public static final class BigQueryConfig.Builder extends GeneratedMessageV3.Builder<BigQueryConfig.Builder> implements BigQueryConfigOrBuilder
Message of configurations for BigQuery processor.
Protobuf type google.events.cloud.visionai.v1.BigQueryConfig
Inherited Members
com.google.protobuf.GeneratedMessageV3.Builder.getUnknownFieldSetBuilder()
com.google.protobuf.GeneratedMessageV3.Builder.internalGetMapFieldReflection(int)
com.google.protobuf.GeneratedMessageV3.Builder.internalGetMutableMapFieldReflection(int)
com.google.protobuf.GeneratedMessageV3.Builder.mergeUnknownLengthDelimitedField(int,com.google.protobuf.ByteString)
com.google.protobuf.GeneratedMessageV3.Builder.mergeUnknownVarintField(int,int)
com.google.protobuf.GeneratedMessageV3.Builder.parseUnknownField(com.google.protobuf.CodedInputStream,com.google.protobuf.ExtensionRegistryLite,int)
com.google.protobuf.GeneratedMessageV3.Builder.setUnknownFieldSetBuilder(com.google.protobuf.UnknownFieldSet.Builder)
Static Methods
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()
Methods
addRepeatedField(Descriptors.FieldDescriptor field, Object value)
public BigQueryConfig.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Overrides
build()
public BigQueryConfig build()
buildPartial()
public BigQueryConfig buildPartial()
clear()
public BigQueryConfig.Builder clear()
Overrides
clearCloudFunctionMapping()
public BigQueryConfig.Builder clearCloudFunctionMapping()
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;
clearField(Descriptors.FieldDescriptor field)
public BigQueryConfig.Builder clearField(Descriptors.FieldDescriptor field)
Overrides
clearOneof(Descriptors.OneofDescriptor oneof)
public BigQueryConfig.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Overrides
clearTable()
public BigQueryConfig.Builder clearTable()
BigQuery table resource for Vision AI Platform to ingest annotations to.
string table = 1;
clone()
public BigQueryConfig.Builder clone()
Overrides
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
|
getCloudFunctionMapping()
public Map<String,String> getCloudFunctionMapping()
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;
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;
| 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()
getDescriptorForType()
public Descriptors.Descriptor getDescriptorForType()
Overrides
getMutableCloudFunctionMapping()
public Map<String,String> getMutableCloudFunctionMapping()
Use alternate mutation accessors instead.
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()
Overrides
internalGetMapField(int number)
protected MapField internalGetMapField(int number)
| Parameter |
| Name |
Description |
number |
int
|
Overrides
internalGetMutableMapField(int number)
protected MapField internalGetMutableMapField(int number)
| Parameter |
| Name |
Description |
number |
int
|
Overrides
isInitialized()
public final boolean isInitialized()
Overrides
mergeFrom(BigQueryConfig other)
public BigQueryConfig.Builder mergeFrom(BigQueryConfig other)
public BigQueryConfig.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Overrides
mergeFrom(Message other)
public BigQueryConfig.Builder mergeFrom(Message other)
| Parameter |
| Name |
Description |
other |
Message
|
Overrides
mergeUnknownFields(UnknownFieldSet unknownFields)
public final BigQueryConfig.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Overrides
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;
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;
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
|
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 |
boolean
The createDefaultTableIfNotExists to set.
|
setField(Descriptors.FieldDescriptor field, Object value)
public BigQueryConfig.Builder setField(Descriptors.FieldDescriptor field, Object value)
Overrides
setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
public BigQueryConfig.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
Overrides
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 |
String
The table to set.
|
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 |
ByteString
The bytes for table to set.
|
setUnknownFields(UnknownFieldSet unknownFields)
public final BigQueryConfig.Builder setUnknownFields(UnknownFieldSet unknownFields)
Overrides
