Packages

p

org.mlflow.spark

autologging

package autologging

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Type Members

  1. trait MlflowAutologEventSubscriber extends AnyRef

    Trait defining subscriber interface for receiving information about Spark datasource reads.

    Trait defining subscriber interface for receiving information about Spark datasource reads. This trait can be implemented in Python in order to obtain datasource read information, see https://www.py4j.org/advanced_topics.html#implementing-java-interfaces-from-python-callback

  2. class ReplAwareSparkDataSourceListener extends SparkDataSourceListener

    Implementation of the SparkListener interface used to detect Spark datasource reads.

    Implementation of the SparkListener interface used to detect Spark datasource reads. and notify subscribers. Used in REPL-ID aware environments (e.g. Databricks)

  3. class SparkDataSourceListener extends SparkListener

    Implementation of the SparkListener interface used to detect Spark datasource reads.

    Implementation of the SparkListener interface used to detect Spark datasource reads. and notify subscribers.

Value Members

  1. object DatasourceAttributeExtractor extends DatasourceAttributeExtractorBase

    Default datasource attribute extractor

  2. object MlflowAutologEventPublisher extends MlflowAutologEventPublisherImpl

    Object exposing the actual implementation of MlflowAutologEventPublisher.

    Object exposing the actual implementation of MlflowAutologEventPublisher. We opt for this pattern (an object extending a trait) so that we can mock methods of the trait in testing

  3. object ReplAwareDatasourceAttributeExtractor extends DatasourceAttributeExtractorBase

    Datasource attribute extractor for REPL-ID aware environments (e.g.

    Datasource attribute extractor for REPL-ID aware environments (e.g. Databricks)

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