pulumi-azure-native-kotlin/com.pulumi.azurenative.streamanalytics.kotlin/FunctionArgs

FunctionArgs

data class FunctionArgs(val functionName: Output<String>? = null, val jobName: Output<String>? = null, val name: Output<String>? = null, val properties: Output<ScalarFunctionPropertiesArgs>? = null, val resourceGroupName: Output<String>? = null) : ConvertibleToJava<FunctionArgs>

A function object, containing all information associated with the named function. All functions are contained under a streaming job. API Version: 2016-03-01.

Example Usage

Create a JavaScript function

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using AzureNative = Pulumi.AzureNative;
return await Deployment.RunAsync(() =>
{
    var function = new AzureNative.StreamAnalytics.Function("function", new()
    {
        FunctionName = "function8197",
        JobName = "sj8653",
        Properties = new AzureNative.StreamAnalytics.Inputs.ScalarFunctionPropertiesArgs
        {
            Binding = new AzureNative.StreamAnalytics.Inputs.JavaScriptFunctionBindingArgs
            {
                Script = "function (x, y) { return x + y; }",
                Type = "Microsoft.StreamAnalytics/JavascriptUdf",
            },
            Inputs = new[]
            {
                new AzureNative.StreamAnalytics.Inputs.FunctionInputArgs
                {
                    DataType = "Any",
                },
            },
            Output = new AzureNative.StreamAnalytics.Inputs.FunctionOutputArgs
            {
                DataType = "Any",
            },
            Type = "Scalar",
        },
        ResourceGroupName = "sjrg1637",
    });
});

package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.azurenative.streamanalytics.Function;
import com.pulumi.azurenative.streamanalytics.FunctionArgs;
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 function = new Function("function", FunctionArgs.builder()
            .functionName("function8197")
            .jobName("sj8653")
            .properties(Map.ofEntries(
                Map.entry("binding", Map.ofEntries(
                    Map.entry("script", "function (x, y) { return x + y; }"),
                    Map.entry("type", "Microsoft.StreamAnalytics/JavascriptUdf")
                )),
                Map.entry("inputs", Map.of("dataType", "Any")),
                Map.entry("output", Map.of("dataType", "Any")),
                Map.entry("type", "Scalar")
            ))
            .resourceGroupName("sjrg1637")
            .build());
    }
}

Create an Azure ML function

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using AzureNative = Pulumi.AzureNative;
return await Deployment.RunAsync(() =>
{
    var function = new AzureNative.StreamAnalytics.Function("function", new()
    {
        FunctionName = "function588",
        JobName = "sj9093",
        Properties = new AzureNative.StreamAnalytics.Inputs.ScalarFunctionPropertiesArgs
        {
            Binding = new AzureNative.StreamAnalytics.Inputs.AzureMachineLearningWebServiceFunctionBindingArgs
            {
                ApiKey = "someApiKey==",
                BatchSize = 1000,
                Endpoint = "someAzureMLEndpointURL",
                Inputs = new AzureNative.StreamAnalytics.Inputs.AzureMachineLearningWebServiceInputsArgs
                {
                    ColumnNames = new[]
                    {
                        new AzureNative.StreamAnalytics.Inputs.AzureMachineLearningWebServiceInputColumnArgs
                        {
                            DataType = "string",
                            MapTo = 0,
                            Name = "tweet",
                        },
                    },
                    Name = "input1",
                },
                Outputs = new[]
                {
                    new AzureNative.StreamAnalytics.Inputs.AzureMachineLearningWebServiceOutputColumnArgs
                    {
                        DataType = "string",
                        Name = "Sentiment",
                    },
                },
                Type = "Microsoft.MachineLearning/WebService",
            },
            Inputs = new[]
            {
                new AzureNative.StreamAnalytics.Inputs.FunctionInputArgs
                {
                    DataType = "nvarchar(max)",
                },
            },
            Output = new AzureNative.StreamAnalytics.Inputs.FunctionOutputArgs
            {
                DataType = "nvarchar(max)",
            },
            Type = "Scalar",
        },
        ResourceGroupName = "sjrg7",
    });
});

package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.azurenative.streamanalytics.Function;
import com.pulumi.azurenative.streamanalytics.FunctionArgs;
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 function = new Function("function", FunctionArgs.builder()
            .functionName("function588")
            .jobName("sj9093")
            .properties(Map.ofEntries(
                Map.entry("binding", Map.ofEntries(
                    Map.entry("apiKey", "someApiKey=="),
                    Map.entry("batchSize", 1000),
                    Map.entry("endpoint", "someAzureMLEndpointURL"),
                    Map.entry("inputs", Map.ofEntries(
                        Map.entry("columnNames", Map.ofEntries(
                            Map.entry("dataType", "string"),
                            Map.entry("mapTo", 0),
                            Map.entry("name", "tweet")
                        )),
                        Map.entry("name", "input1")
                    )),
                    Map.entry("outputs", Map.ofEntries(
                        Map.entry("dataType", "string"),
                        Map.entry("name", "Sentiment")
                    )),
                    Map.entry("type", "Microsoft.MachineLearning/WebService")
                )),
                Map.entry("inputs", Map.of("dataType", "nvarchar(max)")),
                Map.entry("output", Map.of("dataType", "nvarchar(max)")),
                Map.entry("type", "Scalar")
            ))
            .resourceGroupName("sjrg7")
            .build());
    }
}

Import

An existing resource can be imported using its type token, name, and identifier, e.g.

$ pulumi import azure-native:streamanalytics:Function function588 /subscriptions/56b5e0a9-b645-407d-99b0-c64f86013e3d/resourceGroups/sjrg7/providers/Microsoft.StreamAnalytics/streamingjobs/sj9093/functions/function588

Constructors

FunctionArgs

constructor(functionName: Output<String>? = null, jobName: Output<String>? = null, name: Output<String>? = null, properties: Output<ScalarFunctionPropertiesArgs>? = null, resourceGroupName: Output<String>? = null)