726 lines
41 KiB
C++
726 lines
41 KiB
C++
/**
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* Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
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* SPDX-License-Identifier: Apache-2.0.
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*/
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#pragma once
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#include <aws/kinesisanalytics/KinesisAnalytics_EXPORTS.h>
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#include <aws/kinesisanalytics/KinesisAnalyticsRequest.h>
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#include <aws/core/utils/memory/stl/AWSString.h>
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#include <aws/core/utils/memory/stl/AWSVector.h>
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#include <aws/kinesisanalytics/model/Input.h>
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#include <aws/kinesisanalytics/model/Output.h>
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#include <aws/kinesisanalytics/model/CloudWatchLoggingOption.h>
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#include <aws/kinesisanalytics/model/Tag.h>
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#include <utility>
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namespace Aws
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{
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namespace KinesisAnalytics
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{
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namespace Model
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{
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/**
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* <p>TBD</p><p><h3>See Also:</h3> <a
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* href="http://docs.aws.amazon.com/goto/WebAPI/kinesisanalytics-2015-08-14/CreateApplicationRequest">AWS
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* API Reference</a></p>
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*/
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class AWS_KINESISANALYTICS_API CreateApplicationRequest : public KinesisAnalyticsRequest
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{
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public:
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CreateApplicationRequest();
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// Service request name is the Operation name which will send this request out,
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// each operation should has unique request name, so that we can get operation's name from this request.
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// Note: this is not true for response, multiple operations may have the same response name,
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// so we can not get operation's name from response.
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inline virtual const char* GetServiceRequestName() const override { return "CreateApplication"; }
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Aws::String SerializePayload() const override;
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Aws::Http::HeaderValueCollection GetRequestSpecificHeaders() const override;
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/**
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* <p>Name of your Amazon Kinesis Analytics application (for example,
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* <code>sample-app</code>).</p>
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*/
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inline const Aws::String& GetApplicationName() const{ return m_applicationName; }
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/**
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* <p>Name of your Amazon Kinesis Analytics application (for example,
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* <code>sample-app</code>).</p>
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*/
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inline bool ApplicationNameHasBeenSet() const { return m_applicationNameHasBeenSet; }
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/**
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* <p>Name of your Amazon Kinesis Analytics application (for example,
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* <code>sample-app</code>).</p>
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*/
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inline void SetApplicationName(const Aws::String& value) { m_applicationNameHasBeenSet = true; m_applicationName = value; }
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/**
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* <p>Name of your Amazon Kinesis Analytics application (for example,
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* <code>sample-app</code>).</p>
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*/
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inline void SetApplicationName(Aws::String&& value) { m_applicationNameHasBeenSet = true; m_applicationName = std::move(value); }
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/**
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* <p>Name of your Amazon Kinesis Analytics application (for example,
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* <code>sample-app</code>).</p>
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*/
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inline void SetApplicationName(const char* value) { m_applicationNameHasBeenSet = true; m_applicationName.assign(value); }
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/**
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* <p>Name of your Amazon Kinesis Analytics application (for example,
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* <code>sample-app</code>).</p>
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*/
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inline CreateApplicationRequest& WithApplicationName(const Aws::String& value) { SetApplicationName(value); return *this;}
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/**
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* <p>Name of your Amazon Kinesis Analytics application (for example,
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* <code>sample-app</code>).</p>
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*/
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inline CreateApplicationRequest& WithApplicationName(Aws::String&& value) { SetApplicationName(std::move(value)); return *this;}
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/**
