Class TablesDatasetMetadata.Builder (2.3.3)

Version 2.3.3

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public static final class TablesDatasetMetadata.Builder extends GeneratedMessageV3.Builder<TablesDatasetMetadata.Builder> implements TablesDatasetMetadataOrBuilder

Metadata for a dataset used for AutoML Tables.

Protobuf type google.cloud.automl.v1beta1.TablesDatasetMetadata

Inheritance

Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > TablesDatasetMetadata.Builder

Implements

TablesDatasetMetadataOrBuilder

Inherited Members

AbstractMessage.Builder.findInitializationErrors()

AbstractMessage.Builder.getInitializationErrorString()

AbstractMessage.Builder.internalMergeFrom(AbstractMessageLite)

AbstractMessage.Builder.mergeFrom(byte[])

AbstractMessage.Builder.mergeFrom(byte[],ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(byte[],int,int)

AbstractMessage.Builder.mergeFrom(byte[],int,int,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(ByteString)

AbstractMessage.Builder.mergeFrom(ByteString,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(CodedInputStream)

AbstractMessage.Builder.mergeFrom(CodedInputStream,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(Message)

AbstractMessage.Builder.mergeFrom(InputStream)

AbstractMessage.Builder.mergeFrom(InputStream,ExtensionRegistryLite)

AbstractMessage.Builder.newUninitializedMessageException(Message)

AbstractMessage.Builder.toString()

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,Collection<? super T>)

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,List<? super T>)

AbstractMessageLite.Builder.internalMergeFrom(MessageType)

AbstractMessageLite.Builder.mergeDelimitedFrom(InputStream)

AbstractMessageLite.Builder.mergeDelimitedFrom(InputStream,ExtensionRegistryLite)

AbstractMessageLite.Builder.mergeFrom(MessageLite)

AbstractMessageLite.Builder.newUninitializedMessageException(MessageLite)

GeneratedMessageV3.Builder.addRepeatedField(Descriptors.FieldDescriptor,Object)

GeneratedMessageV3.Builder.clear()

GeneratedMessageV3.Builder.clearField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.clearOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.clone()

GeneratedMessageV3.Builder.getAllFields()

GeneratedMessageV3.Builder.getDescriptorForType()

GeneratedMessageV3.Builder.getField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getFieldBuilder(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getOneofFieldDescriptor(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.getParentForChildren()

GeneratedMessageV3.Builder.getRepeatedField(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.Builder.getRepeatedFieldBuilder(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.Builder.getRepeatedFieldCount(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getUnknownFields()

GeneratedMessageV3.Builder.hasField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.hasOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.internalGetFieldAccessorTable()

GeneratedMessageV3.Builder.internalGetMapField(int)

GeneratedMessageV3.Builder.internalGetMutableMapField(int)

GeneratedMessageV3.Builder.isClean()

GeneratedMessageV3.Builder.isInitialized()

GeneratedMessageV3.Builder.markClean()

GeneratedMessageV3.Builder.mergeUnknownFields(UnknownFieldSet)

GeneratedMessageV3.Builder.newBuilderForField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.onBuilt()

GeneratedMessageV3.Builder.onChanged()

GeneratedMessageV3.Builder.setField(Descriptors.FieldDescriptor,Object)

GeneratedMessageV3.Builder.setRepeatedField(Descriptors.FieldDescriptor,int,Object)

GeneratedMessageV3.Builder.setUnknownFields(UnknownFieldSet)

GeneratedMessageV3.Builder.setUnknownFieldsProto3(UnknownFieldSet)

Object.equals(Object)

Object.finalize()

Object.getClass()

Object.hashCode()

Object.notify()

Object.notifyAll()

Object.wait()

Object.wait(long)

Object.wait(long,int)

Static Methods

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()

Returns

Type	Description
Descriptor

Methods

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public TablesDatasetMetadata.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)

Parameters

Name	Description
field	FieldDescriptor
value	Object

Returns

Type	Description
TablesDatasetMetadata.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.addRepeatedField(Descriptors.FieldDescriptor field, Object value)

build()

public TablesDatasetMetadata build()

Returns

Type	Description
TablesDatasetMetadata

buildPartial()

public TablesDatasetMetadata buildPartial()

