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HCL Commerce is a high-availability, highly scalable and customizable e-commerce platform. Able to support hundreds of thousands of transactions per day, HCL Commerce allows you to do business with consumers (B2C) or directly with businesses (B2B). HCL Commerce uses cloud friendly technology to make deployment and operation both easy and efficient. It provides easy-to-use tools for business users to centrally manage a cross-channel strategy. Business users can create and manage precision marketing campaigns, promotions, catalog, and merchandising across all sales channels. Business users can also use AI enabled content management capabilities.
Customizing
The topics in the Customizing section describe tasks performed by an application developer to customize HCL Commerce.
Search
HCL Commerce comes with a powerful and fully integrated search function. The search functions in HCL Commerce provide an enriched customer experience, with features such as automatic search term suggestions and spelling correction. Since it is built on industry standards, HCL Commerce Search is highly flexible and extensible. Starter stores can use the search engine's most sophisticated features without requiring extra customization. Starting with Version 9.1, HCL Commerce Search with Elasticsearch microservices manage indexing and other crucial tasks, with no performance impact on the storefront or transaction server.
Elasticsearch-based solution
The topics in this section describe tasks performed by an application developer to customize the Elasticsearch-based search solution. You can extend the Ingest Service and Query Service to meet your business requirements.
Extending the Query Service
The Query service builds the search expressions and then hands the expression to Elasticsearch. You can customize this service to create your own expression providers, pre-processors, post-processors, and custom handlers as per your business requirements. There is no JDBC connectivity from the Query service to the Commerce database. This architecture ensures that the application can be stateless and scaled independently. Business data can still be provided to the Query service either by indexing or through other micro-services.
Query service configuration
You can build profiles for Ingest service customizations in ZooKeeper. Endpoints for configuring both development and production environment customizations are available. Note that these endpoints are available from within the Data environment and Development environment only. They are not available for the shopper to use through the Query service in either the Commerce Authoring or Live environment.
Adding custom range filter to Matchmaker
Inside ZooKeeper is a node with the name filter, which is used to parse or ignore redundant words from the search term during Natural Language Processing. At present the operations supported with filter are update, delete, and retrieve. The add operation is currently not supported. New records are added using the POST request method. The existing records are updated (add, update, delete record) using the PATCH request method.

