# Quartz — Enterprise Job Scheduling for Java

> Feature-rich open-source job scheduling library for Java that supports cron expressions, clustering, and persistent job stores.

## Install

Save in your project root:

# Quartz — Enterprise Job Scheduling for Java

## Quick Use
```java
SchedulerFactory sf = new StdSchedulerFactory();
Scheduler scheduler = sf.getScheduler();
JobDetail job = newJob(MyJob.class)
    .withIdentity("myJob").build();
Trigger trigger = newTrigger()
    .withSchedule(cronSchedule("0 0/5 * * * ?")).build();
scheduler.scheduleJob(job, trigger);
scheduler.start();
```

## Introduction
Quartz is a widely adopted open-source job scheduling library for Java applications. It lets developers define jobs as simple Java classes and schedule them using cron expressions, intervals, or calendar-based triggers. Quartz can run embedded within an application server or as a standalone process, and supports clustering across multiple nodes with JDBC-backed job stores for persistence and failover.

## What Quartz Does
- Schedules jobs using cron expressions, fixed intervals, or calendar rules
- Persists job definitions and triggers to a relational database via JDBC
- Supports clustered execution where multiple scheduler instances share work
- Provides listeners and plugins for job lifecycle events, logging, and history
- Handles misfired triggers with configurable recovery policies

## Architecture Overview
A Quartz Scheduler manages a JobStore that holds job definitions and trigger states. The RAMJobStore keeps everything in memory for fast single-node use, while the JDBCJobStore persists to a database for durability and clustering. A thread pool of configurable size executes jobs when their triggers fire. In clustered mode, multiple Scheduler instances use database row-level locking to coordinate trigger ownership, ensuring each job fires exactly once across the cluster.

## Self-Hosting & Configuration
- Add `org.quartz-scheduler:quartz` to your Maven or Gradle dependencies
- Configure via `quartz.properties` with thread pool size, job store type, and data source
- Define jobs by implementing the `org.quartz.Job` interface
- Build triggers with the fluent `TriggerBuilder` and `CronScheduleBuilder` APIs
- For clustering, set `org.quartz.jobStore.isClustered = true` and point all nodes at the same database

## Key Features
- Cron expressions support second-level granularity beyond standard Unix cron
- JDBC job store provides persistence across application restarts
- Built-in clustering with automatic failover and load balancing
- Misfire handling policies let you skip, fire immediately, or reschedule missed triggers
- Calendar exclusions can block job execution on holidays or maintenance windows

## Comparison with Similar Tools
- **Spring @Scheduled** — simple annotation-based cron for Spring apps; Quartz adds persistence and clustering
- **Temporal** — durable workflow orchestration; Quartz is lighter for simple job scheduling
- **Celery Beat** — Python periodic task scheduler; Quartz serves the Java/JVM ecosystem
- **Hangfire** — .NET background jobs; Quartz is the Java equivalent with JDBC stores
- **Airflow** — DAG-based workflow orchestration; Quartz handles individual recurring jobs

## FAQ
**Q: Can Quartz run in a Spring Boot application?**
A: Yes. Spring Boot has built-in auto-configuration for Quartz via the `spring-boot-starter-quartz` dependency.

**Q: How does Quartz handle a missed job trigger?**
A: Configurable misfire instructions let you fire immediately, discard the missed run, or reschedule to the next valid time.

**Q: Does Quartz support distributed execution across servers?**
A: Yes. Configure JDBC job store with clustering enabled and all nodes sharing the same database.

**Q: What databases does the JDBC job store support?**
A: Quartz provides SQL scripts for PostgreSQL, MySQL, Oracle, SQL Server, H2, and other databases.

## Sources
- https://github.com/quartz-scheduler/quartz
- https://www.quartz-scheduler.org/documentation/

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Source: https://tokrepo.com/en/workflows/asset-6369fc9f
Author: AI Open Source