Jakarta Batch

Jakarta Batch
Name	Jakarta Batch
Developer	Eclipse Foundation
Released	2017
Latest release	1.1
Programming language	Java (programming language)
Operating system	Cross-platform
License	Eclipse Public License

Jakarta Batch Jakarta Batch is a specification for batch processing for the Java Platform, Enterprise Edition family managed by the Eclipse Foundation. It standardizes APIs and behavioral contracts for defining, deploying, monitoring, and scaling long-running batch jobs on platforms such as Apache Tomcat, WildFly, Open Liberty, and GlassFish. The specification builds on prior work from the Java Community Process and aligns with related standards like Jakarta EE and Java Specification Requests.

Overview

Jakarta Batch defines a container-oriented model for executing batch jobs composed of steps, partitions, readers, processors, and writers. It targets use in enterprise contexts including integration with MicroProfile, Kubernetes, Docker, and orchestration systems such as Apache Mesos and Kubernetes Operators. The specification complements APIs from Jakarta Transactions and Jakarta Persistence to provide consistent behavior for transaction boundaries, checkpointing, and restart semantics. Jakarta Batch aims to be implementation-agnostic so runtimes like Apache OpenEJB, Payara Server, and Red Hat JBoss EAP can provide portable execution environments.

History and development

Jakarta Batch originated from the Java batch processing work in JSR 352 under the Java Community Process and was transferred to the Eclipse Foundation when the EE technologies moved to the Jakarta brand. Early implementations and reference works included projects from IBM, Oracle Corporation, Red Hat, and Apache Software Foundation contributors. The specification evolved through community-driven proposals, expert group meetings, and issue-based governance involving stakeholders from companies such as Fujitsu, Tomitribe, and Payara. Subsequent revisions aligned with Jakarta EE platform changes, API package renaming, and updates to interoperate with Jakarta Transactions and Jakarta Persistence semantics.

Architecture and components

Jakarta Batch defines a set of runtime components and XML artifacts used by container providers. Key artifacts include a job XML descriptor (Job Specification) and programmatic components such as javax.batch.api.chunk.ItemReader, javax.batch.api.chunk.ItemProcessor, and javax.batch.api.chunk.ItemWriter adapted to the Jakarta namespace. The runtime architecture integrates with container services like the Java Naming and Directory Interface provider and transaction managers such as Arjuna Transaction Service or Narayana. Core components include the Job Operator, Job Repository, Job Instances, Job Executions, and Step Executions, which interact with persistent stores like PostgreSQL, MySQL, and Oracle Database for job metadata. Implementations often add monitoring endpoints compatible with Prometheus, logging via Logback or Log4j, and management through JMX.

Core concepts and programming model

The model organizes work into jobs composed of sequential or flow-controlled steps; steps can be chunk-oriented or task-oriented. Chunk processing uses readers, processors, and writers with checkpoint algorithms to ensure at-least-once or exactly-once semantics when combined with Jakarta Transactions. Partitioning enables parallel execution across threads or nodes using strategies that integrate with thread pools from ManagedExecutorService or external schedulers like Quartz (software). The Job Operator API provides lifecycle operations such as start, stop, restart, and abandon; job definitions are expressed in XML conforming to the Job Specification and can be augmented with annotations from CDI and Jakarta Inject for dependency injection. Exception handling and retry behavior align with rules defined in the specification to enable predictable failure recovery.

Implementations and integrations

Several Jakarta EE vendors and open-source projects provide Jakarta Batch implementations or adaptors. Examples include the batch runtime in Apache OpenEJB derivatives, batch modules in Payara Server, and integrations within Quarkus extensions and Spring Batch interoperability layers. Cloud-native deployments often combine Jakarta Batch implementations with Kubernetes, OpenShift, or serverless platforms mediated by operators and CI/CD systems like Jenkins or GitLab CI. Connectors exist for common systems such as Apache Kafka, Amazon S3, Google Cloud Storage, and relational databases to enable ETL pipelines, event-driven batching, and large-scale data ingestion.

Use cases and examples

Typical use cases encompass ETL pipelines for Hadoop Distributed File System integration, invoice processing for SAP SE backends, nightly data warehousing loads to Snowflake (data warehouse), mass email campaigns coordinated with SendGrid, and large-scale report generation for Tableau Software consumption. Example patterns include partitioned chunk steps for parallel file processing, restartable jobs for reliable financial settlement, and task steps for orchestration tasks that invoke Apache Camel routes or gRPC services. Jakarta Batch is also used in migration projects converting legacy COBOL batch workloads to modern Java runtimes.

Community and governance

The specification and related projects are governed under the Eclipse Foundation Jakarta EE Working Group and contributor agreements. Development proceeds through mailing lists, issue trackers, and specification review processes with participation from vendors such as IBM, Red Hat, Oracle Corporation, Payara, and independent contributors from organizations like The Linux Foundation. Compliance and TCK efforts are coordinated to ensure interoperability across implementations, with community events held at conferences such as JavaOne, Devoxx, and EclipseCon.

Category:Jakarta EE specifications