Documentation
HCL Commerce is a high-availability, highly scalable and customizable e-commerce platform. Able to support hundreds of thousands of transactions per day, HCL Commerce allows you to do business with consumers (B2C) or directly with businesses (B2B). HCL Commerce uses cloud friendly technology to make deployment and operation both easy and efficient. It provides easy-to-use tools for business users to centrally manage a cross-channel strategy. Business users can create and manage precision marketing campaigns, promotions, catalog, and merchandising across all sales channels. Business users can also use AI enabled content management capabilities.
- Getting started
  HCL Commerce has different advantages for business users, administrators and developers. HCL Commerce targets each of these roles with a tailored set of offerings so that each of your users can get maximum benefit.
- Installing and deploying
  Learn how to install and deploy HCL Commerce development environments and HCL Commerce production environments.
- Migrating
  Before you migrate to HCL Commerce Version 9.1, review this information to help plan and execute your migration.
- Operating
  Topics in the Operating category highlight tasks that are typically performed by business users, customer support representatives, to complete their day-to-day tasks in the operation of the HCL Commerce site.
- Integrating
  Topics in the Integrating category highlight the tasks that are commonly performed for using HCL Commerce in combination with other products.
- Administering
  Topics in the Administering category highlight tasks that are typically performed by the Site Administrator, to support daily operations of the HCL Commerce site.
- Customizing
  The topics in the Customizing section describe tasks performed by an application developer to customize HCL Commerce.
  - Customizing Management Center for HCL Commerce
    HCL Commerce allows you to pull the GIT bundle of Management Center source code and start the application locally to customize the Management Center.
  - Managed asset deployment
    Managed assets are files that are uploaded by business users to be used for store marketing, or to supplement products. They are added to HCL Commerce through the Assets tool or the Marketing tool in Management Center. By default, managed assets are extracted and deployed through the HCL Commerce EAR. To maintain performance in a large-scale production environment, site administrators must switch to alternative extraction and deployment methods for managed assets.
  - HCL Commerce development environment
    HCL Commerce Developer is the development toolkit for customizing a HCL Commerce application.
  - Functional architecture
    Functional architecture provides both the set of patterns used to implement the business functionality and the frameworks in which these business functions execute.
  - Persistent object model
    HCL Commerce deals with a large amount of persistent data. There are numerous tables defined in the current database schema. Even with this extensive schema, however, you might need to extend or customize the database schema for your particular business needs.
  - Creating your custom store
    After you install and set up your programming environment, you can create your custom store and customize your storefront. You must ensure that the store server is properly configured, and that your store assets are moved to the Store server.
  - Presentation layer
    HCL Commerce uses Java Server Pages (JSP) to implement the view layer of the Model-View-Controller (MVC) design pattern. The view layer is in charge of retrieving data from the database through the use of data beans and formatting it to meet the display requirements. The view layers determines whether the request is sent to a browser or streamed out as XML. JSP files present a clean separation between data content and presentation.
  - Controller layer
    The Controller layer is the conductor of operations for a request. It controls the transaction scope and manages the session related information for the request. The controller first dispatches to a command and then calls the appropriate view processing logic to render the response.
  - Business logic layer
    The business logic layer is the business components that provide OAGIS services to return data or start business processes. The presentation layer uses these OAGIS services to display data, or to invoke a business process. The business logic provides data required by the presentation layer. The business logic layer exists because more than just fetching and updating data is required by an application; there is also additional business logic independent of the presentation layer.
  - Persistence layer
    The interaction between the business objects and persistence layer is isolated in an object called the Business Object Mediator. Business object document (BOD) commands interact with the Business Object Mediator to handle the interaction with the logical objects and how they are persisted.
  - Business model information model
    A business model, a representation of the business processes used throughout the site, provides a sample commerce solution which includes an organization structure, default user roles and access control policies, one or more starter stores, administration tools, and business processes that demonstrate best practices. A business model can be customized to support business requirements and scenarios. HCL Commerce provides sample business models that show some common commerce solutions. These business models are created by setting up an organization hierarchy structure, access control policies, stores, and contracts that help satisfy the necessary business requirements.
  - Business models
    Before starting to develop your site with HCL Commerce, you need to determine the business model supported by HCL Commerce that best represents the purpose of your site. Usually sites created with HCL Commerce will be implemented based on of one of these business models.
  - Store data information model
    Store data is the information that is loaded into the Transaction server database, which allows your store to function. The URL Registry Entries and View Registry Entries packages are included in the diagram, but they are not database assets. These entries are presentation configuration (that is, struts actions and forwards) that must be deployed. URL registry entries are shown in the diagram to illustrate the entire store data information model. To operate properly, a store must have the data in place to support all customer activities. For example, in order for a customer to make a purchase, your store must contain a catalog of goods for sale (catalog data), the data associated with processing orders (tax and shipping data), and the inventory to fulfill the request (inventory and fulfillment data).
  - Customizing HCL Commerce
    You can extend the HCL Commerce product to fit your business needs. This topic describes the prerequisite skills and required knowledge that you need to customize business logic. After you have the required knowledge, use HCL Commerce Developer to take tutorials that guide you step-by-step through various customization scenarios.
  - Run Engine command framework
