import * as pulumi from "@pulumi/pulumi";
import * as inputs from "../types/input";
import * as outputs from "../types/output";
/**
 * A user-defined function or a stored procedure that belongs to a Dataset
 *
 * To get more information about Routine, see:
 *
 * * [API documentation](https://cloud.google.com/bigquery/docs/reference/rest/v2/routines)
 * * How-to Guides
 *     * [Routines Intro](https://cloud.google.com/bigquery/docs/reference/rest/v2/routines)
 *
 * ## Example Usage
 *
 * ### Bigquery Routine Basic
 *
 * ```typescript
 * import * as pulumi from "@pulumi/pulumi";
 * import * as gcp from "@pulumi/gcp";
 *
 * const test = new gcp.bigquery.Dataset("test", {datasetId: "dataset_id"});
 * const sproc = new gcp.bigquery.Routine("sproc", {
 *     datasetId: test.datasetId,
 *     routineId: "routine_id",
 *     routineType: "PROCEDURE",
 *     language: "SQL",
 *     securityMode: "INVOKER",
 *     definitionBody: "CREATE FUNCTION Add(x FLOAT64, y FLOAT64) RETURNS FLOAT64 AS (x + y);",
 * });
 * ```
 * ### Bigquery Routine Json
 *
 * ```typescript
 * import * as pulumi from "@pulumi/pulumi";
 * import * as gcp from "@pulumi/gcp";
 *
 * const test = new gcp.bigquery.Dataset("test", {datasetId: "dataset_id"});
 * const sproc = new gcp.bigquery.Routine("sproc", {
 *     datasetId: test.datasetId,
 *     routineId: "routine_id",
 *     routineType: "SCALAR_FUNCTION",
 *     language: "JAVASCRIPT",
 *     definitionBody: "CREATE FUNCTION multiplyInputs return x*y;",
 *     arguments: [
 *         {
 *             name: "x",
 *             dataType: "{\"typeKind\" :  \"FLOAT64\"}",
 *         },
 *         {
 *             name: "y",
 *             dataType: "{\"typeKind\" :  \"FLOAT64\"}",
 *         },
 *     ],
 *     returnType: "{\"typeKind\" :  \"FLOAT64\"}",
 * });
 * ```
 * ### Bigquery Routine Tvf
 *
 * ```typescript
 * import * as pulumi from "@pulumi/pulumi";
 * import * as gcp from "@pulumi/gcp";
 *
 * const test = new gcp.bigquery.Dataset("test", {datasetId: "dataset_id"});
 * const sproc = new gcp.bigquery.Routine("sproc", {
 *     datasetId: test.datasetId,
 *     routineId: "routine_id",
 *     routineType: "TABLE_VALUED_FUNCTION",
 *     language: "SQL",
 *     definitionBody: "SELECT 1 + value AS value\n",
 *     arguments: [{
 *         name: "value",
 *         argumentKind: "FIXED_TYPE",
 *         dataType: JSON.stringify({
 *             typeKind: "INT64",
 *         }),
 *     }],
 *     returnTableType: JSON.stringify({
 *         columns: [{
 *             name: "value",
 *             type: {
 *                 typeKind: "INT64",
 *             },
 *         }],
 *     }),
 * });
 * ```
 * ### Bigquery Routine Pyspark
 *
 * ```typescript
 * import * as pulumi from "@pulumi/pulumi";
 * import * as gcp from "@pulumi/gcp";
 *
 * const test = new gcp.bigquery.Dataset("test", {datasetId: "dataset_id"});
 * const testConnection = new gcp.bigquery.Connection("test", {
 *     connectionId: "connection_id",
 *     location: "US",
 *     spark: {},
 * });
 * const pyspark = new gcp.bigquery.Routine("pyspark", {
 *     datasetId: test.datasetId,
 *     routineId: "routine_id",
 *     routineType: "PROCEDURE",
 *     language: "PYTHON",
 *     definitionBody: `from pyspark.sql import SparkSession
 *
 * spark = SparkSession.builder.appName(\\"spark-bigquery-demo\\").getOrCreate()
 *
 * # Load data from BigQuery.
