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/*
* Copyright 2024 Google LLC
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* https://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
// Generated by the protocol buffer compiler. DO NOT EDIT!
// source: google/cloud/dataplex/v1/data_profile.proto
// Protobuf Java Version: 3.25.3
package com.google.cloud.dataplex.v1;
/**
*
*
*
* DataProfileResult defines the output of DataProfileScan. Each field of the
* table will have field type specific profile result.
*
*
* Protobuf type {@code google.cloud.dataplex.v1.DataProfileResult}
*/
public final class DataProfileResult extends com.google.protobuf.GeneratedMessageV3
implements
// @@protoc_insertion_point(message_implements:google.cloud.dataplex.v1.DataProfileResult)
DataProfileResultOrBuilder {
private static final long serialVersionUID = 0L;
// Use DataProfileResult.newBuilder() to construct.
private DataProfileResult(com.google.protobuf.GeneratedMessageV3.Builder builder) {
super(builder);
}
private DataProfileResult() {}
@java.lang.Override
@SuppressWarnings({"unused"})
protected java.lang.Object newInstance(UnusedPrivateParameter unused) {
return new DataProfileResult();
}
public static final com.google.protobuf.Descriptors.Descriptor getDescriptor() {
return com.google.cloud.dataplex.v1.DataProfileProto
.internal_static_google_cloud_dataplex_v1_DataProfileResult_descriptor;
}
@java.lang.Override
protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
internalGetFieldAccessorTable() {
return com.google.cloud.dataplex.v1.DataProfileProto
.internal_static_google_cloud_dataplex_v1_DataProfileResult_fieldAccessorTable
.ensureFieldAccessorsInitialized(
com.google.cloud.dataplex.v1.DataProfileResult.class,
com.google.cloud.dataplex.v1.DataProfileResult.Builder.class);
}
public interface ProfileOrBuilder
extends
// @@protoc_insertion_point(interface_extends:google.cloud.dataplex.v1.DataProfileResult.Profile)
com.google.protobuf.MessageOrBuilder {
/**
*
*
*
* List of fields with structural and profile information for each field.
*
* Contains name, type, mode and field type specific profile information.
*
*
* Protobuf type {@code google.cloud.dataplex.v1.DataProfileResult.Profile}
*/
public static final class Profile extends com.google.protobuf.GeneratedMessageV3
implements
// @@protoc_insertion_point(message_implements:google.cloud.dataplex.v1.DataProfileResult.Profile)
ProfileOrBuilder {
private static final long serialVersionUID = 0L;
// Use Profile.newBuilder() to construct.
private Profile(com.google.protobuf.GeneratedMessageV3.Builder builder) {
super(builder);
}
private Profile() {
fields_ = java.util.Collections.emptyList();
}
@java.lang.Override
@SuppressWarnings({"unused"})
protected java.lang.Object newInstance(UnusedPrivateParameter unused) {
return new Profile();
}
public static final com.google.protobuf.Descriptors.Descriptor getDescriptor() {
return com.google.cloud.dataplex.v1.DataProfileProto
.internal_static_google_cloud_dataplex_v1_DataProfileResult_Profile_descriptor;
}
@java.lang.Override
protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
internalGetFieldAccessorTable() {
return com.google.cloud.dataplex.v1.DataProfileProto
.internal_static_google_cloud_dataplex_v1_DataProfileResult_Profile_fieldAccessorTable
.ensureFieldAccessorsInitialized(
com.google.cloud.dataplex.v1.DataProfileResult.Profile.class,
com.google.cloud.dataplex.v1.DataProfileResult.Profile.Builder.class);
}
public interface FieldOrBuilder
extends
// @@protoc_insertion_point(interface_extends:google.cloud.dataplex.v1.DataProfileResult.Profile.Field)
com.google.protobuf.MessageOrBuilder {
/**
*
*
*
* The name of the field.
*
*
* string name = 1;
*
* @return The name.
*/
java.lang.String getName();
/**
*
*
*
* The name of the field.
*
*
* string name = 1;
*
* @return The bytes for name.
*/
com.google.protobuf.ByteString getNameBytes();
/**
*
*
*
* The data type retrieved from the schema of the data source. For
* instance, for a BigQuery native table, it is the [BigQuery Table
* Schema](https://cloud.google.com/bigquery/docs/reference/rest/v2/tables#tablefieldschema).
* For a Dataplex Entity, it is the [Entity
* Schema](https://cloud.google.com/dataplex/docs/reference/rpc/google.cloud.dataplex.v1#type_3).
*
*
* string type = 2;
*
* @return The type.
*/
java.lang.String getType();
/**
*
*
*
* The data type retrieved from the schema of the data source. For
* instance, for a BigQuery native table, it is the [BigQuery Table
* Schema](https://cloud.google.com/bigquery/docs/reference/rest/v2/tables#tablefieldschema).
* For a Dataplex Entity, it is the [Entity
* Schema](https://cloud.google.com/dataplex/docs/reference/rpc/google.cloud.dataplex.v1#type_3).
*
*
* string type = 2;
*
* @return The bytes for type.
*/
com.google.protobuf.ByteString getTypeBytes();
/**
*
*
*
* The mode of the field. Possible values include:
*
* * REQUIRED, if it is a required field.
* * NULLABLE, if it is an optional field.
* * REPEATED, if it is a repeated field.
*
* The mode of the field. Possible values include:
*
* * REQUIRED, if it is a required field.
* * NULLABLE, if it is an optional field.
* * REPEATED, if it is a repeated field.
*
*
* string mode = 3;
*
* @return The bytes for mode.
*/
com.google.protobuf.ByteString getModeBytes();
/**
*
*
*
* Profile information for the corresponding field.
*
*
* .google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo profile = 4;
*
*
* @return Whether the profile field is set.
*/
boolean hasProfile();
/**
*
*
*
* Profile information for the corresponding field.
*
* Ratio of rows with distinct values against total scanned rows.
* Not available for complex non-groupable field type RECORD and fields
* with REPEATABLE mode.
*
* The list of top N non-null values, frequency and ratio with which
* they occur in the scanned data. N is 10 or equal to the number of
* distinct values in the field, whichever is smaller. Not available for
* complex non-groupable field type RECORD and fields with REPEATABLE
* mode.
*
* The list of top N non-null values, frequency and ratio with which
* they occur in the scanned data. N is 10 or equal to the number of
* distinct values in the field, whichever is smaller. Not available for
* complex non-groupable field type RECORD and fields with REPEATABLE
* mode.
*
* The list of top N non-null values, frequency and ratio with which
* they occur in the scanned data. N is 10 or equal to the number of
* distinct values in the field, whichever is smaller. Not available for
* complex non-groupable field type RECORD and fields with REPEATABLE
* mode.
*
* The list of top N non-null values, frequency and ratio with which
* they occur in the scanned data. N is 10 or equal to the number of
* distinct values in the field, whichever is smaller. Not available for
* complex non-groupable field type RECORD and fields with REPEATABLE
* mode.
*
* The list of top N non-null values, frequency and ratio with which
* they occur in the scanned data. N is 10 or equal to the number of
* distinct values in the field, whichever is smaller. Not available for
* complex non-groupable field type RECORD and fields with REPEATABLE
* mode.
*
* Minimum of non-null values in the scanned data. NaN, if the field
* has a NaN.
*
*
* int64 min = 4;
*
* @return The min.
*/
long getMin();
/**
*
*
*
* A quartile divides the number of data points into four parts, or
* quarters, of more-or-less equal size. Three main quartiles used
* are: The first quartile (Q1) splits off the lowest 25% of data from
* the highest 75%. It is also known as the lower or 25th empirical
* quartile, as 25% of the data is below this point. The second
* quartile (Q2) is the median of a data set. So, 50% of the data lies
* below this point. The third quartile (Q3) splits off the highest
* 25% of data from the lowest 75%. It is known as the upper or 75th
* empirical quartile, as 75% of the data lies below this point.
* Here, the quartiles is provided as an ordered list of approximate
* quartile values for the scanned data, occurring in order Q1,
* median, Q3.
*
*
* repeated int64 quartiles = 6;
*
* @return A list containing the quartiles.
*/
java.util.List getQuartilesList();
/**
*
*
*
* A quartile divides the number of data points into four parts, or
* quarters, of more-or-less equal size. Three main quartiles used
* are: The first quartile (Q1) splits off the lowest 25% of data from
* the highest 75%. It is also known as the lower or 25th empirical
* quartile, as 25% of the data is below this point. The second
* quartile (Q2) is the median of a data set. So, 50% of the data lies
* below this point. The third quartile (Q3) splits off the highest
* 25% of data from the lowest 75%. It is known as the upper or 75th
* empirical quartile, as 75% of the data lies below this point.
* Here, the quartiles is provided as an ordered list of approximate
* quartile values for the scanned data, occurring in order Q1,
* median, Q3.
*
*
* repeated int64 quartiles = 6;
*
* @return The count of quartiles.
*/
int getQuartilesCount();
/**
*
*
*
* A quartile divides the number of data points into four parts, or
* quarters, of more-or-less equal size. Three main quartiles used
* are: The first quartile (Q1) splits off the lowest 25% of data from
* the highest 75%. It is also known as the lower or 25th empirical
* quartile, as 25% of the data is below this point. The second
* quartile (Q2) is the median of a data set. So, 50% of the data lies
* below this point. The third quartile (Q3) splits off the highest
* 25% of data from the lowest 75%. It is known as the upper or 75th
* empirical quartile, as 75% of the data lies below this point.
* Here, the quartiles is provided as an ordered list of approximate
* quartile values for the scanned data, occurring in order Q1,
* median, Q3.
*
*
* repeated int64 quartiles = 6;
*
* @param index The index of the element to return.
* @return The quartiles at the given index.
*/
long getQuartiles(int index);
/**
*
*
*
* Maximum of non-null values in the scanned data. NaN, if the field
* has a NaN.
*
*
* int64 max = 5;
*
* @return The max.
*/
long getMax();
}
/**
*
*
*
* The profile information for an integer type field.
*
*
* Protobuf type {@code
* google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo}
*/
public static final class IntegerFieldInfo extends com.google.protobuf.GeneratedMessageV3
implements
// @@protoc_insertion_point(message_implements:google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo)
IntegerFieldInfoOrBuilder {
private static final long serialVersionUID = 0L;
// Use IntegerFieldInfo.newBuilder() to construct.
private IntegerFieldInfo(com.google.protobuf.GeneratedMessageV3.Builder builder) {
super(builder);
}
private IntegerFieldInfo() {
quartiles_ = emptyLongList();
}
@java.lang.Override
@SuppressWarnings({"unused"})
protected java.lang.Object newInstance(UnusedPrivateParameter unused) {
return new IntegerFieldInfo();
}
public static final com.google.protobuf.Descriptors.Descriptor getDescriptor() {
return com.google.cloud.dataplex.v1.DataProfileProto
.internal_static_google_cloud_dataplex_v1_DataProfileResult_Profile_Field_ProfileInfo_IntegerFieldInfo_descriptor;
}
@java.lang.Override
protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
internalGetFieldAccessorTable() {
return com.google.cloud.dataplex.v1.DataProfileProto
.internal_static_google_cloud_dataplex_v1_DataProfileResult_Profile_Field_ProfileInfo_IntegerFieldInfo_fieldAccessorTable
.ensureFieldAccessorsInitialized(
com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
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com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.IntegerFieldInfo.Builder.class);
}
public static final int AVERAGE_FIELD_NUMBER = 1;
private double average_ = 0D;
/**
*
*
*
* Average of non-null values in the scanned data. NaN, if the field
* has a NaN.
*
*
* double average = 1;
*
* @return The average.
*/
@java.lang.Override
public double getAverage() {
return average_;
}
public static final int STANDARD_DEVIATION_FIELD_NUMBER = 3;
private double standardDeviation_ = 0D;
/**
*
*
*
* Standard deviation of non-null values in the scanned data. NaN, if
* the field has a NaN.
*
*
* double standard_deviation = 3;
*
* @return The standardDeviation.
*/
@java.lang.Override
public double getStandardDeviation() {
return standardDeviation_;
}
public static final int MIN_FIELD_NUMBER = 4;
private long min_ = 0L;
/**
*
*
*
* Minimum of non-null values in the scanned data. NaN, if the field
* has a NaN.
*
*
* int64 min = 4;
*
* @return The min.
*/
@java.lang.Override
public long getMin() {
return min_;
}
public static final int QUARTILES_FIELD_NUMBER = 6;
@SuppressWarnings("serial")
private com.google.protobuf.Internal.LongList quartiles_ = emptyLongList();
/**
*
*
*
* A quartile divides the number of data points into four parts, or
* quarters, of more-or-less equal size. Three main quartiles used
* are: The first quartile (Q1) splits off the lowest 25% of data from
* the highest 75%. It is also known as the lower or 25th empirical
* quartile, as 25% of the data is below this point. The second
* quartile (Q2) is the median of a data set. So, 50% of the data lies
* below this point. The third quartile (Q3) splits off the highest
* 25% of data from the lowest 75%. It is known as the upper or 75th
* empirical quartile, as 75% of the data lies below this point.
