b2c-querying-data

name

b2c-querying-data

description

Write efficient data queries in B2C Commerce for products, customers, and orders. Use this skill whenever the user needs to search products on a storefront page, look up customer profiles, query orders, paginate search results, or fix slow category pages. Also use when they ask about performance problems with data access, replacing database-intensive APIs with index-backed alternatives, or choosing between search vs query methods — even if they just say "my category page is slow" or "how do I find customers by email".

Querying Data in B2C Commerce

Efficient data querying is critical for storefront performance and job stability. B2C Commerce provides index-backed search APIs and database query APIs—choosing the right one for each use case avoids performance problems.

Product Search (Storefront)

Use ProductSearchModel for all storefront product searches. It is index-backed and designed for high-traffic pages.

Basic Product Search

var ProductSearchModel = require('dw/catalog/ProductSearchModel');

var psm = new ProductSearchModel();
psm.setCategoryID('electronics');
psm.setOrderableProductsOnly(true); // Only in-stock products
psm.setSearchPhrase('laptop');
psm.search();

var hits = psm.getProductSearchHits();
while (hits.hasNext()) {
    var hit = hits.next();
    var productID = hit.productID;
    var minPrice = hit.minPrice;
    var maxPrice = hit.maxPrice;
}
hits.close();

Paging Search Results

Always page results—never load the full result set:

var ProductSearchModel = require('dw/catalog/ProductSearchModel');
var PagingModel = require('dw/web/PagingModel');

var psm = new ProductSearchModel();
psm.setCategoryID('mens-clothing');
psm.setOrderableProductsOnly(true);
psm.search();

var pagingModel = new PagingModel(psm.getProductSearchHits(), psm.count);
pagingModel.setPageSize(12);
pagingModel.setStart(0); // page offset

var pageElements = pagingModel.pageElements;
while (pageElements.hasNext()) {
    var hit = pageElements.next();
    // Render product tile
}

Getting Variation Data from Search Hits

Use ProductSearchHit methods instead of loading full product objects:

// GOOD: Get variation info from the search hit (index-backed)
var representedColors = hit.getRepresentedVariationValues('color');
var representedIDs = hit.getRepresentedProductIDs();
var minPrice = hit.getMinPrice();
var maxPrice = hit.getMaxPrice();

// BAD: Loading the full product and iterating variants (database-intensive)
var product = hit.product;
var variants = product.getVariants(); // Expensive!
var priceModel = product.getPriceModel(); // Expensive!

Search Refinements

var psm = new ProductSearchModel();
psm.setCategoryID('shoes');
psm.addRefinementValues('color', 'blue');
psm.addRefinementValues('size', '10');
psm.setPriceMin(50);
psm.setPriceMax(200);
psm.search();

// Get available refinement values for the current result set
var refinements = psm.getRefinements();
var colorValues = refinements.getAllRefinementValues('color');

ProductSearchModel API Summary

Method	Description
search()	Execute the search
setCategoryID(id)	Filter by category
setSearchPhrase(phrase)	Set search keywords
setOrderableProductsOnly(flag)	Exclude out-of-stock
addRefinementValues(name, value)	Add refinement filter
setPriceMin(price) / setPriceMax(price)	Price range filter
setSortingRule(rule)	Set sorting rule
getProductSearchHits()	Get result iterator
getRefinements()	Get available refinements
count	Total result count

Order Queries

OrderMgr.searchOrders / queryOrders

Use searchOrders for index-backed order lookups and queryOrders for database queries:

var OrderMgr = require('dw/order/OrderMgr');
var Order = require('dw/order/Order');

// Index-backed search (preferred for common lookups)
var orders = OrderMgr.searchOrders(
    'customerEmail = {0} AND status != {1}',
    'creationDate desc',
    '[e-mail]',
    Order.ORDER_STATUS_FAILED
);

while (orders.hasNext()) {
    var order = orders.next();
    // Process order
}
orders.close(); // Always close iterators

Query by Date Range

var OrderMgr = require('dw/order/OrderMgr');
var Calendar = require('dw/util/Calendar');
var Order = require('dw/order/Order');

var startDate = new Calendar();
startDate.add(Calendar.DAY_OF_YEAR, -7);

var orders = OrderMgr.searchOrders(
    'creationDate >= {0} AND status = {1}',
    'creationDate desc',
    startDate.time,
    Order.ORDER_STATUS_NEW
);

while (orders.hasNext()) {
    var order = orders.next();
    // Process
}
orders.close();

searchOrders vs queryOrders

Aspect	searchOrders	queryOrders
Backing	Search index	Database
Performance	Fast for indexed fields	Slower, full table scan possible
Use when	Querying indexed attributes (status, email, dates)	Querying non-indexed or custom attributes
Result limit	Up to 1000 hits	No hard limit (but use paging)

Prefer searchOrders for storefront and high-traffic code paths. Use queryOrders only when you need to query attributes not available in the search index.