 * words = spark.read.format(\\"bigquery\\") \\\\
 *   .option(\\"table\\", \\"bigquery-public-data:samples.shakespeare\\") \\\\
 *   .load()
 * words.createOrReplaceTempView(\\"words\\")
 *
 * # Perform word count.
 * word_count = words.select('word', 'word_count').groupBy('word').sum('word_count').withColumnRenamed(\\"sum(word_count)\\", \\"sum_word_count\\")
 * word_count.show()
 * word_count.printSchema()
 *
 * # Saving the data to BigQuery
 * word_count.write.format(\\"bigquery\\") \\\\
 *   .option(\\"writeMethod\\", \\"direct\\") \\\\
 *   .save(\\"wordcount_dataset.wordcount_output\\")
 * `,
 *     sparkOptions: {
 *         connection: testConnection.name,
 *         runtimeVersion: "2.1",
 *     },
 * });
 * ```
 * ### Bigquery Routine Pyspark Mainfile
 *
 * ```typescript
 * import * as pulumi from "@pulumi/pulumi";
 * import * as gcp from "@pulumi/gcp";
 *
 * const test = new gcp.bigquery.Dataset("test", {datasetId: "dataset_id"});
 * const testConnection = new gcp.bigquery.Connection("test", {
 *     connectionId: "connection_id",
 *     location: "US",
 *     spark: {},
 * });
 * const pysparkMainfile = new gcp.bigquery.Routine("pyspark_mainfile", {
 *     datasetId: test.datasetId,
 *     routineId: "routine_id",
 *     routineType: "PROCEDURE",
 *     language: "PYTHON",
 *     definitionBody: "",
 *     sparkOptions: {
 *         connection: testConnection.name,
 *         runtimeVersion: "2.1",
 *         mainFileUri: "gs://test-bucket/main.py",
 *         pyFileUris: ["gs://test-bucket/lib.py"],
 *         fileUris: ["gs://test-bucket/distribute_in_executor.json"],
 *         archiveUris: ["gs://test-bucket/distribute_in_executor.tar.gz"],
 *     },
 * });
 * ```
 * ### Bigquery Routine Spark Jar
 *
 * ```typescript
 * import * as pulumi from "@pulumi/pulumi";
 * import * as gcp from "@pulumi/gcp";
 *
 * const test = new gcp.bigquery.Dataset("test", {datasetId: "dataset_id"});
 * const testConnection = new gcp.bigquery.Connection("test", {
 *     connectionId: "connection_id",
 *     location: "US",
 *     spark: {},
 * });
 * const sparkJar = new gcp.bigquery.Routine("spark_jar", {
 *     datasetId: test.datasetId,
 *     routineId: "routine_id",
 *     routineType: "PROCEDURE",
 *     language: "SCALA",
 *     definitionBody: "",
 *     sparkOptions: {
 *         connection: testConnection.name,
 *         runtimeVersion: "2.1",
 *         containerImage: "gcr.io/my-project-id/my-spark-image:latest",
 *         mainClass: "com.google.test.jar.MainClass",
 *         jarUris: ["gs://test-bucket/uberjar_spark_spark3.jar"],
 *         properties: {
 *             "spark.dataproc.scaling.version": "2",
 *             "spark.reducer.fetchMigratedShuffle.enabled": "true",
 *         },
 *     },
 * });
 * ```
 * ### Bigquery Routine Data Governance Type
 *
 * ```typescript
 * import * as pulumi from "@pulumi/pulumi";
 * import * as gcp from "@pulumi/gcp";
 *
 * const test = new gcp.bigquery.Dataset("test", {datasetId: "tf_test_dataset_id_81126"});
 * const customMaskingRoutine = new gcp.bigquery.Routine("custom_masking_routine", {
 *     datasetId: test.datasetId,
 *     routineId: "custom_masking_routine",
 *     routineType: "SCALAR_FUNCTION",
