Apex Batch Jobs: Scheduling, Chaining, and Monitoring in Production

When you need to process thousands or millions of records in Salesforce, Apex Batch Jobs are the answer. This guide covers everything from the basics to production-grade patterns.

Why Batch Jobs?

Salesforce governor limits prevent processing more than ~50,000 records in a single synchronous transaction. Batch Apex solves this by splitting work into chunks (default: 200 records each), each processed in its own transaction.

Use cases:

Mass data updates or migrations
Nightly data synchronization with external systems
Periodic recalculation of aggregate fields
Cleaning up stale or orphaned records

The Three Interfaces

Every batch job implements Database.Batchable<SObject> with three methods:

public class AccountCleanupBatch implements Database.Batchable<SObject> {
 
    // 1. QUERY — defines the dataset to process
    public Database.QueryLocator start(Database.BatchableContext bc) {
        return Database.getQueryLocator([
            SELECT Id, Name, LastActivityDate, OwnerId
            FROM Account
            WHERE LastActivityDate < LAST_N_DAYS:365
            AND Type = 'Prospect'
        ]);
    }
 
    // 2. EXECUTE — called once per chunk (default 200 records)
    public void execute(Database.BatchableContext bc, List<Account> scope) {
        List<Account> toUpdate = new List<Account>();
        for (Account acc : scope) {
            acc.Status__c = 'Dormant';
            toUpdate.add(acc);
        }
        update toUpdate;
    }
 
    // 3. FINISH — called once after all chunks complete
    public void finish(Database.BatchableContext bc) {
        AsyncApexJob job = [
            SELECT Id, Status, NumberOfErrors, JobItemsProcessed, TotalJobItems
            FROM AsyncApexJob
            WHERE Id = :bc.getJobId()
        ];
 
        // Send summary email
        Messaging.SingleEmailMessage mail = new Messaging.SingleEmailMessage();
        mail.setToAddresses(new String[]{ 'admin@yourorg.com' });
        mail.setSubject('AccountCleanupBatch completed: ' + job.Status);
        mail.setPlainTextBody(
            'Processed: ' + job.JobItemsProcessed + '/' + job.TotalJobItems +
            '\nErrors: ' + job.NumberOfErrors
        );
        Messaging.sendEmail(new Messaging.SingleEmailMessage[]{ mail });
    }
}

Choosing the Right Chunk Size

The default chunk size is 200, but you can override it:

// Launch with custom chunk size
Id jobId = Database.executeBatch(new AccountCleanupBatch(), 50);

Chunk size guidelines:

| Scenario | Recommended Size | |----------|-----------------| | Simple field updates | 200 (default) | | Complex triggers on the object | 50–100 | | With HTTP callouts | 1–10 (callout limits) | | Heavy SOQL in execute() | 50–100 | | Memory-intensive processing | 25–50 |

Rule of thumb: If you hit governor limits inside execute(), reduce the chunk size. If the job runs too slowly, increase it.

By default, batch jobs are stateless — member variables reset between chunks. Use Database.Stateful to accumulate results:

public class SalesReportBatch
    implements Database.Batchable<SObject>, Database.Stateful {
 
    // These persist across all chunks
    private Integer totalProcessed = 0;
    private Decimal totalRevenue = 0;
    private List<String> errors = new List<String>();
 
    public Database.QueryLocator start(Database.BatchableContext bc) {
        return Database.getQueryLocator([
            SELECT Id, Amount, StageName FROM Opportunity
            WHERE CloseDate = THIS_YEAR AND StageName = 'Closed Won'
        ]);
    }
 
    public void execute(Database.BatchableContext bc, List<Opportunity> scope) {
        for (Opportunity opp : scope) {
            try {
                totalRevenue += opp.Amount;
                totalProcessed++;
            } catch (Exception e) {
                errors.add('Opp ' + opp.Id + ': ' + e.getMessage());
            }
        }
    }
 
    public void finish(Database.BatchableContext bc) {
        System.debug('Total processed: ' + totalProcessed);
        System.debug('Total revenue: ' + totalRevenue);
        System.debug('Errors: ' + errors.size());
        // Create a custom SalesReport__c record with these totals
    }
}

Caution: Database.Stateful consumes more heap. Don't store large collections — store counters and IDs, not full SObject lists.

