xuang7 opened a new pull request, #4004:
URL: https://github.com/apache/texera/pull/4004

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   ### What changes were proposed in this PR?
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   This PR introduces on-demand (batch) presigning for multipart uploads to 
reduce failures from expired pre-signed URLs. Previously, all part URLs were 
pre-signed at the start using an experimental LakeFS API. For long uploads, 
URLs for later parts could expire (after 15 min locally or 30 min on the 
server), causing the upload to fail midway. The revised implementation uses the 
LakeFS function for the initial batch of URLs, then presigns subsequent batches 
directly using the `S3presigner`.
   
   **Changes (Backend)**
   - Adds a new method, `presignUploadParts`. This method uses `s3Presigner` to 
sign a specific list of provided partNumbers
   - The /multipart-upload endpoint coordinates new signing flow:
     -  type=init: This now only signs and returns the first batch of URLs 
(e.g., parts 1-100 or 1-20).
     -  type=sign(New operation): This endpoint receives a `pendingParts` list 
and `physicalAddress` from the client. It calls the new 
`S3StorageClient.presignUploadParts` to sign the requested batch and returns 
the new URLs.
   
   **Changes (Frontend)**
   - Switch multipart upload pipeline to RxJS expand to implement stateless, 
recursive fetching of pre-signed URL batches:
     - It starts by calling `type=init` to get the first batch.
     - On demand, call `type=sign` for the next range of pendingParts and 
stream those URLs.
   - Introduced a `urlBatchSize` variable (Configurable, default: 100) to 
control how many URLs are requested in each init and sign call.
   
   ### Any related issues, documentation, discussions?
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   Fixes #3837
   Resolves URL expiration for pending parts. Fully handling interruptions 
during part uploads requires resumable uploads.
   
   ### How was this PR tested?
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   Tested with existing automated test cases and local manual tests.
   Additional scenarios (to be added)
   
   ### Was this PR authored or co-authored using generative AI tooling?
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   No
   


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