 *     language: "SQL",
 *     dataGovernanceType: "DATA_MASKING",
 *     definitionBody: "SAFE.REGEXP_REPLACE(ssn, '[0-9]', 'X')",
 *     arguments: [{
 *         name: "ssn",
 *         dataType: "{\"typeKind\" :  \"STRING\"}",
 *     }],
 *     returnType: "{\"typeKind\" :  \"STRING\"}",
 * });
 * ```
 * ### Bigquery Routine Remote Function
 *
 * ```typescript
 * import * as pulumi from "@pulumi/pulumi";
 * import * as gcp from "@pulumi/gcp";
 *
 * const test = new gcp.bigquery.Dataset("test", {datasetId: "dataset_id"});
 * const testConnection = new gcp.bigquery.Connection("test", {
 *     connectionId: "connection_id",
 *     location: "US",
 *     cloudResource: {},
 * });
 * const remoteFunction = new gcp.bigquery.Routine("remote_function", {
 *     datasetId: test.datasetId,
 *     routineId: "routine_id",
 *     routineType: "SCALAR_FUNCTION",
 *     definitionBody: "",
 *     returnType: "{\"typeKind\" :  \"STRING\"}",
 *     remoteFunctionOptions: {
 *         endpoint: "https://us-east1-my_gcf_project.cloudfunctions.net/remote_add",
 *         connection: testConnection.name,
 *         maxBatchingRows: "10",
 *         userDefinedContext: {
 *             z: "1.5",
 *         },
 *     },
 * });
 * ```
 * ### Bigquery Routine Python Function
 *
 * ```typescript
 * import * as pulumi from "@pulumi/pulumi";
 * import * as gcp from "@pulumi/gcp";
 *
 * const test = new gcp.bigquery.Dataset("test", {datasetId: "dataset_id"});
 * const pythonFunction = new gcp.bigquery.Routine("python_function", {
 *     datasetId: test.datasetId,
 *     routineId: "routine_id",
 *     routineType: "SCALAR_FUNCTION",
 *     language: "PYTHON",
 *     arguments: [
 *         {
 *             name: "x",
 *             dataType: "{\"typeKind\" :  \"FLOAT64\"}",
 *         },
 *         {
 *             name: "y",
 *             dataType: "{\"typeKind\" :  \"FLOAT64\"}",
 *         },
 *     ],
 *     definitionBody: `def multiply(x, y):
 *   return x * y
 * `,
 *     returnType: "{\"typeKind\" :  \"FLOAT64\"}",
 *     pythonOptions: {
 *         entryPoint: "multiply",
 *     },
 *     externalRuntimeOptions: {
 *         containerMemory: "512Mi",
 *         containerCpu: 0.5,
 *         runtimeVersion: "python-3.11",
 *     },
 * });
 * ```
 *
 * ## Import
 *
 * Routine can be imported using any of these accepted formats:
 *
 * * `projects/{{project}}/datasets/{{dataset_id}}/routines/{{routine_id}}`
 *
 * * `{{project}}/{{dataset_id}}/{{routine_id}}`
 *
 * * `{{dataset_id}}/{{routine_id}}`
 *
 * When using the `pulumi import` command, Routine can be imported using one of the formats above. For example:
 *
 * ```sh
 * $ pulumi import gcp:bigquery/routine:Routine default projects/{{project}}/datasets/{{dataset_id}}/routines/{{routine_id}}
 * ```
 *
 * ```sh
 * $ pulumi import gcp:bigquery/routine:Routine default {{project}}/{{dataset_id}}/{{routine_id}}
 * ```
 *
 * ```sh
 * $ pulumi import gcp:bigquery/routine:Routine default {{dataset_id}}/{{routine_id}}
 * ```
 */
export declare class Routine extends pulumi.CustomResource {
    /**
     * Get an existing Routine resource's state with the given name, ID, and optional extra
     * properties used to qualify the lookup.