Chaining Batch Jobs

To run jobs in sequence, launch the next job from finish():

public class Step1_DataExtractBatch implements Database.Batchable<SObject> {
 
    public Database.QueryLocator start(Database.BatchableContext bc) {
        return Database.getQueryLocator('SELECT Id FROM Account LIMIT 10000');
    }
 
    public void execute(Database.BatchableContext bc, List<Account> scope) {
        // ... process
    }
 
    public void finish(Database.BatchableContext bc) {
        // Chain to next batch
        Database.executeBatch(new Step2_DataTransformBatch(), 200);
    }
}

Chaining pattern:

Step1_DataExtractBatch.finish()
    → launches Step2_DataTransformBatch
        → Step2.finish() launches Step3_DataLoadBatch
            → Step3.finish() sends completion notification

Important: You can chain indefinitely, but only 5 batch jobs can be queued at once per org. Check the limit in production.

Scheduling Batch Jobs

Method 1: Anonymous Apex (one-time)

// Run immediately
Database.executeBatch(new AccountCleanupBatch(), 200);

Method 2: Scheduled Apex (recurring)

public class AccountCleanupScheduler implements Schedulable {
 
    public void execute(SchedulableContext sc) {
        Database.executeBatch(new AccountCleanupBatch(), 200);
    }
}

Schedule it with a CRON expression:

// Every Sunday at 2am
String cron = '0 0 2 ? * SUN';
System.schedule('Weekly Account Cleanup', cron, new AccountCleanupScheduler());

Common CRON patterns:

| Expression | Meaning | |-----------|---------| | 0 0 2 * * ? | Every day at 2am | | 0 0 0 1 * ? | 1st of every month at midnight | | 0 0 6 ? * MON-FRI | Weekdays at 6am | | 0 0/30 * * * ? | Every 30 minutes |

Method 3: Setup UI

Go to Setup → Apex Classes → Schedule Apex to schedule without code.

Error Handling Inside execute()

Don't let one bad record abort the entire chunk. Use Database.update with allOrNone = false:

public void execute(Database.BatchableContext bc, List<Account> scope) {
    List<Account> toUpdate = new List<Account>();
 
    for (Account acc : scope) {
        acc.LastReviewedDate__c = Date.today();
        toUpdate.add(acc);
    }
 
    // allOrNone = false: partial success allowed
    List<Database.SaveResult> results = Database.update(toUpdate, false);
 
    for (Integer i = 0; i < results.size(); i++) {
        if (!results[i].isSuccess()) {
            for (Database.Error err : results[i].getErrors()) {
                System.debug(LoggingLevel.ERROR,
                    'Failed: ' + toUpdate[i].Id +
                    ' — ' + err.getMessage());
            }
        }
    }
}

Monitoring in Production

Query the AsyncApexJob object

// Check status of a specific job
AsyncApexJob job = [
    SELECT Id, Status, NumberOfErrors, JobItemsProcessed,
           TotalJobItems, CreatedDate, CompletedDate
    FROM AsyncApexJob
    WHERE Id = :jobId
];

Possible statuses:

Queued — waiting to start
Processing — currently running
Completed — finished (check NumberOfErrors)
Failed — job itself failed (not chunk errors)
Aborted — manually stopped

Monitoring via Setup

Setup → Apex Jobs shows all currently running and recently completed batch jobs with status, progress, and error counts.

