com.google.api.services.dlp.v2.model

Class GooglePrivacyDlpV2QuasiId

java.lang.Object

java.util.AbstractMap<String,Object>

com.google.api.client.util.GenericData

com.google.api.client.json.GenericJson

com.google.api.services.dlp.v2.model.GooglePrivacyDlpV2QuasiId

All Implemented Interfaces:

Cloneable, Map<String,Object>

public final class GooglePrivacyDlpV2QuasiId
extends GenericJson

A column with a semantic tag attached.

This is the Java data model class that specifies how to parse/serialize into the JSON that is transmitted over HTTP when working with the Cloud Data Loss Prevention (DLP) API. For a detailed explanation see: https://developers.google.com/api-client-library/java/google-http-java-client/json

Author:

Google, Inc.

Nested Class Summary

Nested classes/interfaces inherited from class com.google.api.client.util.GenericData

GenericData.Flags

Nested classes/interfaces inherited from class java.util.AbstractMap

AbstractMap.SimpleEntry<K,V>, AbstractMap.SimpleImmutableEntry<K,V>

Nested classes/interfaces inherited from interface java.util.Map

Map.Entry<K,V>

Constructor Summary

Constructors

Constructor and Description
GooglePrivacyDlpV2QuasiId()

Method Summary

Modifier and Type	Method and Description
GooglePrivacyDlpV2QuasiId	clone()
String	getCustomTag() A column can be tagged with a custom tag.
GooglePrivacyDlpV2FieldId	getField() Required.
GoogleProtobufEmpty	getInferred() If no semantic tag is indicated, we infer the statistical model from the distribution of values in the input data
GooglePrivacyDlpV2InfoType	getInfoType() A column can be tagged with a InfoType to use the relevant public dataset as a statistical model of population, if available.
GooglePrivacyDlpV2QuasiId	set(String fieldName, Object value)
GooglePrivacyDlpV2QuasiId	setCustomTag(String customTag) A column can be tagged with a custom tag.
GooglePrivacyDlpV2QuasiId	setField(GooglePrivacyDlpV2FieldId field) Required.
GooglePrivacyDlpV2QuasiId	setInferred(GoogleProtobufEmpty inferred) If no semantic tag is indicated, we infer the statistical model from the distribution of values in the input data
GooglePrivacyDlpV2QuasiId	setInfoType(GooglePrivacyDlpV2InfoType infoType) 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 class com.google.api.client.json.GenericJson

getFactory, setFactory, toPrettyString, toString

Methods inherited from class com.google.api.client.util.GenericData

entrySet, equals, get, getClassInfo, getUnknownKeys, hashCode, put, putAll, remove, setUnknownKeys

Methods inherited from class java.util.AbstractMap

clear, containsKey, containsValue, isEmpty, keySet, size, values

Methods inherited from class java.lang.Object

finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface java.util.Map

compute, computeIfAbsent, computeIfPresent, forEach, getOrDefault, merge, putIfAbsent, remove, replace, replace, replaceAll

Constructor Detail

GooglePrivacyDlpV2QuasiId

public GooglePrivacyDlpV2QuasiId()

Method Detail

getCustomTag

public 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).

Returns:

value or null for none

setCustomTag

public GooglePrivacyDlpV2QuasiId setCustomTag(String customTag)

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).

Parameters:

customTag - customTag or null for none

getField

public GooglePrivacyDlpV2FieldId getField()

Required. Identifies the column.

Returns:

value or null for none

setField

public GooglePrivacyDlpV2QuasiId setField(GooglePrivacyDlpV2FieldId field)

Required. Identifies the column.

Parameters:

field - field or null for none

getInferred

public GoogleProtobufEmpty getInferred()

If no semantic tag is indicated, we infer the statistical model from the distribution of values in the input data

Returns:

value or null for none

setInferred

public GooglePrivacyDlpV2QuasiId setInferred(GoogleProtobufEmpty inferred)

If no semantic tag is indicated, we infer the statistical model from the distribution of values in the input data

Parameters:

inferred - inferred or null for none

getInfoType

public GooglePrivacyDlpV2InfoType 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.

Returns:

value or null for none

setInfoType

public GooglePrivacyDlpV2QuasiId setInfoType(GooglePrivacyDlpV2InfoType infoType)

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.

Parameters:

infoType - infoType or null for none

set

public GooglePrivacyDlpV2QuasiId set(String fieldName,
                                     Object value)

Overrides:

set in class GenericJson

clone

public GooglePrivacyDlpV2QuasiId clone()

Overrides:

clone in class GenericJson