     *
     * @param name The _unique_ name of the resulting resource.
     * @param id The _unique_ provider ID of the resource to lookup.
     * @param state Any extra arguments used during the lookup.
     * @param opts Optional settings to control the behavior of the CustomResource.
     */
    static get(name: string, id: pulumi.Input<pulumi.ID>, state?: RoutineState, opts?: pulumi.CustomResourceOptions): Routine;
    /**
     * Returns true if the given object is an instance of Routine.  This is designed to work even
     * when multiple copies of the Pulumi SDK have been loaded into the same process.
     */
    static isInstance(obj: any): obj is Routine;
    /**
     * Input/output argument of a function or a stored procedure.
     * Structure is documented below.
     */
    readonly arguments: pulumi.Output<outputs.bigquery.RoutineArgument[] | undefined>;
    /**
     * The time when this routine was created, in milliseconds since the
     * epoch.
     */
    readonly creationTime: pulumi.Output<number>;
    /**
     * If set to DATA_MASKING, the function is validated and made available as a masking function. For more information, see https://cloud.google.com/bigquery/docs/user-defined-functions#custom-mask
     * Possible values are: `DATA_MASKING`.
     */
    readonly dataGovernanceType: pulumi.Output<string | undefined>;
    /**
     * The ID of the dataset containing this routine
     */
    readonly datasetId: pulumi.Output<string>;
    /**
     * 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.
     */
    readonly definitionBody: pulumi.Output<string>;
    /**
     * The description of the routine if defined.
     */
    readonly description: pulumi.Output<string | undefined>;
    /**
     * The determinism level of the JavaScript UDF if defined.
     * Possible values are: `DETERMINISM_LEVEL_UNSPECIFIED`, `DETERMINISTIC`, `NOT_DETERMINISTIC`.
     */
    readonly determinismLevel: pulumi.Output<string | undefined>;
    /**
     * Options for the runtime of the external system.
     * This field is only applicable for Python UDFs.
     * Structure is documented below.
     */
    readonly externalRuntimeOptions: pulumi.Output<outputs.bigquery.RoutineExternalRuntimeOptions | undefined>;
    /**
     * Optional. If language = "JAVASCRIPT", this field stores the path of the
     * imported JAVASCRIPT libraries.
     */
    readonly importedLibraries: pulumi.Output<string[] | undefined>;
    /**
     * The language of the routine.
     * Possible values are: `SQL`, `JAVASCRIPT`, `PYTHON`, `JAVA`, `SCALA`.
     */
    readonly language: pulumi.Output<string | undefined>;
    /**
     * The time when this routine was modified, in milliseconds since the
     * epoch.
     */
    readonly lastModifiedTime: pulumi.Output<number>;
    /**
     * The ID of the project in which the resource belongs.
     * If it is not provided, the provider project is used.
     */
    readonly project: pulumi.Output<string>;
    /**
     * Options for a user-defined Python function.
     * Structure is documented below.
     */
    readonly pythonOptions: pulumi.Output<outputs.bigquery.RoutinePythonOptions | undefined>;
    /**
     * Remote function specific options.
     * Structure is documented below.
     */
    readonly remoteFunctionOptions: pulumi.Output<outputs.bigquery.RoutineRemoteFunctionOptions | undefined>;
    /**
     * 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.
     */
    readonly returnTableType: pulumi.Output<string | undefined>;
    /**
     * 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.
     */
    readonly returnType: pulumi.Output<string | undefined>;
    /**
     * The ID of the the routine. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters.
     */
    readonly routineId: pulumi.Output<string>;
    /**
     * The type of routine.
     * Possible values are: `SCALAR_FUNCTION`, `PROCEDURE`, `TABLE_VALUED_FUNCTION`.
