XiaoHongbo-Hope commented on PR #7857:
URL: https://github.com/apache/paimon/pull/7857#issuecomment-4681608516

   > This batch query is not meaningful for performance, we need to ensure that 
the local file cache is enabled. See 
[ce38b2c](https://github.com/apache/paimon/commit/ce38b2ccd7cbaabcfc1d5e90f68586ebecc66265)
   
   I ran an OSS benchmark with a 529MB Lumina index, 100 queries, dim=1024.
   ```
     Without Paimon local cache:
     - user-level loop: 188.6s
     - batch: 39.7s
   
     With warm local memory cache:
     - user-level loop: 41.4s
     - batch: 39.7s
   ```
     So without cache, batch is effective. With warm cache, the benefit is very 
small, which matches your
     point.
   
     Since users need a batch API, for the Spark/Flink batch API, which 
direction do you prefer?
     1. implement it by looping single-vector search internally and relying on 
local cache;
     2. continue this PR and add a batch vector search/readBatch path.


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