Token representing a scheduled job. Call jobHandle.Complete() to block main thread until done, or pass as dependency to next job to chain on worker threads.

Why must I complete before read?

Job safety system enforces that reading a NativeArray on the main thread requires no pending writers. Reading while a job writes = data race. Editor throws; Player crashes silently.

When to chain vs complete?

Chain when the next operation is itself a job (stays parallel). Complete when main thread needs to use the data this frame — bridges back to single-threaded code.

Fix: Unity Job System Dependency Not Completed Before Read

Quick answer: Call jobHandle.Complete() before reading the output NativeArray on the main thread. Or chain into another job via dependencies to stay parallel.

A flocking simulation runs an IJobParallelFor to compute boid velocities, then assigns them back to Transforms. Unity logs “Job has not finished writing to the … NativeArray”. The main thread is reading before the job finishes.

Complete on Read

var handle = job.Schedule(count, 64);
// ... other work ...
handle.Complete();   // blocks until done

for (int i = 0; i < count; i++)
    transforms[i].position = positions[i];

Simple but blocks main thread. Useful when the data is needed this frame.

Chain Jobs Instead

var handle1 = boidJob.Schedule(count, 64);
var applyJob = new ApplyPositionsJob { positions = positions, transforms = transformAccessArray };
var handle2 = applyJob.Schedule(transformAccessArray, handle1);
handle2.Complete();   // at end of frame

Chain via dependency. Schedule next job with previous handle. Apply runs after boidJob, both on worker threads.

Diagnose with Safety System

Editor enables safety checks. If you ever see “has not finished writing”, the data race exists. Disabling safety for performance is fine in release, but fix the race first.

Last-Resort Complete in LateUpdate

void Update() {
    handle = job.Schedule(count, 64);
}

void LateUpdate() {
    handle.Complete();
    // read here
}

Gives the job a full Update cycle to run on workers. Most jobs finish before LateUpdate; only blocks if long-running.

Avoid Forgetting Complete

Outstanding JobHandles at frame end cause WorkerThread leak warnings. Make completion a discipline:

Always pair Schedule with Complete (or chain to a final handle that gets completed).
Use JobHandle.ScheduleBatchedJobs() to hint scheduler to start work early.

Verifying

Run Play. No “has not finished writing” errors. Profiler shows worker threads active. Frame time within target with parallelism utilized.

Understanding the issue

This bug class falls into a pattern that's worth understanding beyond the specific case. In Unity Engine, the underlying behavior is shaped by how the engine layers its abstractions - the public API you call, the runtime systems that respond, and the platform-specific implementations underneath. A bug at any layer can produce symptoms that look like they originate at a different layer. Triaging effectively means recognizing which layer the symptom belongs to, even when the gameplay code is what's visible.

The specific bug described above is the kind that surfaces during integration rather than unit testing. It depends on a combination of factors: the asset configuration, the runtime state, the platform's specific behavior. In isolation, each piece looks correct; in combination, the bug emerges. This is why thorough integration testing - playing the actual game in realistic conditions - catches things that automated tests miss.

Why this happens

Bugs of this class are particularly easy to ship past internal QA because they often depend on specific runtime conditions - hardware combinations, network states, or asset configurations that QA didn't reproduce. Players hit them in the wild, file reports that are hard to repro, and the bug accumulates negative reviews while engineering tries to recreate the failure mode.

At the engine level, the behavior comes from a deliberate design decision in Unity. The engine team chose a particular trade-off - usually performance versus convenience, or generality versus specificity - and that trade-off has consequences when you push against it. Understanding the trade-off is what turns 'this bug is mysterious' into 'this bug is the expected consequence of this design'.

Verifying the fix

For shipping games, the safest verification is a staged rollout. Apply the fix to 1% of players for 24 hours; watch the affected metric; expand if green. Skipping the staged rollout means the verification is the entire player base, which is too high a stakes for most fixes.