Abort a Runaway Job

// Abort by JobId
System.abortJob(jobId);

Production Checklist

Before deploying a batch job to production:

[ ] Tested with Test.startTest() / Test.stopTest() in unit tests
[ ] execute() uses Database.DML with allOrNone = false for resilience
[ ] Chunk size validated against your trigger/SOQL complexity
[ ] finish() sends a notification (email or Platform Event)
[ ] Scheduled job documented (purpose, frequency, dependencies)
[ ] Monitoring alert set up for NumberOfErrors > 0
[ ] Chain depth documented — no more than 5 jobs queued

Unit Testing a Batch Job

@isTest
private class AccountCleanupBatch_Test {
 
    @isTest
    static void testBatchRuns() {
        // Arrange: create test accounts
        List<Account> accounts = new List<Account>();
        for (Integer i = 0; i < 10; i++) {
            accounts.add(new Account(Name = 'Test ' + i, Type = 'Prospect'));
        }
        insert accounts;
 
        // Act
        Test.startTest();
        Database.executeBatch(new AccountCleanupBatch(), 200);
        Test.stopTest();
 
        // Assert
        Integer dormant = [SELECT COUNT() FROM Account WHERE Status__c = 'Dormant'];
        System.assertEquals(10, dormant, 'All accounts should be marked Dormant');
    }
}

Test.startTest() / Test.stopTest() forces the batch to complete synchronously in tests — essential for asserting results.

Conclusion

Apex Batch Jobs unlock the ability to process entire datasets safely within Salesforce governor limits. The key principles are: right chunk size, stateful accumulation when needed, partial failure tolerance with allOrNone = false, and always monitoring via finish(). Design your batch jobs with production observability in mind from day one.

Useful Resources:

When you need to process thousands or millions of records in Salesforce, Apex Batch Jobs are the answer. This guide covers everything from the basics to production-grade patterns.

Why Batch Jobs?

Use cases:

Mass data updates or migrations
Nightly data synchronization with external systems
Periodic recalculation of aggregate fields
Cleaning up stale or orphaned records

The Three Interfaces

Every batch job implements Database.Batchable<SObject> with three methods:

public class AccountCleanupBatch implements Database.Batchable<SObject> {
 
    // 1. QUERY — defines the dataset to process
    public Database.QueryLocator start(Database.BatchableContext bc) {
        return Database.getQueryLocator([
            SELECT Id, Name, LastActivityDate, OwnerId
            FROM Account
            WHERE LastActivityDate < LAST_N_DAYS:365
            AND Type = 'Prospect'
        ]);
    }
 
    // 2. EXECUTE — called once per chunk (default 200 records)
    public void execute(Database.BatchableContext bc, List<Account> scope) {
        List<Account> toUpdate = new List<Account>();
        for (Account acc : scope) {
            acc.Status__c = 'Dormant';
            toUpdate.add(acc);
        }
        update toUpdate;
    }
 
    // 3. FINISH — called once after all chunks complete
    public void finish(Database.BatchableContext bc) {
        AsyncApexJob job = [
            SELECT Id, Status, NumberOfErrors, JobItemsProcessed, TotalJobItems
            FROM AsyncApexJob
            WHERE Id = :bc.getJobId()
        ];
 
        // Send summary email
        Messaging.SingleEmailMessage mail = new Messaging.SingleEmailMessage();
        mail.setToAddresses(new String[]{ 'admin@yourorg.com' });
        mail.setSubject('AccountCleanupBatch completed: ' + job.Status);
        mail.setPlainTextBody(
            'Processed: ' + job.JobItemsProcessed + '/' + job.TotalJobItems +
            '\nErrors: ' + job.NumberOfErrors
        );
        Messaging.sendEmail(new Messaging.SingleEmailMessage[]{ mail });
    }
}

Choosing the Right Chunk Size

The default chunk size is 200, but you can override it:

// Launch with custom chunk size
Id jobId = Database.executeBatch(new AccountCleanupBatch(), 50);

Chunk size guidelines:

Rule of thumb: If you hit governor limits inside execute(), reduce the chunk size. If the job runs too slowly, increase it.

