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Laravel bus batches coordinate independent queued jobs; they do not validate or clean imported data for you. For a large CSV, split rows into repeatable chunks, validate and persist each chunk in its job, then use the batch to track progress and respond to completion or failure.
What Laravel batching does—and what it leaves to your application
A batch groups queued jobs so Laravel can coordinate their execution and run lifecycle actions when the group progresses or finishes. With multiple queue workers, jobs may run in parallel, and they can finish in a different order from the order in which they were dispatched. A batch therefore suits independent chunks, not work whose correctness depends on a fixed execution sequence.
Batching does not define what counts as clean data. Your job must implement the rules for validating, rejecting, normalizing, and storing its records, along with any reporting needed to explain invalid rows. Laravel’s batch status describes job execution, not the quality or completeness of the imported data.
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Design chunks that remain correct in any completion order
For a CSV import, divide the input into explicit row ranges and dispatch a job for each range. Laravel’s documentation illustrates this pattern in its CSV import example. Make each job responsible for reading its assigned range and applying the application’s validation and persistence rules.
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- Keep chunks independent so one can finish before another without changing the final result.
- Make retries safe: a job that runs again should not create duplicate or inconsistent records. Use application-level safeguards appropriate to your data model.
- Choose chunk boundaries and size based on the file, database, worker capacity, and operational constraints; Laravel’s documentation does not prescribe a universally correct chunk size.
If the workflow genuinely requires ordered stages, use a job chain rather than relying on batch dispatch order. Laravel also documents combining chains and batches when a workflow needs both sequential stages and parallel work.
Prepare and dispatch a batch
- Create the batch metadata table: run
php artisan make:queue-batches-table, then run your database migrations. - Make each queued job batchable: add the
IlluminateBusBatchabletrait to the job. - Dispatch the jobs: use
Bus::batch([...])and add lifecycle callbacks that match the work your application needs to coordinate. Give the batch a useful name when it will help with operations or debugging.
Every job in a given batch must use the same queue connection and queue. If constructing a very large list of jobs in the request that starts the import is impractical, Laravel supports adding jobs dynamically through the current batch’s add method, for example from a loader job.
Use callbacks for batch-level coordination
Laravel provides before, progress, then, catch, and finally callbacks. Use them for batch-level actions such as recording that work started, updating status as jobs progress, responding to successful completion, handling a failure, or performing final coordination. They do not replace per-row validation or error recording in the jobs themselves.
Laravel serializes callbacks for later execution. Do not use $this inside them; capture only the data the callback needs. The framework also runs batched jobs within database transactions, so avoid SQL statements in a batched job that cause an implicit commit.
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Choose what a failed chunk means
By default, a failed job cancels its batch. If independent valid chunks should continue despite failures elsewhere, call allowFailures() when creating the batch; Laravel also allows a closure to respond to a failure. The batch’s catch callback is invoked for the first failing job, so use per-job or per-record application logic if you need detailed error accounting.
Cancellation and failure handling are separate from data validation: decide whether a failed chunk should stop the overall import, while each job remains responsible for identifying and reporting bad records. A job can check whether its batch was cancelled before continuing, or use Laravel’s SkipIfBatchCancelled middleware.
When retrying is appropriate, Laravel documents the queue:retry-batch command for retrying failed jobs in a batch. Before retrying, ensure the affected jobs can safely run again against data that may already have been written.
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The batch instance exposes an identifier, total job count, pending and failed counts, processed counts, percentage progress, finished state, and cancellation operations. These values help an application show operational status or trigger coordination; the percentage is a job-progress value, not a measure of records validated successfully.
Naming batches can make them easier to identify, and Laravel notes that Horizon and Telescope may show more useful debugging information for named batches. Keep application-level validation results—such as rejected rows or reasons for rejection—in a separate reporting path that reflects your import rules.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Retain batch records deliberately
Schedule queue:prune-batches so completed batch records do not accumulate indefinitely. Laravel’s documented default is to prune finished batches older than 24 hours; the command supports a custom retention window. Choose a window compatible with how long your team or application needs to inspect completed batch status.
Batch or chain: choose by dependency
| Workflow need | Use | Reason |
|---|---|---|
| Independent chunks can run concurrently | Batch | Jobs can execute in parallel when workers are available, and the batch tracks group progress and lifecycle. |
| Each step must wait for the preceding step | Chain | A chain expresses sequential job dependencies rather than relying on completion order in a batch. |
| Sequential stages contain independent parallel work | Combine chains and batches | Laravel documents using chains within batches and batches within chains. |
For the Laravel 13.x guidance on dispatching, callbacks, cancellation, failures, and pruning, see the official queue documentation. The Laravel Batch API reference for 12.x documents the batch status and count operations; confirm the API details for the Laravel version used by your application.
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