     */
    readonly routineType: pulumi.Output<string>;
    /**
     * Optional. The security mode of the routine, if defined. If not defined, the security mode is automatically determined from the routine's configuration.
     * Possible values are: `DEFINER`, `INVOKER`.
     */
    readonly securityMode: pulumi.Output<string | undefined>;
    /**
     * Optional. If language is one of "PYTHON", "JAVA", "SCALA", this field stores the options for spark stored procedure.
     * Structure is documented below.
     */
    readonly sparkOptions: pulumi.Output<outputs.bigquery.RoutineSparkOptions | undefined>;
    /**
     * Create a Routine resource with the given unique name, arguments, and options.
     *
     * @param name The _unique_ name of the resource.
     * @param args The arguments to use to populate this resource's properties.
     * @param opts A bag of options that control this resource's behavior.
     */
    constructor(name: string, args: RoutineArgs, opts?: pulumi.CustomResourceOptions);
}
/**
 * Input properties used for looking up and filtering Routine resources.
 */
export interface RoutineState {
    /**
     * Input/output argument of a function or a stored procedure.
     * Structure is documented below.
     */
    arguments?: pulumi.Input<pulumi.Input<inputs.bigquery.RoutineArgument>[]>;
    /**
     * The time when this routine was created, in milliseconds since the
     * epoch.
     */
    creationTime?: pulumi.Input<number>;
    /**
     * If set to DATA_MASKING, the function is validated and made available as a masking function. For more information, see https://cloud.google.com/bigquery/docs/user-defined-functions#custom-mask
     * Possible values are: `DATA_MASKING`.
     */
    dataGovernanceType?: pulumi.Input<string>;
    /**
     * The ID of the dataset containing this routine
     */
    datasetId?: pulumi.Input<string>;
    /**
     * 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.
     */
    definitionBody?: pulumi.Input<string>;
    /**
     * The description of the routine if defined.
     */
    description?: pulumi.Input<string>;
    /**
     * The determinism level of the JavaScript UDF if defined.
     * Possible values are: `DETERMINISM_LEVEL_UNSPECIFIED`, `DETERMINISTIC`, `NOT_DETERMINISTIC`.
     */
    determinismLevel?: pulumi.Input<string>;
    /**
     * Options for the runtime of the external system.
     * This field is only applicable for Python UDFs.
     * Structure is documented below.
     */
    externalRuntimeOptions?: pulumi.Input<inputs.bigquery.RoutineExternalRuntimeOptions>;
    /**
     * Optional. If language = "JAVASCRIPT", this field stores the path of the
     * imported JAVASCRIPT libraries.
     */
    importedLibraries?: pulumi.Input<pulumi.Input<string>[]>;
    /**
     * The language of the routine.
     * Possible values are: `SQL`, `JAVASCRIPT`, `PYTHON`, `JAVA`, `SCALA`.
     */
    language?: pulumi.Input<string>;
    /**
     * The time when this routine was modified, in milliseconds since the
     * epoch.
     */
    lastModifiedTime?: pulumi.Input<number>;
    /**
     * The ID of the project in which the resource belongs.
     * If it is not provided, the provider project is used.
     */
    project?: pulumi.Input<string>;
    /**
     * Options for a user-defined Python function.
     * Structure is documented below.
     */
    pythonOptions?: pulumi.Input<inputs.bigquery.RoutinePythonOptions>;
    /**
     * Remote function specific options.
     * Structure is documented below.
     */
    remoteFunctionOptions?: pulumi.Input<inputs.bigquery.RoutineRemoteFunctionOptions>;
    /**
     * 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.
     */
    returnTableType?: pulumi.Input<string>;
    /**
     * 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.
     */
    returnType?: pulumi.Input<string>;
    /**
     * The ID of the the routine. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters.
     */
    routineId?: pulumi.Input<string>;
    /**
     * The type of routine.
     * Possible values are: `SCALAR_FUNCTION`, `PROCEDURE`, `TABLE_VALUED_FUNCTION`.
