Is it sufficient to use the checkpoint directory with write-ahead logs?BTW. I use Kafka connector to read data from EventHub
Tree-based estimators in pyspark.ml have an argument called checkpointIntervalcheckpointInterval = Param(parent='undefined', name='checkpointInterval', doc='set checkpoint interval (>= 1) or disable checkpoint (-1). E.g. 10 means that the cache will ...
@Federico Trifoglio​ :If sc.getCheckpointDir() returns None, it means that no checkpoint directory is set in the SparkContext. In this case, the checkpointInterval argument will indeed be ignored. To set a checkpoint directory, you can use the SparkC...
Below function executes fine: def autoload_to_table(data_source, source_format, table_name, checkpoint_directory): query = (spark.readStream .format("cloudFiles") .option("cloudFiles.format", source_format) .option("cloudFile...
Autoloader is not supported on community edition.
