Task-scheduler for Java that was inspired by the need for a clustered java.util.concurrent.ScheduledExecutorService
simpler than Quartz.
See also why not Quartz?
- Cluster-friendly. Guarantees execution by single scheduler instance.
- Persistent tasks. Requires single database-table for persistence.
- Embeddable. Built to be embedded in existing applications.
- Simple.
- Minimal dependencies. (slf4j)
- Add maven dependency
<dependency>
<groupId>com.github.kagkarlsson</groupId>
<artifactId>db-scheduler</artifactId>
<version>6.4</version>
</dependency>
-
Create the
scheduled_tasks
table in your database-schema. See table definition for postgresql, oracle, mssql or mysql. -
Instantiate and start the scheduler, which then will start any defined recurring tasks.
RecurringTask<Void> hourlyTask = Tasks.recurring("my-hourly-task", FixedDelay.ofHours(1))
.execute((inst, ctx) -> {
System.out.println("Executed!");
});
final Scheduler scheduler = Scheduler
.create(dataSource)
.startTasks(hourlyTask)
.threads(5)
.build();
// hourlyTask is automatically scheduled on startup if not already started (i.e. exists in the db)
scheduler.start();
For more examples, continue reading. For details on the inner workings, see How it works. If you have a Spring Boot application, have a look at Spring Boot Usage.
Define a recurring task and schedule the task's first execution on start-up using the startTasks
builder-method. Upon completion, the task will be re-scheduled according to the defined schedule (see pre-defined schedule-types).
RecurringTask<Void> hourlyTask = Tasks.recurring("my-hourly-task", FixedDelay.ofHours(1))
.execute((inst, ctx) -> {
System.out.println("Executed!");
});
final Scheduler scheduler = Scheduler
.create(dataSource)
.startTasks(hourlyTask)
.threads(5)
.build();
// hourlyTask is automatically scheduled on startup if not already started (i.e. exists in the db)
scheduler.start();
An instance of a one-time task has a single execution-time some time in the future (i.e. non-recurring). The instance-id must be unique within this task, and may be used to encode some metadata (e.g. an id). For more complex state, custom serializable java objects are supported (as used in the example).
Define a one-time task and start the scheduler:
OneTimeTask<MyTaskData> myAdhocTask = Tasks.oneTime("my-typed-adhoc-task", MyTaskData.class)
.execute((inst, ctx) -> {
System.out.println("Executed! Custom data, Id: " + inst.getData().id);
});
final Scheduler scheduler = Scheduler
.create(dataSource, myAdhocTask)
.threads(5)
.build();
scheduler.start();
... and then at some point (at runtime), an execution is scheduled using the SchedulerClient
:
// Schedule the task for execution a certain time in the future and optionally provide custom data for the execution
scheduler.schedule(myAdhocTask.instance("1045", new MyTaskData(1001L)), Instant.now().plusSeconds(5));
To avoid unnecessary dead exexutions, it is important to shutdown the scheduler properly, i.e. calling the shutdown
method.
final Scheduler scheduler = Scheduler
.create(dataSource, myAdhocTask)
.build();
Runtime.getRuntime().addShutdownHook(new Thread() {
@Override
public void run() {
LOG.info("Received shutdown signal.");
scheduler.stop();
}
});
scheduler.start();
The scheduler is created using the Scheduler.create(...)
builder. The builder have sensible defaults, but the following options are configurable.
Option | Default | Description |
---|---|---|
.threads(int) |
10 | Number of threads |
.pollingInterval(Duration) |
30s | How often the scheduler checks the database for due executions. |
.pollingLimit(int) |
3 * | Maximum number of executions to fetch on a check for due executions. |
.heartbeatInterval(Duration) |
5m | How often to update the heartbeat timestamp for running executions. |
.schedulerName(SchedulerName) |
hostname | Name of this scheduler-instance. The name is stored in the database when an execution is picked by a scheduler. |
.tableName(String) |
scheduled_tasks |
Name of the table used to track task-executions. Change name in the table definitions accordingly when creating the table. |
.serializer(Serializer) |
standard Java | Serializer implementation to use when serializing task data. |
.enableImmediateExecution() |
false | If this is enabled, the scheduler will attempt to directly execute tasks that are scheduled to now() , or a time in the past. For this to work, the call to schedule(..) must not occur from within a transaction, because the record will not yet be visible to the scheduler (if this is a requirement, see the method scheduler.triggerCheckForDueExecutions() ) |
.executorService(ExecutorService) |
null |
If specified, use this externally managed executor service to run executions. Ideally the number of threads it will use should still be supplied (for scheduler polling optimizations). |
.deleteUnresolvedAfter(Duration) |
14d |
The time after which executions with unknown tasks are automatically deleted. These can typically be old recurring tasks that are not in use anymore. This is non-zero to prevent accidental removal of tasks through a configuration error (missing known-tasks) and problems during rolling upgrades. |
Tasks are created using one of the builder-classes in Tasks
. The builders have sensible defaults, but the following options can be overridden.
