AWS Workshop
  • About
  • Immersion Day
    • 2025.06 - EKS
    • 2025.03 - Generative AI
    • 2025.02 - ECS
    • 2024.09 - EKS
    • 2024.07 - Security
    • 2024.05 - ECS
    • 2024.01 - Generative AI
    • 2023.10 - Security
    • 2023.08 - MSK
    • 2023.06 - DevOps
    • 2023.04 - AI/ML
    • 2023.02 - EKS
    • 2023.01 - General
    • 2022.12 - 광주소프트웨어마이스터고등학교
    • 2022.12 - Data Analytics
      • Getting started
        • Create a Kinesis Data Stream
      • Produce data to Kinesis Data Streams
        • Cofigure AWS Cloud 9 IDE
        • Using the Amazon SDK with Kinesis
          • Working with the SDK
        • Using the Kinesis Producer Library
          • A Simple Producer
          • Error Analysis and Resiliency
          • CloudWatch Metrics from the Kinesis Producer Library
      • Lambda with Kinesis Data Firehose
        • Overview
        • Create Glue Table
        • Create Kinesis Data Firehose Delivery Stream
        • Stream the data and validate output
      • Clean, Aggregate, and Enrich Events with Kinesis Data Analytics
        • Setup Kinesis Data Analytics Studio
        • Stream the data and validate output
    • 2022.11 - General
    • 2022.10 - EKS
    • 2022.09 - General
    • 2022.08 - 큐피스트
    • 2022.08 - Security
    • 2022.07 - General
    • 2022.06 - Serverless
    • 2022.05 - EKS
    • 2022.05 - 백패커
    • 2022.05 - General
    • 2022.04 - DevOps
    • 2022.04 - Data Analytics
      • Getting started
        • Create a Kinesis Data Stream
      • Produce data to Kinesis Data Streams
        • Cofigure AWS Cloud 9 IDE
        • Using the Amazon SDK with Kinesis
          • Working with the SDK
        • Using the Kinesis Producer Library
          • A Simple Producer
          • Error Analysis and Resiliency
          • CloudWatch Metrics from the Kinesis Producer Library
      • Lambda with Kinesis Data Firehose
        • Overview
        • Create Glue Table
        • Create Kinesis Data Firehose Delivery Stream
        • Stream the data and validate output
      • Clean, Aggregate, and Enrich Events with Kinesis Data Analytics
        • Setup Kinesis Data Analytics Studio
        • Stream the data and validate output
    • 2022.03 - General
    • 2022.02 - AI/ML
    • 2022.01 - General
    • 2021.12 - Container
    • 2021.11 - General
    • 2021.10 - General
  • Seminar
    • 2024.07 - 동국대 특강
    • 2024.06 - Generative AI
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  1. Immersion Day
  2. 2022.04 - Data Analytics
  3. Clean, Aggregate, and Enrich Events with Kinesis Data Analytics

Setup Kinesis Data Analytics Studio

PreviousClean, Aggregate, and Enrich Events with Kinesis Data AnalyticsNextStream the data and validate output

Last updated 3 years ago

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1. Amazon Kinesis Analytics 서비스로 이동하여 Studio 탭을 선택합니다.

2. Create with custom settings를 선택하고 Studio notebook 이름을 입력합니다.

3. IAM roles that Kinesis Data Analytics can assume를 선택하고 IAM 역할 목록에서 kinesis-analytics-KDA 역할을 선택합니다. AWS Glue database 목록에서 kinesislab 데이터베이스를 선택합니다.

4. Custom connectors 탭이 보일때까지 아래로 스크롤합니다. Add custom connector를 클릭합니다.

5. Location of custom connector in S3에 s3://youngwjung, Path to S3 object에 labs/kinesis/flink-sql-connector-elasticsearch7_2.12-1.13.2.jar를 입력하고 Save Change를 선택합니다.

6. Next를 선택합니다.

7. 페이지 맨 아래로 스크롤하고 Create studio notebook를 선택합니다.