* Here, the quartiles is provided as an ordered list of approximate
* quartile values for the scanned data, occurring in order Q1,
* median, Q3.
*
*
* repeated int64 quartiles = 6;
*
* @return A list containing the quartiles.
*/
@java.lang.Override
public java.util.List getQuartilesList() {
return quartiles_;
}
/**
*
*
*
* A quartile divides the number of data points into four parts, or
* quarters, of more-or-less equal size. Three main quartiles used
* are: The first quartile (Q1) splits off the lowest 25% of data from
* the highest 75%. It is also known as the lower or 25th empirical
* quartile, as 25% of the data is below this point. The second
* quartile (Q2) is the median of a data set. So, 50% of the data lies
* below this point. The third quartile (Q3) splits off the highest
* 25% of data from the lowest 75%. It is known as the upper or 75th
* empirical quartile, as 75% of the data lies below this point.
* Here, the quartiles is provided as an ordered list of approximate
* quartile values for the scanned data, occurring in order Q1,
* median, Q3.
*
*
* repeated int64 quartiles = 6;
*
* @return The count of quartiles.
*/
public int getQuartilesCount() {
return quartiles_.size();
}
/**
*
*
*
* A quartile divides the number of data points into four parts, or
* quarters, of more-or-less equal size. Three main quartiles used
* are: The first quartile (Q1) splits off the lowest 25% of data from
* the highest 75%. It is also known as the lower or 25th empirical
* quartile, as 25% of the data is below this point. The second
* quartile (Q2) is the median of a data set. So, 50% of the data lies
* below this point. The third quartile (Q3) splits off the highest
* 25% of data from the lowest 75%. It is known as the upper or 75th
* empirical quartile, as 75% of the data lies below this point.
* Here, the quartiles is provided as an ordered list of approximate
* quartile values for the scanned data, occurring in order Q1,
* median, Q3.
*
*
* repeated int64 quartiles = 6;
*
* @param index The index of the element to return.
* @return The quartiles at the given index.
*/
public long getQuartiles(int index) {
return quartiles_.getLong(index);
}
private int quartilesMemoizedSerializedSize = -1;
public static final int MAX_FIELD_NUMBER = 5;
private long max_ = 0L;
/**
*
*
*
* Maximum of non-null values in the scanned data. NaN, if the field
* has a NaN.
*
*
* int64 max = 5;
*
* @return The max.
*/
@java.lang.Override
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return max_;
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private byte memoizedIsInitialized = -1;
@java.lang.Override
public final boolean isInitialized() {
byte isInitialized = memoizedIsInitialized;
if (isInitialized == 1) return true;
if (isInitialized == 0) return false;
memoizedIsInitialized = 1;
return true;
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@java.lang.Override
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throws java.io.IOException {
getSerializedSize();
if (java.lang.Double.doubleToRawLongBits(average_) != 0) {
output.writeDouble(1, average_);
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if (java.lang.Double.doubleToRawLongBits(standardDeviation_) != 0) {
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for (int i = 0; i < quartiles_.size(); i++) {
output.writeInt64NoTag(quartiles_.getLong(i));
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getUnknownFields().writeTo(output);
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@java.lang.Override
public int getSerializedSize() {
int size = memoizedSize;
if (size != -1) return size;
size = 0;
if (java.lang.Double.doubleToRawLongBits(average_) != 0) {
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quartilesMemoizedSerializedSize = dataSize;
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size += getUnknownFields().getSerializedSize();
memoizedSize = size;
return size;
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@java.lang.Override
public boolean equals(final java.lang.Object obj) {
if (obj == this) {
return true;
}
if (!(obj
instanceof
com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.IntegerFieldInfo)) {
return super.equals(obj);
}
com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
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obj;
if (java.lang.Double.doubleToLongBits(getAverage())
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if (java.lang.Double.doubleToLongBits(getStandardDeviation())
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if (getMin() != other.getMin()) return false;
if (!getQuartilesList().equals(other.getQuartilesList())) return false;
if (getMax() != other.getMax()) return false;
if (!getUnknownFields().equals(other.getUnknownFields())) return false;
return true;
}
@java.lang.Override
public int hashCode() {
if (memoizedHashCode != 0) {
return memoizedHashCode;
}
int hash = 41;
hash = (19 * hash) + getDescriptor().hashCode();
hash = (37 * hash) + AVERAGE_FIELD_NUMBER;
hash =
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parseFrom(java.nio.ByteBuffer data)
throws com.google.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data);
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public static com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
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parseFrom(
java.nio.ByteBuffer data,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws com.google.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data, extensionRegistry);
}
public static com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.IntegerFieldInfo
parseFrom(com.google.protobuf.ByteString data)
throws com.google.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data);
}
public static com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.IntegerFieldInfo
parseFrom(
com.google.protobuf.ByteString data,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws com.google.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data, extensionRegistry);
}
public static com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.IntegerFieldInfo
parseFrom(byte[] data) throws com.google.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data);
}
public static com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
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parseFrom(byte[] data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws com.google.protobuf.InvalidProtocolBufferException {
return PARSER.parseFrom(data, extensionRegistry);
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public static com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
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parseFrom(java.io.InputStream input) throws java.io.IOException {
return com.google.protobuf.GeneratedMessageV3.parseWithIOException(PARSER, input);
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public static com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.IntegerFieldInfo
parseFrom(
java.io.InputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws java.io.IOException {
return com.google.protobuf.GeneratedMessageV3.parseWithIOException(
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public static com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
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parseDelimitedFrom(java.io.InputStream input) throws java.io.IOException {
return com.google.protobuf.GeneratedMessageV3.parseDelimitedWithIOException(
PARSER, input);
}
public static com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.IntegerFieldInfo
parseDelimitedFrom(
java.io.InputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws java.io.IOException {
return com.google.protobuf.GeneratedMessageV3.parseDelimitedWithIOException(
PARSER, input, extensionRegistry);
}
public static com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.IntegerFieldInfo
parseFrom(com.google.protobuf.CodedInputStream input) throws java.io.IOException {
return com.google.protobuf.GeneratedMessageV3.parseWithIOException(PARSER, input);
}
public static com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.IntegerFieldInfo
parseFrom(
com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws java.io.IOException {
return com.google.protobuf.GeneratedMessageV3.parseWithIOException(
PARSER, input, extensionRegistry);
}
@java.lang.Override
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return newBuilder();
}
public static Builder newBuilder() {
return DEFAULT_INSTANCE.toBuilder();
}
public static Builder newBuilder(
com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.IntegerFieldInfo
prototype) {
return DEFAULT_INSTANCE.toBuilder().mergeFrom(prototype);
}
@java.lang.Override
public Builder toBuilder() {
return this == DEFAULT_INSTANCE ? new Builder() : new Builder().mergeFrom(this);
}
@java.lang.Override
protected Builder newBuilderForType(
com.google.protobuf.GeneratedMessageV3.BuilderParent parent) {
Builder builder = new Builder(parent);
return builder;
}
/**
*
*
*
* The profile information for an integer type field.
*
*
* Protobuf type {@code
* google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo}
*/
public static final class Builder
extends com.google.protobuf.GeneratedMessageV3.Builder
implements
// @@protoc_insertion_point(builder_implements:google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo)
com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.IntegerFieldInfoOrBuilder {
public static final com.google.protobuf.Descriptors.Descriptor getDescriptor() {
return com.google.cloud.dataplex.v1.DataProfileProto
.internal_static_google_cloud_dataplex_v1_DataProfileResult_Profile_Field_ProfileInfo_IntegerFieldInfo_descriptor;
}
@java.lang.Override
protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
internalGetFieldAccessorTable() {
return com.google.cloud.dataplex.v1.DataProfileProto
.internal_static_google_cloud_dataplex_v1_DataProfileResult_Profile_Field_ProfileInfo_IntegerFieldInfo_fieldAccessorTable
.ensureFieldAccessorsInitialized(
com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.IntegerFieldInfo.class,
com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.IntegerFieldInfo.Builder.class);
}
// Construct using
// com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo.newBuilder()
private Builder() {}
private Builder(com.google.protobuf.GeneratedMessageV3.BuilderParent parent) {
super(parent);
}
@java.lang.Override
public Builder clear() {
super.clear();
bitField0_ = 0;
average_ = 0D;
standardDeviation_ = 0D;
min_ = 0L;
quartiles_ = emptyLongList();
max_ = 0L;
return this;
}
@java.lang.Override
public com.google.protobuf.Descriptors.Descriptor getDescriptorForType() {
return com.google.cloud.dataplex.v1.DataProfileProto
.internal_static_google_cloud_dataplex_v1_DataProfileResult_Profile_Field_ProfileInfo_IntegerFieldInfo_descriptor;
}
@java.lang.Override
public com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.IntegerFieldInfo
getDefaultInstanceForType() {
return com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.IntegerFieldInfo.getDefaultInstance();
}
@java.lang.Override
public com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.IntegerFieldInfo
build() {
com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.IntegerFieldInfo
result = buildPartial();
if (!result.isInitialized()) {
throw newUninitializedMessageException(result);
}
return result;
}
@java.lang.Override
public com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.IntegerFieldInfo
buildPartial() {
com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.IntegerFieldInfo
result =
new com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.IntegerFieldInfo(this);
if (bitField0_ != 0) {
buildPartial0(result);
}
onBuilt();
return result;
}
private void buildPartial0(
com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.IntegerFieldInfo
result) {
int from_bitField0_ = bitField0_;
if (((from_bitField0_ & 0x00000001) != 0)) {
result.average_ = average_;
}
if (((from_bitField0_ & 0x00000002) != 0)) {
result.standardDeviation_ = standardDeviation_;
}
if (((from_bitField0_ & 0x00000004) != 0)) {
result.min_ = min_;
}
if (((from_bitField0_ & 0x00000008) != 0)) {
quartiles_.makeImmutable();
result.quartiles_ = quartiles_;
}
if (((from_bitField0_ & 0x00000010) != 0)) {
result.max_ = max_;
}
}
@java.lang.Override
public Builder clone() {
return super.clone();
}
@java.lang.Override
public Builder setField(
com.google.protobuf.Descriptors.FieldDescriptor field, java.lang.Object value) {
return super.setField(field, value);
}
@java.lang.Override
public Builder clearField(com.google.protobuf.Descriptors.FieldDescriptor field) {
return super.clearField(field);
}
@java.lang.Override
public Builder clearOneof(com.google.protobuf.Descriptors.OneofDescriptor oneof) {
return super.clearOneof(oneof);
}
@java.lang.Override
public Builder setRepeatedField(
com.google.protobuf.Descriptors.FieldDescriptor field,
int index,
java.lang.Object value) {
return super.setRepeatedField(field, index, value);
}
@java.lang.Override
public Builder addRepeatedField(
com.google.protobuf.Descriptors.FieldDescriptor field, java.lang.Object value) {
return super.addRepeatedField(field, value);
}
@java.lang.Override
public Builder mergeFrom(com.google.protobuf.Message other) {
if (other
instanceof
com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.IntegerFieldInfo) {
return mergeFrom(
(com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.IntegerFieldInfo)
other);
} else {
super.mergeFrom(other);
return this;
}
}
public Builder mergeFrom(
com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.IntegerFieldInfo
other) {
if (other
== com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.IntegerFieldInfo.getDefaultInstance()) return this;
if (other.getAverage() != 0D) {
setAverage(other.getAverage());
}
if (other.getStandardDeviation() != 0D) {
setStandardDeviation(other.getStandardDeviation());
}
if (other.getMin() != 0L) {
setMin(other.getMin());
}
if (!other.quartiles_.isEmpty()) {
if (quartiles_.isEmpty()) {
quartiles_ = other.quartiles_;
quartiles_.makeImmutable();
bitField0_ |= 0x00000008;
} else {
ensureQuartilesIsMutable();
quartiles_.addAll(other.quartiles_);
}
onChanged();
}
if (other.getMax() != 0L) {
setMax(other.getMax());
}
this.mergeUnknownFields(other.getUnknownFields());
onChanged();
return this;
}
@java.lang.Override
public final boolean isInitialized() {
return true;
}
@java.lang.Override
public Builder mergeFrom(
com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws java.io.IOException {
if (extensionRegistry == null) {
throw new java.lang.NullPointerException();
}
try {
boolean done = false;
while (!done) {
int tag = input.readTag();
switch (tag) {
case 0:
done = true;
break;
case 9:
{
average_ = input.readDouble();
bitField0_ |= 0x00000001;
break;
} // case 9
case 25:
{
standardDeviation_ = input.readDouble();
bitField0_ |= 0x00000002;
break;
} // case 25
case 32:
{
min_ = input.readInt64();
bitField0_ |= 0x00000004;
break;
} // case 32
case 40:
{
max_ = input.readInt64();
bitField0_ |= 0x00000010;
break;
} // case 40
case 48:
{
long v = input.readInt64();
ensureQuartilesIsMutable();
quartiles_.addLong(v);
break;
} // case 48
case 50:
{
int length = input.readRawVarint32();
int limit = input.pushLimit(length);
ensureQuartilesIsMutable();
while (input.getBytesUntilLimit() > 0) {
quartiles_.addLong(input.readInt64());
}
input.popLimit(limit);
break;
} // case 50
default:
{
if (!super.parseUnknownField(input, extensionRegistry, tag)) {
done = true; // was an endgroup tag
}
break;
} // default:
} // switch (tag)
} // while (!done)
} catch (com.google.protobuf.InvalidProtocolBufferException e) {
throw e.unwrapIOException();
} finally {
onChanged();
} // finally
return this;
}
private int bitField0_;
private double average_;
/**
*
*
*
* Average of non-null values in the scanned data. NaN, if the field
* has a NaN.