Returns

Type	Description
TablesDatasetMetadata

clear()

public TablesDatasetMetadata.Builder clear()

Returns

Type	Description
TablesDatasetMetadata.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clear()

clearField(Descriptors.FieldDescriptor field)

public TablesDatasetMetadata.Builder clearField(Descriptors.FieldDescriptor field)

Parameter

Name	Description
field	FieldDescriptor

Returns

Type	Description
TablesDatasetMetadata.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clearField(Descriptors.FieldDescriptor field)

clearMlUseColumnSpecId()

public TablesDatasetMetadata.Builder clearMlUseColumnSpecId()

column_spec_id of the primary table column which specifies a possible ML use of the row, i.e. the column will be used to split the rows into TRAIN, VALIDATE and TEST sets. Required type: STRING. This column, if set, must either have all of TRAIN, VALIDATE, TEST among its values, or only have TEST, UNASSIGNED values. In the latter case the rows with UNASSIGNED value will be assigned by AutoML. Note that if a given ml use distribution makes it impossible to create a "good" model, that call will error describing the issue. If both this column_spec_id and primary table's time_column_spec_id are not set, then all rows are treated as UNASSIGNED. NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.

string ml_use_column_spec_id = 4;

Returns

Type	Description
TablesDatasetMetadata.Builder	This builder for chaining.

clearOneof(Descriptors.OneofDescriptor oneof)

public TablesDatasetMetadata.Builder clearOneof(Descriptors.OneofDescriptor oneof)

Parameter

Name	Description
oneof	OneofDescriptor

Returns

Type	Description
TablesDatasetMetadata.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clearOneof(Descriptors.OneofDescriptor oneof)

clearPrimaryTableSpecId()

public TablesDatasetMetadata.Builder clearPrimaryTableSpecId()

Output only. The table_spec_id of the primary table of this dataset.

string primary_table_spec_id = 1;

Returns

Type	Description
TablesDatasetMetadata.Builder	This builder for chaining.

clearStatsUpdateTime()

public TablesDatasetMetadata.Builder clearStatsUpdateTime()

Output only. The most recent timestamp when target_column_correlations field and all descendant ColumnSpec.data_stats and ColumnSpec.top_correlated_columns fields were last (re-)generated. Any changes that happened to the dataset afterwards are not reflected in these fields values. The regeneration happens in the background on a best effort basis.

.google.protobuf.Timestamp stats_update_time = 7;

Returns

Type	Description
TablesDatasetMetadata.Builder

clearTargetColumnCorrelations()

public TablesDatasetMetadata.Builder clearTargetColumnCorrelations()

Returns

Type	Description
TablesDatasetMetadata.Builder

clearTargetColumnSpecId()

public TablesDatasetMetadata.Builder clearTargetColumnSpecId()

column_spec_id of the primary table's column that should be used as the training & prediction target. This column must be non-nullable and have one of following data types (otherwise model creation will error):

• CATEGORY
• FLOAT64 If the type is CATEGORY , only up to 100 unique values may exist in that column across all rows. NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.

string target_column_spec_id = 2;

Returns

Type	Description
TablesDatasetMetadata.Builder	This builder for chaining.

clearWeightColumnSpecId()

public TablesDatasetMetadata.Builder clearWeightColumnSpecId()

column_spec_id of the primary table's column that should be used as the weight column, i.e. the higher the value the more important the row will be during model training. Required type: FLOAT64. Allowed values: 0 to 10000, inclusive on both ends; 0 means the row is ignored for training. If not set all rows are assumed to have equal weight of 1. NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.

string weight_column_spec_id = 3;

Returns

Type	Description
TablesDatasetMetadata.Builder	This builder for chaining.

clone()

public TablesDatasetMetadata.Builder clone()

Returns

Type	Description
TablesDatasetMetadata.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clone()

containsTargetColumnCorrelations(String key)

public boolean containsTargetColumnCorrelations(String key)

Output only. Correlations between TablesDatasetMetadata.target_column_spec_id, and other columns of the TablesDatasetMetadataprimary_table. Only set if the target column is set. Mapping from other column spec id to its CorrelationStats with the target column. This field may be stale, see the stats_update_time field for for the timestamp at which these stats were last updated.

map<string, .google.cloud.automl.v1beta1.CorrelationStats> target_column_correlations = 6;

