HowTo

In this section we have collected some step-by-step instructions to get you started with Apache Flink® in your own projects. If there’s an example you’d find useful that isn’t here, please open an issue and let us know?

• Create Apache Flink® integrations
• Create an Apache Kafka®-based Apache Flink® table
  • Create an Apache Kafka-based Apache Flink table with Aiven Console
  • Example: Define a Flink table using the standard connector over topic in JSON format
  • Example: Define a Flink table using the standard connector over topic in Avro format
  • Example: Define a Flink table using the upsert connector over topic in Avro format
• Create a PostgreSQL®-based Apache Flink® table
  • Create a PostgreSQL®-based Apache Flink® table with Aiven Console
  • Example: Define a Flink table over a PostgreSQL® table
• Create an OpenSearch®-based Apache Flink® table
  • Create an OpenSearch®-based Apache Flink® table with Aiven Console
  • Example: Define an Apache Flink® table to OpenSearch®
• Create an Apache Flink® job
  • Prerequisites
  • Create a Flink job via Aiven Console
  • Example: Define and Apache Flink® job for basic data filtering
• Define OpenSearch® timestamp data in SQL pipeline
  • Define Apache Flink® target tables including timestamps for OpenSearch®
• Create a real-time alerting solution - Aiven console
  • Architecture overview
  • Requirements
  • Set up Aiven services
  • Set up sample data
  • Create a pipeline for basic filtering
  • Create a pipeline with windowing
  • Create a Flink SQL job using PostgreSQL® thresholds
  • Create an aggregated data pipeline with Apache Kafka® and PostgreSQL®
  • Replicate the filter stream of data to OpenSearch® for further analysis and data visualization