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Graph/cluster-200

ClusterConcept

Hidden Lock Coupling Deadlocks

cluster-200

Locking and execution are coupled in hidden ways—GIL-releasing calls, nested runtime locks (e.g., MySQL driver internals), and multi-resource acquisition—so threads/processes block each other in cycles and the program appears to hang.

Node Details

Public graph metadata

Updated6/24/2026

PageRank0.0004

Connections

40 linked nodes

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As long as you lock more than a single thing at a time, you risk deadlocks. — lock more than a single thing at a time. Tension: You hold B waiting for A, they hold A waiting for B. Outcome: one of you has to abort or you're stuck.

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Each message triggers multiple updates to `chat_members`. — when a chat has many members (e.g., group chats). Tension: This works functionally, but it feels very inefficient and resource-heavy.

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sqlite3.OperationalError: database is locked. — I trigger `/session_a` and `/session_b` almost simultaneously. Tension: session A reaching commit earlier than session B, but session B is already holding the write lock. Outcome: A will inevitably fail with a database is locked error.

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the two requests are executed "in parallel." — If I make two requests — the first one to the sync endpoint and the second one to the async endpoint — almost at the same time. Tension: I expected the event loop to be blocked. Outcome: the two requests are executed "in parallel.".

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The idea is to update this model once hourly without blocking the API's ability to respond. Tension: update this model once hourly without blocking the API's ability to respond to CPU-bound tasks. Outcome: this is all good.

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it will execute only once because added it in lifespan — I have added scheduler code in lifespan. Tension: my scheduler condition is: Run the task everyday at 6 am, with `start_time` being 6 am and `end_time` 8 am. Outcome: how can I execute job everyday.

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My understanding of Python's asyncio library (and async functions for Python in general) is that it uses threads. — Python's asyncio library. Tension: Asynchrony isn't about threads. Outcome: No. Or rather, not necessarily.

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java-17 takes at least twice as long to read for a warm run — a minimal function that just reads the source file from S3. Tension: one of our lambdas that processes large files started to timeout. Outcome: java-11 runs approximately twice as fast as java-17.

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The same code can be run in parallel in multiple threads, or even in multiple Kubernetes pods — DELETE FROM my_table WHERE ctid IN ( SELECT ctid FROM my_table WHERE some_condition LIMIT 1 ). Tension: two threads start fighting for the same record.

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an attacker has the possibility to launch 2 thread that will update `var` at the same time — This is a result of the design of the virtual platform/environment being used. Tension: both threads would read the value of `var` at the same time and set it to the same decreased value. Outcome: the payment would be indeed sent twice.

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Is it possible to lost increment here? Tension: stats.setTotalSold(stats.getTotalSold() + 1); // lost increment? Outcome: Lost increment is impossible with REPEATABLE_READ isolation level (at least in PostgreSQL).

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The program below never ends.

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those polls might be scheduled in parallel — make this concurrent. Tension: there is no ordering guarantee.

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Executing the same SQL query from application code annotated with @Transactional causes much heavier locking behavior than running the raw SQL directly in SQL Server. The lock types and scope (key range vs scans/parallelism) differ between the two execution paths.

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I cannot think of a way to set the `productId` of the new `Product` entity that doesn’t use a blocking database call — I have a Spring Boot microservice that provides non-blocking APIs for creating and managing entities called `Product`. The services uses a MongoDB. Tension: Ideally, I’d like an auto-increment feature that will do this on the entity itself when it is persisted to the database. Outcome: safe from race conditions.

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This code will eventually be executed under a web application, meaning it will be accessed concurrently — It reads an Excel file as a template to write data and saves it locally. Tension: The only thing that may looks marignally relevant is calling the static `OPCPackage.open` method. Outcome: there shouldn't be any problem running this code in a multithreaded environment.

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I'm trying to retrieve `GetLastError` code on `LoadLibraryW` failure via `Linker.Option.captureCallState` — Java 22+. Tension: According to the documentation and this issue on JDK Bug System, `captureCallState` is the preferred way of retrieving such error codes. Outcome: you should see an error code as you expect.