Parameter

Name	Description
key	String

Returns

Type	Description
boolean

getDefaultInstanceForType()

public TablesDatasetMetadata getDefaultInstanceForType()

Returns

Type	Description
TablesDatasetMetadata

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()

Returns

Type	Description
Descriptor

Overrides

GeneratedMessageV3.Builder<BuilderType>.getDescriptorForType()

getMlUseColumnSpecId()

public String getMlUseColumnSpecId()

column_spec_id of the primary table column which specifies a possible ML use of the row, i.e. the column will be used to split the rows into TRAIN, VALIDATE and TEST sets. Required type: STRING. This column, if set, must either have all of TRAIN, VALIDATE, TEST among its values, or only have TEST, UNASSIGNED values. In the latter case the rows with UNASSIGNED value will be assigned by AutoML. Note that if a given ml use distribution makes it impossible to create a "good" model, that call will error describing the issue. If both this column_spec_id and primary table's time_column_spec_id are not set, then all rows are treated as UNASSIGNED. NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.

string ml_use_column_spec_id = 4;

Returns

Type	Description
String	The mlUseColumnSpecId.

getMlUseColumnSpecIdBytes()

public ByteString getMlUseColumnSpecIdBytes()

column_spec_id of the primary table column which specifies a possible ML use of the row, i.e. the column will be used to split the rows into TRAIN, VALIDATE and TEST sets. Required type: STRING. This column, if set, must either have all of TRAIN, VALIDATE, TEST among its values, or only have TEST, UNASSIGNED values. In the latter case the rows with UNASSIGNED value will be assigned by AutoML. Note that if a given ml use distribution makes it impossible to create a "good" model, that call will error describing the issue. If both this column_spec_id and primary table's time_column_spec_id are not set, then all rows are treated as UNASSIGNED. NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.

string ml_use_column_spec_id = 4;

Returns

Type	Description
ByteString	The bytes for mlUseColumnSpecId.

getMutableTargetColumnCorrelations()

public Map<String,CorrelationStats> getMutableTargetColumnCorrelations()

Use alternate mutation accessors instead.

Returns

Type	Description
Map<String,CorrelationStats>

getPrimaryTableSpecId()

public String getPrimaryTableSpecId()

Output only. The table_spec_id of the primary table of this dataset.

string primary_table_spec_id = 1;

Returns

Type	Description
String	The primaryTableSpecId.

getPrimaryTableSpecIdBytes()

public ByteString getPrimaryTableSpecIdBytes()

Output only. The table_spec_id of the primary table of this dataset.

string primary_table_spec_id = 1;

Returns

Type	Description
ByteString	The bytes for primaryTableSpecId.

getStatsUpdateTime()

public Timestamp getStatsUpdateTime()

Output only. The most recent timestamp when target_column_correlations field and all descendant ColumnSpec.data_stats and ColumnSpec.top_correlated_columns fields were last (re-)generated. Any changes that happened to the dataset afterwards are not reflected in these fields values. The regeneration happens in the background on a best effort basis.

.google.protobuf.Timestamp stats_update_time = 7;

Returns

Type	Description
Timestamp	The statsUpdateTime.

getStatsUpdateTimeBuilder()

public Timestamp.Builder getStatsUpdateTimeBuilder()

Output only. The most recent timestamp when target_column_correlations field and all descendant ColumnSpec.data_stats and ColumnSpec.top_correlated_columns fields were last (re-)generated. Any changes that happened to the dataset afterwards are not reflected in these fields values. The regeneration happens in the background on a best effort basis.

.google.protobuf.Timestamp stats_update_time = 7;

Returns

Type	Description
Builder

getStatsUpdateTimeOrBuilder()

public TimestampOrBuilder getStatsUpdateTimeOrBuilder()

Output only. The most recent timestamp when target_column_correlations field and all descendant ColumnSpec.data_stats and ColumnSpec.top_correlated_columns fields were last (re-)generated. Any changes that happened to the dataset afterwards are not reflected in these fields values. The regeneration happens in the background on a best effort basis.

.google.protobuf.Timestamp stats_update_time = 7;

Returns

Type	Description
TimestampOrBuilder

getTargetColumnCorrelations()

public Map<String,CorrelationStats> getTargetColumnCorrelations()

Use #getTargetColumnCorrelationsMap() instead.