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* <p>Name of your Amazon Kinesis Analytics application (for example,
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* <code>sample-app</code>).</p>
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*/
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inline CreateApplicationRequest& WithApplicationName(const char* value) { SetApplicationName(value); return *this;}
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/**
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* <p>Summary description of the application.</p>
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*/
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inline const Aws::String& GetApplicationDescription() const{ return m_applicationDescription; }
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/**
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* <p>Summary description of the application.</p>
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*/
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inline bool ApplicationDescriptionHasBeenSet() const { return m_applicationDescriptionHasBeenSet; }
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/**
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* <p>Summary description of the application.</p>
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*/
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inline void SetApplicationDescription(const Aws::String& value) { m_applicationDescriptionHasBeenSet = true; m_applicationDescription = value; }
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/**
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* <p>Summary description of the application.</p>
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*/
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inline void SetApplicationDescription(Aws::String&& value) { m_applicationDescriptionHasBeenSet = true; m_applicationDescription = std::move(value); }
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/**
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* <p>Summary description of the application.</p>
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*/
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inline void SetApplicationDescription(const char* value) { m_applicationDescriptionHasBeenSet = true; m_applicationDescription.assign(value); }
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/**
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* <p>Summary description of the application.</p>
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*/
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inline CreateApplicationRequest& WithApplicationDescription(const Aws::String& value) { SetApplicationDescription(value); return *this;}
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/**
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* <p>Summary description of the application.</p>
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*/
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inline CreateApplicationRequest& WithApplicationDescription(Aws::String&& value) { SetApplicationDescription(std::move(value)); return *this;}
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/**
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* <p>Summary description of the application.</p>
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*/
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inline CreateApplicationRequest& WithApplicationDescription(const char* value) { SetApplicationDescription(value); return *this;}
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/**
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* <p>Use this parameter to configure the application input.</p> <p>You can
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* configure your application to receive input from a single streaming source. In
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* this configuration, you map this streaming source to an in-application stream
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* that is created. Your application code can then query the in-application stream
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* like a table (you can think of it as a constantly updating table).</p> <p>For
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* the streaming source, you provide its Amazon Resource Name (ARN) and format of
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* data on the stream (for example, JSON, CSV, etc.). You also must provide an IAM
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* role that Amazon Kinesis Analytics can assume to read this stream on your
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* behalf.</p> <p>To create the in-application stream, you need to specify a schema
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* to transform your data into a schematized version used in SQL. In the schema,
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* you provide the necessary mapping of the data elements in the streaming source
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* to record columns in the in-app stream.</p>
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*/
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inline const Aws::Vector<Input>& GetInputs() const{ return m_inputs; }
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/**
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* <p>Use this parameter to configure the application input.</p> <p>You can
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* configure your application to receive input from a single streaming source. In
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* this configuration, you map this streaming source to an in-application stream
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* that is created. Your application code can then query the in-application stream
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* like a table (you can think of it as a constantly updating table).</p> <p>For
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* the streaming source, you provide its Amazon Resource Name (ARN) and format of
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* data on the stream (for example, JSON, CSV, etc.). You also must provide an IAM
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* role that Amazon Kinesis Analytics can assume to read this stream on your
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* behalf.</p> <p>To create the in-application stream, you need to specify a schema
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* to transform your data into a schematized version used in SQL. In the schema,
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* you provide the necessary mapping of the data elements in the streaming source
