perf(worker): Batch testrun fetching and updating for flake processing

[sentry]

Fixes WORKER-Y93. The issue was that: Iterating through uploads and querying testruns for each individually causes an N+1 query problem.

• Refactored get_testruns to get_testruns_for_uploads to accept a list of upload IDs.
• Modified process_single_upload to receive testruns directly, removing its internal query and bulk update.
• Updated process_flakes_for_commit to fetch all relevant testruns for all uploads in a single batched query.
• Consolidated the Testrun bulk update operation to occur once after processing all uploads, improving database efficiency.

This fix was generated by Seer in Sentry, triggered automatically. 👁️ Run ID: 13568247

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Note

Medium Risk
Reduces DB load by changing flake processing to batch-fetch and bulk-update Testrun rows across uploads; risk is moderate due to altered query/update sequencing that could affect which runs get processed or updated.

Overview
Improves flake processing performance by eliminating per-upload Testrun queries (N+1) and instead fetching all recent testruns for a commit’s uploads in one batched query, grouping them by upload_id for processing.

Moves Testrun outcome persistence from per-upload updates to a single bulk_update after all uploads are processed, while keeping flake creation/upsert behavior the same.

^{Reviewed by Cursor Bugbot for commit 35e31ba. Bugbot is set up for automated code reviews on this repo. Configure here.}

[sentry]

Bug: An exception during the upload processing loop will cause all previously processed data from that batch to be lost, as database updates now only occur after the entire loop finishes.
_{Severity: MEDIUM}

Suggested Fix

To restore the previous fault-tolerant behavior, move the Testrun.objects.bulk_update and Flake.objects.bulk_create calls back inside the for loop that iterates through uploads. This could be done by collecting testruns and flakes per-upload and saving them at the end of each loop iteration, or by wrapping each iteration in a transaction.atomic() block to ensure atomicity per upload.

Prompt for AI Agent

Review the code at the location below. A potential bug has been identified by an AI
agent. Verify if this is a real issue. If it is, propose a fix; if not, explain why it's
not valid.

Location: apps/worker/services/test_analytics/ta_process_flakes.py#L128-L134

Potential issue: The refactoring moves the `Testrun.objects.bulk_update` and
`Flake.objects.bulk_create` calls from inside the per-upload processing loop to after
the loop completes. In the original code, if an exception occurred while processing one
upload, the results from previously completed uploads in the same batch were already
persisted. In the new code, if any exception occurs at any point within the loop over
uploads, the entire operation is aborted, and all in-memory changes to `Testrun` objects
and newly created `Flake` objects from preceding, successfully processed uploads are
discarded and never written to the database. While the likelihood of an exception in
`process_single_upload` is low, this change represents a regression in fault tolerance.

_{Did we get this right? 👍 / 👎 to inform future reviews.}

[sentry]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 92.25%. Comparing base (0ad8a0c) to head (35e31ba).
✅ All tests successful. No failed tests found.

Additional details and impacted files

@@           Coverage Diff           @@
##             main     #869   +/-   ##
=======================================
  Coverage   92.25%   92.25%           
=======================================
  Files        1307     1307           
  Lines       48017    48021    +4     
  Branches     1636     1636           
=======================================
+ Hits        44299    44303    +4     
  Misses       3407     3407           
  Partials      311      311           

Flag	Coverage Δ
workerintegration	58.53% <10.00%> (-0.02%)	⬇️
workerunit	90.39% <100.00%> (+<0.01%)	⬆️

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Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ All tests successful. No failed tests found.

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