public static final class BigQueryConfig.Builder extends GeneratedMessageV3.Builder<BigQueryConfig.Builder> implements BigQueryConfigOrBuilderMessage of configurations for BigQuery processor.
Protobuf type google.cloud.visionai.v1.BigQueryConfig
Inheritance
Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > BigQueryConfig.BuilderImplements
BigQueryConfigOrBuilderStatic Methods
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()| Returns | |
|---|---|
| Type | Description |
Descriptor |
|
Methods
addRepeatedField(Descriptors.FieldDescriptor field, Object value)
public BigQueryConfig.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)| Parameters | |
|---|---|
| Name | Description |
field |
FieldDescriptor |
value |
Object |
| Returns | |
|---|---|
| Type | Description |
BigQueryConfig.Builder |
|
build()
public BigQueryConfig build()| Returns | |
|---|---|
| Type | Description |
BigQueryConfig |
|
buildPartial()
public BigQueryConfig buildPartial()| Returns | |
|---|---|
| Type | Description |
BigQueryConfig |
|
clear()
public BigQueryConfig.Builder clear()| Returns | |
|---|---|
| Type | Description |
BigQueryConfig.Builder |
|
clearCloudFunctionMapping()
public BigQueryConfig.Builder clearCloudFunctionMapping()| Returns | |
|---|---|
| Type | Description |
BigQueryConfig.Builder |
|
clearCreateDefaultTableIfNotExists()
public BigQueryConfig.Builder clearCreateDefaultTableIfNotExists()If true, App Platform will create the BigQuery DataSet and the BigQuery Table with default schema if the specified table doesn't exist. This doesn't work if any cloud function customized schema is specified since the system doesn't know your desired schema. JSON column will be used in the default table created by App Platform.
bool create_default_table_if_not_exists = 3;
| Returns | |
|---|---|
| Type | Description |
BigQueryConfig.Builder |
This builder for chaining. |
clearField(Descriptors.FieldDescriptor field)
public BigQueryConfig.Builder clearField(Descriptors.FieldDescriptor field)| Parameter | |
|---|---|
| Name | Description |
field |
FieldDescriptor |
| Returns | |
|---|---|
| Type | Description |
BigQueryConfig.Builder |
|
clearOneof(Descriptors.OneofDescriptor oneof)
public BigQueryConfig.Builder clearOneof(Descriptors.OneofDescriptor oneof)| Parameter | |
|---|---|
| Name | Description |
oneof |
OneofDescriptor |
| Returns | |
|---|---|
| Type | Description |
BigQueryConfig.Builder |
|
clearTable()
public BigQueryConfig.Builder clearTable()BigQuery table resource for Vision AI Platform to ingest annotations to.
string table = 1;
| Returns | |
|---|---|
| Type | Description |
BigQueryConfig.Builder |
This builder for chaining. |
clone()
public BigQueryConfig.Builder clone()| Returns | |
|---|---|
| Type | Description |
BigQueryConfig.Builder |
|
containsCloudFunctionMapping(String key)
public boolean containsCloudFunctionMapping(String key)Data Schema By default, Vision AI Application will try to write annotations to the target BigQuery table using the following schema:
ingestion_time: TIMESTAMP, the ingestion time of the original data.
application: STRING, name of the application which produces the annotation.
instance: STRING, Id of the instance which produces the annotation.
node: STRING, name of the application graph node which produces the annotation.
annotation: STRING or JSON, the actual annotation protobuf will be converted to json string with bytes field as 64 encoded string. It can be written to both String or Json type column.
To forward annotation data to an existing BigQuery table, customer needs to make sure the compatibility of the schema. The map maps application node name to its corresponding cloud function endpoint to transform the annotations directly to the google.cloud.bigquery.storage.v1.AppendRowsRequest (only avro_rows or proto_rows should be set). If configured, annotations produced by corresponding application node will sent to the Cloud Function at first before be forwarded to BigQuery.
If the default table schema doesn't fit, customer is able to transform the annotation output from Vision AI Application to arbitrary BigQuery table schema with CloudFunction.
- The cloud function will receive AppPlatformCloudFunctionRequest where the annotations field will be the json format of Vision AI annotation.
- The cloud function should return AppPlatformCloudFunctionResponse with AppendRowsRequest stored in the annotations field.
