Question
Atom swap! retry limits under high contention
Ira Moss
0 reputation · 26 Dec 2024, 11:16 UTC
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0 reputation · 26 Dec 2024, 11:16 UTC
Clojure Atoms utilize a Compare-And-Swap (CAS) mechanism to ensure thread-safe state transitions. The swap! function applies a transformation function to the current state and retries the operation if the state is modified by another thread before the commit completes.
While this lock-free approach prevents deadlocks, high contention on a single Atom can lead to repeated retries. Because the transformation function may be executed multiple times, the overhead increases as the number of competing threads grows.
There is uncertainty regarding the internal limits of these retry loops and how the JVM handles extreme contention scenarios without a defined timeout or maximum attempt threshold.
swap! before failing?29775 reputation · 26 Dec 2024, 22:56 UTC
Clojure's swap! function uses a Compare-And-Swap (CAS) loop to commit state changes atomically. The Clojure runtime does not enforce a maximum retry count; the loop continues until the CAS succeeds or the thread is interrupted.
Under extreme thread contention, the transformation function supplied to swap! may be re-executed many times. Each failed CAS causes the function to re-run, and with numerous competing threads, CPU utilization can rise sharply as threads repeatedly attempt and fail the compare-and-swap.
Clojure provides no built-in back-off, timeout, or maximum attempt threshold. When the CAS never succeeds—especially if the transformation function has side effects—this pattern can lead to livelock or starvation, and overall application throughput may degrade.
Practical verification
clojure; Example test pattern using Clojure futures
(require '[clojure.core :as core])
(def counter (atom 0))
(doseq [_ (range 20)]
(future (dotimes [_ 1000]
(swap! counter inc))))
(Thread/sleep 5000)
(println "Final value:" @counter)
Execute this with increasing thread counts and monitor CPU usage and log output. A CPU spike correlated with repeated retry attempts confirms the unbounded-retry behavior.
Diagnostic consideration: If your transformation function includes non-idempotent side effects and you need a guaranteed maximum number of attempts, clarifying whether early failure or bounded retries are acceptable will help determine whether a custom wrapper is required.
Use comments to ask for clarification. Post a solution as an answer.
29,775 reputation · 26 Dec 2024, 22:19 UTC
swap!Clojure’s swap! repeatedly calls compareAndSet until the CAS succeeds. The loop is a tight, busy‑waiting construct – there is no built‑in back‑off or yield. Every failed CAS triggers a fresh execution of the supplied transformation function, so the function body runs repeatedly until success.
When high contention is expected, keep the update function pure and lightweight, or switch to a different primitive such as ref with STM, which uses a retry‑and‑back‑off strategy. If you must use swap!, consider wrapping it in a custom retry with exponential back‑off or a maximum attempt counter to avoid livelock.