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Hudi flink jobs often have unreasonable resource allocation. Too much allocation will lead to a waste of resources, and too little will lead to back pressure or OOM.
When allocating resources, you first need to determine the concurrency of the source side to ensure that there is no data backlog upstream when reading. Here is a general configuration situation, such as partitioning by day, with about 15 billion data per day, and about 50 concurrent configurations. Other data volumes can be converted appropriately.
After determining the concurrency on the source side, you can configure the concurrency of write according to the ratio of 1:1.5 or 1:2.
featzhang
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[Feature][Manager] Resource adaptive adjustment for Hudi
[Feature][Manager][Sort] Resource adaptive adjustment for Hudi
Dec 27, 2022
Description
Hudi flink jobs often have unreasonable resource allocation. Too much allocation will lead to a waste of resources, and too little will lead to back pressure or OOM.
When allocating resources, you first need to determine the concurrency of the source side to ensure that there is no data backlog upstream when reading. Here is a general configuration situation, such as partitioning by day, with about 15 billion data per day, and about 50 concurrent configurations. Other data volumes can be converted appropriately.
After determining the concurrency on the source side, you can configure the concurrency of write according to the ratio of 1:1.5 or 1:2.
Use case
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