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Web Workers · 15 Progress Reporting
Series contents · Technology map
Stage: Queues and Error Recovery · Editable example · Storage ID: web-workers-step-15
Goals and learning outcomes
- Learning outcome: explain the role of Reporting frequency. Input cases: a task with 100 chunks.
- Deliverable: message count and progress sequence. Explain the rationale for handling Monotonic progress, linking it to the code.
Prerequisites
Prepare the experiment results for Ownership tracking and Cancellation policy from Unit 14, “Transfer and Cancellation”.
Key concepts and explanations
Reporting frequency
Sending a message for every element increases communication volume. Limit progress reports to points such as chunk boundaries.
Monotonic progress
Progress for one request must not decrease before completion. Reset to new progress when the request ID changes.
Practice setup
First check the execution scope guidance on the example screen. The following describes the environment needed to extend the assignment in a separate project. The existing web-workers-01·02·03 are starting examples. Implement the new assignments in main.js and worker.js in a separate local HTTP project. Preserve CSP and iframe isolation. For SharedArrayBuffer, check COOP and COEP requirements on an external server you control; use the transfer path if they are not met. Measure performance yourself.
The linked example is a starting point. It does not implement every task below. Complete work beyond its supported scope in a separate project.
Practice tasks
- In src/day-15.js in a separate practice project, send completed-element counts in progress messages and display only the latest ID. Refer to the existing Unit 1·14·28 examples only as starting points.
- Input conditions: a task with 100 chunks. Baseline: Every chunk. Run under the baseline conditions, then record observations and errors in notes/day-15.md.
- Variable: Reporting interval; changed value: Every 10 chunks. Run again through the same input path. Deliverable to save: message count and progress sequence. Hypothesis to check: Fewer messages are sent while the final 100% is retained. Compare it with the actual results, and record whether they agree and why they differ.
Variables to observe
| Variable | Baseline | Change | Expected change / hypothesis |
|---|---|---|---|
| Reporting interval | Every chunk | Every 10 chunks | Fewer messages are sent while the final 100% is retained. |
Predictions in this table are not measured results. Change one condition at a time and record why the actual result differs.
Completion criteria
- Required deliverable: message count and progress sequence. Results are available for both the baseline and changed conditions, allowing comparison of 2 conditions; input values and the execution environment are recorded together.
- The explanation of differences between the two conditions connects both concepts: Reporting frequency and Monotonic progress. For unexpected items, at least 1 cause or reason they remain unresolved is recorded.
Self-check
- Which processing stage does Reporting frequency affect in this exercise? Input cases: a task with 100 chunks.
- Variable: Reporting interval. Hypothesis to check: Fewer messages are sent while the final 100% is retained. Did the actual results agree with the hypothesis? Explain the evidence in terms of Monotonic progress.
Official references
Linked example and execution scope
Example source · Runtime environments and limits
An interactive Progress Reporting experiment with cleanup of the resources it uses.
Source code and records are not overwritten automatically. Resetting an existing example also preserves your notes.
Next learning
Previous: Transfer and Cancellation · Next: A Bounded Task Queue