pyspark.sql.DataFrame.localCheckpoint

DataFrame.localCheckpoint(eager=True)

Returns a locally checkpointed version of this Dataset. 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. Local checkpoints are stored in the executors using the caching subsystem and therefore they are not reliable.

Parameters

eager – Whether to checkpoint this DataFrame immediately

Note

Experimental

New in version 2.3.

pyspark.sql.DataFrame.limit pyspark.sql.DataFrame.mapInPandas