avro783 B
Avro — Row Binary + Schema
The same records as Apache Avro — a compact row-based binary format that embeds its own schema, widely used in Kafka pipelines. For testing Avro decoders and schema evolution.
Preview — schema + first 5 rowsavro
| idint64 | namestring | emailstring | departmentstring | activebool | scoredouble | joineddate |
|---|---|---|---|---|---|---|
| 1001 | Ada Lovelace | ada.lovelace@example.com | Engineering | true | 98.5 | 2021-03-01 |
| 1002 | Alan Turing | alan.turing@example.com | Research | true | 95 | 2020-06-15 |
| 1003 | Grace Hopper | grace.hopper@example.com | Engineering | false | 91.2 | 2019-11-20 |
| 1004 | Katherine Johnson | katherine.johnson@example.com | Operations | true | 96.8 | 2022-01-10 |
| 1005 | Edsger Dijkstra | edsger.dijkstra@example.com | Research | false | 89.4 | 2018-09-05 |
Decoded table — all 5 rows shown.
Specifications
- Rows
- 5
- Columns
- 7
- Format
- Apache Avro
- Layout
- row
- Schema
- embedded
Related files
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- csvE-commerce Customers (CSV, 500 rows)A realistic e-commerce customer directory (500 rows) — part of a relational dataset (products, customers, orders) with CSV, JSON, SQL, and Parquet twins for testing joins, imports, and conversion.
- csvE-commerce Orders (CSV, 2000 rows)A realistic e-commerce order lines (customer_id → customers, product_id → products) (2000 rows) — part of a relational dataset (products, customers, orders) with CSV, JSON, SQL, and Parquet twins for testing joins, imports, and conversion.
- parquetE-commerce Orders (Parquet, 2000 rows)The e-commerce orders table as Apache Parquet — the columnar twin, for testing analytics engines (pandas, DuckDB, Spark).
- csvE-commerce Products (CSV, 200 rows)A realistic e-commerce product catalogue (200 rows) — part of a relational dataset (products, customers, orders) with CSV, JSON, SQL, and Parquet twins for testing joins, imports, and conversion.
- parquetE-commerce Products (Parquet, 200 rows)The e-commerce products table as Apache Parquet — the columnar twin, for testing analytics engines (pandas, DuckDB, Spark).
Generated by generation/data_binary.py. Free for any use, no attribution required — license.