/instance: kyuubi
      app.kubernetes.io/name: kyuubi
# kubectl get po -l app.kubernetes.io/instance=kyuubi
NAME       READY   STATUS    RESTARTS   AGE
kyuubi-0   1/1     Running   0          24m
kyuubi-1   1/1     Running   0          22m
# kubectl get po -l  app.kubernetes.io/name=kyuubi
NAME       READY   STATUS    RESTARTS   AGE
kyuubi-0   1/1     Running   0          24m
kyuubi-1   1/1     Running   0          23m
```
### Was this patch authored or co-authored using generative AI tooling?

No

Closes #6840 from zhifanggao/change_podmonitor.

Closes #6840

092f13f87 [zhifanggao] change the podmonitor to select pods correctly

Authored-by: zhifanggao <28681649@qq.com>
Signed-off-by: Cheng Pan <chengpan@apache.org>
(cherry picked from commit 99e27d4f99)
Signed-off-by: Cheng Pan <chengpan@apache.org>
2024-12-09 21:49:16 +08:00
.github [KYUUBI #6837] [INFRA] Disable K8s CI image GHA cache 2024-12-04 20:34:05 +08:00
.idea
bin [KYUUBI #6609] Bump Spark 3.5.2 2024-08-14 20:57:06 +08:00
build [KYUUBI #6762] [BUILD] cleanup dockerfile warnings 2024-10-22 13:38:02 +08:00
charts/kyuubi [KYUUBI #6840] Fix PodMonitor pods selection 2024-12-09 21:49:16 +08:00
conf [KYUUBI #6268] Specify logDir for RollingFile filePattern 2024-04-09 17:27:56 +08:00
dev [KYUUBI #6836] Ship kafka-clients in binary distribution tarball without compression libs 2024-12-05 13:59:54 +08:00
docker [KYUUBI #6762] [BUILD] cleanup dockerfile warnings 2024-10-22 13:38:02 +08:00
docs [KYUUBI #6829] Add metrics for batch pending max elapse time 2024-12-05 18:12:50 +08:00
extensions [KYUUBI #6820] Explicitly disable attach-scaladocs for pure Java modules 2024-11-22 17:12:18 +08:00
externals Bump 1.10.1-SNAPSHOT 2024-11-01 10:22:38 +08:00
integration-tests Bump 1.10.1-SNAPSHOT 2024-11-01 10:22:38 +08:00
kyuubi-assembly Bump 1.10.1-SNAPSHOT 2024-11-01 10:22:38 +08:00
kyuubi-common [KYUUBI #6829] Add metrics for batch pending max elapse time 2024-12-05 18:12:50 +08:00
kyuubi-ctl Bump 1.10.1-SNAPSHOT 2024-11-01 10:22:38 +08:00
kyuubi-events Bump 1.10.1-SNAPSHOT 2024-11-01 10:22:38 +08:00
kyuubi-ha [KYUUBI #6790] Fix engine cannot exit when gracefully stopped 2024-11-04 21:17:25 -08:00
kyuubi-hive-beeline Bump 1.10.1-SNAPSHOT 2024-11-01 10:22:38 +08:00
kyuubi-hive-jdbc [KYUUBI #6828] Clean up and improve error message for KyuubiBaseResultSet 2024-11-29 11:49:00 +08:00
kyuubi-hive-jdbc-shaded Bump 1.10.1-SNAPSHOT 2024-11-01 10:22:38 +08:00
kyuubi-metrics [KYUUBI #6829] Add metrics for batch pending max elapse time 2024-12-05 18:12:50 +08:00
kyuubi-rest-client Bump 1.10.1-SNAPSHOT 2024-11-01 10:22:38 +08:00
kyuubi-server [KYUUBI #6829] Add metrics for batch pending max elapse time 2024-12-05 18:12:50 +08:00
kyuubi-util Bump 1.10.1-SNAPSHOT 2024-11-01 10:22:38 +08:00
kyuubi-util-scala Bump 1.10.1-SNAPSHOT 2024-11-01 10:22:38 +08:00
kyuubi-zookeeper Bump 1.10.1-SNAPSHOT 2024-11-01 10:22:38 +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 #6485] Fix the Presto TABLE NOT FOUND error message that failed to match 2024-08-12 08:38:09 +00:00
.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 #6587] Periodically expire temp files and operation logs on server to avoid memeory leak by Files.deleteOnExit 2024-08-28 17:13:27 +08:00
.rat-excludes [KYUUBI #5686][FOLLOWUP] Rename pyhive to python 2024-04-09 20:30:02 +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 [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 #6836] Ship kafka-clients in binary distribution tarball without compression libs 2024-12-05 13:59:54 +08:00
NOTICE [KYUUBI #6434] Add footnote about pyhive origin 2024-06-24 10:30:51 +08:00
NOTICE-binary [KYUUBI #6836] Ship kafka-clients in binary distribution tarball without compression libs 2024-12-05 13:59:54 +08:00
pom.xml [KYUUBI #6836] Ship kafka-clients in binary distribution tarball without compression libs 2024-12-05 13:59:54 +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.