*
*
* double average = 1;
*
* @return The average.
*/
@java.lang.Override
public double getAverage() {
return average_;
}
/**
*
*
*
* Average of non-null values in the scanned data. NaN, if the field
* has a NaN.
*
*
* double average = 1;
*
* @param value The average to set.
* @return This builder for chaining.
*/
public Builder setAverage(double value) {
average_ = value;
bitField0_ |= 0x00000001;
onChanged();
return this;
}
/**
*
*
*
* Average of non-null values in the scanned data. NaN, if the field
* has a NaN.
*
*
* double average = 1;
*
* @return This builder for chaining.
*/
public Builder clearAverage() {
bitField0_ = (bitField0_ & ~0x00000001);
average_ = 0D;
onChanged();
return this;
}
private double standardDeviation_;
/**
*
*
*
* Standard deviation of non-null values in the scanned data. NaN, if
* the field has a NaN.
*
* Standard deviation of non-null values in the scanned data. NaN, if
* the field has a NaN.
*
*
* double standard_deviation = 3;
*
* @param value The standardDeviation to set.
* @return This builder for chaining.
*/
public Builder setStandardDeviation(double value) {
standardDeviation_ = value;
bitField0_ |= 0x00000002;
onChanged();
return this;
}
/**
*
*
*
* Standard deviation of non-null values in the scanned data. NaN, if
* the field has a NaN.
*
*
* double standard_deviation = 3;
*
* @return This builder for chaining.
*/
public Builder clearStandardDeviation() {
bitField0_ = (bitField0_ & ~0x00000002);
standardDeviation_ = 0D;
onChanged();
return this;
}
private long min_;
/**
*
*
*
* Minimum of non-null values in the scanned data. NaN, if the field
* has a NaN.
*
*
* int64 min = 4;
*
* @return The min.
*/
@java.lang.Override
public long getMin() {
return min_;
}
/**
*
*
*
* Minimum of non-null values in the scanned data. NaN, if the field
* has a NaN.
*
*
* int64 min = 4;
*
* @param value The min to set.
* @return This builder for chaining.
*/
public Builder setMin(long value) {
min_ = value;
bitField0_ |= 0x00000004;
onChanged();
return this;
}
/**
*
*
*
* Minimum of non-null values in the scanned data. NaN, if the field
* has a NaN.
*
* A quartile divides the number of data points into four parts, or
* quarters, of more-or-less equal size. Three main quartiles used
* are: The first quartile (Q1) splits off the lowest 25% of data from
* the highest 75%. It is also known as the lower or 25th empirical
* quartile, as 25% of the data is below this point. The second
* quartile (Q2) is the median of a data set. So, 50% of the data lies
* below this point. The third quartile (Q3) splits off the highest
* 25% of data from the lowest 75%. It is known as the upper or 75th
* empirical quartile, as 75% of the data lies below this point.
* Here, the quartiles is provided as an ordered list of approximate
* quartile values for the scanned data, occurring in order Q1,
* median, Q3.
*
*
* repeated int64 quartiles = 6;
*
* @return A list containing the quartiles.
*/
public java.util.List getQuartilesList() {
quartiles_.makeImmutable();
return quartiles_;
}
/**
*
*
*
* A quartile divides the number of data points into four parts, or
* quarters, of more-or-less equal size. Three main quartiles used
* are: The first quartile (Q1) splits off the lowest 25% of data from
* the highest 75%. It is also known as the lower or 25th empirical
* quartile, as 25% of the data is below this point. The second
* quartile (Q2) is the median of a data set. So, 50% of the data lies
* below this point. The third quartile (Q3) splits off the highest
* 25% of data from the lowest 75%. It is known as the upper or 75th
* empirical quartile, as 75% of the data lies below this point.
* Here, the quartiles is provided as an ordered list of approximate
* quartile values for the scanned data, occurring in order Q1,
* median, Q3.
*
*
* repeated int64 quartiles = 6;
*
* @return The count of quartiles.
*/
public int getQuartilesCount() {
return quartiles_.size();
}
/**
*
*
*
* A quartile divides the number of data points into four parts, or
* quarters, of more-or-less equal size. Three main quartiles used
* are: The first quartile (Q1) splits off the lowest 25% of data from
* the highest 75%. It is also known as the lower or 25th empirical
* quartile, as 25% of the data is below this point. The second
* quartile (Q2) is the median of a data set. So, 50% of the data lies
* below this point. The third quartile (Q3) splits off the highest
* 25% of data from the lowest 75%. It is known as the upper or 75th
* empirical quartile, as 75% of the data lies below this point.
* Here, the quartiles is provided as an ordered list of approximate
* quartile values for the scanned data, occurring in order Q1,
* median, Q3.
*
*
* repeated int64 quartiles = 6;
*
* @param index The index of the element to return.
* @return The quartiles at the given index.
*/
public long getQuartiles(int index) {
return quartiles_.getLong(index);
}
/**
*
*
*
* A quartile divides the number of data points into four parts, or
* quarters, of more-or-less equal size. Three main quartiles used
* are: The first quartile (Q1) splits off the lowest 25% of data from
* the highest 75%. It is also known as the lower or 25th empirical
* quartile, as 25% of the data is below this point. The second
* quartile (Q2) is the median of a data set. So, 50% of the data lies
* below this point. The third quartile (Q3) splits off the highest
* 25% of data from the lowest 75%. It is known as the upper or 75th
* empirical quartile, as 75% of the data lies below this point.
* Here, the quartiles is provided as an ordered list of approximate
* quartile values for the scanned data, occurring in order Q1,
* median, Q3.
*
*
* repeated int64 quartiles = 6;
*
* @param index The index to set the value at.
* @param value The quartiles to set.
* @return This builder for chaining.
*/
public Builder setQuartiles(int index, long value) {
ensureQuartilesIsMutable();
quartiles_.setLong(index, value);
bitField0_ |= 0x00000008;
onChanged();
return this;
}
/**
*
*
*
* A quartile divides the number of data points into four parts, or
* quarters, of more-or-less equal size. Three main quartiles used
* are: The first quartile (Q1) splits off the lowest 25% of data from
* the highest 75%. It is also known as the lower or 25th empirical
* quartile, as 25% of the data is below this point. The second
* quartile (Q2) is the median of a data set. So, 50% of the data lies
* below this point. The third quartile (Q3) splits off the highest
* 25% of data from the lowest 75%. It is known as the upper or 75th
* empirical quartile, as 75% of the data lies below this point.
* Here, the quartiles is provided as an ordered list of approximate
* quartile values for the scanned data, occurring in order Q1,
* median, Q3.
*
*
* repeated int64 quartiles = 6;
*
* @param value The quartiles to add.
* @return This builder for chaining.
*/
public Builder addQuartiles(long value) {
ensureQuartilesIsMutable();
quartiles_.addLong(value);
bitField0_ |= 0x00000008;
onChanged();
return this;
}
/**
*
*
*
* A quartile divides the number of data points into four parts, or
* quarters, of more-or-less equal size. Three main quartiles used
* are: The first quartile (Q1) splits off the lowest 25% of data from
* the highest 75%. It is also known as the lower or 25th empirical
* quartile, as 25% of the data is below this point. The second
* quartile (Q2) is the median of a data set. So, 50% of the data lies
* below this point. The third quartile (Q3) splits off the highest
* 25% of data from the lowest 75%. It is known as the upper or 75th
* empirical quartile, as 75% of the data lies below this point.
* Here, the quartiles is provided as an ordered list of approximate
* quartile values for the scanned data, occurring in order Q1,
* median, Q3.
*
*
* repeated int64 quartiles = 6;
*
* @param values The quartiles to add.
* @return This builder for chaining.
*/
public Builder addAllQuartiles(java.lang.Iterable values) {
ensureQuartilesIsMutable();
com.google.protobuf.AbstractMessageLite.Builder.addAll(values, quartiles_);
bitField0_ |= 0x00000008;
onChanged();
return this;
}
/**
*
*
*
* A quartile divides the number of data points into four parts, or
* quarters, of more-or-less equal size. Three main quartiles used
* are: The first quartile (Q1) splits off the lowest 25% of data from
* the highest 75%. It is also known as the lower or 25th empirical
* quartile, as 25% of the data is below this point. The second
* quartile (Q2) is the median of a data set. So, 50% of the data lies
* below this point. The third quartile (Q3) splits off the highest
* 25% of data from the lowest 75%. It is known as the upper or 75th
* empirical quartile, as 75% of the data lies below this point.
* Here, the quartiles is provided as an ordered list of approximate
* quartile values for the scanned data, occurring in order Q1,
* median, Q3.
*
*
* repeated int64 quartiles = 6;
*
* @return This builder for chaining.
*/
public Builder clearQuartiles() {
quartiles_ = emptyLongList();
bitField0_ = (bitField0_ & ~0x00000008);
onChanged();
return this;
}
private long max_;
/**
*
*
*
* Maximum of non-null values in the scanned data. NaN, if the field
* has a NaN.
*
*
* int64 max = 5;
*
* @return The max.
*/
@java.lang.Override
public long getMax() {
return max_;
}
/**
*
*
*
* Maximum of non-null values in the scanned data. NaN, if the field
* has a NaN.
*
*
* int64 max = 5;
*
* @param value The max to set.
* @return This builder for chaining.
*/
public Builder setMax(long value) {
max_ = value;
bitField0_ |= 0x00000010;
onChanged();
return this;
}
/**
*
*
*
* Maximum of non-null values in the scanned data. NaN, if the field
* has a NaN.
*
*
* int64 max = 5;
*
* @return This builder for chaining.
*/
public Builder clearMax() {
bitField0_ = (bitField0_ & ~0x00000010);
max_ = 0L;
onChanged();
return this;
}
@java.lang.Override
public final Builder setUnknownFields(
final com.google.protobuf.UnknownFieldSet unknownFields) {
return super.setUnknownFields(unknownFields);
}
@java.lang.Override
public final Builder mergeUnknownFields(
final com.google.protobuf.UnknownFieldSet unknownFields) {
return super.mergeUnknownFields(unknownFields);
}
// @@protoc_insertion_point(builder_scope:google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo)
}
// @@protoc_insertion_point(class_scope:google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.IntegerFieldInfo)
private static final com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field
.ProfileInfo.IntegerFieldInfo
DEFAULT_INSTANCE;
static {
DEFAULT_INSTANCE =
new com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.IntegerFieldInfo();
}
public static com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.IntegerFieldInfo
getDefaultInstance() {
return DEFAULT_INSTANCE;
}
private static final com.google.protobuf.Parser PARSER =
new com.google.protobuf.AbstractParser() {
@java.lang.Override
public IntegerFieldInfo parsePartialFrom(
com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws com.google.protobuf.InvalidProtocolBufferException {
Builder builder = newBuilder();
try {
builder.mergeFrom(input, extensionRegistry);
} catch (com.google.protobuf.InvalidProtocolBufferException e) {
throw e.setUnfinishedMessage(builder.buildPartial());
} catch (com.google.protobuf.UninitializedMessageException e) {
throw e.asInvalidProtocolBufferException()
.setUnfinishedMessage(builder.buildPartial());
} catch (java.io.IOException e) {
throw new com.google.protobuf.InvalidProtocolBufferException(e)
.setUnfinishedMessage(builder.buildPartial());
}
return builder.buildPartial();
}
};
public static com.google.protobuf.Parser parser() {
return PARSER;
}
@java.lang.Override
public com.google.protobuf.Parser getParserForType() {
return PARSER;
}
@java.lang.Override
public com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.IntegerFieldInfo
getDefaultInstanceForType() {
return DEFAULT_INSTANCE;
}
}
public interface DoubleFieldInfoOrBuilder
extends
// @@protoc_insertion_point(interface_extends:google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.DoubleFieldInfo)
com.google.protobuf.MessageOrBuilder {
/**
*
*
*
* Average of non-null values in the scanned data. NaN, if the field
* has a NaN.
*
*
* double average = 1;
*
* @return The average.
*/
double getAverage();
/**
*
*
*
* Standard deviation of non-null values in the scanned data. NaN, if
* the field has a NaN.
*
* Minimum of non-null values in the scanned data. NaN, if the field
* has a NaN.
*
*
* double min = 4;
*
* @return The min.
*/
double getMin();
/**
*
*
*
* A quartile divides the number of data points into four parts, or
* quarters, of more-or-less equal size. Three main quartiles used
* are: The first quartile (Q1) splits off the lowest 25% of data from
* the highest 75%. It is also known as the lower or 25th empirical
* quartile, as 25% of the data is below this point. The second
* quartile (Q2) is the median of a data set. So, 50% of the data lies
* below this point. The third quartile (Q3) splits off the highest
* 25% of data from the lowest 75%. It is known as the upper or 75th
* empirical quartile, as 75% of the data lies below this point.
