# Examples

- [Process 2.4TB of Parquet Files in 76s](https://docs.burla.dev/examples/process-2.4tb-of-parquet-files-in-76s.md): With <30 lines of Python.
- [Parallel Hyperparameter Tuning](https://docs.burla.dev/examples/parallel-hyperparameter-tuning.md)
- [Genomic Pipeline on 1,000 CPUs](https://docs.burla.dev/examples/multi-stage-genomic-pipeline.md)
- [More Examples](https://docs.burla.dev/examples/demo-walkthroughs.md)
- [ML, embeddings, and search](https://docs.burla.dev/examples/demo-walkthroughs/ml-embeddings-and-search.md)
- [GPU embeddings on A100s](https://docs.burla.dev/examples/demo-walkthroughs/ml-embeddings-and-search/gpu-embedding-demo.md)
- [Batch inference without serving](https://docs.burla.dev/examples/demo-walkthroughs/ml-embeddings-and-search/ml-inference-batch.md)
- [Embed the whole arXiv](https://docs.burla.dev/examples/demo-walkthroughs/ml-embeddings-and-search/arxiv-fossils.md)
- [Label-free visual search over the Met](https://docs.burla.dev/examples/demo-walkthroughs/ml-embeddings-and-search/met-weirdest-art.md)
- [Multimodal Airbnb analysis](https://docs.burla.dev/examples/demo-walkthroughs/ml-embeddings-and-search/airbnb-burla.md)
- [Full-corpus analysis](https://docs.burla.dev/examples/demo-walkthroughs/full-corpus-analysis.md)
- [571M Amazon reviews](https://docs.burla.dev/examples/demo-walkthroughs/full-corpus-analysis/amazon-review-distiller.md)
- [NYC taxi history](https://docs.burla.dev/examples/demo-walkthroughs/full-corpus-analysis/nyc-ghost-neighborhoods.md)
- [9.49M Flickr photos](https://docs.burla.dev/examples/demo-walkthroughs/full-corpus-analysis/world-photo-index.md)
- [NOAA rain extremes](https://docs.burla.dev/examples/demo-walkthroughs/full-corpus-analysis/ghcn-rainiest-day.md)
- [One million GitHub READMEs](https://docs.burla.dev/examples/demo-walkthroughs/full-corpus-analysis/github-repo-summarizer.md)
- [Production data jobs](https://docs.burla.dev/examples/demo-walkthroughs/production-data-jobs.md)
- [S3 to Postgres ETL](https://docs.burla.dev/examples/demo-walkthroughs/production-data-jobs/python-etl-no-airflow.md)
- [Millions of image resizes](https://docs.burla.dev/examples/demo-walkthroughs/production-data-jobs/image-dataset-resize.md)
- [One Parquet file per worker](https://docs.burla.dev/examples/demo-walkthroughs/production-data-jobs/parquet-parallel.md)
- [Pandas apply in parallel](https://docs.burla.dev/examples/demo-walkthroughs/production-data-jobs/pandas-apply-parallel.md)
- [Enrich millions of users through a rate-limited API](https://docs.burla.dev/examples/demo-walkthroughs/production-data-jobs/rate-limited-api-requests.md)
- [Crawl a million website pages without hiding failures](https://docs.burla.dev/examples/demo-walkthroughs/production-data-jobs/parallel-web-scraping.md)
- [Scientific and geospatial work](https://docs.burla.dev/examples/demo-walkthroughs/scientific-and-geospatial-work.md)
- [Genome alignment](https://docs.burla.dev/examples/demo-walkthroughs/scientific-and-geospatial-work/bioinformatics-alignment.md)
- [GDAL raster processing](https://docs.burla.dev/examples/demo-walkthroughs/scientific-and-geospatial-work/gdal-raster-processing.md)
- [Billion-path Monte Carlo](https://docs.burla.dev/examples/demo-walkthroughs/scientific-and-geospatial-work/monte-carlo-simulation.md)


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.burla.dev/examples.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.