Custom Catalog Filter Module for 1C-Bitrix

Imagine: your catalog has grown to 50,000 products, and the standard Bitrix filter starts loading the page in 10 seconds. We've encountered this on almost every second project. Over 8 years developing modules for Bitrix, we've crafted a solution that provides a performance guarantee even on catalogs with 200+ properties. Savings on server resources through optimized queries can reduce infrastructure costs by up to 60% for high-volume catalogs. Typical investment starts at $2,000 for a basic module.

The standard component catalog.section.list with the filter catalog.section.list.filter works out-of-the-box, but with a large number of properties (b_iblock_element_prop_s*, b_iblock_element_prop_m*), queries become slow due to multiple JOINs. Checkboxes show all possible values without considering how many products are behind them — users click and get an empty result. Dynamic filter rebuilding kills performance on catalogs from 10,000 items.

Denormalized Index Acceleration of Filtering

The root cause is the storage architecture of infoblock properties. Each property requires a separate JOIN. Our solution is a denormalized filter index. The module creates and maintains a table myvendor_filter_index where for each product a flat structure of all filterable property values is stored in JSONB:

CREATE TABLE myvendor_filter_index (
    element_id  INT PRIMARY KEY,
    section_id  INT NOT NULL,
    price_min   DECIMAL(12,2),
    in_stock    BOOLEAN,
    props       JSONB NOT NULL  -- {"brand": "Samsung", "color": ["black", "white"]}
);

CREATE INDEX idx_filter_props ON myvendor_filter_index USING gin(props);
CREATE INDEX idx_filter_section ON myvendor_filter_index(section_id);
CREATE INDEX idx_filter_price ON myvendor_filter_index(price_min);

The indexing approach uses GIN which supports advanced operators like @>, ?, ?|. The index is updated via the OnAfterIBlockElementUpdate event for a specific product and via an agent for bulk recalculation. According to our tests with EXPLAIN ANALYZE, the JSONB index executes queries 15 times faster than standard JOINs on catalogs from 50,000 products, reducing query plan cost from thousands to tens.

Importance of Smart Counters (Facets) for UX

This is a key feature — showing next to each filter value the number of products that correspond to it taking into account already selected filters. This behavior is called faceted search (Faceted search).

-- Counting options for the filter "Brand"
-- taking into account the already selected filter "Color: black"
SELECT
    props->>'brand' AS brand,
    COUNT(*) AS cnt
FROM myvendor_filter_index
WHERE
    section_id = :section_id
    AND in_stock = true
    AND props @> '{"color": "black"}'::jsonb
GROUP BY props->>'brand'
ORDER BY cnt DESC;

This query returns all brands with the count of in-stock black products. A separate such query is executed for each property — but it's fast thanks to the GIN index. The count results are cached with tags based on the section and the active filter set. When any product changes, the tag is reset. Cache TTL is 30 minutes.

AJAX Update Mechanism

When the filter changes, the page does not reload: an AJAX request goes to /api/catalog/filter/, the server returns JSON with the IDs of filtered products and updated counters. The frontend updates the list and checkboxes. The browser history is updated via history.pushState. This ensures smooth navigation without flickering.

Filter URL Scheme

The filter builds "clean" URLs that are SEO-friendly:

• /catalog/smartphones/brand-samsung/color-black/ — a page with filters and product list
• /catalog/smartphones/brand-samsung/ — a category filter with its own H1 and description

Key filter pages can have unique meta tags set via the module's admin interface. Others are automatically generated based on a template. This improves indexing and ranking in search engines.

Results Ranking

In addition to filtering, the module manages sorting: by price, popularity (number of orders from b_sale_basket), novelty, rating. "Popularity" is recalculated by an agent once a day and stored in myvendor_filter_index.popularity_score.

Comparison: Standard Filter vs Our Module

Stages of Filter Module Development

1. Audit of the current catalog architecture and infoblock properties.
2. Designing the denormalized index schema based on your data volume.
3. Implementing facets with smart counters and caching.
4. Configuring AJAX updates and clean URLs.
5. Query optimization for catalogs up to 500,000 products.
6. Documentation for maintenance and training administrators.

