checkpoint(eager: bool = True) → pyspark.sql.dataframe.DataFrame¶
Returns a checkpointed version of this
DataFrame. Checkpointing can be used to truncate the logical plan of this
DataFrame, which is especially useful in iterative algorithms where the plan may grow exponentially. It will be saved to files inside the checkpoint directory set with
- eagerbool, optional
Whether to checkpoint this
This API is experimental.