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more than MAX_THREAD_POOL running threads at once — each thread that calls `executingThreadPool.add` immediately uses `executingThreadPool.poll`. Tension: your locks don't prevent more than MAX_THREAD_POOL running threads at once. Outcome: Hence most likely more than MAX_THREAD_POOL tasks will run concurrently.

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Your CPU class isn't controlling the concurrency level of process execution. — The threads you start in CPUDemo are doing their own processing. Tension: the CPU isn't starting the "processing" threads itself. Outcome: Try to to decouple thread creation from task execution.

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Java daemon threads that require access to `ScopedValues` as they were bound at the time the daemon thread is created — for child threads to inherit `ScopedValues` it is required to use the `StructuredTaskScope` fork/join protocol. Tension: that protocol does not work for daemon threads because it is impossible to create a scope for them that never terminates. Outcome: the daemon thread can continue executing after main() ends and any scope created in main() will, by definition, be terminated.

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Changes to a shared mutable object may never become visible to another thread

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wouldn't it be a waste of DB space if I'm storing millions of tasks that I only ever need to process once

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I can't store all of my tasks inside a BlockingQueue first because it would be too many tasks to handle in-memory

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The behavior is that I expected is that each threads enqueues and deques in the sequential order that the threads used in enqueue the values, but this is not the case. — using `built-in java ArrayBlockingQueue` and `custom implementation`. Outcome: q.add(...) and q.poll() may alternate.

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Multiple threads are writing in the file concurrently. — I need to persist this counter because if process get restarted then it counter should start from last count. Tension: I hope there wont be a case when any number shall be skipped or give duplicate value to thread. Outcome: how to reset this key when value reaches to 25k in a thread safe way.

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tput cols — when running it again in 2025 it is partly broken. Tension: always returns default 80. Outcome: small example that isolates the problem.

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The goal is to observe the traces, despite using virtual threads. Tension: There are challenges adapting to my piece of code:. Outcome: Yes, `Executors.newVirtualThreadPerTaskExecutor()` should work fine as far as Observation Propagation is concerned.

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the Main thread was blocked till the subscribe method completion — Mono.just(getValue()).subscribe(value -> System.out.println(value));. Outcome: Can someone make this program asynchronous?

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Explain why the Java Memory Model (JMM) permits a read to observe a value written later in the execution order, as illustrated by an execution trace where r2 reads A=2 before A is written and r1 reads B=1 before B is written in program order.

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But it doesn't work like that. — I wanted to try power of virtual threads in Java in a simple application which consists of many tasks. Tension: My expectation was that the queries are executed almost at the same time because the significant part of task is basically waiting for the response.

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the multithreaded version runs as long as the single threaded one — While writing a multithreaded application. Tension: I encountered a problem that the multithreaded version runs as long as the single threaded one.

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there seems to be two different thread states: `JVM thread_state` and `java.lang.Thread.State` — In below thread dump. Tension: Which one is the actual state of the thread? Outcome: You can see java.lang.Thread.State and thread_state as two different “perspectives” the JVM has over a thread state.

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Testing the catch path of code that calls Thread.sleep()

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How do I list all the virtual threads in a JVM?

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do my fences interrupt other guests on the machine? — running in a VM on a cloud provider. Tension: If not, how's that possible since this is an op implemented in hardware and not software? Outcome: Fences are local, affecting only the current thread.

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I want to figure out which thread read which part of data in matrix. — I am learning CuTe's thread value layout, and I followed leimao's blog. Tension: when you print this MMA atom, you got this info.

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workers can pick up tasks within a reasonable time — io_context workers. Tension: are not stuck running long or blocking operations.

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this does not happen — whenever the tracee creates a new thread. Tension: I must also follow all threads created by the traced program.

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vote toggling can farm XP — Current implementation awards XP every time `value === 1` is upserted. Tension: simple, but exploitable via vote toggling. Outcome: Option 3 (idempotent by vote ID) is the cleanest balance.

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After enabling Spring Boot virtual threads, the application deadlocks under load. Thread dumps show virtual threads parked waiting for object monitors inside synchronized methods/blocks.

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