* Here, the quartiles is provided as an ordered list of quartile
* values for the scanned data, occurring in order Q1, median, Q3.
*
*
* repeated double quartiles = 6;
*
* @return A list containing the quartiles.
*/
java.util.List getQuartilesList();
/**
*
*
*
* A quartile divides the number of data points into four parts, or
* quarters, of more-or-less equal size. Three main quartiles used
* are: The first quartile (Q1) splits off the lowest 25% of data from
* the highest 75%. It is also known as the lower or 25th empirical
* quartile, as 25% of the data is below this point. The second
* quartile (Q2) is the median of a data set. So, 50% of the data lies
* below this point. The third quartile (Q3) splits off the highest
* 25% of data from the lowest 75%. It is known as the upper or 75th
* empirical quartile, as 75% of the data lies below this point.
* Here, the quartiles is provided as an ordered list of quartile
* values for the scanned data, occurring in order Q1, median, Q3.
*
*
* repeated double quartiles = 6;
*
* @return The count of quartiles.
*/
int getQuartilesCount();
/**
*
*
*
* A quartile divides the number of data points into four parts, or
* quarters, of more-or-less equal size. Three main quartiles used
* are: The first quartile (Q1) splits off the lowest 25% of data from
* the highest 75%. It is also known as the lower or 25th empirical
* quartile, as 25% of the data is below this point. The second
* quartile (Q2) is the median of a data set. So, 50% of the data lies
* below this point. The third quartile (Q3) splits off the highest
* 25% of data from the lowest 75%. It is known as the upper or 75th
* empirical quartile, as 75% of the data lies below this point.
* Here, the quartiles is provided as an ordered list of quartile
* values for the scanned data, occurring in order Q1, median, Q3.
*
*
* repeated double quartiles = 6;
*
* @param index The index of the element to return.
* @return The quartiles at the given index.
*/
double getQuartiles(int index);
/**
*
*
*
* Maximum of non-null values in the scanned data. NaN, if the field
* has a NaN.
*
*
* double max = 5;
*
* @return The max.
*/
double getMax();
}
/**
*
*
*
* The profile information for a double type field.
*
*
* Protobuf type {@code
* google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.DoubleFieldInfo}
*/
public static final class DoubleFieldInfo extends com.google.protobuf.GeneratedMessageV3
implements
// @@protoc_insertion_point(message_implements:google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.DoubleFieldInfo)
DoubleFieldInfoOrBuilder {
private static final long serialVersionUID = 0L;
// Use DoubleFieldInfo.newBuilder() to construct.
private DoubleFieldInfo(com.google.protobuf.GeneratedMessageV3.Builder builder) {
super(builder);
}
private DoubleFieldInfo() {
quartiles_ = emptyDoubleList();
}
@java.lang.Override
@SuppressWarnings({"unused"})
protected java.lang.Object newInstance(UnusedPrivateParameter unused) {
return new DoubleFieldInfo();
}
public static final com.google.protobuf.Descriptors.Descriptor getDescriptor() {
return com.google.cloud.dataplex.v1.DataProfileProto
.internal_static_google_cloud_dataplex_v1_DataProfileResult_Profile_Field_ProfileInfo_DoubleFieldInfo_descriptor;
}
@java.lang.Override
protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
internalGetFieldAccessorTable() {
return com.google.cloud.dataplex.v1.DataProfileProto
.internal_static_google_cloud_dataplex_v1_DataProfileResult_Profile_Field_ProfileInfo_DoubleFieldInfo_fieldAccessorTable
.ensureFieldAccessorsInitialized(
com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.DoubleFieldInfo.class,
com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.DoubleFieldInfo.Builder.class);
}
public static final int AVERAGE_FIELD_NUMBER = 1;
private double average_ = 0D;
/**
*
*
*
* Average of non-null values in the scanned data. NaN, if the field
* has a NaN.
*
*
* double average = 1;
*
* @return The average.
*/
@java.lang.Override
public double getAverage() {
return average_;
}
public static final int STANDARD_DEVIATION_FIELD_NUMBER = 3;
private double standardDeviation_ = 0D;
/**
*
*
*
* Standard deviation of non-null values in the scanned data. NaN, if
* the field has a NaN.
*
*
* double standard_deviation = 3;
*
* @return The standardDeviation.
*/
@java.lang.Override
public double getStandardDeviation() {
return standardDeviation_;
}
public static final int MIN_FIELD_NUMBER = 4;
private double min_ = 0D;
/**
*
*
*
* Minimum of non-null values in the scanned data. NaN, if the field
* has a NaN.
*
*
* double min = 4;
*
* @return The min.
*/
@java.lang.Override
public double getMin() {
return min_;
}
public static final int QUARTILES_FIELD_NUMBER = 6;
@SuppressWarnings("serial")
private com.google.protobuf.Internal.DoubleList quartiles_ = emptyDoubleList();
/**
*
*
*
* A quartile divides the number of data points into four parts, or
* quarters, of more-or-less equal size. Three main quartiles used
* are: The first quartile (Q1) splits off the lowest 25% of data from
* the highest 75%. It is also known as the lower or 25th empirical
* quartile, as 25% of the data is below this point. The second
* quartile (Q2) is the median of a data set. So, 50% of the data lies
* below this point. The third quartile (Q3) splits off the highest
* 25% of data from the lowest 75%. It is known as the upper or 75th
* empirical quartile, as 75% of the data lies below this point.
* Here, the quartiles is provided as an ordered list of quartile
* values for the scanned data, occurring in order Q1, median, Q3.
*
*
* repeated double quartiles = 6;
*
* @return A list containing the quartiles.
*/
@java.lang.Override
public java.util.List getQuartilesList() {
return quartiles_;
}
/**
*
*
*
* A quartile divides the number of data points into four parts, or
* quarters, of more-or-less equal size. Three main quartiles used
* are: The first quartile (Q1) splits off the lowest 25% of data from
* the highest 75%. It is also known as the lower or 25th empirical
* quartile, as 25% of the data is below this point. The second
* quartile (Q2) is the median of a data set. So, 50% of the data lies
* below this point. The third quartile (Q3) splits off the highest
* 25% of data from the lowest 75%. It is known as the upper or 75th
* empirical quartile, as 75% of the data lies below this point.
* Here, the quartiles is provided as an ordered list of quartile
* values for the scanned data, occurring in order Q1, median, Q3.
*
*
* repeated double quartiles = 6;
*
* @return The count of quartiles.
*/
public int getQuartilesCount() {
return quartiles_.size();
}
/**
*
*
*
* A quartile divides the number of data points into four parts, or
* quarters, of more-or-less equal size. Three main quartiles used
* are: The first quartile (Q1) splits off the lowest 25% of data from
* the highest 75%. It is also known as the lower or 25th empirical
* quartile, as 25% of the data is below this point. The second
* quartile (Q2) is the median of a data set. So, 50% of the data lies
* below this point. The third quartile (Q3) splits off the highest
* 25% of data from the lowest 75%. It is known as the upper or 75th
* empirical quartile, as 75% of the data lies below this point.
* Here, the quartiles is provided as an ordered list of quartile
* values for the scanned data, occurring in order Q1, median, Q3.
*
*
* repeated double quartiles = 6;
*
* @param index The index of the element to return.
* @return The quartiles at the given index.
*/
public double getQuartiles(int index) {
return quartiles_.getDouble(index);
}
private int quartilesMemoizedSerializedSize = -1;
public static final int MAX_FIELD_NUMBER = 5;
private double max_ = 0D;
/**
*
*
*
* Maximum of non-null values in the scanned data. NaN, if the field
* has a NaN.
*
* The profile information for a double type field.
*
*
* Protobuf type {@code
* google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.DoubleFieldInfo}
*/
public static final class Builder
extends com.google.protobuf.GeneratedMessageV3.Builder
implements
// @@protoc_insertion_point(builder_implements:google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.DoubleFieldInfo)
com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.DoubleFieldInfoOrBuilder {
public static final com.google.protobuf.Descriptors.Descriptor getDescriptor() {
return com.google.cloud.dataplex.v1.DataProfileProto
.internal_static_google_cloud_dataplex_v1_DataProfileResult_Profile_Field_ProfileInfo_DoubleFieldInfo_descriptor;
}
@java.lang.Override
protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
internalGetFieldAccessorTable() {
return com.google.cloud.dataplex.v1.DataProfileProto
.internal_static_google_cloud_dataplex_v1_DataProfileResult_Profile_Field_ProfileInfo_DoubleFieldInfo_fieldAccessorTable
.ensureFieldAccessorsInitialized(
com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.DoubleFieldInfo.class,
com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.DoubleFieldInfo.Builder.class);
}
// Construct using
// com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.DoubleFieldInfo.newBuilder()
private Builder() {}
private Builder(com.google.protobuf.GeneratedMessageV3.BuilderParent parent) {
super(parent);
}
@java.lang.Override
public Builder clear() {
super.clear();
bitField0_ = 0;
average_ = 0D;
standardDeviation_ = 0D;
min_ = 0D;
quartiles_ = emptyDoubleList();
max_ = 0D;
return this;
}
@java.lang.Override
public com.google.protobuf.Descriptors.Descriptor getDescriptorForType() {
return com.google.cloud.dataplex.v1.DataProfileProto
.internal_static_google_cloud_dataplex_v1_DataProfileResult_Profile_Field_ProfileInfo_DoubleFieldInfo_descriptor;
}
@java.lang.Override
public com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.DoubleFieldInfo
getDefaultInstanceForType() {
return com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.DoubleFieldInfo.getDefaultInstance();
}
@java.lang.Override
public com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.DoubleFieldInfo
build() {
com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.DoubleFieldInfo
result = buildPartial();
if (!result.isInitialized()) {
throw newUninitializedMessageException(result);
}
return result;
}
@java.lang.Override
public com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.DoubleFieldInfo
buildPartial() {
com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.DoubleFieldInfo
result =
new com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.DoubleFieldInfo(this);
if (bitField0_ != 0) {
buildPartial0(result);
}
onBuilt();
return result;
}
private void buildPartial0(
com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.DoubleFieldInfo
result) {
int from_bitField0_ = bitField0_;
if (((from_bitField0_ & 0x00000001) != 0)) {
result.average_ = average_;
}
if (((from_bitField0_ & 0x00000002) != 0)) {
result.standardDeviation_ = standardDeviation_;
}
if (((from_bitField0_ & 0x00000004) != 0)) {
result.min_ = min_;
}
if (((from_bitField0_ & 0x00000008) != 0)) {
quartiles_.makeImmutable();
result.quartiles_ = quartiles_;
}
if (((from_bitField0_ & 0x00000010) != 0)) {
result.max_ = max_;
}
}
@java.lang.Override
public Builder clone() {
return super.clone();
}
@java.lang.Override
public Builder setField(
com.google.protobuf.Descriptors.FieldDescriptor field, java.lang.Object value) {
return super.setField(field, value);
}
@java.lang.Override
public Builder clearField(com.google.protobuf.Descriptors.FieldDescriptor field) {
return super.clearField(field);
}
@java.lang.Override
public Builder clearOneof(com.google.protobuf.Descriptors.OneofDescriptor oneof) {
return super.clearOneof(oneof);
}
@java.lang.Override
public Builder setRepeatedField(
com.google.protobuf.Descriptors.FieldDescriptor field,
int index,
java.lang.Object value) {
return super.setRepeatedField(field, index, value);
}
@java.lang.Override
public Builder addRepeatedField(
com.google.protobuf.Descriptors.FieldDescriptor field, java.lang.Object value) {
return super.addRepeatedField(field, value);
}
@java.lang.Override
public Builder mergeFrom(com.google.protobuf.Message other) {
if (other
instanceof
com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.DoubleFieldInfo) {
return mergeFrom(
(com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.DoubleFieldInfo)
other);
} else {
super.mergeFrom(other);
return this;
}
}
public Builder mergeFrom(
com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.DoubleFieldInfo
other) {
if (other
== com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.DoubleFieldInfo.getDefaultInstance()) return this;
if (other.getAverage() != 0D) {
setAverage(other.getAverage());
}
if (other.getStandardDeviation() != 0D) {
setStandardDeviation(other.getStandardDeviation());
}
if (other.getMin() != 0D) {
setMin(other.getMin());
}
if (!other.quartiles_.isEmpty()) {
if (quartiles_.isEmpty()) {
quartiles_ = other.quartiles_;
quartiles_.makeImmutable();
bitField0_ |= 0x00000008;
} else {
ensureQuartilesIsMutable();
quartiles_.addAll(other.quartiles_);
}
onChanged();
}
if (other.getMax() != 0D) {
setMax(other.getMax());
}
this.mergeUnknownFields(other.getUnknownFields());
onChanged();
return this;
}
@java.lang.Override
public final boolean isInitialized() {
return true;
}
@java.lang.Override
public Builder mergeFrom(
com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws java.io.IOException {
if (extensionRegistry == null) {
throw new java.lang.NullPointerException();
}
try {
boolean done = false;
while (!done) {
int tag = input.readTag();
switch (tag) {
case 0:
done = true;
break;
case 9:
{
average_ = input.readDouble();
bitField0_ |= 0x00000001;
break;
} // case 9
case 25:
{
standardDeviation_ = input.readDouble();
bitField0_ |= 0x00000002;
break;
} // case 25
case 33:
{
min_ = input.readDouble();
bitField0_ |= 0x00000004;
break;
} // case 33
case 41:
{
max_ = input.readDouble();
bitField0_ |= 0x00000010;
break;
} // case 41
case 49:
{
double v = input.readDouble();
ensureQuartilesIsMutable();
quartiles_.addDouble(v);
break;
} // case 49
case 50:
{
int length = input.readRawVarint32();
int limit = input.pushLimit(length);
int alloc = length > 4096 ? 4096 : length;
ensureQuartilesIsMutable(alloc / 8);
while (input.getBytesUntilLimit() > 0) {
quartiles_.addDouble(input.readDouble());
}
input.popLimit(limit);
break;
} // case 50
default:
{
if (!super.parseUnknownField(input, extensionRegistry, tag)) {
done = true; // was an endgroup tag
}
break;
} // default:
} // switch (tag)
} // while (!done)
} catch (com.google.protobuf.InvalidProtocolBufferException e) {
throw e.unwrapIOException();
} finally {
onChanged();
} // finally
return this;
}
private int bitField0_;
private double average_;
/**
*
*
*
* Average of non-null values in the scanned data. NaN, if the field
* has a NaN.
