Package org.mlflow.api.proto

Interface Service.DatasetOrBuilder

  • All Superinterfaces:
    com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder
    All Known Implementing Classes:
    Service.Dataset, Service.Dataset.Builder
    Enclosing class:
    Service
    public static interface Service.DatasetOrBuilder
extends com.google.protobuf.MessageOrBuilder

    • Method Summary

      All Methods Instance Methods Abstract Methods 
      Modifier and Type Method Description
      java.lang.String getDigest()
      Dataset digest, e.g.
      com.google.protobuf.ByteString getDigestBytes()
      Dataset digest, e.g.
      java.lang.String getName()
      The name of the dataset.
      com.google.protobuf.ByteString getNameBytes()
      The name of the dataset.
      java.lang.String getProfile()
      The profile of the dataset.
      com.google.protobuf.ByteString getProfileBytes()
      The profile of the dataset.
      java.lang.String getSchema()
      The schema of the dataset.
      com.google.protobuf.ByteString getSchemaBytes()
      The schema of the dataset.
      java.lang.String getSource()
      The type of the dataset source, e.g.
      com.google.protobuf.ByteString getSourceBytes()
      The type of the dataset source, e.g.
      java.lang.String getSourceType()
      Source information for the dataset.
      com.google.protobuf.ByteString getSourceTypeBytes()
      Source information for the dataset.
      boolean hasDigest()
      Dataset digest, e.g.
      boolean hasName()
      The name of the dataset.
      boolean hasProfile()
      The profile of the dataset.
      boolean hasSchema()
      The schema of the dataset.
      boolean hasSource()
      The type of the dataset source, e.g.
      boolean hasSourceType()
      Source information for the dataset.

      • Methods inherited from interface com.google.protobuf.MessageLiteOrBuilder

        isInitialized

      • Methods inherited from interface com.google.protobuf.MessageOrBuilder

        findInitializationErrors, getAllFields, getDefaultInstanceForType, getDescriptorForType, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof

    • Method Detail

      • hasName

        boolean hasName()
         The name of the dataset. E.g. “my.uc.table@2” “nyc-taxi-dataset”, “fantastic-elk-3”
        optional string name = 1 [(.mlflow.validate_required) = true];
        Returns:
        Whether the name field is set.

      • getName

        java.lang.String getName()
         The name of the dataset. E.g. “my.uc.table@2” “nyc-taxi-dataset”, “fantastic-elk-3”
        optional string name = 1 [(.mlflow.validate_required) = true];
        Returns:
        The name.

      • getNameBytes

        com.google.protobuf.ByteString getNameBytes()
         The name of the dataset. E.g. “my.uc.table@2” “nyc-taxi-dataset”, “fantastic-elk-3”
        optional string name = 1 [(.mlflow.validate_required) = true];
        Returns:
        The bytes for name.

      • hasDigest

        boolean hasDigest()
         Dataset digest, e.g. an md5 hash of the dataset that uniquely identifies it
 within datasets of the same name.
        optional string digest = 2 [(.mlflow.validate_required) = true];
        Returns:
        Whether the digest field is set.

      • getDigest

        java.lang.String getDigest()
         Dataset digest, e.g. an md5 hash of the dataset that uniquely identifies it
 within datasets of the same name.
        optional string digest = 2 [(.mlflow.validate_required) = true];
        Returns:
        The digest.

      • getDigestBytes

        com.google.protobuf.ByteString getDigestBytes()
         Dataset digest, e.g. an md5 hash of the dataset that uniquely identifies it
 within datasets of the same name.
        optional string digest = 2 [(.mlflow.validate_required) = true];
        Returns:
        The bytes for digest.

      • hasSourceType

        boolean hasSourceType()
         Source information for the dataset. Note that the source may not exactly reproduce the
 dataset if it was transformed / modified before use with MLflow.
        optional string source_type = 3 [(.mlflow.validate_required) = true];
        Returns:
        Whether the sourceType field is set.

      • getSourceType

        java.lang.String getSourceType()
         Source information for the dataset. Note that the source may not exactly reproduce the
 dataset if it was transformed / modified before use with MLflow.
        optional string source_type = 3 [(.mlflow.validate_required) = true];
        Returns:
        The sourceType.

      • getSourceTypeBytes

        com.google.protobuf.ByteString getSourceTypeBytes()
         Source information for the dataset. Note that the source may not exactly reproduce the
 dataset if it was transformed / modified before use with MLflow.
        optional string source_type = 3 [(.mlflow.validate_required) = true];
        Returns:
        The bytes for sourceType.

      • hasSource

        boolean hasSource()
         The type of the dataset source, e.g. ‘databricks-uc-table’, ‘DBFS’, ‘S3’, ...
        optional string source = 4 [(.mlflow.validate_required) = true];
        Returns:
        Whether the source field is set.

      • getSource

        java.lang.String getSource()
         The type of the dataset source, e.g. ‘databricks-uc-table’, ‘DBFS’, ‘S3’, ...
        optional string source = 4 [(.mlflow.validate_required) = true];
        Returns:
        The source.

      • getSourceBytes

        com.google.protobuf.ByteString getSourceBytes()
         The type of the dataset source, e.g. ‘databricks-uc-table’, ‘DBFS’, ‘S3’, ...
        optional string source = 4 [(.mlflow.validate_required) = true];
        Returns:
        The bytes for source.

      • hasSchema

        boolean hasSchema()
         The schema of the dataset. E.g., MLflow ColSpec JSON for a dataframe, MLflow TensorSpec JSON
 for an ndarray, or another schema format.
        optional string schema = 5;
        Returns:
        Whether the schema field is set.

      • getSchema

        java.lang.String getSchema()
         The schema of the dataset. E.g., MLflow ColSpec JSON for a dataframe, MLflow TensorSpec JSON
 for an ndarray, or another schema format.
        optional string schema = 5;
        Returns:
        The schema.

      • getSchemaBytes

        com.google.protobuf.ByteString getSchemaBytes()
         The schema of the dataset. E.g., MLflow ColSpec JSON for a dataframe, MLflow TensorSpec JSON
 for an ndarray, or another schema format.
        optional string schema = 5;
        Returns:
        The bytes for schema.

      • hasProfile

        boolean hasProfile()
         The profile of the dataset. Summary statistics for the dataset, such as the number of rows
 in a table, the mean / std / mode of each column in a table, or the number of elements
 in an array.
        optional string profile = 6;
        Returns:
        Whether the profile field is set.

      • getProfile

        java.lang.String getProfile()
         The profile of the dataset. Summary statistics for the dataset, such as the number of rows
 in a table, the mean / std / mode of each column in a table, or the number of elements
 in an array.
        optional string profile = 6;
        Returns:
        The profile.

      • getProfileBytes

        com.google.protobuf.ByteString getProfileBytes()
         The profile of the dataset. Summary statistics for the dataset, such as the number of rows
 in a table, the mean / std / mode of each column in a table, or the number of elements
 in an array.
        optional string profile = 6;
        Returns:
        The bytes for profile.