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* to record columns in the in-app stream.</p>
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*/
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inline bool InputsHasBeenSet() const { return m_inputsHasBeenSet; }
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/**
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* <p>Use this parameter to configure the application input.</p> <p>You can
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* configure your application to receive input from a single streaming source. In
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* this configuration, you map this streaming source to an in-application stream
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* that is created. Your application code can then query the in-application stream
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* like a table (you can think of it as a constantly updating table).</p> <p>For
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* the streaming source, you provide its Amazon Resource Name (ARN) and format of
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* data on the stream (for example, JSON, CSV, etc.). You also must provide an IAM
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* role that Amazon Kinesis Analytics can assume to read this stream on your
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* behalf.</p> <p>To create the in-application stream, you need to specify a schema
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* to transform your data into a schematized version used in SQL. In the schema,
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* you provide the necessary mapping of the data elements in the streaming source
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* to record columns in the in-app stream.</p>
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*/
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inline void SetInputs(const Aws::Vector<Input>& value) { m_inputsHasBeenSet = true; m_inputs = value; }
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/**
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* <p>Use this parameter to configure the application input.</p> <p>You can
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* configure your application to receive input from a single streaming source. In
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* this configuration, you map this streaming source to an in-application stream
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* that is created. Your application code can then query the in-application stream
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* like a table (you can think of it as a constantly updating table).</p> <p>For
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* the streaming source, you provide its Amazon Resource Name (ARN) and format of
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* data on the stream (for example, JSON, CSV, etc.). You also must provide an IAM
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* role that Amazon Kinesis Analytics can assume to read this stream on your
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* behalf.</p> <p>To create the in-application stream, you need to specify a schema
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* to transform your data into a schematized version used in SQL. In the schema,
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* you provide the necessary mapping of the data elements in the streaming source
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* to record columns in the in-app stream.</p>
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*/
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inline void SetInputs(Aws::Vector<Input>&& value) { m_inputsHasBeenSet = true; m_inputs = std::move(value); }
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/**
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* <p>Use this parameter to configure the application input.</p> <p>You can
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* configure your application to receive input from a single streaming source. In
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* this configuration, you map this streaming source to an in-application stream
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* that is created. Your application code can then query the in-application stream
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* like a table (you can think of it as a constantly updating table).</p> <p>For
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* the streaming source, you provide its Amazon Resource Name (ARN) and format of
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* data on the stream (for example, JSON, CSV, etc.). You also must provide an IAM
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* role that Amazon Kinesis Analytics can assume to read this stream on your
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* behalf.</p> <p>To create the in-application stream, you need to specify a schema
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* to transform your data into a schematized version used in SQL. In the schema,
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* you provide the necessary mapping of the data elements in the streaming source
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* to record columns in the in-app stream.</p>
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*/
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inline CreateApplicationRequest& WithInputs(const Aws::Vector<Input>& value) { SetInputs(value); return *this;}
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/**
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* <p>Use this parameter to configure the application input.</p> <p>You can
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* configure your application to receive input from a single streaming source. In
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* this configuration, you map this streaming source to an in-application stream
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* that is created. Your application code can then query the in-application stream
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* like a table (you can think of it as a constantly updating table).</p> <p>For
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* the streaming source, you provide its Amazon Resource Name (ARN) and format of
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* data on the stream (for example, JSON, CSV, etc.). You also must provide an IAM
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* role that Amazon Kinesis Analytics can assume to read this stream on your
