Index

Index is crucial for managing your product data's structure and organization. It plays a pivotal role in how information is indexed and accessed, directly influencing the search functionality's effectiveness. In these settings, you define and organize the data so that it can be efficiently searched and retrieved.

Overview

This tab serves as a dashboard, providing key metrics and insights related to the indexing process. The layout is divided into several sections:

1. Key Metrics

This section provides an at-a-glance view of important index-related statistics. The metrics displayed include:

Total Records: The total number of records currently in the index, along with a trend indicator showing the change over time.
Failed Records: The number of records that failed to be indexed, with a view list option to examine these records.
Indexing Errors: The number of errors encountered during indexing, with a view list option to further investigate the errors.

2. Schema Summary

This section provides an overview of the fields defined in the index schema. The summary includes:

Total Fields: The total number of fields defined in the schema.
Searchable Fields: The number of fields that are searchable.
Facetable Fields: The number of fields that can be used for faceting.
Filterable Fields: The number of fields that can be filtered.
Sortable Fields: The number of fields that can be sorted.

Each of these metrics helps in understanding the structure and capabilities of the index schema.

3. Index Operations

This section provides a graphical representation of the indexing activities over time. It provides insights into how the index operations are performing, allowing users to monitor trends and identify potential issues.

Schema

The schema serves as a roadmap to the data structure within your index, detailing the fields within the documents, their data types, and configurations. It is vital as it determines how data is processed and retrieved during searches. A well-defined schema ensures that your search functionality is both accurate and efficient. Read more.

Attribute Mapping

This section is where you define how different attributes of your listings or documents are mapped and displayed. Proper configuration here ensures that your data is accurately represented and easily searchable.

Primary Key

The Primary Key is a unique identifier for each document or listing in your index. It's essential for efficient data retrieval and avoiding duplicate entries. This key must be configured for indexing purposes.

Usage: For example, in an e-commerce database, the primary key could be a product SKU.

Title

The title is the main identifier of a listing or document. It should be concise yet descriptive, giving a clear idea of the content or product at a glance.

Usage: For example, in an e-commerce setting, the title could be the name of the product, like "Samsung Galaxy S21 Smartphone."

Image URL

This field stores the URL of the image associated with the listing. Images play a crucial role in visual identification and appeal.

Usage: In an online catalog, the image URL would link to the product image, displaying it in search results for better user engagement.

Selling Price

It represents the price at which a product is being sold. It's a critical attribute for commerce-related searches.

Usage: Used to display product prices in search results, aiding in price-based decision-making for customers.

Brand Name

The brand name attribute is used to identify the maker or brand of a product. This field is especially important in scenarios where brand recognition influences purchasing decisions.

Usage: For instance, in a clothing store's search, users might filter results to show only "Nike" or "Adidas" products.

Summary

This field contains a brief description or summary of the listing. While optional, it can provide valuable context to the users.

Usage: For a book in an online library, the summary might give a brief overview of the plot or subject matter.

Attribute Groups

Combine multiple attributes under a group. There might be multiple attributes that have a similar meaning or connotation. For example, material-related or color-related attributes should be grouped together.

Attribute Groups allow you to organize and combine similar attributes, enhancing data management and search efficiency. For instance, you might group together similar attributes related to materials or colors under your index. This grouping helps in creating more focused and efficient searches.

Tip: While you can include as many attributes as needed, remember that a higher number of attributes can slow down the response time for queries. Optimize the number of attributes for better performance.

Note: Any changes made to the Schema, Primary Key, or Attribute Groups necessitate re-indexing. The 'Re-Index' button becomes active following any such modifications.

General Configurations

Category Hierarchy

Category hierarchy is a way to structure data in a multi-level system where items are grouped based on common characteristics or themes. At the highest level are the most general categories, and beneath these are more specific subcategories, with further subdivisions as necessary. This hierarchy allows for the logical classification of items, making it easier for users to navigate and for the system to manage.

Hierarchy Configurations: This section is dedicated to defining the structure of your product categories. It’s where you can map out the schema field against the hierarchy level.

Updates Log: This section tracks any changes made for any category within the category hierarchy.

Category Tree: This visual representation helps users understand the current structure of the category hierarchy at a glance. It's an interactive tree where each node represents a category level, allowing users to navigate through different categories and subcategories to see their relationship and organization.