Beaver (Oracle Conversion)

Converted version of the Beaver dataset for Oracle. This repository contains only data and usage notes.

The original Beaver dataset is published here: https://peterbaile.github.io/beaver/

Installation

No software installation is required for this repository. Use the files directly with your existing Oracle tools and environment

Documentation

Dataset contents

beaver_ddl.json - 475 converted DDL objects (one JSON object per line)

beaver_dml.json - All converted DML statements in a single JSON file.

beaver_nl2sql.jsonl - All 209 natural-language to Oracle SQL pairs (one JSON object per line)

How to use the data with Oracle

You can load the dataset in either of the following ways

1) SQL client workflow (SQLcl / SQL*Plus )

• Extract the SQL text from each JSON record using your preferred tooling (for example, a JSON prorcessor or internal script)
• Apply DDLs from beaver_ddl.jsonl first to create the required objects, then apply DMLs from beaver_dml.json to populate the data
• Adjust schema / object names before execution to match your environment if needed and run the statements as standard SQL scripts

2) Programatic workflow (your own script)

• Write a script (example, in Python) that:
  • Reads each json / jsonl record
  • Retrievs the SQL text
  • Optionally transforms it (example, schema prefixes, data literal handling)
  • Executes statements against your Oracle database

Each line of beaver_ddl.jsonl is a JSON object that includes a field containing the DDL SQL.

• Extract that field with your preferred JSON tooling / process and execute with your Oracle client (example, SQLcl, Sql Developer Web)

• Or, write a python script to read each record, retrieve SQL text from the fiel, optionally transform it (eg. sche)

Notes and Guidance

• For date/time strings, don't rely on session NLS. Detect date-like literals (like 2015-02-03 20:02:07) in the DMLs and wrap with TO_DATE(...,'YYYY-MM-DD HH24:MI:SS') or use TO_TIMESTAMP / TO_TIMESTAMP_TZ

• Use executemany to run speed up bulk inserts and updates

• You may need to change schema names or add a prefix to table names to match your environment. Plan for consistent naming (for example, a staging prefix) before execution.

• Record every statement in a lightweight results file (table, SQL, status, and any error), and include a retry step that re-executes only the failures after you’ve fixed the underlying issue.

Security

Please consult the security guide for our responsible security vulnerability disclosure process

License

Copyright (c) 2025 Oracle and/or its affiliates.

Released under the Universal Permissive License v1.0 as shown at https://oss.oracle.com/licenses/upl/.