To write a dataframe generated in a Flyte task into a FlyteFile, save the dataframe to a file (e.g., CSV or Parquet) within the task, then return a FlyteFile pointing to that file path. Flyte will handle uploading the file to the configured object store and passing it as a FlyteFile to downstream tasks. Example:

import pandas as pd
from flytekit import task
from flytekit.types.file import FlyteFile

@task
def write_df_to_file() -> FlyteFile:
    df = pd.DataFrame({"a": [1, 2], "b": [3, 4]})
    file_path = "output.csv"
    df.to_csv(file_path, index=False)
    return FlyteFile(path=file_path)

This approach is documented in the FlyteFile user guide and Flytesnacks examples. Would you like more detail or examples for other file formats? Sources: - https://github.com/flyteorg/flyte/issues/4241 - https://github.com/flyteorg/flyte/issues/3708 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.

To handle a Spark DataFrame in a Flyte task and write it to a FlyteFile, save the Spark DataFrame to a file (e.g., Parquet) using the Spark API, then return a FlyteFile pointing to the output file or directory. For example:

from flytekit import task
from flytekit.types.file import FlyteFile

@task
def write_spark_df_to_file() -> FlyteFile:
    spark = flytekit.current_context().spark_session
    df = spark.createDataFrame([("Alice", 1), ("Bob", 2)], ["name", "id"])
    output_path = "output.parquet"
    df.write.mode("overwrite").parquet(output_path)
    return FlyteFile(path=output_path)

This method leverages Spark's native file writing and FlyteFile's automatic upload. For more advanced Spark integration, consider using StructuredDataset, which natively supports Spark DataFrames and Parquet serialization. Would you like more detail or an example using StructuredDataset? Sources: - https://github.com/flyteorg/flytesnacks/blob/master/examples/k8s_spark_plugin/k8s_spark_plugin/dataframe_passing.py - https://github.com/flyteorg/flytekit/blob/master/plugins/flytekit-spark/flytekitplugins/spark/schema.py 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.