Datasets:
license: other
license_name: mixed-per-document
task_categories:
- text-generation
- question-answering
language:
- en
tags:
- data-engineering
- documentation
- corpus
- retrieval
size_categories:
- 10K<n<100K
configs:
- config_name: default
data_files: corpus-*.parquet
DE-Corpus v0
31,216 cleaned technical documents on data engineering: official documentation, GitHub issues and pull requests, Apache JIRA tickets, PEPs, PostgreSQL manuals and arXiv papers. This is the source material from which DE-Bench was written.
⚠️ There is no single licence for this corpus
Do not treat this as one licensed work. Every document carries its own license and source_url, and
both must be preserved if you redistribute any of it.
| Licence | Documents | Share |
|---|---|---|
| Apache-2.0 | 20,543 | 65.8% |
| MIT | 2,928 | 9.4% |
| Public Domain | 2,097 | 6.7% |
| PSF License | 1,936 | 6.2% |
| PostgreSQL | 1,843 | 5.9% |
| CC-BY-4.0 | 695 | 2.2% |
| BSD-3-Clause | 652 | 2.1% |
| MPL-2.0 | 522 | 1.7% |
The 695 CC-BY-4.0 documents require attribution. The source_url column is that attribution — keep it.
Share-alike material was removed. 24 documents (chunks of two arXiv papers) were CC-BY-SA-4.0 and are excluded, because share-alike obligations propagate to derivative works. No DE-Bench item cites either paper, which was verified rather than assumed.
If you need a single-licence subset, filter on the license column. Filtering to Apache-2.0 alone still
leaves 20,543 documents.
Composition
| Source type | Documents |
|---|---|
| Official documentation | 26,333 |
| GitHub issues | 1,938 |
| Apache JIRA tickets | 1,355 |
| GitHub pull requests | 1,119 |
| arXiv papers | 471 |
Coverage is deepest on Kafka, Python, Flink, dbt, PostgreSQL, Spark, DuckDB, Dagster and Airflow, and thinner on Debezium, Schema Registry, Prefect and pandera. Commercial warehouses (Snowflake, BigQuery, Redshift) are essentially absent, because only open-source documentation was collected — worth knowing before using this for retrieval on those platforms.
Fields: doc_id, source_type, source_url, license, title, content, project, tags,
word_count, lang, quality_score, scraped_at.
Processing
Scraped between 2026-09-15 and 2026-09-21, then text-extracted, cleaned, PII-scrubbed and deduplicated.
Long documents are split into sections, so several rows can share a source_url — doc_id is the unique
key, not source_url.
Uses and limits
Reasonable uses: retrieval-augmented data-engineering assistants, domain pretraining or continued pretraining, and studying documentation coverage across the ecosystem.
Things to be careful about:
- Snapshot, not a feed. Documentation reflects tool versions as of 2026-09-21 and has since moved on. Nothing here is updated.
- Not reproducible by re-scraping. The sites change continuously; re-running the scrapers yields a different corpus. This snapshot is the artifact.
- Do not use it to evaluate models on DE-Bench. Benchmark items were written from this corpus. Using it as retrieval context turns the benchmark into an open-book test, which is a valid experiment but is not comparable to a closed-book leaderboard score — and the benchmark's contamination numbers are measured against this corpus specifically.
- PII scrubbing is best-effort. It removed emails and similar identifiers from structured fields; residual personal names remain in free-text issue and JIRA discussions, which are public by origin.
Licence notice
Each document remains under the licence recorded in its license field, held by its original authors. This
collection adds no new licence over the documents and claims none. Attribution requirements (CC-BY-4.0) and
notice requirements (Apache-2.0, MPL-2.0, BSD-3-Clause) travel with the individual documents.