Package software.amazon.awscdk.services.kinesisanalytics

Class CfnApplication

java.lang.Object
software.amazon.jsii.JsiiObject
software.constructs.Construct
software.amazon.awscdk.core.Construct
software.amazon.awscdk.core.CfnElement
software.amazon.awscdk.core.CfnRefElement
software.amazon.awscdk.core.CfnResource
software.amazon.awscdk.services.kinesisanalytics.CfnApplication
All Implemented Interfaces:
IConstruct, IDependable, IInspectable, software.amazon.jsii.JsiiSerializable, software.constructs.IConstruct
@Generated(value="jsii-pacmak/1.84.0 (build 5404dcf)", date="2023-06-19T16:29:58.194Z") @Stability(Stable) public class CfnApplication extends CfnResource implements IInspectable
A CloudFormation AWS::KinesisAnalytics::Application.

The AWS::KinesisAnalytics::Application resource creates an Amazon Kinesis Data Analytics application. For more information, see the Amazon Kinesis Data Analytics Developer Guide .

Example: 

 // The code below shows an example of how to instantiate this type.
 // The values are placeholders you should change.
 import software.amazon.awscdk.services.kinesisanalytics.*;
 CfnApplication cfnApplication = CfnApplication.Builder.create(this, "MyCfnApplication")
         .inputs(List.of(InputProperty.builder()
                 .inputSchema(InputSchemaProperty.builder()
                         .recordColumns(List.of(RecordColumnProperty.builder()
                                 .name("name")
                                 .sqlType("sqlType")
                                 // the properties below are optional
                                 .mapping("mapping")
                                 .build()))
                         .recordFormat(RecordFormatProperty.builder()
                                 .recordFormatType("recordFormatType")
                                 // the properties below are optional
                                 .mappingParameters(MappingParametersProperty.builder()
                                         .csvMappingParameters(CSVMappingParametersProperty.builder()
                                                 .recordColumnDelimiter("recordColumnDelimiter")
                                                 .recordRowDelimiter("recordRowDelimiter")
                                                 .build())
                                         .jsonMappingParameters(JSONMappingParametersProperty.builder()
                                                 .recordRowPath("recordRowPath")
                                                 .build())
                                         .build())
                                 .build())
                         // the properties below are optional
                         .recordEncoding("recordEncoding")
                         .build())
                 .namePrefix("namePrefix")
                 // the properties below are optional
                 .inputParallelism(InputParallelismProperty.builder()
                         .count(123)
                         .build())
                 .inputProcessingConfiguration(InputProcessingConfigurationProperty.builder()
                         .inputLambdaProcessor(InputLambdaProcessorProperty.builder()
                                 .resourceArn("resourceArn")
                                 .roleArn("roleArn")
                                 .build())
                         .build())
                 .kinesisFirehoseInput(KinesisFirehoseInputProperty.builder()
                         .resourceArn("resourceArn")
                         .roleArn("roleArn")
                         .build())
                 .kinesisStreamsInput(KinesisStreamsInputProperty.builder()
                         .resourceArn("resourceArn")
                         .roleArn("roleArn")
                         .build())
                 .build()))
         // the properties below are optional
         .applicationCode("applicationCode")
         .applicationDescription("applicationDescription")
         .applicationName("applicationName")
         .build();

  • Field Details

    • CFN_RESOURCE_TYPE_NAME

      @Stability(Stable) public static final String CFN_RESOURCE_TYPE_NAME
      The CloudFormation resource type name for this resource class.

  • Constructor Details

    • CfnApplication

      protected CfnApplication(software.amazon.jsii.JsiiObjectRef objRef)

    • CfnApplication

      protected CfnApplication(software.amazon.jsii.JsiiObject.InitializationMode initializationMode)

    • CfnApplication

      @Stability(Stable) public CfnApplication(@NotNull Construct scope, @NotNull String id, @NotNull CfnApplicationProps props)
      Create a new AWS::KinesisAnalytics::Application.

      Parameters:
      scope -
      • scope in which this resource is defined.
      This parameter is required.
      id -
      • scoped id of the resource.
      This parameter is required.
      props -
      • resource properties.
      This parameter is required.

  • Method Details

    • inspect

      @Stability(Stable) public void inspect(@NotNull TreeInspector inspector)
      Examines the CloudFormation resource and discloses attributes.

      Specified by:
      inspect in interface IInspectable
      Parameters:
      inspector -
      • tree inspector to collect and process attributes.
      This parameter is required.

