@ancient-wolf-19325 Is using polars' LazyFrames across tasks useless as Flyte calls

.collect()

at the end of a task to serialize it therefore needing potentially a lot of RAM? This would defeat the whole purpose of using

LazyFrame

Yes, using polars'

LazyFrame

as a Flyte task output is currently not effective for memory savings, because Flyte must materialize (i.e., call

.collect()

) the

LazyFrame

to serialize and transfer it between tasks. This means the entire dataset is loaded into memory at the end of the task, which negates the main benefit of `LazyFrame`—deferred, lazy evaluation and low memory usage. This limitation is acknowledged in Flyte's discussions and issues, and users are advised to convert

LazyFrame

to

DataFrame

explicitly if needed, as Flyte's type transformers do not natively support

LazyFrame

without materialization (Flyte Polars plugin discussion; Flyte issue #5678). Would you like more detail on how Flyte handles polars objects or possible workarounds? Sources: - Flyte Issue #5678 👍 0 button 👎 0 button 💡 Hint: Mention @runllm in the thread for followups.