Reproducibility is the prerequisite for verification. If you can't reliably reproduce the bug pre-fix, you can't reliably verify it post-fix. Spend time getting a clean reproduction before you write any fix code. The fix is fast once you understand the reproduction; the reproduction is the slow part.

Variations to watch for

Related bug classes often share the same root cause. If you find yourself fixing this issue, look for cousins: similar symptoms in adjacent systems, the same data flow but a different value, or the same fix pattern in another module. The catalog of 'we've seen this before' becomes valuable institutional knowledge.

Adjacent bugs often share a root cause. After fixing the case you've found, spend an hour searching the codebase for similar patterns. What's the same call with different arguments? The same data flow with a different entity type? The same lifecycle issue in a sibling system? Each match is a candidate for the same fix, or a related fix that prevents future bugs of the same class.

In production

In shipping builds, this issue may interact with other production-only behavior. Stripping, encryption, asset bundling, and platform-specific code paths can each modify the symptoms. When players report a related issue, capture build SHA, platform, and any feature flags - those three fields cover most of the production-only variations.

When triaging a similar issue in production, prioritize gathering data over hypothesizing causes. A player report describes a symptom; what you need is a build SHA, a session timestamp, and ideally a screen recording or session replay. With those, the bug becomes tractable. Without them, you're guessing at hypothetical reproductions that may not match what the player actually hit.

Performance considerations

If this issue manifests under high load (many actors, many particles, many network connections), profile the post-fix code path with realistic counts. The original cost was a bug; the new cost is real work, and real work has a budget.

Diagnostic approach

Diagnosing this class of bug benefits from a structured approach: confirm the symptom, isolate the variables, hypothesize the cause, and verify the hypothesis before writing fix code. Skipping the isolation step is the most common mistake; without it, fixes often address symptoms while the underlying cause continues to produce other variations.

For Unity-specific diagnostics, the editor's profiler is the canonical starting point. Capture a representative frame with the symptom present; compare against a frame without the symptom; the diff often points directly at the cause. If the symptom is non-deterministic, capture multiple frames and look for the pattern - the cause is usually a state transition or a specific input value rather than a continuous effect.

Tooling and ecosystem

Third-party plugins often provide better diagnostics for their own behavior than the engine does. If the affected code is in a plugin, check the plugin's documentation for debug modes, verbose logging, or inspector tools - these can save hours of investigation when they exist.

Within Unity, the relevant diagnostic surfaces include the standard frame debugger, memory profiler, and engine-specific debug overlays. Each one shows a different facet of what's happening. The frame debugger reveals draw call ordering and state transitions; the memory profiler shows allocation patterns; the debug overlay reveals per-system state. Bugs that resist one tool usually surrender to another - the trick is knowing which tool to reach for first.

Edge cases and pitfalls

Boundary conditions deserve specific testing attention. What happens when the input is zero, maximum, negative, or NaN? What happens at the start of a session vs hours in? What happens at the boundary between two systems handling the same data? These are where bugs hide and where regression tests are most valuable.

When writing a regression test for this fix, focus on the boundary conditions that surfaced the original bug. Tests that exercise the happy path catch obvious regressions; tests that exercise the boundary catch the subtler regressions that look like new bugs but are really the original returning. The latter are the tests that earn their keep over the long life of the project.

Team communication

When this bug class affects multiple teams (often the case for cross-system issues), early communication prevents duplicate work. The team that owns the symptom may not own the cause. A 15-minute conversation at the start of triage often saves hours of independent investigation.

If this fix touches a system several engineers work in, a short writeup in the team's engineering channel helps. Not a full design doc - a paragraph explaining what was wrong, what's fixed, and what to watch for. Future engineers encountering similar symptoms will search for the fix; making it findable is a small investment that pays back later.

“Schedule, chain, complete. Three primitives, every safe Job-System data flow.”

For large boid counts (10k+), chain everything and complete in LateUpdate — lets workers overlap render setup.