- To drop the annotation, simply clear the annotations field in the returned AppPlatformCloudFunctionResponse.
map<string, string> cloud_function_mapping = 2;
| Parameter | |
|---|---|
| Name | Description |
key |
String |
| Returns | |
|---|---|
| Type | Description |
boolean |
|
getCloudFunctionMapping() (deprecated)
public Map<String,String> getCloudFunctionMapping()Use #getCloudFunctionMappingMap() instead.
| Returns | |
|---|---|
| Type | Description |
Map<String,String> |
|
getCloudFunctionMappingCount()
public int getCloudFunctionMappingCount()Data Schema By default, Vision AI Application will try to write annotations to the target BigQuery table using the following schema:
ingestion_time: TIMESTAMP, the ingestion time of the original data.
application: STRING, name of the application which produces the annotation.
instance: STRING, Id of the instance which produces the annotation.
node: STRING, name of the application graph node which produces the annotation.
annotation: STRING or JSON, the actual annotation protobuf will be converted to json string with bytes field as 64 encoded string. It can be written to both String or Json type column.
To forward annotation data to an existing BigQuery table, customer needs to make sure the compatibility of the schema. The map maps application node name to its corresponding cloud function endpoint to transform the annotations directly to the google.cloud.bigquery.storage.v1.AppendRowsRequest (only avro_rows or proto_rows should be set). If configured, annotations produced by corresponding application node will sent to the Cloud Function at first before be forwarded to BigQuery.
If the default table schema doesn't fit, customer is able to transform the annotation output from Vision AI Application to arbitrary BigQuery table schema with CloudFunction.
- The cloud function will receive AppPlatformCloudFunctionRequest where the annotations field will be the json format of Vision AI annotation.
- The cloud function should return AppPlatformCloudFunctionResponse with AppendRowsRequest stored in the annotations field.
- To drop the annotation, simply clear the annotations field in the returned AppPlatformCloudFunctionResponse.
map<string, string> cloud_function_mapping = 2;
| Returns | |
|---|---|
| Type | Description |
int |
|
getCloudFunctionMappingMap()
public Map<String,String> getCloudFunctionMappingMap()Data Schema By default, Vision AI Application will try to write annotations to the target BigQuery table using the following schema:
ingestion_time: TIMESTAMP, the ingestion time of the original data.
application: STRING, name of the application which produces the annotation.
instance: STRING, Id of the instance which produces the annotation.
node: STRING, name of the application graph node which produces the annotation.
annotation: STRING or JSON, the actual annotation protobuf will be converted to json string with bytes field as 64 encoded string. It can be written to both String or Json type column.
To forward annotation data to an existing BigQuery table, customer needs to make sure the compatibility of the schema. The map maps application node name to its corresponding cloud function endpoint to transform the annotations directly to the google.cloud.bigquery.storage.v1.AppendRowsRequest (only avro_rows or proto_rows should be set). If configured, annotations produced by corresponding application node will sent to the Cloud Function at first before be forwarded to BigQuery.
If the default table schema doesn't fit, customer is able to transform the annotation output from Vision AI Application to arbitrary BigQuery table schema with CloudFunction.
- The cloud function will receive AppPlatformCloudFunctionRequest where the annotations field will be the json format of Vision AI annotation.
- The cloud function should return AppPlatformCloudFunctionResponse with AppendRowsRequest stored in the annotations field.
- To drop the annotation, simply clear the annotations field in the returned AppPlatformCloudFunctionResponse.
map<string, string> cloud_function_mapping = 2;
| Returns | |
|---|---|
| Type | Description |
Map<String,String> |
|
getCloudFunctionMappingOrDefault(String key, String defaultValue)
public String getCloudFunctionMappingOrDefault(String key, String defaultValue)Data Schema By default, Vision AI Application will try to write annotations to the target BigQuery table using the following schema:
ingestion_time: TIMESTAMP, the ingestion time of the original data.
application: STRING, name of the application which produces the annotation.
instance: STRING, Id of the instance which produces the annotation.
node: STRING, name of the application graph node which produces the annotation.
annotation: STRING or JSON, the actual annotation protobuf will be converted to json string with bytes field as 64 encoded string. It can be written to both String or Json type column.
To forward annotation data to an existing BigQuery table, customer needs to make sure the compatibility of the schema. The map maps application node name to its corresponding cloud function endpoint to transform the annotations directly to the google.cloud.bigquery.storage.v1.AppendRowsRequest (only avro_rows or proto_rows should be set). If configured, annotations produced by corresponding application node will sent to the Cloud Function at first before be forwarded to BigQuery.