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* behalf.</p> <p>To create the in-application stream, you need to specify a schema
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* to transform your data into a schematized version used in SQL. In the schema,
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* you provide the necessary mapping of the data elements in the streaming source
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* to record columns in the in-app stream.</p>
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*/
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inline CreateApplicationRequest& WithInputs(Aws::Vector<Input>&& value) { SetInputs(std::move(value)); return *this;}
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/**
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* <p>Use this parameter to configure the application input.</p> <p>You can
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* configure your application to receive input from a single streaming source. In
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* this configuration, you map this streaming source to an in-application stream
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* that is created. Your application code can then query the in-application stream
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* like a table (you can think of it as a constantly updating table).</p> <p>For
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* the streaming source, you provide its Amazon Resource Name (ARN) and format of
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* data on the stream (for example, JSON, CSV, etc.). You also must provide an IAM
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* role that Amazon Kinesis Analytics can assume to read this stream on your
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* behalf.</p> <p>To create the in-application stream, you need to specify a schema
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* to transform your data into a schematized version used in SQL. In the schema,
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* you provide the necessary mapping of the data elements in the streaming source
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* to record columns in the in-app stream.</p>
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*/
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inline CreateApplicationRequest& AddInputs(const Input& value) { m_inputsHasBeenSet = true; m_inputs.push_back(value); return *this; }
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/**
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* <p>Use this parameter to configure the application input.</p> <p>You can
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* configure your application to receive input from a single streaming source. In
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* this configuration, you map this streaming source to an in-application stream
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* that is created. Your application code can then query the in-application stream
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* like a table (you can think of it as a constantly updating table).</p> <p>For
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* the streaming source, you provide its Amazon Resource Name (ARN) and format of
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* data on the stream (for example, JSON, CSV, etc.). You also must provide an IAM
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* role that Amazon Kinesis Analytics can assume to read this stream on your
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* behalf.</p> <p>To create the in-application stream, you need to specify a schema
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* to transform your data into a schematized version used in SQL. In the schema,
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* you provide the necessary mapping of the data elements in the streaming source
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* to record columns in the in-app stream.</p>
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*/
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inline CreateApplicationRequest& AddInputs(Input&& value) { m_inputsHasBeenSet = true; m_inputs.push_back(std::move(value)); return *this; }
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/**
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* <p>You can configure application output to write data from any of the
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* in-application streams to up to three destinations.</p> <p>These destinations
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* can be Amazon Kinesis streams, Amazon Kinesis Firehose delivery streams, AWS
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* Lambda destinations, or any combination of the three.</p> <p>In the
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* configuration, you specify the in-application stream name, the destination
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* stream or Lambda function Amazon Resource Name (ARN), and the format to use when
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* writing data. You must also provide an IAM role that Amazon Kinesis Analytics
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* can assume to write to the destination stream or Lambda function on your
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* behalf.</p> <p>In the output configuration, you also provide the output stream
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* or Lambda function ARN. For stream destinations, you provide the format of data
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* in the stream (for example, JSON, CSV). You also must provide an IAM role that
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* Amazon Kinesis Analytics can assume to write to the stream or Lambda function on
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* your behalf.</p>
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*/
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inline const Aws::Vector<Output>& GetOutputs() const{ return m_outputs; }
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/**
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* <p>You can configure application output to write data from any of the
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* in-application streams to up to three destinations.</p> <p>These destinations
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* can be Amazon Kinesis streams, Amazon Kinesis Firehose delivery streams, AWS