Returns

Type	Description
Map<String,CorrelationStats>

getTargetColumnCorrelationsCount()

public int getTargetColumnCorrelationsCount()

Output only. Correlations between TablesDatasetMetadata.target_column_spec_id, and other columns of the TablesDatasetMetadataprimary_table. Only set if the target column is set. Mapping from other column spec id to its CorrelationStats with the target column. This field may be stale, see the stats_update_time field for for the timestamp at which these stats were last updated.

map<string, .google.cloud.automl.v1beta1.CorrelationStats> target_column_correlations = 6;

Returns

Type	Description
int

getTargetColumnCorrelationsMap()

public Map<String,CorrelationStats> getTargetColumnCorrelationsMap()

Output only. Correlations between TablesDatasetMetadata.target_column_spec_id, and other columns of the TablesDatasetMetadataprimary_table. Only set if the target column is set. Mapping from other column spec id to its CorrelationStats with the target column. This field may be stale, see the stats_update_time field for for the timestamp at which these stats were last updated.

map<string, .google.cloud.automl.v1beta1.CorrelationStats> target_column_correlations = 6;

Returns

Type	Description
Map<String,CorrelationStats>

getTargetColumnCorrelationsOrDefault(String key, CorrelationStats defaultValue)

public CorrelationStats getTargetColumnCorrelationsOrDefault(String key, CorrelationStats defaultValue)

Output only. Correlations between TablesDatasetMetadata.target_column_spec_id, and other columns of the TablesDatasetMetadataprimary_table. Only set if the target column is set. Mapping from other column spec id to its CorrelationStats with the target column. This field may be stale, see the stats_update_time field for for the timestamp at which these stats were last updated.

map<string, .google.cloud.automl.v1beta1.CorrelationStats> target_column_correlations = 6;

Parameters

Name	Description
key	String
defaultValue	CorrelationStats

Returns

Type	Description
CorrelationStats

getTargetColumnCorrelationsOrThrow(String key)

public CorrelationStats getTargetColumnCorrelationsOrThrow(String key)

Output only. Correlations between TablesDatasetMetadata.target_column_spec_id, and other columns of the TablesDatasetMetadataprimary_table. Only set if the target column is set. Mapping from other column spec id to its CorrelationStats with the target column. This field may be stale, see the stats_update_time field for for the timestamp at which these stats were last updated.

map<string, .google.cloud.automl.v1beta1.CorrelationStats> target_column_correlations = 6;

Parameter

Name	Description
key	String

Returns

Type	Description
CorrelationStats

getTargetColumnSpecId()

public String getTargetColumnSpecId()

column_spec_id of the primary table's column that should be used as the training & prediction target. This column must be non-nullable and have one of following data types (otherwise model creation will error):

• CATEGORY
• FLOAT64 If the type is CATEGORY , only up to 100 unique values may exist in that column across all rows. NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.

string target_column_spec_id = 2;

Returns

Type	Description
String	The targetColumnSpecId.

getTargetColumnSpecIdBytes()

public ByteString getTargetColumnSpecIdBytes()

column_spec_id of the primary table's column that should be used as the training & prediction target. This column must be non-nullable and have one of following data types (otherwise model creation will error):

• CATEGORY
• FLOAT64 If the type is CATEGORY , only up to 100 unique values may exist in that column across all rows. NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.

string target_column_spec_id = 2;

Returns

Type	Description
ByteString	The bytes for targetColumnSpecId.

getWeightColumnSpecId()

public String getWeightColumnSpecId()

column_spec_id of the primary table's column that should be used as the weight column, i.e. the higher the value the more important the row will be during model training. Required type: FLOAT64. Allowed values: 0 to 10000, inclusive on both ends; 0 means the row is ignored for training. If not set all rows are assumed to have equal weight of 1. NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.

string weight_column_spec_id = 3;

Returns

Type	Description
String	The weightColumnSpecId.

getWeightColumnSpecIdBytes()

public ByteString getWeightColumnSpecIdBytes()

column_spec_id of the primary table's column that should be used as the weight column, i.e. the higher the value the more important the row will be during model training. Required type: FLOAT64. Allowed values: 0 to 10000, inclusive on both ends; 0 means the row is ignored for training. If not set all rows are assumed to have equal weight of 1. NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.

string weight_column_spec_id = 3;

Returns

Type	Description
ByteString	The bytes for weightColumnSpecId.

hasStatsUpdateTime()

public boolean hasStatsUpdateTime()

Output only. The most recent timestamp when target_column_correlations field and all descendant ColumnSpec.data_stats and ColumnSpec.top_correlated_columns fields were last (re-)generated. Any changes that happened to the dataset afterwards are not reflected in these fields values. The regeneration happens in the background on a best effort basis.