If the default table schema doesn't fit, customer is able to transform the annotation output from Vision AI Application to arbitrary BigQuery table schema with CloudFunction.
- The cloud function will receive AppPlatformCloudFunctionRequest where the annotations field will be the json format of Vision AI annotation.
- The cloud function should return AppPlatformCloudFunctionResponse with AppendRowsRequest stored in the annotations field.
- To drop the annotation, simply clear the annotations field in the returned AppPlatformCloudFunctionResponse.
map<string, string> cloud_function_mapping = 2;
| Parameters | |
|---|---|
| Name | Description |
key |
String |
defaultValue |
String |
| Returns | |
|---|---|
| Type | Description |
String |
|
getCloudFunctionMappingOrThrow(String key)
public String getCloudFunctionMappingOrThrow(String key)Data Schema By default, Vision AI Application will try to write annotations to the target BigQuery table using the following schema:
ingestion_time: TIMESTAMP, the ingestion time of the original data.
application: STRING, name of the application which produces the annotation.
instance: STRING, Id of the instance which produces the annotation.
node: STRING, name of the application graph node which produces the annotation.
annotation: STRING or JSON, the actual annotation protobuf will be converted to json string with bytes field as 64 encoded string. It can be written to both String or Json type column.
To forward annotation data to an existing BigQuery table, customer needs to make sure the compatibility of the schema. The map maps application node name to its corresponding cloud function endpoint to transform the annotations directly to the google.cloud.bigquery.storage.v1.AppendRowsRequest (only avro_rows or proto_rows should be set). If configured, annotations produced by corresponding application node will sent to the Cloud Function at first before be forwarded to BigQuery.
If the default table schema doesn't fit, customer is able to transform the annotation output from Vision AI Application to arbitrary BigQuery table schema with CloudFunction.
- The cloud function will receive AppPlatformCloudFunctionRequest where the annotations field will be the json format of Vision AI annotation.
- The cloud function should return AppPlatformCloudFunctionResponse with AppendRowsRequest stored in the annotations field.
- To drop the annotation, simply clear the annotations field in the returned AppPlatformCloudFunctionResponse.
map<string, string> cloud_function_mapping = 2;
| Parameter | |
|---|---|
| Name | Description |
key |
String |
| Returns | |
|---|---|
| Type | Description |
String |
|
getCreateDefaultTableIfNotExists()
public boolean getCreateDefaultTableIfNotExists()If true, App Platform will create the BigQuery DataSet and the BigQuery Table with default schema if the specified table doesn't exist. This doesn't work if any cloud function customized schema is specified since the system doesn't know your desired schema. JSON column will be used in the default table created by App Platform.
bool create_default_table_if_not_exists = 3;
| Returns | |
|---|---|
| Type | Description |
boolean |
The createDefaultTableIfNotExists. |
getDefaultInstanceForType()
public BigQueryConfig getDefaultInstanceForType()| Returns | |
|---|---|
| Type | Description |
BigQueryConfig |
|
getDescriptorForType()
public Descriptors.Descriptor getDescriptorForType()| Returns | |
|---|---|
| Type | Description |
Descriptor |
|
getMutableCloudFunctionMapping() (deprecated)
public Map<String,String> getMutableCloudFunctionMapping()Use alternate mutation accessors instead.
| Returns | |
|---|---|
| Type | Description |
Map<String,String> |
|
getTable()
public String getTable()BigQuery table resource for Vision AI Platform to ingest annotations to.
string table = 1;
| Returns | |
|---|---|
| Type | Description |
String |
The table. |
getTableBytes()
public ByteString getTableBytes()BigQuery table resource for Vision AI Platform to ingest annotations to.
