我们可以使用AWS CDK构建基础设施即代码，包括配置Kinesis Data Analytic应用程序的VPC设置。以下是一些示例代码：

import * as cdk from 'aws-cdk-lib';
import * as kinesis from 'aws-cdk-lib/aws-kinesis';
import * as kda from 'aws-cdk-lib/aws-kinesisanalytics';
import * as ec2 from 'aws-cdk-lib/aws-ec2';

const app = new cdk.App();

const stack = new cdk.Stack(app, 'my-stack');

// 创建VPC
const vpc = new ec2.Vpc(stack, 'my-vpc');

// 创建Kinesis Data Stream
const inputStream = new kinesis.Stream(stack, 'my-input-stream', {
  streamName: 'my-input-stream',
  shardCount: 1,
});

// 创建Kinesis Data Analytics应用
const kdaApp = new kda.CfnApplicationV2(stack, 'my-kda-app', {
  applicationName: 'my-kda-app',
  runtimeEnvironment: 'SQL-1_0',
  serviceExecutionRole: 'arn:aws:iam::123456789012:role/my-kda-app-service-role',
  applicationConfiguration: {
    inputs: [{
      namePrefix: 'input',
      inputSchema: {
        recordColumns: [{
          name: 'value',
          mapping: '$.value.N',
          sqlType: 'DOUBLE',
        }],
        recordFormat: {
          recordFormatType: 'JSON',
          mappingParameters: {
            jsonMappingParameters: {
              recordRowPath: '$',
            },
          },
        },
      },
      kinesisStreamsInput: {
        resourceArn: inputStream.streamArn,
        roleArn: 'arn:aws:iam::123456789012:role/my-kda-app-kinesis-streams-input-role',
      },
      inputParallelism: {
        count: 1,
      },
      inputProcessingConfiguration: {
        inputLambdaProcessor: {
          resourceArn: processFunction.functionArn,
          roleArn: 'arn:aws:iam::123456789012:role/my-kda-app-lambda-function-role',
        },
      },
      kinesisFirehoseInput: {
        resourceArn: firehoseStream.streamArn,
        roleArn: 'arn:aws:iam::123456789012:role/my-kda-app-firehose-input-role',
      },
    }],
  },
});

// 更新Kinesis Data Analytics应用的VPC配置
kdaApp.addPropertyOverride('vpcConfiguration', {
  subnetIds: vpc.privateSubnets.map(subnet => subnet.subnetId),
  securityGroupIds: [vpc.vpcDefaultSecurityGroup