.google.protobuf.Timestamp stats_update_time = 7;

Returns

Type	Description
boolean	Whether the statsUpdateTime field is set.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()

Returns

Type	Description
FieldAccessorTable

Overrides

GeneratedMessageV3.Builder<BuilderType>.internalGetFieldAccessorTable()

internalGetMapField(int number)

protected MapField internalGetMapField(int number)

Parameter

Name	Description
number	int

Returns

Type	Description
MapField

Overrides

GeneratedMessageV3.Builder<BuilderType>.internalGetMapField(int fieldNumber)

internalGetMutableMapField(int number)

protected MapField internalGetMutableMapField(int number)

Parameter

Name	Description
number	int

Returns

Type	Description
MapField

Overrides

GeneratedMessageV3.Builder<BuilderType>.internalGetMutableMapField(int fieldNumber)

isInitialized()

public final boolean isInitialized()

Returns

Type	Description
boolean

Overrides

GeneratedMessageV3.Builder<BuilderType>.isInitialized()

mergeFrom(TablesDatasetMetadata other)

public TablesDatasetMetadata.Builder mergeFrom(TablesDatasetMetadata other)

Parameter

Name	Description
other	TablesDatasetMetadata

Returns

Type	Description
TablesDatasetMetadata.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public TablesDatasetMetadata.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Parameters

Name	Description
input	CodedInputStream
extensionRegistry	ExtensionRegistryLite

Returns

Type	Description
TablesDatasetMetadata.Builder

Overrides

AbstractMessage.Builder<BuilderType>.mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Exceptions

Type	Description
IOException

mergeFrom(Message other)

public TablesDatasetMetadata.Builder mergeFrom(Message other)

Parameter

Name	Description
other	Message

Returns

Type	Description
TablesDatasetMetadata.Builder

Overrides

AbstractMessage.Builder<BuilderType>.mergeFrom(Message other)

mergeStatsUpdateTime(Timestamp value)

public TablesDatasetMetadata.Builder mergeStatsUpdateTime(Timestamp value)

Output only. The most recent timestamp when target_column_correlations field and all descendant ColumnSpec.data_stats and ColumnSpec.top_correlated_columns fields were last (re-)generated. Any changes that happened to the dataset afterwards are not reflected in these fields values. The regeneration happens in the background on a best effort basis.

.google.protobuf.Timestamp stats_update_time = 7;

Parameter

Name	Description
value	Timestamp

Returns

Type	Description
TablesDatasetMetadata.Builder

mergeUnknownFields(UnknownFieldSet unknownFields)

public final TablesDatasetMetadata.Builder mergeUnknownFields(UnknownFieldSet unknownFields)

Parameter

Name	Description
unknownFields	UnknownFieldSet

Returns

Type	Description
TablesDatasetMetadata.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.mergeUnknownFields(UnknownFieldSet unknownFields)

putAllTargetColumnCorrelations(Map<String,CorrelationStats> values)

public TablesDatasetMetadata.Builder putAllTargetColumnCorrelations(Map<String,CorrelationStats> values)

Output only. Correlations between TablesDatasetMetadata.target_column_spec_id, and other columns of the TablesDatasetMetadataprimary_table. Only set if the target column is set. Mapping from other column spec id to its CorrelationStats with the target column. This field may be stale, see the stats_update_time field for for the timestamp at which these stats were last updated.

map<string, .google.cloud.automl.v1beta1.CorrelationStats> target_column_correlations = 6;

Parameter

Name	Description
values	Map<String,CorrelationStats>

Returns

Type	Description
TablesDatasetMetadata.Builder

putTargetColumnCorrelations(String key, CorrelationStats value)

public TablesDatasetMetadata.Builder putTargetColumnCorrelations(String key, CorrelationStats value)

