Spring Batch Processing & ETL — Spring Boot 3.4 Architecture Blueprint

Scaffold production-ready Spring Batch Processing & ETL for Spring Boot 3.4: Chunk-oriented ETL steps (ItemReader, ItemProcessor, ItemWriter), skip/retry policies, and cron triggers. Pre-wired JPA, starters, and Docker Compose.

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.