    The Run Engine command framework provides predefined commands, that you can use to change environment parameters or container configurations. This framework is built into the HCL provided Docker images.
  - GraphQL for HCL Commerce
    The GraphQL markup language is available for any API. It is a server-side interpreter for processing queries using a data type system you design. With GraphQL, your data and code are independent of any database or storage system.
  - Representational State Transfer (REST) services
    HCL Commerce uses Representational State Transfer (REST) services to provide a framework that can be used to develop RESTful applications on several platforms. These platforms can include web, mobile, kiosks, and social applications.
  - Web services
  - Search
    HCL Commerce comes with a powerful and fully integrated search function. The search functions in HCL Commerce provide an enriched customer experience, with features such as automatic search term suggestions and spelling correction. Since it is built on industry standards, HCL Commerce Search is highly flexible and extensible. Starter stores can use the search engine's most sophisticated features without requiring extra customization. Starting with Version 9.1, HCL Commerce Search with Elasticsearch microservices manage indexing and other crucial tasks, with no performance impact on the storefront or transaction server.
    - Search terminology
      HCL Commerce Search uses a number of specialized terms. A concise list of the most commonly used terms is provided to get you started.
    - Migrating to Elasticsearch
      You have several options in migrating from the Solr search platform to the Version 9.1 Elasticsearch solution.
    - Elasticsearch-based solution
      The topics in this section describe tasks performed by an application developer to customize the Elasticsearch-based search solution. You can extend the Ingest Service and Query Service to meet your business requirements.
      - Indexing choices
        You have two options for indexing Extended Site (eSite) stores, the legacy eSite Store indexing model, or the Catalog Asset Store (CAS) model. The CAS model is recommended because of its speed and scalability.
      - Extending the Ingest service
        The Version 9.1 HCL Commerce Search service includes Ingest and Elasticsearch, which together form a distributed, scalable search and analytics engine. You can chain together the Ingest service's rule-based aggregations to boost relevancy for hero SKUs or certain facets, and use sophisticated metrics to analyze your search performance.
      - Extending the Query Service
        The Query service builds the search expressions and then hands the expression to Elasticsearch. You can customize this service to create your own expression providers, pre-processors, post-processors, and custom handlers as per your business requirements. There is no JDBC connectivity from the Query service to the Commerce database. This architecture ensures that the application can be stateless and scaled independently. Business data can still be provided to the Query service either by indexing or through other micro-services.
        Query service API specifications
        The Query service uses a REST API for command and communications. There are two specifications you can use: the Version 2 API intended for use with the React storefronts; and a Version 1 spec designed for backward compatibility.
        Query service configuration
        You can build profiles for Ingest service customizations in ZooKeeper. Endpoints for configuring both development and production environment customizations are available. Note that these endpoints are available from within the Data environment and Development environment only. They are not available for the shopper to use through the Query service in either the Commerce Authoring or Live environment.
        Search profiles
        HCL Commerce Search uses search profiles to control the storefront search experience at a page-level. Search profiles group sets of search runtime parameters, such as search index name, search index fields, expression providers, paging, and sorting.
        Configuring Query services in ZooKeeper
        You can build profiles for Ingest service customizations in ZooKeeper. Endpoints for configuring both development and production environment customizations are available. Note that these endpoints are available from within the Data environment and Development environment only. They are not available for the shopper to use through the Query service in either the Commerce Authoring or Live environment.
        Configuring Query xC custom extension
        The /configuration endpoint is used to add the customized configuration details in ZooKeeper node. There is a root node in ZooKeeper with the name /configuration, and inside the root node are child nodes where you can add the configuration.
        Configuring Query runtime custom configuration
        To customize the ZooKeeper node, you can also add a wc-component.json file to override or to add new configuration properties. To know more about component configuration properties refer to search/concepts/componentconfigprop.html
        Remotely debugging the Query service
        You can remote debug extensions to your Query service. This remote facility enables your developers to see the current state of variables, and leverage code hot swapping to see your changes reflected in the server as they develop code.
        Managing stop words
        ZooKeeper is used to manage several kinds of customizable lists of associated terms used by the search function. Stop words are removed from the query before it is processed. Each custom list is accessible and you can directly change stop words in ZooKeeper.
        Working with Search Term Associations (STAs)
        Search Term Associations (STAs) enhances, diversifies, or replaces existing search results. Additionally, search phrases can be associated with particular landing pages in the store. A product recommendation strategy using STA is used to increase store sales by modifying search submissions to target or increase search results.
        Custom color configurations
        In the HCL Commerce Search you can run natural-language searches using colors in product queries. In ZooKeeper, colors are registered as a root node, and en_US is registered as a child of colors. Using this hierarchy you can maintain colors based on locale.
        Adding custom range filter to Matchmaker
        Inside ZooKeeper is a node with the name filter, which is used to parse or ignore redundant words from the search term during Natural Language Processing. At present the operations supported with filter are update, delete, and retrieve. The add operation is currently not supported. New records are added using the POST request method. The existing records are updated (add, update, delete record) using the PATCH request method.
        Adding custom configuration to Measurement Matchmaker
        The Natural Language Processing feature enables you to use units of measure. This feature is available to both the query service, for analyzing the search query string, and NiFi for analysing the attributes of products. Units of measure are updated and deleted using the PATCH request method. To delete a unit of measure, pass an empty value as the key. At present the operations supported with units of measure are update, delete, and retrieve. The add operation is currently not supported. New records are added using the POST request method. The existing records are updated (add, update, delete record) using the PATCH request method.