     */
    routineType?: pulumi.Input<string>;
    /**
     * Optional. The security mode of the routine, if defined. If not defined, the security mode is automatically determined from the routine's configuration.
     * Possible values are: `DEFINER`, `INVOKER`.
     */
    securityMode?: pulumi.Input<string>;
    /**
     * Optional. If language is one of "PYTHON", "JAVA", "SCALA", this field stores the options for spark stored procedure.
     * Structure is documented below.
     */
    sparkOptions?: pulumi.Input<inputs.bigquery.RoutineSparkOptions>;
}
/**
 * The set of arguments for constructing a Routine resource.
 */
export interface RoutineArgs {
    /**
     * Input/output argument of a function or a stored procedure.
     * Structure is documented below.
     */
    arguments?: pulumi.Input<pulumi.Input<inputs.bigquery.RoutineArgument>[]>;
    /**
     * If set to DATA_MASKING, the function is validated and made available as a masking function. For more information, see https://cloud.google.com/bigquery/docs/user-defined-functions#custom-mask
     * Possible values are: `DATA_MASKING`.
     */
    dataGovernanceType?: pulumi.Input<string>;
    /**
     * The ID of the dataset containing this routine
     */
    datasetId: pulumi.Input<string>;
    /**
     * 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.
     */
    definitionBody: pulumi.Input<string>;
    /**
     * The description of the routine if defined.
     */
    description?: pulumi.Input<string>;
    /**
     * The determinism level of the JavaScript UDF if defined.
     * Possible values are: `DETERMINISM_LEVEL_UNSPECIFIED`, `DETERMINISTIC`, `NOT_DETERMINISTIC`.
     */
    determinismLevel?: pulumi.Input<string>;
    /**
     * Options for the runtime of the external system.
     * This field is only applicable for Python UDFs.
     * Structure is documented below.
     */
    externalRuntimeOptions?: pulumi.Input<inputs.bigquery.RoutineExternalRuntimeOptions>;
    /**
     * Optional. If language = "JAVASCRIPT", this field stores the path of the
     * imported JAVASCRIPT libraries.
     */
    importedLibraries?: pulumi.Input<pulumi.Input<string>[]>;
    /**
     * The language of the routine.
     * Possible values are: `SQL`, `JAVASCRIPT`, `PYTHON`, `JAVA`, `SCALA`.
     */
    language?: pulumi.Input<string>;
    /**
     * The ID of the project in which the resource belongs.
     * If it is not provided, the provider project is used.
     */
    project?: pulumi.Input<string>;
    /**
     * Options for a user-defined Python function.
     * Structure is documented below.
     */
    pythonOptions?: pulumi.Input<inputs.bigquery.RoutinePythonOptions>;
    /**
     * Remote function specific options.
     * Structure is documented below.
     */
    remoteFunctionOptions?: pulumi.Input<inputs.bigquery.RoutineRemoteFunctionOptions>;
    /**
     * 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.
     */
    returnTableType?: pulumi.Input<string>;
    /**
     * 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.
     */
    returnType?: pulumi.Input<string>;
    /**
     * The ID of the the routine. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters.
     */
    routineId: pulumi.Input<string>;
    /**
     * The type of routine.
     * Possible values are: `SCALAR_FUNCTION`, `PROCEDURE`, `TABLE_VALUED_FUNCTION`.
     */
    routineType: pulumi.Input<string>;
    /**
     * Optional. The security mode of the routine, if defined. If not defined, the security mode is automatically determined from the routine's configuration.
     * Possible values are: `DEFINER`, `INVOKER`.
     */
    securityMode?: pulumi.Input<string>;
    /**
     * Optional. If language is one of "PYTHON", "JAVA", "SCALA", this field stores the options for spark stored procedure.
     * Structure is documented below.
     */
    sparkOptions?: pulumi.Input<inputs.bigquery.RoutineSparkOptions>;
}
