增大并行度后ALL模式维表缓存带来的数据库连接及内存压力
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Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 25/100
- Issue type
- Feature
- Clarity
- Needs clarification
- Activity status
- Stale
- Domain
- databases, performance, stream-processing
Research direction
Start by locating the ALL-mode dimension-table cache implemented with flatMap, then trace how SQL parallelism causes each parallel task to load the dimension data. Investigate the existing scheduled refresh behavior and how task managers and slots are represented. Done means one copy is loaded per task manager while refreshes continue to work without exhausting database connections or causing excessive memory use.
Written by the indexing model from the issue text.
Description
源码中ALL模式维表缓存是个flatMap操作,当任务数据量和计算压力增大后,增大SQL的并行度,每个并行度都会去维表中加载数据,这样一个是容易出现把维表连接打满的情况,另一个就是带来不小的内存开销。
因为存在定时更新数据,广播可能不太好做,能否实现一个taskmanager只加载一份维表数据,而不是每个slot都去加载一遍
- Dominant language
- Java
- Stars
- 2k
- Forks
- 913
- PR merge metrics
- No merged PRs in 30d
Contributor guide
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