By default, batch jobs are stateless — member variables reset between chunks. Use Database.Stateful to accumulate results:

public class SalesReportBatch
    implements Database.Batchable<SObject>, Database.Stateful {
 
    // These persist across all chunks
    private Integer totalProcessed = 0;
    private Decimal totalRevenue = 0;
    private List<String> errors = new List<String>();
 
    public Database.QueryLocator start(Database.BatchableContext bc) {
        return Database.getQueryLocator([
            SELECT Id, Amount, StageName FROM Opportunity
            WHERE CloseDate = THIS_YEAR AND StageName = 'Closed Won'
        ]);
    }
 
    public void execute(Database.BatchableContext bc, List<Opportunity> scope) {
        for (Opportunity opp : scope) {
            try {
                totalRevenue += opp.Amount;
                totalProcessed++;
            } catch (Exception e) {
                errors.add('Opp ' + opp.Id + ': ' + e.getMessage());
            }
        }
    }
 
    public void finish(Database.BatchableContext bc) {
        System.debug('Total processed: ' + totalProcessed);
        System.debug('Total revenue: ' + totalRevenue);
        System.debug('Errors: ' + errors.size());
        // Create a custom SalesReport__c record with these totals
    }
}

Caution: Database.Stateful consumes more heap. Don't store large collections — store counters and IDs, not full SObject lists.

Chaining Batch Jobs

To run jobs in sequence, launch the next job from finish():

public class Step1_DataExtractBatch implements Database.Batchable<SObject> {
 
    public Database.QueryLocator start(Database.BatchableContext bc) {
        return Database.getQueryLocator('SELECT Id FROM Account LIMIT 10000');
    }
 
    public void execute(Database.BatchableContext bc, List<Account> scope) {
        // ... process
    }
 
    public void finish(Database.BatchableContext bc) {
        // Chain to next batch
        Database.executeBatch(new Step2_DataTransformBatch(), 200);
    }
}

Chaining pattern:

Step1_DataExtractBatch.finish()
    → launches Step2_DataTransformBatch
        → Step2.finish() launches Step3_DataLoadBatch
            → Step3.finish() sends completion notification

Important: You can chain indefinitely, but only 5 batch jobs can be queued at once per org. Check the limit in production.

Scheduling Batch Jobs

Method 1: Anonymous Apex (one-time)

// Run immediately
Database.executeBatch(new AccountCleanupBatch(), 200);

Method 2: Scheduled Apex (recurring)

public class AccountCleanupScheduler implements Schedulable {
 
    public void execute(SchedulableContext sc) {
        Database.executeBatch(new AccountCleanupBatch(), 200);
    }
}

Schedule it with a CRON expression:

// Every Sunday at 2am
String cron = '0 0 2 ? * SUN';
System.schedule('Weekly Account Cleanup', cron, new AccountCleanupScheduler());

Common CRON patterns:

Method 3: Setup UI

Go to Setup → Apex Classes → Schedule Apex to schedule without code.

Error Handling Inside execute()

Don't let one bad record abort the entire chunk. Use Database.update with allOrNone = false:

public void execute(Database.BatchableContext bc, List<Account> scope) {
    List<Account> toUpdate = new List<Account>();
 
    for (Account acc : scope) {
        acc.LastReviewedDate__c = Date.today();
        toUpdate.add(acc);
    }
 
    // allOrNone = false: partial success allowed
    List<Database.SaveResult> results = Database.update(toUpdate, false);
 
    for (Integer i = 0; i < results.size(); i++) {
        if (!results[i].isSuccess()) {
            for (Database.Error err : results[i].getErrors()) {
                System.debug(LoggingLevel.ERROR,
                    'Failed: ' + toUpdate[i].Id +
                    ' — ' + err.getMessage());
            }
        }
    }
}

Monitoring in Production

Query the AsyncApexJob object

// Check status of a specific job
AsyncApexJob job = [
    SELECT Id, Status, NumberOfErrors, JobItemsProcessed,
           TotalJobItems, CreatedDate, CompletedDate
    FROM AsyncApexJob
    WHERE Id = :jobId
];

Possible statuses:

Queued — waiting to start
Processing — currently running
Completed — finished (check NumberOfErrors)
Failed — job itself failed (not chunk errors)
Aborted — manually stopped

Monitoring via Setup

Setup → Apex Jobs shows all currently running and recently completed batch jobs with status, progress, and error counts.