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* Lambda destinations, or any combination of the three.</p> <p>In the
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* configuration, you specify the in-application stream name, the destination
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* stream or Lambda function Amazon Resource Name (ARN), and the format to use when
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* writing data. You must also provide an IAM role that Amazon Kinesis Analytics
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* can assume to write to the destination stream or Lambda function on your
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* behalf.</p> <p>In the output configuration, you also provide the output stream
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* or Lambda function ARN. For stream destinations, you provide the format of data
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* in the stream (for example, JSON, CSV). You also must provide an IAM role that
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* Amazon Kinesis Analytics can assume to write to the stream or Lambda function on
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* your behalf.</p>
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*/
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inline bool OutputsHasBeenSet() const { return m_outputsHasBeenSet; }
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/**
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* <p>You can configure application output to write data from any of the
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* in-application streams to up to three destinations.</p> <p>These destinations
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* can be Amazon Kinesis streams, Amazon Kinesis Firehose delivery streams, AWS
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* Lambda destinations, or any combination of the three.</p> <p>In the
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* configuration, you specify the in-application stream name, the destination
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* stream or Lambda function Amazon Resource Name (ARN), and the format to use when
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* writing data. You must also provide an IAM role that Amazon Kinesis Analytics
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* can assume to write to the destination stream or Lambda function on your
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* behalf.</p> <p>In the output configuration, you also provide the output stream
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* or Lambda function ARN. For stream destinations, you provide the format of data
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* in the stream (for example, JSON, CSV). You also must provide an IAM role that
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* Amazon Kinesis Analytics can assume to write to the stream or Lambda function on
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* your behalf.</p>
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*/
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inline void SetOutputs(const Aws::Vector<Output>& value) { m_outputsHasBeenSet = true; m_outputs = value; }
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/**
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* <p>You can configure application output to write data from any of the
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* in-application streams to up to three destinations.</p> <p>These destinations
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* can be Amazon Kinesis streams, Amazon Kinesis Firehose delivery streams, AWS
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* Lambda destinations, or any combination of the three.</p> <p>In the
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* configuration, you specify the in-application stream name, the destination
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* stream or Lambda function Amazon Resource Name (ARN), and the format to use when
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* writing data. You must also provide an IAM role that Amazon Kinesis Analytics
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* can assume to write to the destination stream or Lambda function on your
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* behalf.</p> <p>In the output configuration, you also provide the output stream
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* or Lambda function ARN. For stream destinations, you provide the format of data
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* in the stream (for example, JSON, CSV). You also must provide an IAM role that
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* Amazon Kinesis Analytics can assume to write to the stream or Lambda function on
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* your behalf.</p>
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*/
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inline void SetOutputs(Aws::Vector<Output>&& value) { m_outputsHasBeenSet = true; m_outputs = std::move(value); }
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/**
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* <p>You can configure application output to write data from any of the
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* in-application streams to up to three destinations.</p> <p>These destinations
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* can be Amazon Kinesis streams, Amazon Kinesis Firehose delivery streams, AWS
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* Lambda destinations, or any combination of the three.</p> <p>In the
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* configuration, you specify the in-application stream name, the destination
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* stream or Lambda function Amazon Resource Name (ARN), and the format to use when
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* writing data. You must also provide an IAM role that Amazon Kinesis Analytics
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* can assume to write to the destination stream or Lambda function on your
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* behalf.</p> <p>In the output configuration, you also provide the output stream
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* or Lambda function ARN. For stream destinations, you provide the format of data
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* in the stream (for example, JSON, CSV). You also must provide an IAM role that
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* Amazon Kinesis Analytics can assume to write to the stream or Lambda function on
