Package com.google.privacy.dlp.v2

Interface QuasiIdOrBuilder

  • All Superinterfaces:
    com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder
    All Known Implementing Classes:
    QuasiId, QuasiId.Builder
    public interface QuasiIdOrBuilder
extends com.google.protobuf.MessageOrBuilder

    • Method Summary

      All Methods Instance Methods Abstract Methods 
      Modifier and Type Method Description
      String getCustomTag()
      A column can be tagged with a custom tag.
      com.google.protobuf.ByteString getCustomTagBytes()
      A column can be tagged with a custom tag.
      FieldId getField()
      Required.
      FieldIdOrBuilder getFieldOrBuilder()
      Required.
      com.google.protobuf.Empty getInferred()
      If no semantic tag is indicated, we infer the statistical model from the distribution of values in the input data
      com.google.protobuf.EmptyOrBuilder getInferredOrBuilder()
      If no semantic tag is indicated, we infer the statistical model from the distribution of values in the input data
      InfoType getInfoType()
      A column can be tagged with a InfoType to use the relevant public dataset as a statistical model of population, if available.
      InfoTypeOrBuilder getInfoTypeOrBuilder()
      A column can be tagged with a InfoType to use the relevant public dataset as a statistical model of population, if available.
      QuasiId.TagCase getTagCase()  
      boolean hasCustomTag()
      A column can be tagged with a custom tag.
      boolean hasField()
      Required.
      boolean hasInferred()
      If no semantic tag is indicated, we infer the statistical model from the distribution of values in the input data
      boolean hasInfoType()
      A column can be tagged with a InfoType to use the relevant public dataset as a statistical model of population, if available.

      • 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

      • hasField

        boolean hasField()
         Required. Identifies the column.
        .google.privacy.dlp.v2.FieldId field = 1 [(.google.api.field_behavior) = REQUIRED];
        Returns:
        Whether the field field is set.

      • getField

        FieldId getField()
         Required. Identifies the column.
        .google.privacy.dlp.v2.FieldId field = 1 [(.google.api.field_behavior) = REQUIRED];
        Returns:
        The field.

      • getFieldOrBuilder

        FieldIdOrBuilder getFieldOrBuilder()
         Required. Identifies the column.
        .google.privacy.dlp.v2.FieldId field = 1 [(.google.api.field_behavior) = REQUIRED];

      • hasInfoType

        boolean hasInfoType()
         A column can be tagged with a InfoType to use the relevant public
 dataset as a statistical model of population, if available. We
 currently support US ZIP codes, region codes, ages and genders.
 To programmatically obtain the list of supported InfoTypes, use
 ListInfoTypes with the supported_by=RISK_ANALYSIS filter.
        .google.privacy.dlp.v2.InfoType info_type = 2;
        Returns:
        Whether the infoType field is set.

      • getInfoType

        InfoType getInfoType()
         A column can be tagged with a InfoType to use the relevant public
 dataset as a statistical model of population, if available. We
 currently support US ZIP codes, region codes, ages and genders.
 To programmatically obtain the list of supported InfoTypes, use
 ListInfoTypes with the supported_by=RISK_ANALYSIS filter.
        .google.privacy.dlp.v2.InfoType info_type = 2;
        Returns:
        The infoType.

      • getInfoTypeOrBuilder

        InfoTypeOrBuilder getInfoTypeOrBuilder()
         A column can be tagged with a InfoType to use the relevant public
 dataset as a statistical model of population, if available. We
 currently support US ZIP codes, region codes, ages and genders.
 To programmatically obtain the list of supported InfoTypes, use
 ListInfoTypes with the supported_by=RISK_ANALYSIS filter.
        .google.privacy.dlp.v2.InfoType info_type = 2;

      • hasCustomTag

        boolean hasCustomTag()
         A column can be tagged with a custom tag. In this case, the user must
 indicate an auxiliary table that contains statistical information on
 the possible values of this column (below).
        string custom_tag = 3;
        Returns:
        Whether the customTag field is set.

      • getCustomTag

        String getCustomTag()
         A column can be tagged with a custom tag. In this case, the user must
 indicate an auxiliary table that contains statistical information on
 the possible values of this column (below).
        string custom_tag = 3;
        Returns:
        The customTag.

      • getCustomTagBytes

        com.google.protobuf.ByteString getCustomTagBytes()
         A column can be tagged with a custom tag. In this case, the user must
 indicate an auxiliary table that contains statistical information on
 the possible values of this column (below).
        string custom_tag = 3;
        Returns:
        The bytes for customTag.

      • hasInferred

        boolean hasInferred()
         If no semantic tag is indicated, we infer the statistical model from
 the distribution of values in the input data
        .google.protobuf.Empty inferred = 4;
        Returns:
        Whether the inferred field is set.

      • getInferred

        com.google.protobuf.Empty getInferred()
         If no semantic tag is indicated, we infer the statistical model from
 the distribution of values in the input data
        .google.protobuf.Empty inferred = 4;
        Returns:
        The inferred.

      • getInferredOrBuilder

        com.google.protobuf.EmptyOrBuilder getInferredOrBuilder()
         If no semantic tag is indicated, we infer the statistical model from
 the distribution of values in the input data
        .google.protobuf.Empty inferred = 4;