perf(preprod): Parallelize and deduplicate snapshot image fetches

[NicoHinderling]

Replaces sequential session.get() calls in compare_snapshots with a
ContextPropagatingThreadPoolExecutor (8 workers) that prefetches all unique
content hashes for each pixel batch concurrently. A per-batch dict cache
keyed by content hash deduplicates fetches — if the same blob appears as
head_hash for one pair and base_hash for another, it's only downloaded
once.

Previously, each image pair fetched its head and base images sequentially,
with no dedup across pairs. For a batch of 50 pairs sharing some hashes,
this could mean 100 individual blocking HTTP round-trips when only ~70
unique hashes exist.

The objectstore Session.get() is thread-safe (no mutable instance state,
urllib3 pool handles concurrency internally), so no changes to the
objectstore client are needed.

Closes EME-828

[linear-code]

EME-828 Batch download images in compare worker

[cursor]

Cursor Bugbot has reviewed your changes and found 1 potential issue.

Bugbot Autofix prepared a fix for the issue found in the latest run.

• ✅ Fixed: Unconsumed executor.map iterator cancels pending fetch futures
  • The executor.map result is now eagerly consumed with list(...), ensuring all hash-fetch futures run to completion and preventing missing cache entries.

Or push these changes by commenting:

@cursor push 2c8ccbee25

Preview (2c8ccbee25)

diff --git a/src/sentry/preprod/snapshots/tasks.py b/src/sentry/preprod/snapshots/tasks.py
--- a/src/sentry/preprod/snapshots/tasks.py
+++ b/src/sentry/preprod/snapshots/tasks.py
@@ -375,7 +375,7 @@
 
                 # Fetch unique hashes in parallel; session.get() is thread-safe
                 with ContextPropagatingThreadPoolExecutor(max_workers=8) as executor:
-                    executor.map(_fetch_hash, unique_hashes)
+                    list(executor.map(_fetch_hash, unique_hashes))
 
                 for candidate in batch:
                     if candidate.head_hash in failed_hashes or candidate.base_hash in failed_hashes:

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