*
*
* double average = 1;
*
* @return The average.
*/
@java.lang.Override
public double getAverage() {
return average_;
}
/**
*
*
*
* Average of non-null values in the scanned data. NaN, if the field
* has a NaN.
*
*
* double average = 1;
*
* @param value The average to set.
* @return This builder for chaining.
*/
public Builder setAverage(double value) {
average_ = value;
bitField0_ |= 0x00000001;
onChanged();
return this;
}
/**
*
*
*
* Average of non-null values in the scanned data. NaN, if the field
* has a NaN.
*
*
* double average = 1;
*
* @return This builder for chaining.
*/
public Builder clearAverage() {
bitField0_ = (bitField0_ & ~0x00000001);
average_ = 0D;
onChanged();
return this;
}
private double standardDeviation_;
/**
*
*
*
* Standard deviation of non-null values in the scanned data. NaN, if
* the field has a NaN.
*
* Minimum of non-null values in the scanned data. NaN, if the field
* has a NaN.
*
*
* double min = 4;
*
* @return The min.
*/
@java.lang.Override
public double getMin() {
return min_;
}
/**
*
*
*
* Minimum of non-null values in the scanned data. NaN, if the field
* has a NaN.
*
*
* double min = 4;
*
* @param value The min to set.
* @return This builder for chaining.
*/
public Builder setMin(double value) {
min_ = value;
bitField0_ |= 0x00000004;
onChanged();
return this;
}
/**
*
*
*
* Minimum of non-null values in the scanned data. NaN, if the field
* has a NaN.
*
* A quartile divides the number of data points into four parts, or
* quarters, of more-or-less equal size. Three main quartiles used
* are: The first quartile (Q1) splits off the lowest 25% of data from
* the highest 75%. It is also known as the lower or 25th empirical
* quartile, as 25% of the data is below this point. The second
* quartile (Q2) is the median of a data set. So, 50% of the data lies
* below this point. The third quartile (Q3) splits off the highest
* 25% of data from the lowest 75%. It is known as the upper or 75th
* empirical quartile, as 75% of the data lies below this point.
* Here, the quartiles is provided as an ordered list of quartile
* values for the scanned data, occurring in order Q1, median, Q3.
*
*
* repeated double quartiles = 6;
*
* @return A list containing the quartiles.
*/
public java.util.List getQuartilesList() {
quartiles_.makeImmutable();
return quartiles_;
}
/**
*
*
*
* A quartile divides the number of data points into four parts, or
* quarters, of more-or-less equal size. Three main quartiles used
* are: The first quartile (Q1) splits off the lowest 25% of data from
* the highest 75%. It is also known as the lower or 25th empirical
* quartile, as 25% of the data is below this point. The second
* quartile (Q2) is the median of a data set. So, 50% of the data lies
* below this point. The third quartile (Q3) splits off the highest
* 25% of data from the lowest 75%. It is known as the upper or 75th
* empirical quartile, as 75% of the data lies below this point.
* Here, the quartiles is provided as an ordered list of quartile
* values for the scanned data, occurring in order Q1, median, Q3.
*
*
* repeated double quartiles = 6;
*
* @return The count of quartiles.
*/
public int getQuartilesCount() {
return quartiles_.size();
}
/**
*
*
*
* A quartile divides the number of data points into four parts, or
* quarters, of more-or-less equal size. Three main quartiles used
* are: The first quartile (Q1) splits off the lowest 25% of data from
* the highest 75%. It is also known as the lower or 25th empirical
* quartile, as 25% of the data is below this point. The second
* quartile (Q2) is the median of a data set. So, 50% of the data lies
* below this point. The third quartile (Q3) splits off the highest
* 25% of data from the lowest 75%. It is known as the upper or 75th
* empirical quartile, as 75% of the data lies below this point.
* Here, the quartiles is provided as an ordered list of quartile
* values for the scanned data, occurring in order Q1, median, Q3.
*
*
* repeated double quartiles = 6;
*
* @param index The index of the element to return.
* @return The quartiles at the given index.
*/
public double getQuartiles(int index) {
return quartiles_.getDouble(index);
}
/**
*
*
*
* A quartile divides the number of data points into four parts, or
* quarters, of more-or-less equal size. Three main quartiles used
* are: The first quartile (Q1) splits off the lowest 25% of data from
* the highest 75%. It is also known as the lower or 25th empirical
* quartile, as 25% of the data is below this point. The second
* quartile (Q2) is the median of a data set. So, 50% of the data lies
* below this point. The third quartile (Q3) splits off the highest
* 25% of data from the lowest 75%. It is known as the upper or 75th
* empirical quartile, as 75% of the data lies below this point.
* Here, the quartiles is provided as an ordered list of quartile
* values for the scanned data, occurring in order Q1, median, Q3.
*
*
* repeated double quartiles = 6;
*
* @param index The index to set the value at.
* @param value The quartiles to set.
* @return This builder for chaining.
*/
public Builder setQuartiles(int index, double value) {
ensureQuartilesIsMutable();
quartiles_.setDouble(index, value);
bitField0_ |= 0x00000008;
onChanged();
return this;
}
/**
*
*
*
* A quartile divides the number of data points into four parts, or
* quarters, of more-or-less equal size. Three main quartiles used
* are: The first quartile (Q1) splits off the lowest 25% of data from
* the highest 75%. It is also known as the lower or 25th empirical
* quartile, as 25% of the data is below this point. The second
* quartile (Q2) is the median of a data set. So, 50% of the data lies
* below this point. The third quartile (Q3) splits off the highest
* 25% of data from the lowest 75%. It is known as the upper or 75th
* empirical quartile, as 75% of the data lies below this point.
* Here, the quartiles is provided as an ordered list of quartile
* values for the scanned data, occurring in order Q1, median, Q3.
*
*
* repeated double quartiles = 6;
*
* @param value The quartiles to add.
* @return This builder for chaining.
*/
public Builder addQuartiles(double value) {
ensureQuartilesIsMutable();
quartiles_.addDouble(value);
bitField0_ |= 0x00000008;
onChanged();
return this;
}
/**
*
*
*
* A quartile divides the number of data points into four parts, or
* quarters, of more-or-less equal size. Three main quartiles used
* are: The first quartile (Q1) splits off the lowest 25% of data from
* the highest 75%. It is also known as the lower or 25th empirical
* quartile, as 25% of the data is below this point. The second
* quartile (Q2) is the median of a data set. So, 50% of the data lies
* below this point. The third quartile (Q3) splits off the highest
* 25% of data from the lowest 75%. It is known as the upper or 75th
* empirical quartile, as 75% of the data lies below this point.
* Here, the quartiles is provided as an ordered list of quartile
* values for the scanned data, occurring in order Q1, median, Q3.
*
*
* repeated double quartiles = 6;
*
* @param values The quartiles to add.
* @return This builder for chaining.
*/
public Builder addAllQuartiles(java.lang.Iterable values) {
ensureQuartilesIsMutable();
com.google.protobuf.AbstractMessageLite.Builder.addAll(values, quartiles_);
bitField0_ |= 0x00000008;
onChanged();
return this;
}
/**
*
*
*
* A quartile divides the number of data points into four parts, or
* quarters, of more-or-less equal size. Three main quartiles used
* are: The first quartile (Q1) splits off the lowest 25% of data from
* the highest 75%. It is also known as the lower or 25th empirical
* quartile, as 25% of the data is below this point. The second
* quartile (Q2) is the median of a data set. So, 50% of the data lies
* below this point. The third quartile (Q3) splits off the highest
* 25% of data from the lowest 75%. It is known as the upper or 75th
* empirical quartile, as 75% of the data lies below this point.
* Here, the quartiles is provided as an ordered list of quartile
* values for the scanned data, occurring in order Q1, median, Q3.
*
* Maximum of non-null values in the scanned data. NaN, if the field
* has a NaN.
*
*
* double max = 5;
*
* @return The max.
*/
@java.lang.Override
public double getMax() {
return max_;
}
/**
*
*
*
* Maximum of non-null values in the scanned data. NaN, if the field
* has a NaN.
*
*
* double max = 5;
*
* @param value The max to set.
* @return This builder for chaining.
*/
public Builder setMax(double value) {
max_ = value;
bitField0_ |= 0x00000010;
onChanged();
return this;
}
/**
*
*
*
* Maximum of non-null values in the scanned data. NaN, if the field
* has a NaN.
*
*
* double max = 5;
*
* @return This builder for chaining.
*/
public Builder clearMax() {
bitField0_ = (bitField0_ & ~0x00000010);
max_ = 0D;
onChanged();
return this;
}
@java.lang.Override
public final Builder setUnknownFields(
final com.google.protobuf.UnknownFieldSet unknownFields) {
return super.setUnknownFields(unknownFields);
}
@java.lang.Override
public final Builder mergeUnknownFields(
final com.google.protobuf.UnknownFieldSet unknownFields) {
return super.mergeUnknownFields(unknownFields);
}
// @@protoc_insertion_point(builder_scope:google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.DoubleFieldInfo)
}
// @@protoc_insertion_point(class_scope:google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.DoubleFieldInfo)
private static final com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field
.ProfileInfo.DoubleFieldInfo
DEFAULT_INSTANCE;
static {
DEFAULT_INSTANCE =
new com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.DoubleFieldInfo();
}
public static com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.DoubleFieldInfo
getDefaultInstance() {
return DEFAULT_INSTANCE;
}
private static final com.google.protobuf.Parser PARSER =
new com.google.protobuf.AbstractParser() {
@java.lang.Override
public DoubleFieldInfo parsePartialFrom(
com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws com.google.protobuf.InvalidProtocolBufferException {
Builder builder = newBuilder();
try {
builder.mergeFrom(input, extensionRegistry);
} catch (com.google.protobuf.InvalidProtocolBufferException e) {
throw e.setUnfinishedMessage(builder.buildPartial());
} catch (com.google.protobuf.UninitializedMessageException e) {
throw e.asInvalidProtocolBufferException()
.setUnfinishedMessage(builder.buildPartial());
} catch (java.io.IOException e) {
throw new com.google.protobuf.InvalidProtocolBufferException(e)
.setUnfinishedMessage(builder.buildPartial());
}
return builder.buildPartial();
}
};
public static com.google.protobuf.Parser parser() {
return PARSER;
}
@java.lang.Override
public com.google.protobuf.Parser getParserForType() {
return PARSER;
}
@java.lang.Override
public com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.DoubleFieldInfo
getDefaultInstanceForType() {
return DEFAULT_INSTANCE;
}
}
public interface TopNValueOrBuilder
extends
// @@protoc_insertion_point(interface_extends:google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.TopNValue)
com.google.protobuf.MessageOrBuilder {
/**
*
*
*
* String value of a top N non-null value.
*
*
* string value = 1;
*
* @return The value.
*/
java.lang.String getValue();
/**
*
*
*
* String value of a top N non-null value.
*
*
* string value = 1;
*
* @return The bytes for value.
*/
com.google.protobuf.ByteString getValueBytes();
/**
*
*
*
* Count of the corresponding value in the scanned data.
*
*
* int64 count = 2;
*
* @return The count.
*/
long getCount();
/**
*
*
*
* Ratio of the corresponding value in the field against the total
* number of rows in the scanned data.
*
*
* double ratio = 3;
*
* @return The ratio.
*/
double getRatio();
}
/**
*
*
*
* Top N non-null values in the scanned data.