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* your behalf.</p>
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*/
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inline CreateApplicationRequest& WithOutputs(const Aws::Vector<Output>& value) { SetOutputs(value); return *this;}
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/**
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* <p>You can configure application output to write data from any of the
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* in-application streams to up to three destinations.</p> <p>These destinations
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* can be Amazon Kinesis streams, Amazon Kinesis Firehose delivery streams, AWS
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|
* Lambda destinations, or any combination of the three.</p> <p>In the
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* configuration, you specify the in-application stream name, the destination
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* stream or Lambda function Amazon Resource Name (ARN), and the format to use when
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* writing data. You must also provide an IAM role that Amazon Kinesis Analytics
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* can assume to write to the destination stream or Lambda function on your
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* behalf.</p> <p>In the output configuration, you also provide the output stream
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* or Lambda function ARN. For stream destinations, you provide the format of data
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* in the stream (for example, JSON, CSV). You also must provide an IAM role that
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* Amazon Kinesis Analytics can assume to write to the stream or Lambda function on
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* your behalf.</p>
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*/
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inline CreateApplicationRequest& WithOutputs(Aws::Vector<Output>&& value) { SetOutputs(std::move(value)); return *this;}
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/**
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* <p>You can configure application output to write data from any of the
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* in-application streams to up to three destinations.</p> <p>These destinations
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* can be Amazon Kinesis streams, Amazon Kinesis Firehose delivery streams, AWS
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|
* Lambda destinations, or any combination of the three.</p> <p>In the
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* configuration, you specify the in-application stream name, the destination
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* stream or Lambda function Amazon Resource Name (ARN), and the format to use when
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* writing data. You must also provide an IAM role that Amazon Kinesis Analytics
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* can assume to write to the destination stream or Lambda function on your
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* behalf.</p> <p>In the output configuration, you also provide the output stream
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* or Lambda function ARN. For stream destinations, you provide the format of data
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* in the stream (for example, JSON, CSV). You also must provide an IAM role that
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* Amazon Kinesis Analytics can assume to write to the stream or Lambda function on
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* your behalf.</p>
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*/
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inline CreateApplicationRequest& AddOutputs(const Output& value) { m_outputsHasBeenSet = true; m_outputs.push_back(value); return *this; }
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/**
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* <p>You can configure application output to write data from any of the
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* in-application streams to up to three destinations.</p> <p>These destinations
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* can be Amazon Kinesis streams, Amazon Kinesis Firehose delivery streams, AWS
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* Lambda destinations, or any combination of the three.</p> <p>In the
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* configuration, you specify the in-application stream name, the destination
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* stream or Lambda function Amazon Resource Name (ARN), and the format to use when
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* writing data. You must also provide an IAM role that Amazon Kinesis Analytics
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* can assume to write to the destination stream or Lambda function on your
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* behalf.</p> <p>In the output configuration, you also provide the output stream
|
|
* or Lambda function ARN. For stream destinations, you provide the format of data
|
|
* in the stream (for example, JSON, CSV). You also must provide an IAM role that
|
|
* Amazon Kinesis Analytics can assume to write to the stream or Lambda function on
|
|
* your behalf.</p>
|
|
*/
|
|
inline CreateApplicationRequest& AddOutputs(Output&& value) { m_outputsHasBeenSet = true; m_outputs.push_back(std::move(value)); return *this; }
|
|
|
|
|
|
/**
|
|
* <p>Use this parameter to configure a CloudWatch log stream to monitor
|
|
* application configuration errors. For more information, see <a
|
|
* href="https://docs.aws.amazon.com/kinesisanalytics/latest/dev/cloudwatch-logs.html">Working
|
|
* with Amazon CloudWatch Logs</a>.</p>
|
|
*/
|
|
inline const Aws::Vector<CloudWatchLoggingOption>& GetCloudWatchLoggingOptions() const{ return m_cloudWatchLoggingOptions; }
|
|
|
|
/**
|
|
* <p>Use this parameter to configure a CloudWatch log stream to monitor
|
|
* application configuration errors. For more information, see <a
|
|
* href="https://docs.aws.amazon.com/kinesisanalytics/latest/dev/cloudwatch-logs.html">Working
|
|
* with Amazon CloudWatch Logs</a>.</p>
|
|
*/
|
|
inline bool CloudWatchLoggingOptionsHasBeenSet() const { return m_cloudWatchLoggingOptionsHasBeenSet; }
|
|
|
|
/**
|
|
* <p>Use this parameter to configure a CloudWatch log stream to monitor
|
|
