tpch/README.md

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# TPC-H

## Generating TPC-H data with Spark

Databricks provides tooling for generating TPC-H datasets in a Spark cluster:

[https://github.com/databricks/spark-sql-perf](https://github.com/databricks/spark-sql-perf)

## Generating TPC-H data without Spark

For local development and testing, we provide a Python script to generate TPC-H CSV data and convert it into Parquet, 
using DataFusion.

The script requires Docker to be available because it uses the Docker image `ghcr.io/scalytics/tpch-docker` to run
the TPC-H data generator.

Data can be generated as a single Parquet file per table by specifying `--partitions 1`. 

Data will be generated into a `data` directory in the current working directory.

```shell
python tpchgen.py generate --scale-factor 1 --partitions 1
python tpchgen.py convert --scale-factor 1 --partitions 1
```

Data can be generated as multiple Parquet files per table by specifying `--partitions` greater than one. 

```shell
python tpchgen.py generate --scale-factor 1000 --partitions 64
python tpchgen.py convert --scale-factor 1000 --partitions 64
```