Using a custom batch sink

For custom processing that Polars doesn't natively support, you can pass your own function. The team wants to see this pattern even though they'd normally use a built-in sink. Stream digital_rows through the pre-defined record_batch function.

digital_rows is preloaded. A record_batch(batch) function that records each batch's row count and checkout sum into batch_summaries is also defined for you.

This exercise is part of the course

Scaling and Optimizing Data Pipelines with Polars

View Course

Exercise instructions

Stream digital_rows through the function in 5,000-row batches on the streaming engine.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Stream batches through the record_batch function
digital_rows.____(
    record_batch,
    ____=5_000,
    ____="streaming",
)

result = pl.DataFrame(batch_summaries)
print(result)

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