Customer / Profile Queries

CustomerMgr (Preferred)

Use searchProfiles for index-backed searches and processProfiles for batch processing in jobs:

var CustomerMgr = require('dw/customer/CustomerMgr');

// Index-backed search (storefront use)
var profiles = CustomerMgr.searchProfiles(
    'email = {0}',
    'lastLoginTime desc',
    '[e-mail]'
);

while (profiles.hasNext()) {
    var profile = profiles.next();
    // Process profile
}
profiles.close();

Batch Processing (Jobs)

Use processProfiles for jobs that need to iterate over many profiles—it has optimized memory management:

var CustomerMgr = require('dw/customer/CustomerMgr');

function processProfile(profile) {
    // Process each profile individually
    // Memory is managed automatically
}

// Process all profiles matching the query
CustomerMgr.processProfiles('gender = {0}', processProfile, 1);

Important: processProfiles replaces the older queryProfiles and SystemObjectMgr.querySystemObjects for customer data. It uses the full-text search service with better performance and memory characteristics.

Customer Query Behaviors

• Wildcards (*, %, +) are filtered from queries and replaced by spaces
• LIKE and ILIKE execute as full-text queries (match whole words, not substrings)
• LIKE is case-insensitive
• Combining AND and OR in the same query degrades performance
• Range queries (e.g., a > b) impact performance
• Results are limited to the first 1000 hits

System Object Queries (SystemObjectMgr)

For querying system objects other than customers (e.g., SitePreferences, catalogs):

var SystemObjectMgr = require('dw/object/SystemObjectMgr');

// Query system objects
var results = SystemObjectMgr.querySystemObjects(
    'Profile',
    'custom.loyaltyTier = {0}',
    'lastLoginTime desc',
    'Gold'
);

while (results.hasNext()) {
    var obj = results.next();
    // Process
}
results.close();

Note: For customer profiles specifically, prefer CustomerMgr.searchProfiles or CustomerMgr.processProfiles over SystemObjectMgr.querySystemObjects—they use the search index and perform significantly better.

Database-Intensive APIs to Avoid

These APIs hit the database directly and are expensive on high-traffic pages. Replace them with index-friendly alternatives. See Performance-Critical APIs for the complete list with impact details.

Avoid (Database-Intensive)	Use Instead (Index-Friendly)
Category.getProducts() / getOnlineProducts()	ProductSearchModel.setCategoryID()
ProductMgr.queryAllSiteProducts()	ProductSearchModel.search()
Product.getVariants() / getVariationModel()	ProductSearchHit methods
Product.getPriceModel() (in loops)	ProductSearchHit.getMinPrice() / getMaxPrice()
CustomerMgr.queryProfiles()	CustomerMgr.searchProfiles() or processProfiles()

Related Skills

• b2c-ordering — Order lifecycle, status transitions, creation flows
• b2c-custom-objects — Custom object CRUD, OCAPI search queries

Best Practices

Do

• Always close iterators — unclosed iterators leak resources (results.close())
• Page results — use PagingModel or limit result counts; never load unbounded result sets
• Put all filtering in the query — don't post-process or filter results in custom code
• Use index-backed APIs — ProductSearchModel, searchOrders, searchProfiles for storefront pages
• Use processProfiles for batch customer operations in jobs (optimized memory)
• Limit page size — maximum ~120 products per page for search result pages
• Use setOrderableProductsOnly(true) — to filter unavailable products at the search level

Don't

• Don't iterate over product variants on search result pages — use ProductSearchHit methods instead
• Don't post-process search results — all criteria must go into the query for efficient execution
• Don't use queryAllSiteProducts() on storefront pages — it bypasses the search index
• Don't combine AND + OR in customer queries — it degrades performance
• Don't rely on getting more than 1000 results — search APIs cap at 1000 hits
• Don't call database-intensive APIs on high-traffic pages — category pages, search results, PDPs, and homepage

Job-Specific Guidelines

• Use processProfiles over queryProfiles for large customer data sets
• Design loop logic so memory consumption doesn't grow with result set size
• Keep only the currently processed object in memory; don't retain references
• Stream data to files regularly; don't build large structures in memory
• Limit transaction size to under 1000 modified business objects

Detailed References

• Performance-Critical APIs — full list of index-friendly vs database-intensive APIs