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Graph/9a06c7f0-5bb8-4b7b-a837-8020d521e29f

Problemunvalidated

after a few hundred requests. Tension: inconsistent responses mostly happen during concurrent requests for the same user ID.

9a06c7f0-5bb8-4b7b-a837-8020d521e29f

after a few hundred requests. Tension: inconsistent responses mostly happen during concurrent requests for the same user ID.

Node Details

Public graph metadata

Updated4/30/2026

PageRank0.0000

Effectiveness0.000

Connections

26 linked nodes

DESCRIBESQuestion

CAUSED_BYRootCause

Seems like vanilla case of deadlock, the asyncio only lock the same process. — To avoid race conditions, I added an asyncio.Lock() around Redis writes. Tension: it didn’t help. Outcome: You can use redis lock to solve this.

MANIFESTS_ASSymptom

PERTAIN_TODomain

PERTAIN_TODomain

PERTAIN_TODomain

Async Programming

FIXED_BYSolution

maybe you can swap your post to axios, because it has a timeout property — if you only want to do this once. Tension: some requests take too long to download content (about a minute). Outcome: can you in anyway batch your requests, so you are sending more requests in order to receive smaller responses?

FIXED_BYSolution

It will be 10 seconds after the previous request completes. — If `refetchInterval` is set to 10 seconds in `useQuery`. Tension: Understanding the behavior would help me to pick correct `refetchInterval` value. Outcome: The timer re-starts every time when data is put into the cache.

FIXED_BYSolution

You can use redis lock to solve this — around each change you are making to the redis/DB. Outcome: put this lock around each change you are making to the redis/DB.

FIXED_BYSolution

Tension: as the browser might be waiting for a response to the previous request from the server.

FIXED_BYSolution

making sure you pace your requests to stay below those limits — API rate limits. Tension: allowing room for your normal operations, too. Outcome: handle any 429 responses gracefully to retry.

FIXED_BYSolution

The default value in EMR 7.0.0 is 50. Tension: the number of incoming requests to S3 exceeds the capacity of the connection pool. Outcome: `--conf spark.sql.catalog.{ice_catalog}.http-client.apache.max-connections=3000`.

FIXED_BYSolution

on subsequent requests. Tension: you need a way to invalidate and recreate the token when these parameters change.

FIXED_BYSolution

I am seeing an increase in latencies in requests that do succeed — I have a logic of the sort :. Tension: none of them enforce a timeout on the total duration of the request. Outcome: Then properly close the connection in a finally / try-resource block.

FIXED_BYSolution

the solution shown below — exceeding the SQL parameter limit. Tension: Each batch is queried separately, and the results are collected, sorted, and then paginated on the Java side. Outcome: batching the viewerIds list into smaller chunks of 2100 IDs or less.

FIXED_BYSolution

If you start the server and wait several minutes before visiting any pages — does it still take several minutes for that first page? Tension: long startup in general or something request specific. Outcome: Figuring out if it is a long startup in general or something request specific could be a good spot to start.

FIXED_BYSolution

Fixed 30s retry on 429 keeps hammering. — when clearly rate-limited. Tension: keeps hammering. Outcome: Exponential backoff + hard rejection during cooldown.

Concurrent State Interference

Small Writes Causing Throttling

Request Stall from Concurrency

Confused Context Wiring

Concurrent Request Race Inconsistency

Cross-System Concurrency Gaps

Connection-Scoped Context Drift

Cloud Run Task Shutdown

Selector Recreation Tension

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