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[KYUUBI #4042] Fix a typo from architect to architecture in README.md

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### _Why are the changes needed?_

Fixes a typo in README.md from architect to architecture. This is a simple typo fix.

### _How was this patch tested?_
- [ ] Add some test cases that check the changes thoroughly including negative and positive cases if possible

- [ ] Add screenshots for manual tests if appropriate

- [ ] [Run test](https://kyuubi.apache.org/docs/latest/develop_tools/testing.html#running-tests) locally before make a pull request

Simple typo fix, and I checked it manually via the web browser.

Closes #4042 from HyukjinKwon/minor-typo.

Closes #4042

dec2faae [Hyukjin Kwon] Fix a typo from architect to architecture in README.md

Authored-by: Hyukjin Kwon <gurwls223@apache.org>
Signed-off-by: Cheng Pan <chengpan@apache.org>
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Hyukjin Kwon 2022-12-29 19:50:10 +08:00 committed by Cheng Pan
parent ad1e9a422b
commit a64436459c
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@ -67,7 +67,7 @@ In typical big data production environments, especially secured ones, all bundle
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 architect 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.
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.