> For the complete documentation index, see [llms.txt](https://v2.dataos.info/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://v2.dataos.info/concepts/resources/nilus/pipeline-optimization.md).

# Pipeline Optimization

Pipeline optimization is a measured change to improve one of three outcomes: shorter runtime, lower resource use, or a better destination layout.

## Optimize Only With a Symptom

| Symptom                                                              | First pages                                                                                                                                          |
| -------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------- |
| Pipeline takes too long                                              | [Optimizing for Time](/concepts/resources/nilus/pipeline-optimization/optimizing-for-time.md)                                                        |
| Pipeline uses too much CPU or memory                                 | [Optimizing for Resource](/concepts/resources/nilus/pipeline-optimization/optimizing-for-resource.md)                                                |
| Destination has too many files, poor partitioning, or costly queries | [Optimize Sink Datasets](/concepts/resources/nilus/pipeline-optimization/optimize-sink-datasets.md)                                                  |
| Large Lakehouse (Iceberg) load is slow or runs out of memory         | [Tuning Large Lakehouse (Iceberg) Loads](/concepts/resources/nilus/pipeline-optimization/optimize-sink-datasets/optimize-lakehouse-iceberg-loads.md) |
| Pipeline fails or produces unexpected data                           | [Troubleshooting](/concepts/resources/nilus/troubleshooting.md)                                                                                      |

## Measurement Loop

1. Capture the current run: status, duration, records processed, CPU, memory, source object, destination, and config.
2. Pick one hypothesis: extraction bottleneck, load bottleneck, destination layout, source throttling, or resource pressure.
3. Change one knob.
4. Run the same workload again.
5. Compare duration, throughput, cost, and destination correctness.
6. Keep the change only if it improves the symptom without hiding a correctness issue.

## Common Knobs

| Knob                          | Placement                                 | Use for                                                              |
| ----------------------------- | ----------------------------------------- | -------------------------------------------------------------------- |
| `page_size`                   | `source.options`                          | Reducing memory pressure or API/page overhead.                       |
| `extract_parallelism`         | `source.options`                          | Increasing supported extraction concurrency.                         |
| `loader_file_size`            | `sink.options`                            | Reducing small files or loader batch overhead.                       |
| `partition_by`                | `sink.options`                            | Improving lakehouse query pruning.                                   |
| `cluster_by`                  | `sink.options`                            | Improving locality for common filters where supported.               |
| `DATA_WRITER__FILE_MAX_BYTES` | `spec.use.projection.projections.envVars` | Controlling per-file byte size for Iceberg destinations.             |
| `LOAD__WORKERS`               | `spec.use.projection.projections.envVars` | Increasing destination load worker concurrency for large writes.     |
| `NORMALIZE__WORKERS`          | `spec.use.projection.projections.envVars` | Increasing normalization worker concurrency for wide or nested data. |

All runtime env vars go under `spec.use.projection.projections.envVars` (not `spec.runtime.env`). For the wiring pattern and validated Lakehouse configurations, see [Optimizing for Time](/concepts/resources/nilus/pipeline-optimization/optimizing-for-time.md) and [Tuning Large Lakehouse (Iceberg) Loads](/concepts/resources/nilus/pipeline-optimization/optimize-sink-datasets/optimize-lakehouse-iceberg-loads.md).

## Related docs

* [Observability](/concepts/resources/nilus/observability.md)
* [Optimizing for Time](/concepts/resources/nilus/pipeline-optimization/optimizing-for-time.md)
* [Optimizing for Resource](/concepts/resources/nilus/pipeline-optimization/optimizing-for-resource.md)
* [Optimize Sink Datasets](/concepts/resources/nilus/pipeline-optimization/optimize-sink-datasets.md)
* [Tuning Large Lakehouse (Iceberg) Loads](/concepts/resources/nilus/pipeline-optimization/optimize-sink-datasets/optimize-lakehouse-iceberg-loads.md)


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