*
*
* Protobuf type {@code
* google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.TopNValue}
*/
public static final class TopNValue extends com.google.protobuf.GeneratedMessageV3
implements
// @@protoc_insertion_point(message_implements:google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.TopNValue)
TopNValueOrBuilder {
private static final long serialVersionUID = 0L;
// Use TopNValue.newBuilder() to construct.
private TopNValue(com.google.protobuf.GeneratedMessageV3.Builder builder) {
super(builder);
}
private TopNValue() {
value_ = "";
}
@java.lang.Override
@SuppressWarnings({"unused"})
protected java.lang.Object newInstance(UnusedPrivateParameter unused) {
return new TopNValue();
}
public static final com.google.protobuf.Descriptors.Descriptor getDescriptor() {
return com.google.cloud.dataplex.v1.DataProfileProto
.internal_static_google_cloud_dataplex_v1_DataProfileResult_Profile_Field_ProfileInfo_TopNValue_descriptor;
}
@java.lang.Override
protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
internalGetFieldAccessorTable() {
return com.google.cloud.dataplex.v1.DataProfileProto
.internal_static_google_cloud_dataplex_v1_DataProfileResult_Profile_Field_ProfileInfo_TopNValue_fieldAccessorTable
.ensureFieldAccessorsInitialized(
com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.TopNValue.class,
com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.TopNValue.Builder.class);
}
public static final int VALUE_FIELD_NUMBER = 1;
@SuppressWarnings("serial")
private volatile java.lang.Object value_ = "";
/**
*
*
*
*
* string value = 1;
*
* @return The bytes for value.
*/
public com.google.protobuf.ByteString getValueBytes() {
java.lang.Object ref = value_;
if (ref instanceof String) {
com.google.protobuf.ByteString b =
com.google.protobuf.ByteString.copyFromUtf8((java.lang.String) ref);
value_ = b;
return b;
} else {
return (com.google.protobuf.ByteString) ref;
}
}
/**
*
*
*
* String value of a top N non-null value.
*
*
* string value = 1;
*
* @param value The value to set.
* @return This builder for chaining.
*/
public Builder setValue(java.lang.String value) {
if (value == null) {
throw new NullPointerException();
}
value_ = value;
bitField0_ |= 0x00000001;
onChanged();
return this;
}
/**
*
*
*
* String value of a top N non-null value.
*
*
* string value = 1;
*
* @return This builder for chaining.
*/
public Builder clearValue() {
value_ = getDefaultInstance().getValue();
bitField0_ = (bitField0_ & ~0x00000001);
onChanged();
return this;
}
/**
*
*
*
* String value of a top N non-null value.
*
*
* string value = 1;
*
* @param value The bytes for value to set.
* @return This builder for chaining.
*/
public Builder setValueBytes(com.google.protobuf.ByteString value) {
if (value == null) {
throw new NullPointerException();
}
checkByteStringIsUtf8(value);
value_ = value;
bitField0_ |= 0x00000001;
onChanged();
return this;
}
private long count_;
/**
*
*
*
* Count of the corresponding value in the scanned data.
*
*
* int64 count = 2;
*
* @return The count.
*/
@java.lang.Override
public long getCount() {
return count_;
}
/**
*
*
*
* Count of the corresponding value in the scanned data.
*
*
* int64 count = 2;
*
* @param value The count to set.
* @return This builder for chaining.
*/
public Builder setCount(long value) {
count_ = value;
bitField0_ |= 0x00000002;
onChanged();
return this;
}
/**
*
*
*
* Count of the corresponding value in the scanned data.
*
* Ratio of the corresponding value in the field against the total
* number of rows in the scanned data.
*
*
* double ratio = 3;
*
* @return The ratio.
*/
@java.lang.Override
public double getRatio() {
return ratio_;
}
/**
*
*
*
* Ratio of the corresponding value in the field against the total
* number of rows in the scanned data.
*
*
* double ratio = 3;
*
* @param value The ratio to set.
* @return This builder for chaining.
*/
public Builder setRatio(double value) {
ratio_ = value;
bitField0_ |= 0x00000004;
onChanged();
return this;
}
/**
*
*
*
* Ratio of the corresponding value in the field against the total
* number of rows in the scanned data.
*
*
* double ratio = 3;
*
* @return This builder for chaining.
*/
public Builder clearRatio() {
bitField0_ = (bitField0_ & ~0x00000004);
ratio_ = 0D;
onChanged();
return this;
}
@java.lang.Override
public final Builder setUnknownFields(
final com.google.protobuf.UnknownFieldSet unknownFields) {
return super.setUnknownFields(unknownFields);
}
@java.lang.Override
public final Builder mergeUnknownFields(
final com.google.protobuf.UnknownFieldSet unknownFields) {
return super.mergeUnknownFields(unknownFields);
}
// @@protoc_insertion_point(builder_scope:google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.TopNValue)
}
// @@protoc_insertion_point(class_scope:google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.TopNValue)
private static final com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field
.ProfileInfo.TopNValue
DEFAULT_INSTANCE;
static {
DEFAULT_INSTANCE =
new com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.TopNValue();
}
public static com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.TopNValue
getDefaultInstance() {
return DEFAULT_INSTANCE;
}
private static final com.google.protobuf.Parser PARSER =
new com.google.protobuf.AbstractParser() {
@java.lang.Override
public TopNValue parsePartialFrom(
com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws com.google.protobuf.InvalidProtocolBufferException {
Builder builder = newBuilder();
try {
builder.mergeFrom(input, extensionRegistry);
} catch (com.google.protobuf.InvalidProtocolBufferException e) {
throw e.setUnfinishedMessage(builder.buildPartial());
} catch (com.google.protobuf.UninitializedMessageException e) {
throw e.asInvalidProtocolBufferException()
.setUnfinishedMessage(builder.buildPartial());
} catch (java.io.IOException e) {
throw new com.google.protobuf.InvalidProtocolBufferException(e)
.setUnfinishedMessage(builder.buildPartial());
}
return builder.buildPartial();
}
};
public static com.google.protobuf.Parser parser() {
return PARSER;
}
@java.lang.Override
public com.google.protobuf.Parser getParserForType() {
return PARSER;
}
@java.lang.Override
public com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.TopNValue
getDefaultInstanceForType() {
return DEFAULT_INSTANCE;
}
}
private int fieldInfoCase_ = 0;
@SuppressWarnings("serial")
private java.lang.Object fieldInfo_;
public enum FieldInfoCase
implements
com.google.protobuf.Internal.EnumLite,
com.google.protobuf.AbstractMessage.InternalOneOfEnum {
STRING_PROFILE(101),
INTEGER_PROFILE(102),
DOUBLE_PROFILE(103),
FIELDINFO_NOT_SET(0);
private final int value;
private FieldInfoCase(int value) {
this.value = value;
}
/**
* @param value The number of the enum to look for.
* @return The enum associated with the given number.
* @deprecated Use {@link #forNumber(int)} instead.
*/
@java.lang.Deprecated
public static FieldInfoCase valueOf(int value) {
return forNumber(value);
}
public static FieldInfoCase forNumber(int value) {
switch (value) {
case 101:
return STRING_PROFILE;
case 102:
return INTEGER_PROFILE;
case 103:
return DOUBLE_PROFILE;
case 0:
return FIELDINFO_NOT_SET;
default:
return null;
}
}
public int getNumber() {
return this.value;
}
};
public FieldInfoCase getFieldInfoCase() {
return FieldInfoCase.forNumber(fieldInfoCase_);
}
public static final int NULL_RATIO_FIELD_NUMBER = 2;
private double nullRatio_ = 0D;
/**
*
*
*
* Ratio of rows with null value against total scanned rows.
*
*
* double null_ratio = 2;
*
* @return The nullRatio.
*/
@java.lang.Override
public double getNullRatio() {
return nullRatio_;
}
public static final int DISTINCT_RATIO_FIELD_NUMBER = 3;
private double distinctRatio_ = 0D;
/**
*
*
*
* Ratio of rows with distinct values against total scanned rows.
* Not available for complex non-groupable field type RECORD and fields
* with REPEATABLE mode.
*
*
* double distinct_ratio = 3;
*
* @return The distinctRatio.
*/
@java.lang.Override
public double getDistinctRatio() {
return distinctRatio_;
}
public static final int TOP_N_VALUES_FIELD_NUMBER = 4;
@SuppressWarnings("serial")
private java.util.List<
com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.TopNValue>
topNValues_;
/**
*
*
*
* The list of top N non-null values, frequency and ratio with which
* they occur in the scanned data. N is 10 or equal to the number of
* distinct values in the field, whichever is smaller. Not available for
* complex non-groupable field type RECORD and fields with REPEATABLE
* mode.
*
* The list of top N non-null values, frequency and ratio with which
* they occur in the scanned data. N is 10 or equal to the number of
* distinct values in the field, whichever is smaller. Not available for
* complex non-groupable field type RECORD and fields with REPEATABLE
* mode.
*
* The list of top N non-null values, frequency and ratio with which
* they occur in the scanned data. N is 10 or equal to the number of
* distinct values in the field, whichever is smaller. Not available for
* complex non-groupable field type RECORD and fields with REPEATABLE
* mode.
*
* The list of top N non-null values, frequency and ratio with which
* they occur in the scanned data. N is 10 or equal to the number of
* distinct values in the field, whichever is smaller. Not available for
* complex non-groupable field type RECORD and fields with REPEATABLE
* mode.
*
* The list of top N non-null values, frequency and ratio with which
* they occur in the scanned data. N is 10 or equal to the number of
* distinct values in the field, whichever is smaller. Not available for
* complex non-groupable field type RECORD and fields with REPEATABLE
* mode.
*
*
*
* repeated .google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.TopNValue top_n_values = 4;
*
*/
@java.lang.Override
public com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo
.TopNValueOrBuilder
getTopNValuesOrBuilder(int index) {
return topNValues_.get(index);
}
public static final int STRING_PROFILE_FIELD_NUMBER = 101;
/**
*
*
*
* String type field information.
*
*
*
* .google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.StringFieldInfo string_profile = 101;
*
*
* @return Whether the stringProfile field is set.
*/
@java.lang.Override
public boolean hasStringProfile() {
return fieldInfoCase_ == 101;
}
/**
*
*
*
* Ratio of rows with distinct values against total scanned rows.
* Not available for complex non-groupable field type RECORD and fields
* with REPEATABLE mode.
*
* Ratio of rows with distinct values against total scanned rows.
* Not available for complex non-groupable field type RECORD and fields
* with REPEATABLE mode.
*
*
* double distinct_ratio = 3;
*
* @param value The distinctRatio to set.
* @return This builder for chaining.
*/
public Builder setDistinctRatio(double value) {
distinctRatio_ = value;
bitField0_ |= 0x00000002;
onChanged();
return this;
}
/**
*
*
*
* Ratio of rows with distinct values against total scanned rows.
* Not available for complex non-groupable field type RECORD and fields
* with REPEATABLE mode.
*
* The list of top N non-null values, frequency and ratio with which
* they occur in the scanned data. N is 10 or equal to the number of
* distinct values in the field, whichever is smaller. Not available for
* complex non-groupable field type RECORD and fields with REPEATABLE
* mode.
*
* The list of top N non-null values, frequency and ratio with which
* they occur in the scanned data. N is 10 or equal to the number of
* distinct values in the field, whichever is smaller. Not available for
* complex non-groupable field type RECORD and fields with REPEATABLE
* mode.
*
* The list of top N non-null values, frequency and ratio with which
* they occur in the scanned data. N is 10 or equal to the number of
* distinct values in the field, whichever is smaller. Not available for
* complex non-groupable field type RECORD and fields with REPEATABLE
* mode.
*
* The list of top N non-null values, frequency and ratio with which
* they occur in the scanned data. N is 10 or equal to the number of
* distinct values in the field, whichever is smaller. Not available for
* complex non-groupable field type RECORD and fields with REPEATABLE
* mode.
*
*
*
* repeated .google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.TopNValue top_n_values = 4;
*
*/
public Builder setTopNValues(
int index,
com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.TopNValue
value) {
if (topNValuesBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensureTopNValuesIsMutable();
topNValues_.set(index, value);
onChanged();
} else {
topNValuesBuilder_.setMessage(index, value);
}
return this;
}
/**
*
*
*
* The list of top N non-null values, frequency and ratio with which
* they occur in the scanned data. N is 10 or equal to the number of
* distinct values in the field, whichever is smaller. Not available for
* complex non-groupable field type RECORD and fields with REPEATABLE
* mode.
*
* The list of top N non-null values, frequency and ratio with which
* they occur in the scanned data. N is 10 or equal to the number of
* distinct values in the field, whichever is smaller. Not available for
* complex non-groupable field type RECORD and fields with REPEATABLE
* mode.
*
* The list of top N non-null values, frequency and ratio with which
* they occur in the scanned data. N is 10 or equal to the number of
* distinct values in the field, whichever is smaller. Not available for
* complex non-groupable field type RECORD and fields with REPEATABLE
* mode.
*
*
*
* repeated .google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.TopNValue top_n_values = 4;
*
*/
public Builder addTopNValues(
int index,
com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.TopNValue
value) {
if (topNValuesBuilder_ == null) {
if (value == null) {
throw new NullPointerException();
}
ensureTopNValuesIsMutable();
topNValues_.add(index, value);
onChanged();
} else {
topNValuesBuilder_.addMessage(index, value);
}
return this;
}
/**
*
*
*
* The list of top N non-null values, frequency and ratio with which
* they occur in the scanned data. N is 10 or equal to the number of
* distinct values in the field, whichever is smaller. Not available for
* complex non-groupable field type RECORD and fields with REPEATABLE
* mode.
