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1Repair Windows errors before they cause bigger problems2Scan for outdated or missing drivers - takes under a minute3Clear out junk files and repair common Windows errorsLaravel bus batches coordinate groups of queued jobs; they do not clean or validate data for you. For a large CSV import, split the input into independent row ranges, make each job apply the application’s validation and persistence rules, and use batch callbacks to track the work. With multiple queue workers, jobs can run in parallel and finish in a different order from the one in which they were dispatched.
What Laravel batching does—and what it leaves to your application
A batch groups jobs so Laravel can coordinate their execution, report progress, and run callbacks when the group changes state or finishes. Laravel describes the feature as a way to execute a group of jobs in parallel and then take an action after the batch completes. Whether the imported records are valid, consistent, or safe to persist remains an application responsibility.
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For a data import, define the work unit first. A job might process a specific range of CSV rows, validate each row against your rules, and persist accepted records while recording rejected ones. Make chunks independent and repeatable: a chunk should not rely on another chunk finishing first, and retrying it should not corrupt or duplicate results. Choose chunk size based on the file, workload, and available workers; Laravel’s documentation does not prescribe a universal size.
Prepare the batchable jobs
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Create the batch metadata table and apply the migration:
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php artisan make:queue-batches-table php artisan migrate -
Use Laravel’s
IlluminateBusBatchabletrait in each job that belongs to a batch. The trait gives a job access to its batch, including whether the batch has been cancelled. -
Pass each job an explicit, bounded unit of work—for example, the file identifier and a starting and ending row. Keep validation and persistence rules in the job or the application services it calls, not in the batching mechanism.
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Ensure every job in a given batch uses the same queue connection and queue. Laravel’s batch API requires this consistency.
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Laravel’s official CSV example uses row ranges to divide a file into jobs. See Laravel’s 13.x queue documentation and its queue documentation source.
Dispatch work and choose the right execution shape
Use Bus::batch([...]) to dispatch a known set of jobs. Add lifecycle callbacks for the operational events you need, and give the batch a descriptive name when it will help identify an import in logs or monitoring tools.
Batches are suited to independent chunks, not ordering. When multiple workers are available, jobs may run concurrently and complete in any order. If correctness depends on stages running sequentially, use a job chain. Laravel also supports chains inside batches and batches inside chains, so a workflow can combine parallel work within a stage and ordered transitions between stages.
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| Choice | Use it when | Key behavior |
|---|---|---|
| Parallel batch | Chunks are independent and can be processed in any completion order. | Jobs can execute concurrently with multiple workers; dispatch order does not guarantee completion order. |
| Job chain | A later job must wait for an earlier job to complete. | Jobs run in sequence rather than as independent parallel chunks. |
For a very large or incrementally discovered workload, a loader job can add jobs to its current batch using the batch’s add method. This avoids having to construct and dispatch the entire job list at the start, such as inside a web request. See Laravel’s batching and chain guidance.
Use callbacks for batch-level coordination
Laravel provides before, progress, then, catch, and finally callbacks. Use them for batch-level status or coordination: for example, recording that an import began, updating progress, marking successful completion, responding to the first failure, or performing final cleanup. They do not replace per-row validation or an application’s record-level error report.
Callbacks are serialized for later execution. Laravel warns not to use $this inside them. Keep callback behavior self-contained and avoid capturing unserializable state. The catch callback runs for the first failing job, so it is not a complete list of every failed chunk.
The batch instance exposes identifiers, total and pending job counts, processed and failed counts, percentage progress, finished state, and cancellation operations. Treat the percentage as framework batch progress, not as a measure of how many rows passed validation or how clean the imported data is. The Laravel Batch API reference documents these status and control methods.
Decide how a failed chunk affects the import
By default, a failed job cancels its batch. If chunks are independent and you want other valid chunks to continue despite a failure, call allowFailures() when defining the batch. Laravel also permits a closure to handle individual failures in that mode. Choose deliberately: continuing may preserve useful partial work, but the application must expose failures clearly and decide whether the import as a whole can be considered complete.
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Use the catch callback for a batch-level response to the first failing job; use job-level handling or application records when operators need details about individual failed chunks or rejected rows. When a failed job is appropriate to run again, Laravel documents the queue:retry-batch command:
php artisan queue:retry-batch <batch-id>Before retrying, make sure the job’s persistence behavior is safe to repeat. Otherwise, successful side effects from an earlier attempt could be applied twice.
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A job can check whether its batch has been cancelled before continuing expensive work, or use Laravel’s SkipIfBatchCancelled middleware to skip a cancelled batch’s jobs. Check at a useful boundary in the job so cancellation can prevent further processing rather than merely being noticed after the work is done.
Laravel runs batched jobs within database transactions. Avoid SQL statements that trigger implicit commits inside those jobs; an implicit commit can interfere with the transaction behavior Laravel expects. Keep schema changes and other transaction-disrupting operations out of the batch’s data-processing path.
Monitor and prune batch records
Name batches when useful for debugging. Laravel notes that Horizon and Telescope may display more useful debugging information for named batches. For operational status, the batch’s counts and progress can help show how much queued work remains, but application-level validation results and row-level errors need their own reporting.
Batch metadata is stored in the database, so schedule pruning rather than allowing finished records to accumulate indefinitely. Laravel’s queue:prune-batches command prunes finished batches older than 24 hours by default and accepts a custom retention window. Set the retention period to match how long your team needs batch history for troubleshooting.
Quick Recap
Keep the data-quality contract in the jobs
- Validate each record: enforce the application’s required fields, formats, relationships, and business rules before persistence.
- Make chunks repeatable: design safe retry behavior and prevent duplicate side effects.
- Do not assume order: make chunks independent, or express required sequencing with chains.
- Report rejected data separately: batch progress reports job execution, not row acceptance or data quality.
- Choose failure policy intentionally: decide whether one failed chunk should cancel the batch or whether independent work should continue.
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