Routine
A user-defined function or a stored procedure that belongs to a Dataset To get more information about Routine, see:
How-to Guides
Example Usage
Big Query Routine Basic
package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.bigquery.Dataset;
import com.pulumi.gcp.bigquery.DatasetArgs;
import com.pulumi.gcp.bigquery.Routine;
import com.pulumi.gcp.bigquery.RoutineArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;
public class App {
public static void main(String[] args) {
Pulumi.run(App::stack);
}
public static void stack(Context ctx) {
var test = new Dataset("test", DatasetArgs.builder()
.datasetId("dataset_id")
.build());
var sproc = new Routine("sproc", RoutineArgs.builder()
.datasetId(test.datasetId())
.routineId("routine_id")
.routineType("PROCEDURE")
.language("SQL")
.definitionBody("CREATE FUNCTION Add(x FLOAT64, y FLOAT64) RETURNS FLOAT64 AS (x + y);")
.build());
}
}Big Query Routine Json
package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.bigquery.Dataset;
import com.pulumi.gcp.bigquery.DatasetArgs;
import com.pulumi.gcp.bigquery.Routine;
import com.pulumi.gcp.bigquery.RoutineArgs;
import com.pulumi.gcp.bigquery.inputs.RoutineArgumentArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;
public class App {
public static void main(String[] args) {
Pulumi.run(App::stack);
}
public static void stack(Context ctx) {
var test = new Dataset("test", DatasetArgs.builder()
.datasetId("dataset_id")
.build());
var sproc = new Routine("sproc", RoutineArgs.builder()
.datasetId(test.datasetId())
.routineId("routine_id")
.routineType("SCALAR_FUNCTION")
.language("JAVASCRIPT")
.definitionBody("CREATE FUNCTION multiplyInputs return x*y;")
.arguments(
RoutineArgumentArgs.builder()
.name("x")
.dataType("{\"typeKind\" : \"FLOAT64\"}")
.build(),
RoutineArgumentArgs.builder()
.name("y")
.dataType("{\"typeKind\" : \"FLOAT64\"}")
.build())
.returnType("{\"typeKind\" : \"FLOAT64\"}")
.build());
}
}Big Query Routine Tvf
package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.bigquery.Dataset;
import com.pulumi.gcp.bigquery.DatasetArgs;
import com.pulumi.gcp.bigquery.Routine;
import com.pulumi.gcp.bigquery.RoutineArgs;
import com.pulumi.gcp.bigquery.inputs.RoutineArgumentArgs;
import static com.pulumi.codegen.internal.Serialization.*;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;
public class App {
public static void main(String[] args) {
Pulumi.run(App::stack);
}
public static void stack(Context ctx) {
var test = new Dataset("test", DatasetArgs.builder()
.datasetId("dataset_id")
.build());
var sproc = new Routine("sproc", RoutineArgs.builder()
.datasetId(test.datasetId())
.routineId("routine_id")
.routineType("TABLE_VALUED_FUNCTION")
.language("SQL")
.definitionBody("""
SELECT 1 + value AS value
""")
.arguments(RoutineArgumentArgs.builder()
.name("value")
.argumentKind("FIXED_TYPE")
.dataType(serializeJson(
jsonObject(
jsonProperty("typeKind", "INT64")
)))
.build())
.returnTableType(serializeJson(
jsonObject(
jsonProperty("columns", jsonArray(jsonObject(
jsonProperty("name", "value"),
jsonProperty("type", jsonObject(
jsonProperty("typeKind", "INT64")
))
)))
)))
.build());
}
}Import
Routine can be imported using any of these accepted formats
$ pulumi import gcp:bigquery/routine:Routine default projects/{{project}}/datasets/{{dataset_id}}/routines/{{routine_id}}$ pulumi import gcp:bigquery/routine:Routine default {{project}}/{{dataset_id}}/{{routine_id}}$ pulumi import gcp:bigquery/routine:Routine default {{dataset_id}}/{{routine_id}}Constructors
Properties
Input/output argument of a function or a stored procedure. Structure is documented below.
The body of the routine. For functions, this is the expression in the AS clause. If language=SQL, it is the substring inside (but excluding) the parentheses.
The description of the routine if defined.
The determinism level of the JavaScript UDF if defined. Possible values are: DETERMINISM_LEVEL_UNSPECIFIED, DETERMINISTIC, NOT_DETERMINISTIC.
Optional. If language = "JAVASCRIPT", this field stores the path of the imported JAVASCRIPT libraries.
Optional. Can be set only if routineType = "TABLE_VALUED_FUNCTION". If absent, the return table type is inferred from definitionBody at query time in each query that references this routine. If present, then the columns in the evaluated table result will be cast to match the column types specificed in return table type, at query time.
A JSON schema for the return type. Optional if language = "SQL"; required otherwise. If absent, the return type is inferred from definitionBody at query time in each query that references this routine. If present, then the evaluated result will be cast to the specified returned type at query time. ~>NOTE: Because this field expects a JSON string, any changes to the string will create a diff, even if the JSON itself hasn't changed. If the API returns a different value for the same schema, e.g. it switche d the order of values or replaced STRUCT field type with RECORD field type, we currently cannot suppress the recurring diff this causes. As a workaround, we recommend using the schema as returned by the API.
The type of routine. Possible values are: SCALAR_FUNCTION, PROCEDURE, TABLE_VALUED_FUNCTION.