Overview & Architecture Pattern
Chunk-oriented ETL steps (ItemReader, ItemProcessor, ItemWriter), skip/retry policies, and cron triggers.
Architecture Pattern: Data Processing & Pipelines
Primary Use Case: Nightly banking reconciliation, bulk CSV/XML importing, database data warehousing.
Included Dependencies & Starters
spring-boot-starter-batch, data-jpa, postgresql, actuator
Domain Entities & Scaffolding Defaults
ProcessedRecord (jobExecutionId, recordKey, payload, status, processedAt)
Quickstart: Running Your Project
# 1. Start required infrastructure containers
docker compose up -d
# 2. Run the Spring Boot 3.4 application (Maven)
./mvnw spring-boot:run
# Or run with Gradle
./gradlew bootRun
Frequently Asked Questions
- What starters are included in the Spring Batch Processing & ETL blueprint?
- The Spring Batch Processing & ETL blueprint includes spring-boot-starter-batch, data-jpa, postgresql, actuator, pre-configured application.yml properties, and production-ready connection pools.
- How do I run the generated Spring Batch Processing & ETL project locally?
- Extract the downloaded ZIP, start dependencies with 'docker compose up -d', and execute './mvnw spring-boot:run' (Maven) or './gradlew bootRun' (Gradle).
- Can I customize entities and database schemas in this blueprint?
- Yes, SpringForge allows you to visually add or modify JPA entities, field types, validation rules, and relational mappings, or import SQL DDL schemas.