What's Included in the Deliverables

• Complete source code of the custom filter module
• Detailed technical documentation and deployment guide
• Admin training session (up to 4 hours)
• 6 months of support and bug fixes
• Performance report with before/after metrics

Development Timelines

The number of infoblock properties and catalog size are the main factors in choosing the architecture. With 200+ properties, the JSONB approach requires careful index schema design.

Why Choose Us

We have been developing modules for Bitrix for over 8 years, implementing 40+ projects with catalog filtering. We guarantee performance on volumes from 10,000 products. We offer turnkey filter module development — write to us for a free project evaluation. The package includes everything you need: documentation, training, and ongoing support. Contact us today to get a customized solution within your budget.

1C-Bitrix Module Development and Setup

The main trap of Bitrix is init.php. You add an OnBeforeIBlockElementUpdate handler there, then another one — a year later the file is 2000 lines, and on every hit all that code executes. We move business logic into full-fledged modules with D7 ORM, custom tables, and administrative interface. The module can be disabled, transferred to another project, covered with tests — none of that is possible with init.php. Our team has 10+ years of Bitrix experience, certified specialists, and a 6-month code guarantee. Request a consultation — we'll explain how to migrate legacy code to a modular architecture.

Why is init.php the worst place for business logic?

Init.php does not support class autoloading, lacks an isolated namespace, cannot be unit tested, and cannot be disabled without editing the file itself. Every handler written there runs on every request, even if not needed. In a module, you register handlers through EventManager, and they only execute when the event occurs. Performance difference: up to 3x with 10+ handlers.

Standard Modules: Typical Problems and Solutions

Information blocks. IBlock architecture is the first thing we review on any project. A classic mistake: one catalog infoblock with 80 properties, 30 of which are multiple. The b_iblock_element_property table swells to millions of rows, and CIBlockElement::GetList with filtering on three properties does a full scan. We move reference data to Highload-blocks, eliminate multiple properties where possible, and design the structure for 5x growth.

e-Store (sale). Cart business rules are a separate story. We set discount priorities to prevent two campaigns from giving 60% instead of 30%, connect payment handlers, and write custom validation via OnSaleOrderBeforeSaved.

Search. The built-in search module with morphology works up to 10–15 thousand elements. Beyond that — Elasticsearch. We configure it via the Bitrix search module API, indexing through CSearchFullText or custom indexers.

Highload-blocks for dictionaries, logs, user data — instead of bloated IBlocks. Direct queries via Bitrix\Highloadblock\HighloadBlockTable, custom tables instead of the EAV structure of standard infoblocks. A million records — no degradation.

Mail events. Configuration is not just templates in b_event_message. The key is SPF, DKIM, DMARC on the DNS, otherwise transactional emails go to spam. We check deliverability and set up bounce handling.

How to Design Infoblocks for Performance?

We use Highload-blocks for reference data (colors, sizes, manufacturers) that are not involved in complex queries. For SKUs — a separate infoblock with linking via IBLOCK_ELEMENT_PROPERTY. Enable INDEX_PROPERTY for frequently filtered properties. Tagged caching: when an element changes, only the related cache is cleared. Highload-blocks process up to 10x faster than infoblocks with multiple properties on volumes of 100,000 records.

Custom Module Development

Each module follows the structure /local/modules/vendor.modulename/:

• install/index.php — setup class, create tables via $DB->RunSQLBatch()
• lib/ — D7 ORM classes, extending Bitrix\Main\ORM\Data\DataManager
• admin/ — administrative pages using CAdminList, CAdminForm
• include.php — autoloading, event handler registration via EventManager::getInstance()->registerEventHandler()
• REST API endpoints via \Bitrix\Rest\RestManager

The module registers in the system, appears in the "Installed Solutions" list, and has its own settings at /bitrix/admin/settings.php?mid=vendor.modulename. It can be enabled, disabled, and updated through UpdateSystem or custom migration mechanics.

