Diagnose slow queries on large objects by checking selectivity, indexes, and Query Plan output, then choose the right fix: custom index, skinny table, or rewritten SOQL. The key is recognizing when a field lacks an index and how that drives a full table scan.
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Domain overview
This domain covers Salesforce performance at scale: query selectivity, indexes, skinny tables, and query plans on objects with millions of records. Questions present slow SOQL or search scenarios and ask you to diagnose the cause and select the correct Large Data Volume feature or indexing strategy.
Exam objectives
Identifying custom indexes and external ID fields as the fix for slow filtered SOQL on large objects
Reading Query Plan in Developer Console to evaluate cost, leading operations, and table scans
Knowing skinny tables return read-only copies of frequently queried fields, maintained by Salesforce
Applying selective filter criteria and avoiding non-selective queries on large custom objects
Assuming a custom field is automatically indexed; only external ID and unique fields get an index by default
Requesting a skinny table for write-heavy logic, ignoring that skinny tables are read-only and need Salesforce support
Treating Query Plan cost as absolute; it is a relative estimate and can mislead without comparing alternatives
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Universal Containers has 50 million records in a custom object. A report summarizing these records times out. Which strategy is most effective for improving report performance?
2A company is migrating 100 million records into Salesforce. Which TWO actions should the architect take to optimize performance and prevent row locking?
3Refer to the exhibit. What is the most likely reason this query fails?
4Which platform feature is best used to move data off-platform to avoid Large Data Volume issues?
5When dealing with high-frequency updates on a parent object, what is the best practice to prevent lock contention?
6Which TWO strategies help manage row locking when inserting records into an object with multiple lookup relationships?
7A large custom object has 20 million records. A SOQL query is taking too long. What should the architect evaluate first?
8Which design pattern effectively handles high-volume record updates while avoiding 'Too many SOQL queries' errors?
9What is the primary function of a skinny table in Salesforce?
10Refer to the exhibit. A batch job is failing consistently with the provided error message. The job updates child records that have a Master-Detail relationship with a parent Account. What is the primary cause of this error?
11You are auditing a Salesforce environment and discover a custom object with 20 million records. Users report that searching for records by a custom field 'External_ID__c' is extremely slow. What is the most appropriate action to take?
12Which strategy should be employed when designing a data archiving solution for a high-volume object to ensure continued system performance?
13What is the primary architectural goal of using the Salesforce Bulk API 2.0?
14When designing a system that requires frequent querying of very large objects, which approach provides the best performance while maintaining data integrity?
15Which TWO of the following are consequences of having excessive indexes on a Salesforce object with large data volumes?
16Why is it recommended to perform large data deletes using a soft-delete approach followed by a hard-delete during off-peak hours?
17Which TWO of the following are true regarding the impact of 'Formula Fields' on Large Data Volumes?
18What is the primary architectural benefit of using 'External Objects' (Salesforce Connect) for large volumes of historical data?
19A company is importing 50 million records into a custom object. Which strategy should be used to minimize record locking contention during the high-volume insert operation?
20When dealing with LDV, what is the primary benefit of using External Objects via Salesforce Connect instead of standard Salesforce tables?
21What is the recommended approach to manage 'Skinny Tables' in an environment with Large Data Volumes?
22Refer to the exhibit. In a 50 million record Account table, why might this query perform poorly?
23What is a 'Selective Query' in the context of Salesforce LDV?
24Which object type is most likely to cause performance issues in an LDV environment if not managed correctly?
25What is the consequence of having a 'non-selective' query running on an object with 50 million records?
26When designing a system for LDV, what is the role of an 'Indexed Field'?
27A data architect is designing a solution for a custom object Order__c that will contain 30 million records. Users need to frequently query orders by Customer__c (a lookup to Account) and Order_Date__c. The architect plans to create a composite custom index on Customer__c and Order_Date__c. Which consideration is most critical for the index to be used by the query optimizer?
28A Salesforce org has a custom object Log__c with 5 million records. The object has a lookup to Case. Users report that when they view a Case record, the related list of Log__c records takes a long time to load. The data architect decides to create a custom index on the Case lookup field. After the index is created, performance improves. Which statement best explains why the index improved performance?
29A custom object named Invoice__c contains 15 million records. Reports and list views frequently filter on a custom date field, Invoice_Date__c, and are timing out. The field is not indexed. Which action should a data architect take to improve query performance while keeping the field available for filtering?
30A Salesforce org has a custom object Invoice__c with 8 million records. The business requires a dashboard that shows the total invoice amount grouped by Account and by Fiscal Year. The dashboard must refresh quickly, even during peak usage. The Invoice__c object has a lookup to Account and a formula field Fiscal_Year__c that extracts the year from Invoice_Date__c. What is the most appropriate design to support this dashboard efficiently?
31A custom object 'Invoice__c' contains 8 million records and has a lookup to Account. A nightly batch job deletes approximately 2 million old invoices using Database.delete() in batches of 200. Users report that the batch sometimes fails with 'UNABLE_TO_LOCK_ROW' errors when running concurrently with account updates. What is the most likely cause of these lock contention errors?
32A Salesforce org has a custom object Shipment__c with 12 million records. Users frequently run a SOQL query that filters on Status__c and Order_Date__c, and sorts by CreatedDate. The query is timing out. The org has an index on Status__c and a custom index on Order_Date__c. What is the most likely reason the query is still slow?
33A data architect is planning to implement a Skinny Table for a custom object with 10 million records to improve query performance. Which two considerations are critical when designing the Skinny Table? (Choose two.)
34A company maintains a custom object Asset__c with 5 million records. They need to archive records older than 7 years to a Big Object for compliance. After archiving, the records must be queryable via SOQL for audits, but not editable. Which approach should an architect recommend?
35A data architect is reviewing a custom object that has grown to 8 million records. Users report that list views and reports are slow because they sort on a text field, Priority__c, which has only three possible values. What should the architect recommend to improve performance?
36A Salesforce org has a custom object Case_Comment__c with 5 million records. The object has a lookup to Case. Users frequently run SOQL queries that filter by CaseId and OrderBy CreatedDate. The queries are slow. What should be done to improve performance?
Diagnose slow queries on large objects by checking selectivity, indexes, and Query Plan output, then choose the right fix: custom index, skinny table, or rewritten SOQL. The key is recognizing when a field lacks an index and how that drives a full table scan.
The Courseiva SF-Data-Arch question bank contains 36 questions in the Large Data Volume Considerations domain. Click any question to see the full explanation and answer breakdown.
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