string table = 1;
| Returns | |
|---|---|
| Type | Description |
ByteString |
The bytes for table. |
internalGetFieldAccessorTable()
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()| Returns | |
|---|---|
| Type | Description |
FieldAccessorTable |
|
internalGetMapFieldReflection(int number)
protected MapFieldReflectionAccessor internalGetMapFieldReflection(int number)| Parameter | |
|---|---|
| Name | Description |
number |
int |
| Returns | |
|---|---|
| Type | Description |
com.google.protobuf.MapFieldReflectionAccessor |
|
internalGetMutableMapFieldReflection(int number)
protected MapFieldReflectionAccessor internalGetMutableMapFieldReflection(int number)| Parameter | |
|---|---|
| Name | Description |
number |
int |
| Returns | |
|---|---|
| Type | Description |
com.google.protobuf.MapFieldReflectionAccessor |
|
isInitialized()
public final boolean isInitialized()| Returns | |
|---|---|
| Type | Description |
boolean |
|
mergeFrom(BigQueryConfig other)
public BigQueryConfig.Builder mergeFrom(BigQueryConfig other)| Parameter | |
|---|---|
| Name | Description |
other |
BigQueryConfig |
| Returns | |
|---|---|
| Type | Description |
BigQueryConfig.Builder |
|
mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public BigQueryConfig.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)| Parameters | |
|---|---|
| Name | Description |
input |
CodedInputStream |
extensionRegistry |
ExtensionRegistryLite |
| Returns | |
|---|---|
| Type | Description |
BigQueryConfig.Builder |
|
| Exceptions | |
|---|---|
| Type | Description |
IOException |
|
mergeFrom(Message other)
public BigQueryConfig.Builder mergeFrom(Message other)| Parameter | |
|---|---|
| Name | Description |
other |
Message |
| Returns | |
|---|---|
| Type | Description |
BigQueryConfig.Builder |
|
mergeUnknownFields(UnknownFieldSet unknownFields)
public final BigQueryConfig.Builder mergeUnknownFields(UnknownFieldSet unknownFields)| Parameter | |
|---|---|
| Name | Description |
unknownFields |
UnknownFieldSet |
| Returns | |
|---|---|
| Type | Description |
BigQueryConfig.Builder |
|
putAllCloudFunctionMapping(Map<String,String> values)
public BigQueryConfig.Builder putAllCloudFunctionMapping(Map<String,String> values)Data Schema By default, Vision AI Application will try to write annotations to the target BigQuery table using the following schema:
ingestion_time: TIMESTAMP, the ingestion time of the original data.
application: STRING, name of the application which produces the annotation.
instance: STRING, Id of the instance which produces the annotation.
node: STRING, name of the application graph node which produces the annotation.
annotation: STRING or JSON, the actual annotation protobuf will be converted to json string with bytes field as 64 encoded string. It can be written to both String or Json type column.
To forward annotation data to an existing BigQuery table, customer needs to make sure the compatibility of the schema. The map maps application node name to its corresponding cloud function endpoint to transform the annotations directly to the google.cloud.bigquery.storage.v1.AppendRowsRequest (only avro_rows or proto_rows should be set). If configured, annotations produced by corresponding application node will sent to the Cloud Function at first before be forwarded to BigQuery.
If the default table schema doesn't fit, customer is able to transform the annotation output from Vision AI Application to arbitrary BigQuery table schema with CloudFunction.
- The cloud function will receive AppPlatformCloudFunctionRequest where the annotations field will be the json format of Vision AI annotation.
- The cloud function should return AppPlatformCloudFunctionResponse with AppendRowsRequest stored in the annotations field.
- To drop the annotation, simply clear the annotations field in the returned AppPlatformCloudFunctionResponse.
map<string, string> cloud_function_mapping = 2;
| Parameter | |
|---|---|
| Name | Description |
values |
Map<String,String> |
| Returns | |
|---|---|
| Type | Description |
BigQueryConfig.Builder |
|
putCloudFunctionMapping(String key, String value)
public BigQueryConfig.Builder putCloudFunctionMapping(String key, String value)Data Schema By default, Vision AI Application will try to write annotations to the target BigQuery table using the following schema:
ingestion_time: TIMESTAMP, the ingestion time of the original data.
application: STRING, name of the application which produces the annotation.
instance: STRING, Id of the instance which produces the annotation.
node: STRING, name of the application graph node which produces the annotation.
annotation: STRING or JSON, the actual annotation protobuf will be converted to json string with bytes field as 64 encoded string. It can be written to both String or Json type column.
To forward annotation data to an existing BigQuery table, customer needs to make sure the compatibility of the schema. The map maps application node name to its corresponding cloud function endpoint to transform the annotations directly to the google.cloud.bigquery.storage.v1.AppendRowsRequest (only avro_rows or proto_rows should be set). If configured, annotations produced by corresponding application node will sent to the Cloud Function at first before be forwarded to BigQuery.
If the default table schema doesn't fit, customer is able to transform the annotation output from Vision AI Application to arbitrary BigQuery table schema with CloudFunction.
- The cloud function will receive AppPlatformCloudFunctionRequest where the annotations field will be the json format of Vision AI annotation.
