SOQL Bulk Query

Understanding SOQL Bulk Queries

SOQL (Salesforce Object Query Language) bulk queries are designed to handle large volumes of data efficiently. In Salesforce Apex, these queries are often used with a FOR loop to iterate over large data sets without hitting governor limits, which are critical to maintaining performance in multi-tenant environments.

Why Use SOQL Bulk Queries?

Using SOQL bulk queries helps you:

• Optimize Performance: Retrieve large data sets in a single query, reducing the number of queries and improving execution time.
• Avoid Governor Limits: By processing records in batches, you avoid exceeding Salesforce's strict limits on the number of queries and records processed.

Basic Syntax of a SOQL Bulk Query

for (List<Account> accList : [SELECT Id, Name FROM Account]) {
    for (Account acc : accList) {
        System.debug('Account Name: ' + acc.Name);
    }
}

In the example above, the SOQL query retrieves all accounts in the database, and the FOR loop iterates over these records in batches. This approach ensures that you handle large volumes of data efficiently.

Handling Large Data Sets

When dealing with especially large data sets, it's crucial to implement additional logic to manage processing and error handling. Here’s a more detailed example:

for (List<Contact> conList : [SELECT Id, LastName FROM Contact WHERE LastName LIKE 'A%']) {
    try {
        for (Contact con : conList) {
            System.debug('Contact Last Name: ' + con.LastName);
            // Additional processing logic here
        }
    } catch (Exception e) {
        System.debug('Error processing contacts: ' + e.getMessage());
    }
}

This example demonstrates how to use a bulk query to retrieve contacts with last names starting with 'A'. It includes a try-catch block for error handling, ensuring that any issues during processing do not halt the entire operation.

Best Practices for SOQL Bulk Queries

• Limit Your Query: Always use filters to limit the scope of your query to only the necessary records.
• Use Efficient Loops: Ensure the inner loop processes records without unnecessary logic to optimize performance.
• Handle Exceptions: Implement robust error handling to manage any exceptions during data processing.