        Adding custom configuration to Dimension Matchmaker
        In the HCL Commerce Search, you can run natural-language searches using product dimensions (Length, Width, Height) in product search queries. The product dimension pattern can be configured in the zookeeper dimensions node. If no pattern is specified, then the default WLH pattern is used.The product depth dimension can also be configured in the zookeeper dimensions node by setting up the potential value (Width, Length, Height) for the key. This value of the key is used as a replacement of D (deep/depth/thick/thickness) while indexing (for example, 10 m L x 20 m H x 30 " D ) and while searching (for example, find 10 m L x 20 m H having depth 20 " ) products at the storefront. New product dimensions are added using the POST request method. The existing product dimensions are updated using the PATCH request method.
        Adding custom configuration to part number pattern
        In the HCL Commerce Search, you can run natural-language searches using product part number. Apart from the default part number patterns, you can also add the new part number patterns to run the search using the product part number. For more information on the search based on product part number, refer to search/concepts/csdquery_nlp.html#csdquery_nlp__Product_part_number. The part number pattern can be configured in the zookeeper wc-component node. You can add comma-separated pattern in this node. New part number patterns are added using the POST request method. The existing part number patterns are updated using the PATCH request method.
        Adding custom NER nouns
        Name Entity Recognition (NER) is one of the most common text pre-processing techniques used in Natural Language Processing (NLP). NER is used in many fields in Artificial Intelligence (AI) including Natural Language Processing (NLP) and Machine Learning. Apart from the default entities for NER in the Stanford CoreNLP Natural Language Processor, you can also add custom language specific nouns and classifications for NER. The custom noun and classification for NER can be configured in the zookeeper filter node. New nouns and classifications are added using the POST request method. The existing nouns and classifications are updated using the PATCH request method.
        Extending NLP profiles
        A Natural Language Processor (NLP) profile is used to control the preprocessing flow of search terms before executing an Elasticsearch query. The profile is a .json file and stored in your query runtime container.
        Tuning index field boost relevancy
        You can use the node index_field_relevancy to add the boost value for an index field at query time. This is used to boost the result based on the field. You can add or update using the POST method; to delete the existing value use the PATCH method for the endpoint by passing an empty value as its key.
        Enabling deep search sequencing
        Deep search sequencing refers to the process of ordering products within a category and all its subcategories. This process is used to enhance the storefront by enabling category-based browsing flows for your customers.
        Hero product image (Product grouping)
        Set up a Hero product image to increase the relevancy of products and search results in the storefront.
        Customizing spell check correction suggestions
      - Extending Elasticsearch
        You can customize the behavior of Elasticsearch through ZooKeeper, or by adding your own REST API endpoints. A variety of approaches to extending the Elasticsearch service are discussed and methods are provided.
      - Fine-tuning search results
        HCL Commerce Search helps you to enhance the search experience of shoppers by adjusting your search results based on your shoppers' interactions at the storefront.
      - CI/CD strategy to deploy customizations
        The HCL Commerce Search Elasticsearch solution does not dictate the data repository or scripting needed to automate a Continuous Integration/Continuous Delivery (CI/CD) pipeline. You have the flexibility to use your own data repository and build structure. The following topics describe a recommended approach including a suggested data pipeline structure.
      - Migrating Elasticsearch customizations
        You can migrate existing Solr extensions to the data service model, and keep your custom connectors and NiFi flows up to date with the latest version of HCL Commerce Search.
    - Solr-based solution
      In keeping with HCL's commitment to current and open standards, HCL Commerce Search uses Apache Lucene as the basis of its Search framework. Lucene powers the Apache Solr search engine and the Elasticsearch search engine. The indexing pipeline is a more open, flexible and scalable and is tightly integrated with the data service. Using the underlying dataflow technology and architecture, you can easily customize the pipelines. This open-standards approach considerably eases the process of integrating Search with existing and third-party applications.
- Tutorials
  HCL Commerce provides many tutorials to help you customize and understand your HCL Commerce instance and stores.
- Samples
  Topics in the Samples category highlight the various samples that are provided with HCL Commerce.
- Compliance
  The following section describes how you can leverage HCL Commerce features and functionality to help your site be compliant with different privacy and security standards.
- Securing
  These topics describe the security features of HCL Commerce and how to configure these features.
- Performance
  Topics in the Performance section describe the means by which to plan, implement, test, and re-visit the optimization of HCL Commerce site performance.
- Troubleshooting
  Topics in the Troubleshooting section highlight common issues that are encountered with HCL Commerce, and how they can be addressed or mitigated.
- Reference
  Topics in the Reference section contain all of the HCL Commerce reference documentation.

Adding custom range filter to Matchmaker

Inside ZooKeeper is a node with the name filter, which is used to parse or ignore redundant words from the search term during Natural Language Processing. At present the operations supported with filter are update, delete, and retrieve. The add operation is currently not supported. New records are added using the POST request method. The existing records are updated (add, update, delete record) using the PATCH request method.

Note: No range filter configurations are available for the Finnish or Swedish languages in the default configuration. You can add these languages using the configuration endpoint.

Endpoint

The endpoint for this service is:

http://data_environment_hostname:30921/search/resources/api/v2/configuration?nodeName=filter&envType=auth&locale=en_US

Example

Following is a sample filter.json file, for filtering or term-ignore.

{
	"quarter": "TO_NUMBER~0.25"
	"half": "TO_NUMBER~0.50",
	"one and half": "TO_NUMBER~1.5",
	"but": "IGNORE_TERM",
	"usd": "IGNORE_TERM",
	"sterling": "IGNORE_TERM",
	"up to": "FILTER_LTE~1",
	"less than": "FILTER_LTE~1"
	"expensive": "FILTER_GTE~-1",
}