- The cloud function should return AppPlatformCloudFunctionResponse with AppendRowsRequest stored in the annotations field.
- To drop the annotation, simply clear the annotations field in the returned AppPlatformCloudFunctionResponse.
map<string, string> cloud_function_mapping = 2;
| Parameters | |
|---|---|
| Name | Description |
key |
String |
value |
String |
| Returns | |
|---|---|
| Type | Description |
BigQueryConfig.Builder |
|
removeCloudFunctionMapping(String key)
public BigQueryConfig.Builder removeCloudFunctionMapping(String key)Data Schema By default, Vision AI Application will try to write annotations to the target BigQuery table using the following schema:
ingestion_time: TIMESTAMP, the ingestion time of the original data.
application: STRING, name of the application which produces the annotation.
instance: STRING, Id of the instance which produces the annotation.
node: STRING, name of the application graph node which produces the annotation.
annotation: STRING or JSON, the actual annotation protobuf will be converted to json string with bytes field as 64 encoded string. It can be written to both String or Json type column.
To forward annotation data to an existing BigQuery table, customer needs to make sure the compatibility of the schema. The map maps application node name to its corresponding cloud function endpoint to transform the annotations directly to the google.cloud.bigquery.storage.v1.AppendRowsRequest (only avro_rows or proto_rows should be set). If configured, annotations produced by corresponding application node will sent to the Cloud Function at first before be forwarded to BigQuery.
If the default table schema doesn't fit, customer is able to transform the annotation output from Vision AI Application to arbitrary BigQuery table schema with CloudFunction.
- The cloud function will receive AppPlatformCloudFunctionRequest where the annotations field will be the json format of Vision AI annotation.
- The cloud function should return AppPlatformCloudFunctionResponse with AppendRowsRequest stored in the annotations field.
- To drop the annotation, simply clear the annotations field in the returned AppPlatformCloudFunctionResponse.
map<string, string> cloud_function_mapping = 2;
| Parameter | |
|---|---|
| Name | Description |
key |
String |
| Returns | |
|---|---|
| Type | Description |
BigQueryConfig.Builder |
|
setCreateDefaultTableIfNotExists(boolean value)
public BigQueryConfig.Builder setCreateDefaultTableIfNotExists(boolean value)If true, App Platform will create the BigQuery DataSet and the BigQuery Table with default schema if the specified table doesn't exist. This doesn't work if any cloud function customized schema is specified since the system doesn't know your desired schema. JSON column will be used in the default table created by App Platform.
bool create_default_table_if_not_exists = 3;
| Parameter | |
|---|---|
| Name | Description |
value |
booleanThe createDefaultTableIfNotExists to set. |
| Returns | |
|---|---|
| Type | Description |
BigQueryConfig.Builder |
This builder for chaining. |
setField(Descriptors.FieldDescriptor field, Object value)
public BigQueryConfig.Builder setField(Descriptors.FieldDescriptor field, Object value)| Parameters | |
|---|---|
| Name | Description |
field |
FieldDescriptor |
value |
Object |
| Returns | |
|---|---|
| Type | Description |
BigQueryConfig.Builder |
|
setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
public BigQueryConfig.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)| Parameters | |
|---|---|
| Name | Description |
field |
FieldDescriptor |
index |
int |
value |
Object |
| Returns | |
|---|---|
| Type | Description |
BigQueryConfig.Builder |
|
setTable(String value)
public BigQueryConfig.Builder setTable(String value)BigQuery table resource for Vision AI Platform to ingest annotations to.
string table = 1;
| Parameter | |
|---|---|
| Name | Description |
value |
StringThe table to set. |
| Returns | |
|---|---|
| Type | Description |
BigQueryConfig.Builder |
This builder for chaining. |
setTableBytes(ByteString value)
public BigQueryConfig.Builder setTableBytes(ByteString value)BigQuery table resource for Vision AI Platform to ingest annotations to.
string table = 1;
| Parameter | |
|---|---|
| Name | Description |
value |
ByteStringThe bytes for table to set. |
| Returns | |
|---|---|
| Type | Description |
BigQueryConfig.Builder |
This builder for chaining. |
setUnknownFields(UnknownFieldSet unknownFields)
public final BigQueryConfig.Builder setUnknownFields(UnknownFieldSet unknownFields)| Parameter | |
|---|---|
| Name | Description |
unknownFields |
UnknownFieldSet |
| Returns | |
|---|---|
| Type | Description |
BigQueryConfig.Builder |
|