leesf commented on code in PR #5567: URL: https://github.com/apache/hudi/pull/5567#discussion_r873741734
########## rfc/rfc-53/rfc-53.md: ########## @@ -0,0 +1,120 @@ +<!-- + Licensed to the Apache Software Foundation (ASF) under one or more + contributor license agreements. See the NOTICE file distributed with + this work for additional information regarding copyright ownership. + The ASF licenses this file to You under the Apache License, Version 2.0 + (the "License"); you may not use this file except in compliance with + the License. You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + + Unless required by applicable law or agreed to in writing, software + distributed under the License is distributed on an "AS IS" BASIS, + WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + See the License for the specific language governing permissions and + limitations under the License. +--> +# RFC-53: Use Lock-Free Message Queue Improving Hoodie Writing Efficiency + + +## Proposers +@zhangyue19921010 + +## Approvers + +## Status + +JIRA: https://issues.apache.org/jira/browse/HUDI-3963 + + +## Abstract + +New option which use Lock-Free Message Queue called Disruptor as inner message queue to improve hoodie writing performance and optimize writing efficiency. + +Disruptor linked: https://lmax-exchange.github.io/disruptor/user-guide/index.html#_introduction + + +## Background + +Based on master branch, hoodie consumes upstream data (Kafka or S3 files) into the lake is a standard production-consumption model. +Currently, hoodie uses `LinkedBlockingQueue` as a inner message queue between Producer and Consumer. + +However, this lock model may become the bottleneck of application throughput when data volume is much larger. +What's worse is that even if we increase the number of the executors, it is still difficult to improve the throughput. + +In other words, users may encounter throughput bottlenecks when writing data into hudi in some scenarios, and increasing the physical hardware scale and parameter tuning cannot solve this problem. Review Comment: `in some scenerios`, can we describe the scenerios in detail, such as the scenarios your company met? -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