Output only. Correlations between TablesDatasetMetadata.target_column_spec_id, and other columns of the TablesDatasetMetadataprimary_table. Only set if the target column is set. Mapping from other column spec id to its CorrelationStats with the target column. This field may be stale, see the stats_update_time field for for the timestamp at which these stats were last updated.

map<string, .google.cloud.automl.v1beta1.CorrelationStats> target_column_correlations = 6;

Parameters

Name	Description
key	String
value	CorrelationStats

Returns

Type	Description
TablesDatasetMetadata.Builder

removeTargetColumnCorrelations(String key)

public TablesDatasetMetadata.Builder removeTargetColumnCorrelations(String key)

Output only. Correlations between TablesDatasetMetadata.target_column_spec_id, and other columns of the TablesDatasetMetadataprimary_table. Only set if the target column is set. Mapping from other column spec id to its CorrelationStats with the target column. This field may be stale, see the stats_update_time field for for the timestamp at which these stats were last updated.

map<string, .google.cloud.automl.v1beta1.CorrelationStats> target_column_correlations = 6;

Parameter

Name	Description
key	String

Returns

Type	Description
TablesDatasetMetadata.Builder

setField(Descriptors.FieldDescriptor field, Object value)

public TablesDatasetMetadata.Builder setField(Descriptors.FieldDescriptor field, Object value)

Parameters

Name	Description
field	FieldDescriptor
value	Object

Returns

Type	Description
TablesDatasetMetadata.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setField(Descriptors.FieldDescriptor field, Object value)

setMlUseColumnSpecId(String value)

public TablesDatasetMetadata.Builder setMlUseColumnSpecId(String value)

column_spec_id of the primary table column which specifies a possible ML use of the row, i.e. the column will be used to split the rows into TRAIN, VALIDATE and TEST sets. Required type: STRING. This column, if set, must either have all of TRAIN, VALIDATE, TEST among its values, or only have TEST, UNASSIGNED values. In the latter case the rows with UNASSIGNED value will be assigned by AutoML. Note that if a given ml use distribution makes it impossible to create a "good" model, that call will error describing the issue. If both this column_spec_id and primary table's time_column_spec_id are not set, then all rows are treated as UNASSIGNED. NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.

string ml_use_column_spec_id = 4;

Parameter

Name	Description
value	String The mlUseColumnSpecId to set.

Returns

Type	Description
TablesDatasetMetadata.Builder	This builder for chaining.

setMlUseColumnSpecIdBytes(ByteString value)

public TablesDatasetMetadata.Builder setMlUseColumnSpecIdBytes(ByteString value)

column_spec_id of the primary table column which specifies a possible ML use of the row, i.e. the column will be used to split the rows into TRAIN, VALIDATE and TEST sets. Required type: STRING. This column, if set, must either have all of TRAIN, VALIDATE, TEST among its values, or only have TEST, UNASSIGNED values. In the latter case the rows with UNASSIGNED value will be assigned by AutoML. Note that if a given ml use distribution makes it impossible to create a "good" model, that call will error describing the issue. If both this column_spec_id and primary table's time_column_spec_id are not set, then all rows are treated as UNASSIGNED. NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.

string ml_use_column_spec_id = 4;

Parameter

Name	Description
value	ByteString The bytes for mlUseColumnSpecId to set.

Returns

Type	Description
TablesDatasetMetadata.Builder	This builder for chaining.

setPrimaryTableSpecId(String value)

public TablesDatasetMetadata.Builder setPrimaryTableSpecId(String value)

Output only. The table_spec_id of the primary table of this dataset.

string primary_table_spec_id = 1;

Parameter

Name	Description
value	String The primaryTableSpecId to set.

Returns

Type	Description
TablesDatasetMetadata.Builder	This builder for chaining.

setPrimaryTableSpecIdBytes(ByteString value)

public TablesDatasetMetadata.Builder setPrimaryTableSpecIdBytes(ByteString value)

Output only. The table_spec_id of the primary table of this dataset.

string primary_table_spec_id = 1;

Parameter

Name	Description
value	ByteString The bytes for primaryTableSpecId to set.