* application configuration errors. For more information, see <a
|
|
* href="https://docs.aws.amazon.com/kinesisanalytics/latest/dev/cloudwatch-logs.html">Working
|
|
* with Amazon CloudWatch Logs</a>.</p>
|
|
*/
|
|
inline void SetCloudWatchLoggingOptions(const Aws::Vector<CloudWatchLoggingOption>& value) { m_cloudWatchLoggingOptionsHasBeenSet = true; m_cloudWatchLoggingOptions = value; }
|
|
|
|
/**
|
|
* <p>Use this parameter to configure a CloudWatch log stream to monitor
|
|
* application configuration errors. For more information, see <a
|
|
* href="https://docs.aws.amazon.com/kinesisanalytics/latest/dev/cloudwatch-logs.html">Working
|
|
* with Amazon CloudWatch Logs</a>.</p>
|
|
*/
|
|
inline void SetCloudWatchLoggingOptions(Aws::Vector<CloudWatchLoggingOption>&& value) { m_cloudWatchLoggingOptionsHasBeenSet = true; m_cloudWatchLoggingOptions = std::move(value); }
|
|
|
|
/**
|
|
* <p>Use this parameter to configure a CloudWatch log stream to monitor
|
|
* application configuration errors. For more information, see <a
|
|
* href="https://docs.aws.amazon.com/kinesisanalytics/latest/dev/cloudwatch-logs.html">Working
|
|
* with Amazon CloudWatch Logs</a>.</p>
|
|
*/
|
|
inline CreateApplicationRequest& WithCloudWatchLoggingOptions(const Aws::Vector<CloudWatchLoggingOption>& value) { SetCloudWatchLoggingOptions(value); return *this;}
|
|
|
|
/**
|
|
* <p>Use this parameter to configure a CloudWatch log stream to monitor
|
|
* application configuration errors. For more information, see <a
|
|
* href="https://docs.aws.amazon.com/kinesisanalytics/latest/dev/cloudwatch-logs.html">Working
|
|
* with Amazon CloudWatch Logs</a>.</p>
|
|
*/
|
|
inline CreateApplicationRequest& WithCloudWatchLoggingOptions(Aws::Vector<CloudWatchLoggingOption>&& value) { SetCloudWatchLoggingOptions(std::move(value)); return *this;}
|
|
|
|
/**
|
|
* <p>Use this parameter to configure a CloudWatch log stream to monitor
|
|
* application configuration errors. For more information, see <a
|
|
* href="https://docs.aws.amazon.com/kinesisanalytics/latest/dev/cloudwatch-logs.html">Working
|
|
* with Amazon CloudWatch Logs</a>.</p>
|
|
*/
|
|
inline CreateApplicationRequest& AddCloudWatchLoggingOptions(const CloudWatchLoggingOption& value) { m_cloudWatchLoggingOptionsHasBeenSet = true; m_cloudWatchLoggingOptions.push_back(value); return *this; }
|
|
|
|
/**
|
|
* <p>Use this parameter to configure a CloudWatch log stream to monitor
|
|
* application configuration errors. For more information, see <a
|
|
* href="https://docs.aws.amazon.com/kinesisanalytics/latest/dev/cloudwatch-logs.html">Working
|
|
* with Amazon CloudWatch Logs</a>.</p>
|
|
*/
|
|
inline CreateApplicationRequest& AddCloudWatchLoggingOptions(CloudWatchLoggingOption&& value) { m_cloudWatchLoggingOptionsHasBeenSet = true; m_cloudWatchLoggingOptions.push_back(std::move(value)); return *this; }
|
|
|
|
|
|
/**
|
|
* <p>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 <a
|
|
* href="https://docs.aws.amazon.com/kinesisanalytics/latest/dev/how-it-works-app-code.html">Application
|
|
* Code</a>. </p> <p>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.</p> <p>Note
|
|
* that the application code must create the streams with names specified in the
|
|
* <code>Outputs</code>. For example, if your <code>Outputs</code> defines output
|
|
* streams named <code>ExampleOutputStream1</code> and
|
|
* <code>ExampleOutputStream2</code>, then your application code must create these
|
|
* streams. </p>
|
|
*/
|
|
inline const Aws::String& GetApplicationCode() const{ return m_applicationCode; }
|
|
|
|
/**
|
|
* <p>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 <a
|
|
* href="https://docs.aws.amazon.com/kinesisanalytics/latest/dev/how-it-works-app-code.html">Application
|
|
* Code</a>. </p> <p>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.</p> <p>Note
|
|
* that the application code must create the streams with names specified in the
|
|
* <code>Outputs</code>. For example, if your <code>Outputs</code> defines output
|
|
* streams named <code>ExampleOutputStream1</code> and
|
|
* <code>ExampleOutputStream2</code>, then your application code must create these
|
|
* streams. </p>
|
|
*/
|
|
inline bool ApplicationCodeHasBeenSet() const { return m_applicationCodeHasBeenSet; }
|
|
|
|
/**
|
|
* <p>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 <a
|
|
* href="https://docs.aws.amazon.com/kinesisanalytics/latest/dev/how-it-works-app-code.html">Application
|
|
* Code</a>. </p> <p>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.</p> <p>Note
|
|
* that the application code must create the streams with names specified in the
|
|
* <code>Outputs</code>. For example, if your <code>Outputs</code> defines output
|
|
* streams named <code>ExampleOutputStream1</code> and
|
|
* <code>ExampleOutputStream2</code>, then your application code must create these
|
|
* streams. </p>
|
|
*/
|
|
inline void SetApplicationCode(const Aws::String& value) { m_applicationCodeHasBeenSet = true; m_applicationCode = value; }
|
|
|
|
/**
|
|
* <p>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 <a
|
|
* href="https://docs.aws.amazon.com/kinesisanalytics/latest/dev/how-it-works-app-code.html">Application
|
|
* Code</a>. </p> <p>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.</p> <p>Note
|
|
* that the application code must create the streams with names specified in the
|
|
* <code>Outputs</code>. For example, if your <code>Outputs</code> defines output
|
|
* streams named <code>ExampleOutputStream1</code> and
|
|
* <code>ExampleOutputStream2</code>, then your application code must create these
|
|
* streams. </p>
|
|
*/
|
|
inline void SetApplicationCode(Aws::String&& value) { m_applicationCodeHasBeenSet = true; m_applicationCode = std::move(value); }
|
|
|
|
/**
|
|
* <p>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 <a
|
|
* href="https://docs.aws.amazon.com/kinesisanalytics/latest/dev/how-it-works-app-code.html">Application
|
|
* Code</a>. </p> <p>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.</p> <p>Note
|
|
* that the application code must create the streams with names specified in the
|
|
* <code>Outputs</code>. For example, if your <code>Outputs</code> defines output
|
|
* streams named <code>ExampleOutputStream1</code> and
|
|
* <code>ExampleOutputStream2</code>, then your application code must create these
|
|
* streams. </p>
|
|
*/
|
|
inline void SetApplicationCode(const char* value) { m_applicationCodeHasBeenSet = true; m_applicationCode.assign(value); }
|
|
|
|
/**
|
|
* <p>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 <a
|
|
* href="https://docs.aws.amazon.com/kinesisanalytics/latest/dev/how-it-works-app-code.html">Application
|
|
* Code</a>. </p> <p>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.</p> <p>Note
|
|
* that the application code must create the streams with names specified in the
