spark-board: interactive PySpark dataframes visualization

spark-board provides an interactive way to analize PySpark data frame execution plans as a static website displaying the transformations DAG.

Check out the examples for a quick overview of the features (and the corresponding examples source code here).

If you intend to develop spark-board or run from source, check out the documentation.

Usage

spark-board takes a PySpark data frame and inspects the operations to build the DAG. This usually is the final step of a PySpark script, right before writing it to disk.

Install spark-board

pip install spark-board

Run spark-board

from spark_board.html import dump_dataframe, DefaultSettings

# get the PySpark data frame that will be displayed
df = ...

dump_dataframe(
    df=df,
    output_dir="./spark_board_output",
    overwrite=True,  # overwrite output_dir if it already exists
    default_settings=DefaultSettings(),  # override default settings if desired
)

and that's it! spark-board will generate a static website in the defined output_dir folder. You can now serve the website using any web server and inspect the operations.

You can check out the available default settings here.

Serving

spark-board is intended to be a live documentation of PySpark scripts. Because of this, it's advisable to run it every time the source code is updated. For example, spark-board can be run as part of a CI pipeline and the generated website uploaded to a static website hosting service, like Github or Gitlab pages (we actually do this to update and serve the examples in this repository).