*
* The list of top N non-null values, frequency and ratio with which
* they occur in the scanned data. N is 10 or equal to the number of
* distinct values in the field, whichever is smaller. Not available for
* complex non-groupable field type RECORD and fields with REPEATABLE
* mode.
*
* The list of top N non-null values, frequency and ratio with which
* they occur in the scanned data. N is 10 or equal to the number of
* distinct values in the field, whichever is smaller. Not available for
* complex non-groupable field type RECORD and fields with REPEATABLE
* mode.
*
* The list of top N non-null values, frequency and ratio with which
* they occur in the scanned data. N is 10 or equal to the number of
* distinct values in the field, whichever is smaller. Not available for
* complex non-groupable field type RECORD and fields with REPEATABLE
* mode.
*
* The list of top N non-null values, frequency and ratio with which
* they occur in the scanned data. N is 10 or equal to the number of
* distinct values in the field, whichever is smaller. Not available for
* complex non-groupable field type RECORD and fields with REPEATABLE
* mode.
*
* The list of top N non-null values, frequency and ratio with which
* they occur in the scanned data. N is 10 or equal to the number of
* distinct values in the field, whichever is smaller. Not available for
* complex non-groupable field type RECORD and fields with REPEATABLE
* mode.
*
* The list of top N non-null values, frequency and ratio with which
* they occur in the scanned data. N is 10 or equal to the number of
* distinct values in the field, whichever is smaller. Not available for
* complex non-groupable field type RECORD and fields with REPEATABLE
* mode.
*
* The list of top N non-null values, frequency and ratio with which
* they occur in the scanned data. N is 10 or equal to the number of
* distinct values in the field, whichever is smaller. Not available for
* complex non-groupable field type RECORD and fields with REPEATABLE
* mode.
*
* The list of top N non-null values, frequency and ratio with which
* they occur in the scanned data. N is 10 or equal to the number of
* distinct values in the field, whichever is smaller. Not available for
* complex non-groupable field type RECORD and fields with REPEATABLE
* mode.
*
* The list of top N non-null values, frequency and ratio with which
* they occur in the scanned data. N is 10 or equal to the number of
* distinct values in the field, whichever is smaller. Not available for
* complex non-groupable field type RECORD and fields with REPEATABLE
* mode.
*
* The list of top N non-null values, frequency and ratio with which
* they occur in the scanned data. N is 10 or equal to the number of
* distinct values in the field, whichever is smaller. Not available for
* complex non-groupable field type RECORD and fields with REPEATABLE
* mode.
*
*
* string name = 1;
*
* @return The bytes for name.
*/
@java.lang.Override
public com.google.protobuf.ByteString getNameBytes() {
java.lang.Object ref = name_;
if (ref instanceof java.lang.String) {
com.google.protobuf.ByteString b =
com.google.protobuf.ByteString.copyFromUtf8((java.lang.String) ref);
name_ = b;
return b;
} else {
return (com.google.protobuf.ByteString) ref;
}
}
public static final int TYPE_FIELD_NUMBER = 2;
@SuppressWarnings("serial")
private volatile java.lang.Object type_ = "";
/**
*
*
*
* The data type retrieved from the schema of the data source. For
* instance, for a BigQuery native table, it is the [BigQuery Table
* Schema](https://cloud.google.com/bigquery/docs/reference/rest/v2/tables#tablefieldschema).
* For a Dataplex Entity, it is the [Entity
* Schema](https://cloud.google.com/dataplex/docs/reference/rpc/google.cloud.dataplex.v1#type_3).
*
* The data type retrieved from the schema of the data source. For
* instance, for a BigQuery native table, it is the [BigQuery Table
* Schema](https://cloud.google.com/bigquery/docs/reference/rest/v2/tables#tablefieldschema).
* For a Dataplex Entity, it is the [Entity
* Schema](https://cloud.google.com/dataplex/docs/reference/rpc/google.cloud.dataplex.v1#type_3).
*
*
* string type = 2;
*
* @return The bytes for type.
*/
@java.lang.Override
public com.google.protobuf.ByteString getTypeBytes() {
java.lang.Object ref = type_;
if (ref instanceof java.lang.String) {
com.google.protobuf.ByteString b =
com.google.protobuf.ByteString.copyFromUtf8((java.lang.String) ref);
type_ = b;
return b;
} else {
return (com.google.protobuf.ByteString) ref;
}
}
public static final int MODE_FIELD_NUMBER = 3;
@SuppressWarnings("serial")
private volatile java.lang.Object mode_ = "";
/**
*
*
*
* The mode of the field. Possible values include:
*
* * REQUIRED, if it is a required field.
* * NULLABLE, if it is an optional field.
* * REPEATED, if it is a repeated field.
*
* The mode of the field. Possible values include:
*
* * REQUIRED, if it is a required field.
* * NULLABLE, if it is an optional field.
* * REPEATED, if it is a repeated field.
*
*
* string mode = 3;
*
* @return The bytes for mode.
*/
@java.lang.Override
public com.google.protobuf.ByteString getModeBytes() {
java.lang.Object ref = mode_;
if (ref instanceof java.lang.String) {
com.google.protobuf.ByteString b =
com.google.protobuf.ByteString.copyFromUtf8((java.lang.String) ref);
mode_ = b;
return b;
} else {
return (com.google.protobuf.ByteString) ref;
}
}
public static final int PROFILE_FIELD_NUMBER = 4;
private com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo profile_;
/**
*
*
*
* Profile information for the corresponding field.
*
*
* .google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo profile = 4;
*
*
* @return Whether the profile field is set.
*/
@java.lang.Override
public boolean hasProfile() {
return ((bitField0_ & 0x00000001) != 0);
}
/**
*
*
*
* Profile information for the corresponding field.
*
*
* string name = 1;
*
* @return The bytes for name.
*/
public com.google.protobuf.ByteString getNameBytes() {
java.lang.Object ref = name_;
if (ref instanceof String) {
com.google.protobuf.ByteString b =
com.google.protobuf.ByteString.copyFromUtf8((java.lang.String) ref);
name_ = b;
return b;
} else {
return (com.google.protobuf.ByteString) ref;
}
}
/**
*
*
*
* The name of the field.
*
*
* string name = 1;
*
* @param value The name to set.
* @return This builder for chaining.
*/
public Builder setName(java.lang.String value) {
if (value == null) {
throw new NullPointerException();
}
name_ = value;
bitField0_ |= 0x00000001;
onChanged();
return this;
}
/**
*
*
*
* The name of the field.
*
*
* string name = 1;
*
* @return This builder for chaining.
*/
public Builder clearName() {
name_ = getDefaultInstance().getName();
bitField0_ = (bitField0_ & ~0x00000001);
onChanged();
return this;
}
/**
*
*
*
* The name of the field.
*
*
* string name = 1;
*
* @param value The bytes for name to set.
* @return This builder for chaining.
*/
public Builder setNameBytes(com.google.protobuf.ByteString value) {
if (value == null) {
throw new NullPointerException();
}
checkByteStringIsUtf8(value);
name_ = value;
bitField0_ |= 0x00000001;
onChanged();
return this;
}
private java.lang.Object type_ = "";
/**
*
*
*
* The data type retrieved from the schema of the data source. For
* instance, for a BigQuery native table, it is the [BigQuery Table
* Schema](https://cloud.google.com/bigquery/docs/reference/rest/v2/tables#tablefieldschema).
* For a Dataplex Entity, it is the [Entity
* Schema](https://cloud.google.com/dataplex/docs/reference/rpc/google.cloud.dataplex.v1#type_3).
*
* The data type retrieved from the schema of the data source. For
* instance, for a BigQuery native table, it is the [BigQuery Table
* Schema](https://cloud.google.com/bigquery/docs/reference/rest/v2/tables#tablefieldschema).
* For a Dataplex Entity, it is the [Entity
* Schema](https://cloud.google.com/dataplex/docs/reference/rpc/google.cloud.dataplex.v1#type_3).
*
*
* string type = 2;
*
* @return The bytes for type.
*/
public com.google.protobuf.ByteString getTypeBytes() {
java.lang.Object ref = type_;
if (ref instanceof String) {
com.google.protobuf.ByteString b =
com.google.protobuf.ByteString.copyFromUtf8((java.lang.String) ref);
type_ = b;
return b;
} else {
return (com.google.protobuf.ByteString) ref;
}
}
/**
*
*
*
* The data type retrieved from the schema of the data source. For
* instance, for a BigQuery native table, it is the [BigQuery Table
* Schema](https://cloud.google.com/bigquery/docs/reference/rest/v2/tables#tablefieldschema).
* For a Dataplex Entity, it is the [Entity
* Schema](https://cloud.google.com/dataplex/docs/reference/rpc/google.cloud.dataplex.v1#type_3).
*
*
* string type = 2;
*
* @param value The type to set.
* @return This builder for chaining.
*/
public Builder setType(java.lang.String value) {
if (value == null) {
throw new NullPointerException();
}
type_ = value;
bitField0_ |= 0x00000002;
onChanged();
return this;
}
/**
*
*
*
* The data type retrieved from the schema of the data source. For
* instance, for a BigQuery native table, it is the [BigQuery Table
* Schema](https://cloud.google.com/bigquery/docs/reference/rest/v2/tables#tablefieldschema).
* For a Dataplex Entity, it is the [Entity
* Schema](https://cloud.google.com/dataplex/docs/reference/rpc/google.cloud.dataplex.v1#type_3).
*
*
* string type = 2;
*
* @return This builder for chaining.
*/
public Builder clearType() {
type_ = getDefaultInstance().getType();
bitField0_ = (bitField0_ & ~0x00000002);
onChanged();
return this;
}
/**
*
*
*
* The data type retrieved from the schema of the data source. For
* instance, for a BigQuery native table, it is the [BigQuery Table
* Schema](https://cloud.google.com/bigquery/docs/reference/rest/v2/tables#tablefieldschema).
* For a Dataplex Entity, it is the [Entity
* Schema](https://cloud.google.com/dataplex/docs/reference/rpc/google.cloud.dataplex.v1#type_3).
*
*
* string type = 2;
*
* @param value The bytes for type to set.
* @return This builder for chaining.
*/
public Builder setTypeBytes(com.google.protobuf.ByteString value) {
if (value == null) {
throw new NullPointerException();
}
checkByteStringIsUtf8(value);
type_ = value;
bitField0_ |= 0x00000002;
onChanged();
return this;
}
private java.lang.Object mode_ = "";
/**
*
*
*
* The mode of the field. Possible values include:
*
* * REQUIRED, if it is a required field.
* * NULLABLE, if it is an optional field.
* * REPEATED, if it is a repeated field.
*
* The mode of the field. Possible values include:
*
* * REQUIRED, if it is a required field.
* * NULLABLE, if it is an optional field.
* * REPEATED, if it is a repeated field.
*
*
* string mode = 3;
*
* @return The bytes for mode.
*/
public com.google.protobuf.ByteString getModeBytes() {
java.lang.Object ref = mode_;
if (ref instanceof String) {
com.google.protobuf.ByteString b =
com.google.protobuf.ByteString.copyFromUtf8((java.lang.String) ref);
mode_ = b;
return b;
} else {
return (com.google.protobuf.ByteString) ref;
}
}
/**
*
*
*
* The mode of the field. Possible values include:
*
* * REQUIRED, if it is a required field.
* * NULLABLE, if it is an optional field.
* * REPEATED, if it is a repeated field.
*
*
* string mode = 3;
*
* @param value The mode to set.
* @return This builder for chaining.
*/
public Builder setMode(java.lang.String value) {
if (value == null) {
throw new NullPointerException();
}
mode_ = value;
bitField0_ |= 0x00000004;
onChanged();
return this;
}
/**
*
*
*
* The mode of the field. Possible values include:
*
* * REQUIRED, if it is a required field.
* * NULLABLE, if it is an optional field.
* * REPEATED, if it is a repeated field.
*
* The mode of the field. Possible values include:
*
* * REQUIRED, if it is a required field.
* * NULLABLE, if it is an optional field.
* * REPEATED, if it is a repeated field.
*
*
* string mode = 3;
*
* @param value The bytes for mode to set.
* @return This builder for chaining.
*/
public Builder setModeBytes(com.google.protobuf.ByteString value) {
if (value == null) {
throw new NullPointerException();
}
checkByteStringIsUtf8(value);
mode_ = value;
bitField0_ |= 0x00000004;
onChanged();
return this;
}
private com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo profile_;
private com.google.protobuf.SingleFieldBuilderV3<
com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo,
com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo.Builder,
com.google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfoOrBuilder>
profileBuilder_;
/**
*
*
*
* Profile information for the corresponding field.
*
*
* .google.cloud.dataplex.v1.DataProfileResult.Profile.Field.ProfileInfo profile = 4;
*
*
* @return Whether the profile field is set.
*/
public boolean hasProfile() {
return ((bitField0_ & 0x00000008) != 0);
}
/**
*
*
*
* Profile information for the corresponding field.