    • renderProperties

      @Stability(Stable) @NotNull protected Map<String,Object> renderProperties(@NotNull Map<String,Object> props)
      Overrides:
      renderProperties in class CfnResource
      Parameters:
      props - This parameter is required.

    • getCfnProperties

      @Stability(Stable) @NotNull protected Map<String,Object> getCfnProperties()
      Overrides:
      getCfnProperties in class CfnResource

    • getInputs

      @Stability(Stable) @NotNull public Object getInputs()
      Use this parameter to configure the application input.

      You can configure your application to receive input from a single streaming source. In this configuration, you map this streaming source to an in-application stream that is created. Your application code can then query the in-application stream like a table (you can think of it as a constantly updating table).

      For the streaming source, you provide its Amazon Resource Name (ARN) and format of data on the stream (for example, JSON, CSV, etc.). You also must provide an IAM role that Amazon Kinesis Analytics can assume to read this stream on your behalf.

      To create the in-application stream, you need to specify a schema to transform your data into a schematized version used in SQL. In the schema, you provide the necessary mapping of the data elements in the streaming source to record columns in the in-app stream.

    • setInputs

      @Stability(Stable) public void setInputs(@NotNull IResolvable value)
      Use this parameter to configure the application input.

      You can configure your application to receive input from a single streaming source. In this configuration, you map this streaming source to an in-application stream that is created. Your application code can then query the in-application stream like a table (you can think of it as a constantly updating table).

      For the streaming source, you provide its Amazon Resource Name (ARN) and format of data on the stream (for example, JSON, CSV, etc.). You also must provide an IAM role that Amazon Kinesis Analytics can assume to read this stream on your behalf.

      To create the in-application stream, you need to specify a schema to transform your data into a schematized version used in SQL. In the schema, you provide the necessary mapping of the data elements in the streaming source to record columns in the in-app stream.

    • setInputs

      @Stability(Stable) public void setInputs(@NotNull List<Object> value)
      Use this parameter to configure the application input.

      You can configure your application to receive input from a single streaming source. In this configuration, you map this streaming source to an in-application stream that is created. Your application code can then query the in-application stream like a table (you can think of it as a constantly updating table).

      For the streaming source, you provide its Amazon Resource Name (ARN) and format of data on the stream (for example, JSON, CSV, etc.). You also must provide an IAM role that Amazon Kinesis Analytics can assume to read this stream on your behalf.

      To create the in-application stream, you need to specify a schema to transform your data into a schematized version used in SQL. In the schema, you provide the necessary mapping of the data elements in the streaming source to record columns in the in-app stream.

    • getApplicationCode

      @Stability(Stable) @Nullable public String getApplicationCode()
      One or more SQL statements that read input data, transform it, and generate output.

      For example, you can write a SQL statement that reads data from one in-application stream, generates a running average of the number of advertisement clicks by vendor, and insert resulting rows in another in-application stream using pumps. For more information about the typical pattern, see Application Code .

      You can provide such series of SQL statements, where output of one statement can be used as the input for the next statement. You store intermediate results by creating in-application streams and pumps.

      Note that the application code must create the streams with names specified in the Outputs . For example, if your Outputs defines output streams named ExampleOutputStream1 and ExampleOutputStream2 , then your application code must create these streams.

    • setApplicationCode

      @Stability(Stable) public void setApplicationCode(@Nullable String value)
      One or more SQL statements that read input data, transform it, and generate output.

      For example, you can write a SQL statement that reads data from one in-application stream, generates a running average of the number of advertisement clicks by vendor, and insert resulting rows in another in-application stream using pumps. For more information about the typical pattern, see Application Code .

      You can provide such series of SQL statements, where output of one statement can be used as the input for the next statement. You store intermediate results by creating in-application streams and pumps.

      Note that the application code must create the streams with names specified in the Outputs . For example, if your Outputs defines output streams named ExampleOutputStream1 and ExampleOutputStream2 , then your application code must create these streams.

    • getApplicationDescription

      @Stability(Stable) @Nullable public String getApplicationDescription()
      Summary description of the application.

    • setApplicationDescription

      @Stability(Stable) public void setApplicationDescription(@Nullable String value)
      Summary description of the application.

    • getApplicationName

      @Stability(Stable) @Nullable public String getApplicationName()
      Name of your Amazon Kinesis Analytics application (for example, sample-app ).

    • setApplicationName

      @Stability(Stable) public void setApplicationName(@Nullable String value)
      Name of your Amazon Kinesis Analytics application (for example, sample-app ).