SeaTunnel: Distributed Data Integration Platform and Its Application in Traffic Management

SeaTunnel is a distributed, high‑performance, and easy‑to‑use data integration platform that supports both real‑time streaming and batch processing, built on Apache Spark and Apache Flink. It simplifies data synchronization and transformation tasks without requiring programming, offering a rich set of input, filter/transform, and output plugins.

The platform provides several technical advantages: simple configuration, SQL‑based processing, high scalability, modular plugin architecture, and the ability to leverage Spark/Flink for distributed execution. Its workflow follows an Input → Filter/Transform → Output pipeline, which can be constructed via configuration or SQL.

SeaTunnel’s plugin ecosystem includes numerous Input sources (e.g., Oracle, Kafka, HDFS), Filter/Transform plugins (e.g., SQL, Convert, Checksum), and Output sinks (e.g., ClickHouse, Elasticsearch, MySQL). Users can also develop custom plugins to meet specific requirements.

In the traffic‑management scenario, SeaTunnel is used to extract incremental data from Oracle databases within a secure government network, transform it (filtering by update timestamps, type conversion, and SQL aggregation), and load it into a ClickHouse data warehouse. The incremental column is tracked via checkpoints stored in HDFS.

The implementation steps include: (1) configuring Spark resources; (2) defining the Oracle source and HDFS checkpoint handling; (3) applying filter and SQL plugins for data cleaning and incremental logic; (4) outputting the result to ClickHouse; and (5) orchestrating the process with a shell script executed via nohup and scheduled with Crontab or Dolphin Scheduler.

SeaTunnel’s ease of deployment, extensive plugin support, and ability to handle large‑scale data integration make it suitable for scenarios such as massive ETL, data aggregation, and multi‑source processing, especially in environments where data security and incremental updates are critical.