*
* The result of post scan actions of DataProfileScan job.
*
*
* Protobuf type {@code google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult}
*/
public static final class PostScanActionsResult extends com.google.protobuf.GeneratedMessageV3
implements
// @@protoc_insertion_point(message_implements:google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult)
PostScanActionsResultOrBuilder {
private static final long serialVersionUID = 0L;
// Use PostScanActionsResult.newBuilder() to construct.
private PostScanActionsResult(com.google.protobuf.GeneratedMessageV3.Builder builder) {
super(builder);
}
private PostScanActionsResult() {}
@java.lang.Override
@SuppressWarnings({"unused"})
protected java.lang.Object newInstance(UnusedPrivateParameter unused) {
return new PostScanActionsResult();
}
public static final com.google.protobuf.Descriptors.Descriptor getDescriptor() {
return com.google.cloud.dataplex.v1.DataProfileProto
.internal_static_google_cloud_dataplex_v1_DataProfileResult_PostScanActionsResult_descriptor;
}
@java.lang.Override
protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
internalGetFieldAccessorTable() {
return com.google.cloud.dataplex.v1.DataProfileProto
.internal_static_google_cloud_dataplex_v1_DataProfileResult_PostScanActionsResult_fieldAccessorTable
.ensureFieldAccessorsInitialized(
com.google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult.class,
com.google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult.Builder.class);
}
public interface BigQueryExportResultOrBuilder
extends
// @@protoc_insertion_point(interface_extends:google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult.BigQueryExportResult)
com.google.protobuf.MessageOrBuilder {
/**
*
*
*
* Output only. Execution state for the BigQuery exporting.
*
*
*
* .google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult.BigQueryExportResult.State state = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
*
*
* @return The enum numeric value on the wire for state.
*/
int getStateValue();
/**
*
*
*
* Output only. Execution state for the BigQuery exporting.
*
*
* STATE_UNSPECIFIED = 0;
*/
public static final int STATE_UNSPECIFIED_VALUE = 0;
/**
*
*
*
* The exporting completed successfully.
*
*
* SUCCEEDED = 1;
*/
public static final int SUCCEEDED_VALUE = 1;
/**
*
*
*
* The exporting is no longer running due to an error.
*
*
* FAILED = 2;
*/
public static final int FAILED_VALUE = 2;
/**
*
*
*
* The exporting is skipped due to no valid scan result to export
* (usually caused by scan failed).
*
*
* SKIPPED = 3;
*/
public static final int SKIPPED_VALUE = 3;
public final int getNumber() {
if (this == UNRECOGNIZED) {
throw new java.lang.IllegalArgumentException(
"Can't get the number of an unknown enum value.");
}
return value;
}
/**
* @param value The numeric wire value of the corresponding enum entry.
* @return The enum associated with the given numeric wire value.
* @deprecated Use {@link #forNumber(int)} instead.
*/
@java.lang.Deprecated
public static State valueOf(int value) {
return forNumber(value);
}
/**
* @param value The numeric wire value of the corresponding enum entry.
* @return The enum associated with the given numeric wire value.
*/
public static State forNumber(int value) {
switch (value) {
case 0:
return STATE_UNSPECIFIED;
case 1:
return SUCCEEDED;
case 2:
return FAILED;
case 3:
return SKIPPED;
default:
return null;
}
}
public static com.google.protobuf.Internal.EnumLiteMap internalGetValueMap() {
return internalValueMap;
}
private static final com.google.protobuf.Internal.EnumLiteMap internalValueMap =
new com.google.protobuf.Internal.EnumLiteMap() {
public State findValueByNumber(int number) {
return State.forNumber(number);
}
};
public final com.google.protobuf.Descriptors.EnumValueDescriptor getValueDescriptor() {
if (this == UNRECOGNIZED) {
throw new java.lang.IllegalStateException(
"Can't get the descriptor of an unrecognized enum value.");
}
return getDescriptor().getValues().get(ordinal());
}
public final com.google.protobuf.Descriptors.EnumDescriptor getDescriptorForType() {
return getDescriptor();
}
public static final com.google.protobuf.Descriptors.EnumDescriptor getDescriptor() {
return com.google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult
.BigQueryExportResult.getDescriptor()
.getEnumTypes()
.get(0);
}
private static final State[] VALUES = values();
public static State valueOf(com.google.protobuf.Descriptors.EnumValueDescriptor desc) {
if (desc.getType() != getDescriptor()) {
throw new java.lang.IllegalArgumentException(
"EnumValueDescriptor is not for this type.");
}
if (desc.getIndex() == -1) {
return UNRECOGNIZED;
}
return VALUES[desc.getIndex()];
}
private final int value;
private State(int value) {
this.value = value;
}
// @@protoc_insertion_point(enum_scope:google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult.BigQueryExportResult.State)
}
public static final int STATE_FIELD_NUMBER = 1;
private int state_ = 0;
/**
*
*
*
* Output only. Execution state for the BigQuery exporting.
*
*
*
* .google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult.BigQueryExportResult.State state = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
*
*
* @return The enum numeric value on the wire for state.
*/
@java.lang.Override
public int getStateValue() {
return state_;
}
/**
*
*
*
* Output only. Execution state for the BigQuery exporting.
*
*
*
* .google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult.BigQueryExportResult.State state = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
*
*
* @return The state.
*/
@java.lang.Override
public com.google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult
.BigQueryExportResult.State
getState() {
com.google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult.BigQueryExportResult
.State
result =
com.google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult
.BigQueryExportResult.State.forNumber(state_);
return result == null
? com.google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult
.BigQueryExportResult.State.UNRECOGNIZED
: result;
}
public static final int MESSAGE_FIELD_NUMBER = 2;
@SuppressWarnings("serial")
private volatile java.lang.Object message_ = "";
/**
*
*
*
* Output only. Additional information about the BigQuery exporting.
*
* The result of BigQuery export post scan action.
*
*
* Protobuf type {@code
* google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult.BigQueryExportResult}
*/
public static final class Builder
extends com.google.protobuf.GeneratedMessageV3.Builder
implements
// @@protoc_insertion_point(builder_implements:google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult.BigQueryExportResult)
com.google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult
.BigQueryExportResultOrBuilder {
public static final com.google.protobuf.Descriptors.Descriptor getDescriptor() {
return com.google.cloud.dataplex.v1.DataProfileProto
.internal_static_google_cloud_dataplex_v1_DataProfileResult_PostScanActionsResult_BigQueryExportResult_descriptor;
}
@java.lang.Override
protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable
internalGetFieldAccessorTable() {
return com.google.cloud.dataplex.v1.DataProfileProto
.internal_static_google_cloud_dataplex_v1_DataProfileResult_PostScanActionsResult_BigQueryExportResult_fieldAccessorTable
.ensureFieldAccessorsInitialized(
com.google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult
.BigQueryExportResult.class,
com.google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult
.BigQueryExportResult.Builder.class);
}
// Construct using
// com.google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult.BigQueryExportResult.newBuilder()
private Builder() {}
private Builder(com.google.protobuf.GeneratedMessageV3.BuilderParent parent) {
super(parent);
}
@java.lang.Override
public Builder clear() {
super.clear();
bitField0_ = 0;
state_ = 0;
message_ = "";
return this;
}
@java.lang.Override
public com.google.protobuf.Descriptors.Descriptor getDescriptorForType() {
return com.google.cloud.dataplex.v1.DataProfileProto
.internal_static_google_cloud_dataplex_v1_DataProfileResult_PostScanActionsResult_BigQueryExportResult_descriptor;
}
@java.lang.Override
public com.google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult
.BigQueryExportResult
getDefaultInstanceForType() {
return com.google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult
.BigQueryExportResult.getDefaultInstance();
}
@java.lang.Override
public com.google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult
.BigQueryExportResult
build() {
com.google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult.BigQueryExportResult
result = buildPartial();
if (!result.isInitialized()) {
throw newUninitializedMessageException(result);
}
return result;
}
@java.lang.Override
public com.google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult
.BigQueryExportResult
buildPartial() {
com.google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult.BigQueryExportResult
result =
new com.google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult
.BigQueryExportResult(this);
if (bitField0_ != 0) {
buildPartial0(result);
}
onBuilt();
return result;
}
private void buildPartial0(
com.google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult
.BigQueryExportResult
result) {
int from_bitField0_ = bitField0_;
if (((from_bitField0_ & 0x00000001) != 0)) {
result.state_ = state_;
}
if (((from_bitField0_ & 0x00000002) != 0)) {
result.message_ = message_;
}
}
@java.lang.Override
public Builder clone() {
return super.clone();
}
@java.lang.Override
public Builder setField(
com.google.protobuf.Descriptors.FieldDescriptor field, java.lang.Object value) {
return super.setField(field, value);
}
@java.lang.Override
public Builder clearField(com.google.protobuf.Descriptors.FieldDescriptor field) {
return super.clearField(field);
}
@java.lang.Override
public Builder clearOneof(com.google.protobuf.Descriptors.OneofDescriptor oneof) {
return super.clearOneof(oneof);
}
@java.lang.Override
public Builder setRepeatedField(
com.google.protobuf.Descriptors.FieldDescriptor field,
int index,
java.lang.Object value) {
return super.setRepeatedField(field, index, value);
}
@java.lang.Override
public Builder addRepeatedField(
com.google.protobuf.Descriptors.FieldDescriptor field, java.lang.Object value) {
return super.addRepeatedField(field, value);
}
@java.lang.Override
public Builder mergeFrom(com.google.protobuf.Message other) {
if (other
instanceof
com.google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult
.BigQueryExportResult) {
return mergeFrom(
(com.google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult
.BigQueryExportResult)
other);
} else {
super.mergeFrom(other);
return this;
}
}
public Builder mergeFrom(
com.google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult
.BigQueryExportResult
other) {
if (other
== com.google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult
.BigQueryExportResult.getDefaultInstance()) return this;
if (other.state_ != 0) {
setStateValue(other.getStateValue());
}
if (!other.getMessage().isEmpty()) {
message_ = other.message_;
bitField0_ |= 0x00000002;
onChanged();
}
this.mergeUnknownFields(other.getUnknownFields());
onChanged();
return this;
}
@java.lang.Override
public final boolean isInitialized() {
return true;
}
@java.lang.Override
public Builder mergeFrom(
com.google.protobuf.CodedInputStream input,
com.google.protobuf.ExtensionRegistryLite extensionRegistry)
throws java.io.IOException {
if (extensionRegistry == null) {
throw new java.lang.NullPointerException();
}
try {
boolean done = false;
while (!done) {
int tag = input.readTag();
switch (tag) {
case 0:
done = true;
break;
case 8:
{
state_ = input.readEnum();
bitField0_ |= 0x00000001;
break;
} // case 8
case 18:
{
message_ = input.readStringRequireUtf8();
bitField0_ |= 0x00000002;
break;
} // case 18
default:
{
if (!super.parseUnknownField(input, extensionRegistry, tag)) {
done = true; // was an endgroup tag
}
break;
} // default:
} // switch (tag)
} // while (!done)
} catch (com.google.protobuf.InvalidProtocolBufferException e) {
throw e.unwrapIOException();
} finally {
onChanged();
} // finally
return this;
}
private int bitField0_;
private int state_ = 0;
/**
*
*
*
* Output only. Execution state for the BigQuery exporting.
*
*
*
* .google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult.BigQueryExportResult.State state = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
*
*
* @return The enum numeric value on the wire for state.
*/
@java.lang.Override
public int getStateValue() {
return state_;
}
/**
*
*
*
* Output only. Execution state for the BigQuery exporting.
*
*
*
* .google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult.BigQueryExportResult.State state = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
*
*
* @param value The enum numeric value on the wire for state to set.
* @return This builder for chaining.
*/
public Builder setStateValue(int value) {
state_ = value;
bitField0_ |= 0x00000001;
onChanged();
return this;
}
/**
*
*
*
* Output only. Execution state for the BigQuery exporting.
*
*
*
* .google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult.BigQueryExportResult.State state = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
*
*
* @return The state.
*/
@java.lang.Override
public com.google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult
.BigQueryExportResult.State
getState() {
com.google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult.BigQueryExportResult
.State
result =
com.google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult
.BigQueryExportResult.State.forNumber(state_);
return result == null
? com.google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult
.BigQueryExportResult.State.UNRECOGNIZED
: result;
}
/**
*
*
*
* Output only. Execution state for the BigQuery exporting.
*
*
*
* .google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult.BigQueryExportResult.State state = 1 [(.google.api.field_behavior) = OUTPUT_ONLY];
*
*
* @param value The state to set.
* @return This builder for chaining.
*/
public Builder setState(
com.google.cloud.dataplex.v1.DataProfileResult.PostScanActionsResult
.BigQueryExportResult.State
value) {
if (value == null) {
throw new NullPointerException();
}
bitField0_ |= 0x00000001;
state_ = value.getNumber();
onChanged();
return this;
}
/**
*
*
*
* Output only. Execution state for the BigQuery exporting.
*