Option | Default | Description |
---|---|---|
.onFailure(FailureHandler) |
see desc. | What to do when a ExecutionHandler throws an exception. By default, Recurring tasks are rescheduled according to their Schedule one-time tasks are retried again in 5m. |
.onDeadExecution(DeadExecutionHandler) |
ReviveDeadExecution |
What to do when a dead executions is detected, i.e. an execution with a stale heartbeat timestamp. By default dead executions are rescheduled to now() . |
.initialData(T initialData) |
null |
The data to use the first time a recurring task is scheduled. |
The library contains a number of Schedule-implementations for recurring tasks. See class Schedules
.
Schedule | Description |
---|---|
.daily(LocalTime ...) |
Runs every day at specified times. |
.fixedDelay(Duration) |
Next execution-time is Duration after last completed execution. Note: This Schedule schedules the initial execution to Instant.now() when used in `startTasks(...) |
.cron(String) |
Spring-style cron-expression. |
For Spring Boot applications, there is a starter db-scheduler-spring-boot-starter
making the scheduler-wiring very simple. (See full example project).
- An existing Spring Boot application
- A working
DataSource
with schema initialized. (In the example HSQLDB is used and schema is automatically applied.)
- Add the following Maven dependency
NOTE: This includes the db-scheduler dependency itself.
<dependency> <groupId>com.github.kagkarlsson</groupId> <artifactId>db-scheduler-spring-boot-starter</artifactId> <version>6.4</version> </dependency>
- In your configuration, expose your
Task
's as Spring beans. If they are recurring, they will automatically be picked up and started. - Run the app.
Configuration is mainly done via application.properties
. Configuration of scheduler-name, serializer and executor-service is done by adding a bean of type DbSchedulerCustomizer
to your Spring context.
# application.properties example showing default values
db-scheduler.enabled=true
db-scheduler.heartbeat-interval=5m
db-scheduler.polling-interval=30s
db-scheduler.polling-limit=
db-scheduler.table-name=scheduled_tasks
db-scheduler.immediate-execution-enabled=false
db-scheduler.scheduler-name=
db-scheduler.threads=10
db-scheduler.delay-startup-until-context-ready=false
A single database table is used to track future task-executions. When a task-execution is due, db-scheduler picks it and executes it. When the execution is done, the Task
is consulted to see what should be done. For example, a RecurringTask
is typically rescheduled in the future based on its Schedule
.
Optimistic locking is used to guarantee that a one and only one scheduler-instance gets to pick a task-execution.
The term recurring task is used for tasks that should be run regularly, according to some schedule (see Tasks.recurring(..)
).
When the execution of a recurring task has finished, a Schedule
is consulted to determine what the next time for execution should be, and a future task-execution is created for that time (i.e. it is rescheduled). The time chosen will be the nearest time according to the Schedule
, but still in the future.
To create the initial execution for a RecurringTask
, the scheduler has a method startTasks(...)
that takes a list of tasks that should be "started" if they do not already have a future execution.
The term one-time task is used for tasks that have a single execution-time (see Tasks.oneTime(..)
).
In addition to encode data into the instanceId
of a task-execution, it is possible to store arbitrary binary data in a separate field for use at execution-time. By default, Java serialization is used to marshal/unmarshal the data.
For tasks not fitting the above categories, it is possible to fully customize the behavior of the tasks using Tasks.custom(..)
.
Use-cases might be:
- Recurring tasks that needs to update its data
- Tasks that should be either rescheduled or removed based on output from the actual execution
During execution, the scheduler regularly updates a heartbeat-time for the task-execution. If an execution is marked as executing, but is not receiving updates to the heartbeat-time, it will be considered a dead execution after time X. That may for example happen if the JVM running the scheduler suddenly exits.
When a dead execution is found, the Task
is consulted to see what should be done. A dead RecurringTask
is typically rescheduled to now()
.