Examples of implemented tasks:

• Campaign management — visual condition builder via CAdminCalendar, timers via agents (CAgent::AddAgent), analytics linked to the sale module
• Cost calculator — React widget on the frontend, REST API in the module, formulas stored in a Highload-block
• Booking system — real-time calendar, locking via $DB->StartTransaction() / $DB->Commit() on concurrent requests, integration with channel manager via webhook

Components and Composite Cache

Component customization via result_modifier.php and component_epilog.php, not by editing template.php of the standard template. This way core updates are painless.

Composite cache ("Composite Site" technology) — the server sends ready HTML, bypassing PHP routing. Dynamic areas (cart, authorization) are loaded via CBitrixComponent::setFrameMode(true) and AJAX. TTFB drops to 30–50 ms. But there are caveats: not all components are compatible, $APPLICATION->ShowPanel() breaks composite, and careful markup of <div id="bx-composite-..."> is required.

What to Check Before Installing a Marketplace Module?

Before installing a module from the marketplace, an audit is mandatory. We check: SQL queries without prepared statements (hello SQL injection), direct use of $_REQUEST without filtering, use of outdated kernel API instead of D7, conflicts with the composite cache module. A module with no updates for over a year and a few dozen installations is likely a problem on the next PHP update. A typical case: a module calls CIBlockElement::GetList with no cache reset — the site crashes with 5000 elements.

Migration to D7

When upgrading PHP or switching to a new edition — refactor outdated calls:

• CIBlockElement::GetList() → Bitrix\Iblock\Elements\ElementTable::getList()
• CSaleOrder::GetList() → Bitrix\Sale\Order::getList()
• CModule::IncludeModule() → Bitrix\Main\Loader::includeModule() Testing on staging, rollback via git on issues.

According to official 1C-Bitrix documentation, D7 ORM is the recommended tool for working with data, providing type safety and automatic query generation.

Comparison: Init.php vs Module

Module Development Scope and Cost

What is included in module development?

• Technical specification and architectural plan
• Code following PSR-4 and Bitrix code style
• Unit tests (PHPUnit) for business logic
• Integration tests for events and REST API
• Installation, configuration, and API documentation
• Repository and documentation access
• Administrator training for module usage
• 6-month warranty support

Estimated timelines and complexity:

Cost is calculated individually — contact us for a project estimate.

Module Testing

Unit tests via PHPUnit cover business logic: discount calculation, validation, document generation. Mocks for Bitrix\Main\Application::getConnection() allow tests to be DB-independent. Integration tests verify event handlers on a real database — OnAfterIBlockElementAdd, OnSaleOrderSaved, etc. REST API endpoints are tested via curl or PHPUnit HTTP client. Critical for modules working with b_sale_order, b_catalog_price — where errors cost money.

Compatibility is checked on PHP 7.4, 8.0, 8.1, 8.2 and editions: Standard, Small Business, Business. We check conflicts with popular marketplace modules — they often intercept the same events. Load testing: measurements on 10K, 100K, 1M records, profiling via Xdebug for memory leaks and N+1 queries.

Practical Examples

Campaign module for an electronics chain. The built-in sale module discounts did not cover scenarios like "2+1", a gift with purchase over a certain amount, or combined conditions. We built a visual builder: marketers create rules via drag-and-drop without development tickets. Campaign calendar, auto-deactivation via agents, analytics linked to b_sale_order — conversion, average check, usage count. Time to launch a new campaign dropped from two days to half an hour.

Calculator for builders. Parameters (area, materials, number of floors) → formula → preliminary estimate → lead to CRM via CRest::call('crm.lead.add'). Regional coefficients and seasonal markups from a Highload-block, material prices from 1C exchange. The number of target leads increased by a third: clients see a breakdown before calling a manager.

Booking for a hotel chain. Real-time availability via AJAX requests to a custom table vendor_booking_slots, seasonal tariff calculation, synchronization with Booking.com via channel manager API. Room locking on concurrent booking via SELECT ... FOR UPDATE in transactions. Timezones handled via \DateTimeZone — a guest from Vladivostok and a manager from Moscow see the same picture.

We will evaluate your project within one day. Write to us — we'll tell you what is included in turnkey development. Contact us for a consultation on your project. Order a custom module development — get a ready solution with documentation and support.