Returns

Type	Description
TablesDatasetMetadata.Builder	This builder for chaining.

setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

public TablesDatasetMetadata.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

Parameters

Name	Description
field	FieldDescriptor
index	int
value	Object

Returns

Type	Description
TablesDatasetMetadata.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

setStatsUpdateTime(Timestamp value)

public TablesDatasetMetadata.Builder setStatsUpdateTime(Timestamp value)

Output only. The most recent timestamp when target_column_correlations field and all descendant ColumnSpec.data_stats and ColumnSpec.top_correlated_columns fields were last (re-)generated. Any changes that happened to the dataset afterwards are not reflected in these fields values. The regeneration happens in the background on a best effort basis.

.google.protobuf.Timestamp stats_update_time = 7;

Parameter

Name	Description
value	Timestamp

Returns

Type	Description
TablesDatasetMetadata.Builder

setStatsUpdateTime(Timestamp.Builder builderForValue)

public TablesDatasetMetadata.Builder setStatsUpdateTime(Timestamp.Builder builderForValue)

Output only. The most recent timestamp when target_column_correlations field and all descendant ColumnSpec.data_stats and ColumnSpec.top_correlated_columns fields were last (re-)generated. Any changes that happened to the dataset afterwards are not reflected in these fields values. The regeneration happens in the background on a best effort basis.

.google.protobuf.Timestamp stats_update_time = 7;

Parameter

Name	Description
builderForValue	Builder

Returns

Type	Description
TablesDatasetMetadata.Builder

setTargetColumnSpecId(String value)

public TablesDatasetMetadata.Builder setTargetColumnSpecId(String value)

column_spec_id of the primary table's column that should be used as the training & prediction target. This column must be non-nullable and have one of following data types (otherwise model creation will error):

• CATEGORY
• FLOAT64 If the type is CATEGORY , only up to 100 unique values may exist in that column across all rows. NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.

string target_column_spec_id = 2;

Parameter

Name	Description
value	String The targetColumnSpecId to set.

Returns

Type	Description
TablesDatasetMetadata.Builder	This builder for chaining.

setTargetColumnSpecIdBytes(ByteString value)

public TablesDatasetMetadata.Builder setTargetColumnSpecIdBytes(ByteString value)

column_spec_id of the primary table's column that should be used as the training & prediction target. This column must be non-nullable and have one of following data types (otherwise model creation will error):

• CATEGORY
• FLOAT64 If the type is CATEGORY , only up to 100 unique values may exist in that column across all rows. NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.

string target_column_spec_id = 2;

Parameter

Name	Description
value	ByteString The bytes for targetColumnSpecId to set.

Returns

Type	Description
TablesDatasetMetadata.Builder	This builder for chaining.

setUnknownFields(UnknownFieldSet unknownFields)

public final TablesDatasetMetadata.Builder setUnknownFields(UnknownFieldSet unknownFields)

Parameter

Name	Description
unknownFields	UnknownFieldSet

Returns

Type	Description
TablesDatasetMetadata.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setUnknownFields(UnknownFieldSet unknownFields)

setWeightColumnSpecId(String value)

public TablesDatasetMetadata.Builder setWeightColumnSpecId(String value)

column_spec_id of the primary table's column that should be used as the weight column, i.e. the higher the value the more important the row will be during model training. Required type: FLOAT64. Allowed values: 0 to 10000, inclusive on both ends; 0 means the row is ignored for training. If not set all rows are assumed to have equal weight of 1. NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.

string weight_column_spec_id = 3;

Parameter

Name	Description
value	String The weightColumnSpecId to set.

Returns

Type	Description
TablesDatasetMetadata.Builder	This builder for chaining.

setWeightColumnSpecIdBytes(ByteString value)

public TablesDatasetMetadata.Builder setWeightColumnSpecIdBytes(ByteString value)

column_spec_id of the primary table's column that should be used as the weight column, i.e. the higher the value the more important the row will be during model training. Required type: FLOAT64. Allowed values: 0 to 10000, inclusive on both ends; 0 means the row is ignored for training. If not set all rows are assumed to have equal weight of 1. NOTE: Updates of this field will instantly affect any other users concurrently working with the dataset.

string weight_column_spec_id = 3;

Parameter

Name	Description
value	ByteString The bytes for weightColumnSpecId to set.

Returns

Type	Description
TablesDatasetMetadata.Builder	This builder for chaining.