-
There are no guarantees that all instants in a schedule for a
RecurringTask
will be executed. TheSchedule
is consulted after the previous task-execution finishes, and the closest time in the future will be selected for next execution-time. A new type of task may be added in the future to provide such functionality. -
The methods on
SchedulerClient
(schedule
,cancel
,reschedule
) and theCompletionHandler
will run using a newConnection
from theDataSource
provided. To have the action be a part of a transaction, it must be taken care of by theDataSource
provided, for example using something like Spring'sTransactionAwareDataSourceProxy
. -
Currently, the precision of db-scheduler is depending on the
pollingInterval
(default 10s) which specifies how often to look in the table for due executions. If you know what you are doing, the scheduler may be instructed at runtime to "look early" viascheduler.triggerCheckForDueExecutions()
. (See alsoenableImmediateExecution()
on theBuilder
)
- Added configuration option from version 6.3 (
deleteUnresolvedAfter(Duration)
) to Spring Boot starter.
- PR #80 adds more graceful handling of unresolved tasks. Executions with unknown tasks will not (in extreme cases) be able to block other executions. They will also automatically be removed from the database after a duration controlled by builder-method
deleteUnresolvedAfter(Duration)
, which currently defaults to 14d.
- PR #71 allows for configuring Spring to delay starting the scheduler until after context is fully started. (contributed by evenh)
- PR #68 allows for specifying time-zone for cron-schedules (contributed by paulhilliar)
- PR #63 adds Spring Boot support. Scheduler can now be autoconfigured using tasks available in the Spring context. (contributed by evenh)
- PR #60 changes
RecurringTask
so that initial/first execution-time is defined in theSchedule
and typically is the next Instant according to the Schedule.
- PR #52 redesigns use of the underlying
ExecutorService
, making better use of the backing queue. - PR #53 adds a method to the
SchedulerClient
for checking if aTaskInstance
already exists,client.getScheduledExecution(<task-instance-id>)
(fixes #38. - PR #54 adds a builder-method for supplying an externally managed
ExecutorService
(fixes #51). - PR #56 adds cron-support,
Schedules.cron(<pattern>)
(fixes #40).
- PR #47 allows for setting max number of executions fetched by the scheduler (contributed by bgooren)
- PR #48 fixes a bug for medium-sized volumes where the scheduler would not continue to poll for executions until there were none left (contributed by bgooren)
- Helper for using a version of the scheduler in unit/integration tests is now available in the artifact, through the class
TestHelper.createManualScheduler(...)
. For usage example seeSchedulerClientTest
. - It is now possible to manually trigger a check for due executions in the database. Of course, if this is done too frequently there will be an increased overhead.
- The scheduler can be instructed to do a best-effort attempt at executing executions it sees is being scheduled to run
now()
or earlier through the builder-methodenableImmediateExecution()
. - Bugfix:
scheduler.getScheduledExecutionsForTask(...)
was not working properly
- Track number of consecutive failures of a task. For use in
FailureHandler
to avoid retrying forever, or retry with back-off.
Upgrading to 4.x
- Add column
consecutive_failures
to the database schema. See table definitions for postgresql, oracle or mysql.null
is handled as 0, so no need to update existing records.
- Customizable serlizer (PR kagkarlsson#32)
- Customizable table-name for persistence
- Future executions can now be fetched using the
scheduler.getScheduledExecutions(..)
- New builders for task-creation, making it clearer what the config-options are. (See
Tasks
class and examples) - Better default for failure handling for one-time tasks
- Enables recurring tasks to have data
Schedule.getNextExecutionTime
can now use all data fromExecutionComplete
Upgrading to 3.x
- No schema changes
- Task creation are preferrably done through builders in
Tasks
class
- Possible to
cancel
andreschedule
executions. - Optional data can be stored with the execution. Default using Java Serialization.
- Exposing the
Execution
to theExecutionHandler
.
Upgrading to 2.x
- Add column
task_data
to the database schema. See table definitions for postgresql, oracle or mysql.
The goal of db-scheduler
is to be non-invasive and simple to use, but still solve the persistence problem, and the cluster-coordination problem.
It was originally targeted at applications with modest database schemas, to which adding 11 tables would feel a bit overkill..
KISS. It's the most common type of shared state applications have.
Please create an issue with the feature request and we can discuss it there. If you are impatient (or feel like contributing), pull requests are most welcome :)
Yes. It is used in production at a number of companies, and have so far run smoothly.