|
|
* <code>Outputs</code>. For example, if your <code>Outputs</code> defines output
|
|
* streams named <code>ExampleOutputStream1</code> and
|
|
* <code>ExampleOutputStream2</code>, then your application code must create these
|
|
* streams. </p>
|
|
*/
|
|
inline CreateApplicationRequest& WithApplicationCode(const Aws::String& value) { SetApplicationCode(value); return *this;}
|
|
|
|
/**
|
|
* <p>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 <a
|
|
* href="https://docs.aws.amazon.com/kinesisanalytics/latest/dev/how-it-works-app-code.html">Application
|
|
* Code</a>. </p> <p>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.</p> <p>Note
|
|
* that the application code must create the streams with names specified in the
|
|
* <code>Outputs</code>. For example, if your <code>Outputs</code> defines output
|
|
* streams named <code>ExampleOutputStream1</code> and
|
|
* <code>ExampleOutputStream2</code>, then your application code must create these
|
|
* streams. </p>
|
|
*/
|
|
inline CreateApplicationRequest& WithApplicationCode(Aws::String&& value) { SetApplicationCode(std::move(value)); return *this;}
|
|
|
|
/**
|
|
* <p>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 <a
|
|
* href="https://docs.aws.amazon.com/kinesisanalytics/latest/dev/how-it-works-app-code.html">Application
|
|
* Code</a>. </p> <p>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.</p> <p>Note
|
|
* that the application code must create the streams with names specified in the
|
|
* <code>Outputs</code>. For example, if your <code>Outputs</code> defines output
|
|
* streams named <code>ExampleOutputStream1</code> and
|
|
* <code>ExampleOutputStream2</code>, then your application code must create these
|
|
* streams. </p>
|
|
*/
|
|
inline CreateApplicationRequest& WithApplicationCode(const char* value) { SetApplicationCode(value); return *this;}
|
|
|
|
|
|
/**
|
|
* <p>A list of one or more tags to assign to the application. A tag is a key-value
|
|
* pair that identifies an application. Note that the maximum number of application
|
|
* tags includes system tags. The maximum number of user-defined application tags
|
|
* is 50. For more information, see <a
|
|
* href="https://docs.aws.amazon.com/kinesisanalytics/latest/dev/how-tagging.html">Using
|
|
* Tagging</a>.</p>
|
|
*/
|
|
inline const Aws::Vector<Tag>& GetTags() const{ return m_tags; }
|
|
|
|
/**
|
|
* <p>A list of one or more tags to assign to the application. A tag is a key-value
|
|
* pair that identifies an application. Note that the maximum number of application
|
|
* tags includes system tags. The maximum number of user-defined application tags
|
|
* is 50. For more information, see <a
|
|
* href="https://docs.aws.amazon.com/kinesisanalytics/latest/dev/how-tagging.html">Using
|
|
* Tagging</a>.</p>
|
|
*/
|
|
inline bool TagsHasBeenSet() const { return m_tagsHasBeenSet; }
|
|
|
|
/**
|
|
* <p>A list of one or more tags to assign to the application. A tag is a key-value
|
|
* pair that identifies an application. Note that the maximum number of application
|
|
* tags includes system tags. The maximum number of user-defined application tags
|
|
* is 50. For more information, see <a
|
|
* href="https://docs.aws.amazon.com/kinesisanalytics/latest/dev/how-tagging.html">Using
|
|
* Tagging</a>.</p>
|
|
*/
|
|
inline void SetTags(const Aws::Vector<Tag>& value) { m_tagsHasBeenSet = true; m_tags = value; }
|
|
|
|
/**
|
|
* <p>A list of one or more tags to assign to the application. A tag is a key-value
|
|
* pair that identifies an application. Note that the maximum number of application
|
|
* tags includes system tags. The maximum number of user-defined application tags
|
|
* is 50. For more information, see <a
|
|
* href="https://docs.aws.amazon.com/kinesisanalytics/latest/dev/how-tagging.html">Using
|
|
* Tagging</a>.</p>
|
|
*/
|
|
inline void SetTags(Aws::Vector<Tag>&& value) { m_tagsHasBeenSet = true; m_tags = std::move(value); }
|
|
|
|
/**
|
|
* <p>A list of one or more tags to assign to the application. A tag is a key-value
|
|
* pair that identifies an application. Note that the maximum number of application
|
|
* tags includes system tags. The maximum number of user-defined application tags
|
|
* is 50. For more information, see <a
|
|
* href="https://docs.aws.amazon.com/kinesisanalytics/latest/dev/how-tagging.html">Using
|
|
* Tagging</a>.</p>
|
|
*/
|
|
inline CreateApplicationRequest& WithTags(const Aws::Vector<Tag>& value) { SetTags(value); return *this;}
|
|
|
|
/**
|
|
* <p>A list of one or more tags to assign to the application. A tag is a key-value
|
|
* pair that identifies an application. Note that the maximum number of application
|
|
* tags includes system tags. The maximum number of user-defined application tags
|
|
* is 50. For more information, see <a
|
|
* href="https://docs.aws.amazon.com/kinesisanalytics/latest/dev/how-tagging.html">Using
|
|
* Tagging</a>.</p>
|
|
*/
|
|
inline CreateApplicationRequest& WithTags(Aws::Vector<Tag>&& value) { SetTags(std::move(value)); return *this;}
|
|
|
|
/**
|
|
* <p>A list of one or more tags to assign to the application. A tag is a key-value
|
|
* pair that identifies an application. Note that the maximum number of application
|
|
* tags includes system tags. The maximum number of user-defined application tags
|
|
* is 50. For more information, see <a
|
|
* href="https://docs.aws.amazon.com/kinesisanalytics/latest/dev/how-tagging.html">Using
|
|
* Tagging</a>.</p>
|
|
*/
|
|
inline CreateApplicationRequest& AddTags(const Tag& value) { m_tagsHasBeenSet = true; m_tags.push_back(value); return *this; }
|
|
|
|
/**
|
|
* <p>A list of one or more tags to assign to the application. A tag is a key-value
|
|
* pair that identifies an application. Note that the maximum number of application
|
|
* tags includes system tags. The maximum number of user-defined application tags
|
|
* is 50. For more information, see <a
|
|
* href="https://docs.aws.amazon.com/kinesisanalytics/latest/dev/how-tagging.html">Using
|
|
* Tagging</a>.</p>
|
|
*/
|
|
inline CreateApplicationRequest& AddTags(Tag&& value) { m_tagsHasBeenSet = true; m_tags.push_back(std::move(value)); return *this; }
|
|
|
|
private:
|
|
|
|
Aws::String m_applicationName;
|
|
bool m_applicationNameHasBeenSet;
|
|
|
|
Aws::String m_applicationDescription;
|
|
bool m_applicationDescriptionHasBeenSet;
|
|
|
|
Aws::Vector<Input> m_inputs;
|
|
bool m_inputsHasBeenSet;
|
|
|
|
Aws::Vector<Output> m_outputs;
|
|
bool m_outputsHasBeenSet;
|
|
|
|
Aws::Vector<CloudWatchLoggingOption> m_cloudWatchLoggingOptions;
|
|
bool m_cloudWatchLoggingOptionsHasBeenSet;
|
|
|
|
Aws::String m_applicationCode;
|
|
bool m_applicationCodeHasBeenSet;
|
|
|
|
Aws::Vector<Tag> m_tags;
|
|
bool m_tagsHasBeenSet;
|
|
};
|
|
|
|
} // namespace Model
|
|
} // namespace KinesisAnalytics
|
|
} // namespace Aws
|