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Consider the following code snippet: The Apex method is executed in an environment with a large data volume count for Accounts, and the query is performing poorly. Which technique should the developer implement to ensure the query performs optimally, while preserving the entire result set?
Correct Answer: D
When dealing with large data volumes in Salesforce and ensuring optimal performance for queries, it's important to choose an approach that both handles the data volume efficiently and retrieves the complete result set. Option D is correct because using the Database.QueryLocator method is a best practice for handling large data volumes. It is typically used with batch Apex, which can process records in batches, thus reducing the likelihood of hitting governor limits. It's designed to handle very large data sets that would otherwise exceed normal SOQL query limits. Option A is incorrect because creating a formula field doesn't improve the performance of the query. It simply creates a new field that combines existing data, but it does not inherently optimize the query execution. Option B is incorrect because breaking down the query into two parts and joining them in Apex could potentially be less efficient and would require additional code to manage the combined result sets. This approach does not leverage the built-in Salesforce features designed to handle large data volumes. Option C is incorrect because the @Future annotation makes the method execute asynchronously, but it does not help with query performance or large data volume management. References: Salesforce Documentation on Working with Very Large SOQL Queries: Working with Very Large SOQL Queries Salesforce Documentation on Using Batch Apex: Using Batch Apex
Recent Comments (The most recent comments are at the top.)
Fa3il khayr - Sep 19, 2024
I think this is wrong , and the correct answer is B , here is why :
In large datasets, queries with OR conditions often result in full table scans because they can prevent the database from efficiently using indexes. So By breaking the query into two individual queries (one filtering on CreatedDate and one on RecordTypeId), each query can leverage indexes more effectively, improving performance , altough it will costs you to write a few lines of codes , but it worth
Dan - May 22, 2024
B is correct. The 'OR' in a query will make the query un-selective, especially quering a large of records.Breaking down the query into two parts will get two selective query.
Recent Comments (The most recent comments are at the top.)
I think this is wrong , and the correct answer is B , here is why :
In large datasets, queries with OR conditions often result in full table scans because they can prevent the database from efficiently using indexes.
So By breaking the query into two individual queries (one filtering on CreatedDate and one on RecordTypeId), each query can leverage indexes more effectively, improving performance , altough it will costs you to write a few lines of codes , but it worth
B is correct. The 'OR' in a query will make the query un-selective, especially quering a large of records.Breaking down the query into two parts will get two selective query.