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| Vendor: | Salesforce |
|---|---|
| Exam Code: | Plat-Dev-301 |
| Exam Name: | Salesforce Certified Platform Developer II |
| Exam Questions: | 161 |
| Last Updated: | October 9, 2026 |
| Related Certifications: | Platform Developer II |
| Exam Tags: |
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Consider the following code snippet:78
Java
trigger OpportunityTrigger on Opportunity (before insert, before update) {
for(Opportunity opp : Trigger.new){
OpportunityHandler.setPricingStructure(Opp);
}
}
public class OpportunityHandler{
public static void setPricingStructure(Opportunity thisOpp){
Pricing_Structure_c ps = [Select Type_c FROM Pricing_Structure_c WHERE industry_c = :thisOpp.Account_Industry_c];
thisOpp.Pricing_Structure_c = ps.Type_c;
update thisOpp;
}
}
Which two best practices should the developer implement to optimize this code?
The provided code violates two fundamental Salesforce Apex best practices: bulkification and efficient use of trigger contexts. First, the code performs a SOQL query inside a loop (setPricingStructure is called inside the trigger's for loop). This is a critical performance issue because it consumes one SOQL query per record in the transaction. If 200 opportunities are updated at once, the code will hit the governor limit of 100 SOQL queries and throw an exception. To optimize this, the developer should use a Map or List to query all necessary Pricing_Structure__c records once, outside the loop (Option C), and then reference that collection during processing.
Second, the code is running in a before trigger context. In a before insert or before update trigger, any changes made directly to the records in Trigger.new are automatically saved to the database when the trigger completes without the need for an explicit DML update statement. Including an update thisOpp; statement (Option A) is not only redundant but dangerous, as it can trigger a recursive loop where the update re-fires the same trigger, leading to a 'Maximum stack depth reached' error. By removing the DML statement and bulkifying the query, the code becomes more efficient, scalable, and compliant with platform governor limits.
==========
A company wants to run different logic based on an Opportunity's record type. Which code segment handles this request and follows best practices?
A.
Java
List
Map
for (RecordType rt : recTypes) {
recTypeMap.put(rt.Name, rt.Id);
}
for (Opportunity o : Trigger.new) {
if(o.RecordTypeId == recTypeMap.get('New')) {
// do some logic Record Type 1
} else if (o.RecordTypeId == recTypeMap.get('Renewal')) {
// do some logic for Record Type 2
}
}
B.
Java
for (Opportunity o : Trigger.new) {
if (o.RecordType.Name == 'New') {
// do some logic Record Type 1
}
else if (o.RecordType.Name == 'Renewal') {
// do some logic for Record Type 2
}
}
C.
Java
List
Map
for (RecordType rt : recTypes) {
recTypeMap.put(rt.Name, rt.Id);
}
for (Opportunity o : Trigger.new) {
if (recTypeMap.get('New') != null && o.RecordTypeId == recTypeMap.get('New')) {
// do some logic Record Type 1
}
else if (recTypeMap.get('Renewal') != null && o.RecordTypeId == recTypeMap.get('Renewal')) {
// do some logic for Record Type 2
}
}
D.
Java
Id newRecordTypeId = Schema.SObjectType.Opportunity.getRecordTypeInfosByName().get('New').getRecordTypeId();
Id renewalRecordTypeId = Schema.SObjectType.Opportunity.getRecordTypeInfosByName().get('Renewal').getRecordTypeId();
for (Opportunity o : Trigger.new) {
if (o.RecordTypeId == newRecordTypeId) {
// do some logic Record Type 1
}
else if (o.RecordTypeId == renewalRecordTypeId) {
// do some logic for Record Type 2
}
}
In Salesforce Apex development, the 'Best Practice' for retrieving Record Type IDs is to avoid SOQL queries and instead use the Schema Describe methods. Option D utilizes Schema.SObjectType.Opportunity.getRecordTypeInfosByName(), which retrieves metadata directly from the application's local cache.
There are three primary reasons why Option D is superior to the others:
Governor Limits: Salesforce imposes a strict limit of 100 SOQL queries per synchronous transaction. Options A and C consume one of these limited queries just to fetch metadata. In a complex environment where many triggers and flows execute, 'saving' SOQL for actual business data is crucial. Describe calls do not count against SOQL limits.
Performance: Fetching data from the metadata cache is significantly faster than executing a database query, leading to lower CPU usage and faster trigger execution.
Data Integrity: Option B is a common anti-pattern that will result in a runtime error. In an Apex Trigger, the Trigger.new list only contains the fields of the object itself. It does not include related fields (cross-object fields) like RecordType.Name. Accessing o.RecordType.Name directly would return null or cause a 'System.SObjectException: SObject row was retrieved via SOQL without querying the requested field.'
By using the Schema class, the developer ensures that the code is bulk-safe, performant, and does not hardcode IDs, which can vary between Sandboxes and Production environments.
The use of the transient keyword in Visualforce page helps with which performance issue?
In Visualforce, the 'View State' is a hidden form field that maintains the state of the page (and the controller's variables) across postbacks to the server. If the View State becomes too large, it can slow down page loads and eventually hit the Salesforce View State limit (170KB), causing the page to crash.
The transient keyword is used to declare instance variables in Apex controllers that should not be saved in the View State. When a variable is marked as transient, its value is discarded after the request finishes and is not transmitted back to the client. This effectively reduces the size of the View State. It is commonly used for data that is needed only for the duration of the current request (like a large list of records displayed in a read-only table) and can be easily requeried or recalculated if needed.
A Salesforce org has more than 50,000 contacts. A new business process requires a calculation that aggregates data from all of these contact records. This calculation needs to run once a day after business hours. Which two steps should a developer take to accomplish this?
This scenario presents two distinct requirements: processing a large volume of data (50,000 records) and running the process at a specific time (once a day after business hours).
Database.Batchable (Option B): Processing 50,000 records in a single synchronous transaction will exceed Apex Governor Limits (specifically the CPU time limit or the heap size limit). Batch Apex allows the system to process these records in smaller chunks (batches), ensuring that the calculation completes without hitting limits.
Schedulable (Option C): To ensure the job runs 'once a day after business hours,' the Schedulable interface is required. The developer allows the class to be scheduled via the Apex Scheduler or the UI.
The standard pattern for this use case is to create a class that implements Schedulable, and inside its execute method, instantiate and execute the Batch class (Database.executeBatch). This combines precise timing with bulk processing capabilities.
A company has an Apex process that makes multiple extensive database operations and web service callouts. The database processes and web services can take a long time to run and must be run sequentially. How should the developer write this Apex code without running into governor limits and system limitations?123
This requirement specifies two critical constraints: the operations take a long time (likely exceeding synchronous CPU and timeout limits) and they must be performed sequentially.
Queueable Apex (Option D) is the optimal solution because it supports job chaining. Chaining allows one Queueable job to enqueue another Queueable job from its execute() method. This effectively creates a sequence where Job B only starts after Job A has successfully finished. Each job in the chain starts with a fresh set of governor limits, which is essential for 'extensive database operations' and long-running callouts.
Option C (@future) is unsuitable because future methods cannot be chained; you cannot call one future method from another. Furthermore, the order in which multiple future methods execute is not guaranteed by the platform, violating the 'sequential' requirement. Option A (Apex Scheduler) is intended for delayed or recurring tasks and is not designed for managing immediate sequential dependencies. Option B is a defensive coding practice but does not solve the underlying need to complete the work. Queueable Apex provides the programmatic control needed to manage complex, multi-step asynchronous workflows safely.
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