Design a Search Service
Explore the design of a search service API focusing on key features like searching, sorting, pagination, and filtering. Understand how to ensure scalability, availability, and security while optimizing response times. Learn to implement API versioning and choose suitable architectural styles and data formats. Gain insights into search service internals and design decisions to meet real-world requirements.
Search API: Requirements and foundations
Data-intensive applications demand optimized query mechanisms as data volumes and user bases grow. The search feature, augmented with filtering, sorting, and pagination, enables users to locate specific content efficiently across massive data sets.
Beyond returning relevant results, a search feature enables derivative services, including autocomplete and typeahead based on frequent queries, improved content recommendations, and targeted ad generation. These capabilities inform the following requirements.
Functional requirements
Searching: Return data relevant to the user’s query.
Sorting: Sort data based on client preference.
Pagination: Support paginated responses for large result sets.
Note: Functional requirements are divided into two phases to demonstrate API versioning in practice. Phase one covers searching, sorting, and pagination. Phase two adds filtering.
Nonfunctional requirements
Availability: Be highly available for users.
Scalability: Scale with growing data and query volume.
Security: Deliver personalized results through secure channels.
Low latency: Generate fast responses regardless of query complexity or data set size.
Prerequisites
Web API architectural styles: Informs the communication style between the client, API gateway, and downstream services.
Data formats: Determines the serialization format for data exchange.
HTTP: Guides HTTP version selection for the search API.
Versioning: Enables extending functionality through version control.
Back-of-the-envelope calculations: Supports response time estimation.
How the search service works
Most modern applications provide search functionality. GitHub, for example, uses a search API to locate specific files across more than 200 million repositories. The search API accepts a user query and returns varied responses, including text results, images, video thumbnails, recommendations, and sponsored ads.
The API can perform additional operations on matched records, such as limiting or sorting results. Understanding the service’s internal workings is essential for designing communication protocols between the client, middleware, and backend services.
Indexer and searcher architecture
The search system consists of two core components: an indexer and a searcher.
When the search service receives a query, the searcher parses it and looks up matches in the index table. The index table contains terms and their mappings. The indexer builds it by pre-indexing data during ingestion so the searcher can respond quickly. The searcher aggregates matches and returns them to the search service.
Components in the Search Service
Component | Details |
Indexer |
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Searcher |
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Result sets can range from zero to hundreds of thousands of records, making unbounded responses impractical. Limiting the number of returned records avoids overwhelming clients and burdening backend servers. Pagination addresses this directly.
Note: For deeper coverage of search internals, see the "Design of a Distributed Search" lesson in "Grokking Modern System Design Interview for Engineers & Managers".
For long or computationally heavy queries, the service prioritizes speed over exact matches by enforcing a maximum execution time. If it's exceeded (in rare cases), the API returns a partial response. Query length is also capped (for example, 200 characters).
Sorting
Sorting orders search results by one or more ... ...