Abort a Runaway Job

// Abort by JobId
System.abortJob(jobId);

Production Checklist

Before deploying a batch job to production:

[ ] Tested with Test.startTest() / Test.stopTest() in unit tests
[ ] execute() uses Database.DML with allOrNone = false for resilience
[ ] Chunk size validated against your trigger/SOQL complexity
[ ] finish() sends a notification (email or Platform Event)
[ ] Scheduled job documented (purpose, frequency, dependencies)
[ ] Monitoring alert set up for NumberOfErrors > 0
[ ] Chain depth documented — no more than 5 jobs queued

Unit Testing a Batch Job

@isTest
private class AccountCleanupBatch_Test {
 
    @isTest
    static void testBatchRuns() {
        // Arrange: create test accounts
        List<Account> accounts = new List<Account>();
        for (Integer i = 0; i < 10; i++) {
            accounts.add(new Account(Name = 'Test ' + i, Type = 'Prospect'));
        }
        insert accounts;
 
        // Act
        Test.startTest();
        Database.executeBatch(new AccountCleanupBatch(), 200);
        Test.stopTest();
 
        // Assert
        Integer dormant = [SELECT COUNT() FROM Account WHERE Status__c = 'Dormant'];
        System.assertEquals(10, dormant, 'All accounts should be marked Dormant');
    }
}

Test.startTest() / Test.stopTest() forces the batch to complete synchronously in tests — essential for asserting results.

Conclusion

Useful Resources:

Apex Batch Jobs: Scheduling, Chaining, and Monitoring in Production

Why Batch Jobs?

The Three Interfaces

Choosing the Right Chunk Size

Chaining Batch Jobs

Scheduling Batch Jobs

Method 1: Anonymous Apex (one-time)

Method 2: Scheduled Apex (recurring)

Method 3: Setup UI

Error Handling Inside execute()

Monitoring in Production

Query the AsyncApexJob object

Monitoring via Setup

Abort a Runaway Job

Production Checklist

Unit Testing a Batch Job

Conclusion

Related posts

Apex Batch Jobs: Scheduling, Chaining, and Monitoring in Production

Why Batch Jobs?

The Three Interfaces

Choosing the Right Chunk Size

Chaining Batch Jobs

Scheduling Batch Jobs

Method 1: Anonymous Apex (one-time)

Method 2: Scheduled Apex (recurring)

Method 3: Setup UI

Error Handling Inside execute()

Monitoring in Production

Query the AsyncApexJob object

Monitoring via Setup

Abort a Runaway Job

Production Checklist

Unit Testing a Batch Job

Conclusion

Related posts

Apex Batch Jobs: Scheduling, Chaining, and Monitoring in Production

Why Batch Jobs?

The Three Interfaces

Choosing the Right Chunk Size

Database.Stateful: Sharing State Across Chunks

Chaining Batch Jobs

Scheduling Batch Jobs

Method 1: Anonymous Apex (one-time)

Method 2: Scheduled Apex (recurring)

Method 3: Setup UI

Error Handling Inside execute()

Monitoring in Production

Query the AsyncApexJob object

Monitoring via Setup

Abort a Runaway Job

Production Checklist

Unit Testing a Batch Job

Conclusion

Related posts

Apex Batch Jobs: Scheduling, Chaining, and Monitoring in Production

Why Batch Jobs?

The Three Interfaces

Choosing the Right Chunk Size

Database.Stateful: Sharing State Across Chunks

Chaining Batch Jobs

Scheduling Batch Jobs

Method 1: Anonymous Apex (one-time)

Method 2: Scheduled Apex (recurring)

Method 3: Setup UI

Error Handling Inside execute()

Monitoring in Production

Query the AsyncApexJob object

Monitoring via Setup

Abort a Runaway Job

Production Checklist

Unit Testing a Batch Job

Conclusion

Related posts