Problem Description
Design the high-level pipeline of a web search engine. This system must support internet-scale search, encompassing billions of web pages, while delivering low-latency query responses.
Deliverables
Your design should describe the major components and data flow for two distinct operational sides:
- Offline / Batch Side: Covers the entire process from discovering web pages to building and continuously maintaining the search index.
- Online / Serving Side: Details the flow from when a user submits a query to when they receive ranked search results.
Key Areas to Cover
In your architectural design, ensure you address at least the following aspects:
- Document Discovery and Fetching: How web pages are identified and retrieved from the internet.
- Document Processing and Indexing: The methods for parsing, processing, and indexing documents. This should include considerations for data structures like an inverted index, as well as strategies for sharding and replication.
- User Query Processing: How a user's query is handled, including understanding and normalization techniques.
- Efficient Document Retrieval: Strategies for quickly identifying and retrieving candidate documents relevant to a query.
- Result Ranking: How search results are ordered by relevance. You may optionally discuss the use of Machine Learning (ML) models for ranking.
- System Qualities: How low latency, scalability, and fault tolerance are ensured throughout the system.
- User Interaction Logging: Mechanisms for recording user interactions to facilitate future system improvements and model training.
Scope
Focus on the high-level architecture, major components, and data flow. Detailed APIs or specific code implementations are not required.
AI interview prep
Core dilemma
The central engineering conflict is balancing the completeness and freshness of an internet-scale index (requiring massive, continuous data ingestion and processing) with the need for extremely low-latency query responses and high availability, all while managing immense computational and storage costs.
3 tradeoffs and 3 stress tests locked
Interview prep
Unlock the interviewer X-Ray rubric, tradeoff matrix, stress tests, clarifying questions, and key concepts.
Problem Description
Design the high-level pipeline of a web search engine. This system must support internet-scale search, encompassing billions of web pages, while delivering low-latency query responses.
Deliverables
Your design should describe the major components and data flow for two distinct operational sides:
- Offline / Batch Side: Covers the entire process from discovering web pages to building and continuously maintaining the search index.
- Online / Serving Side: Details the flow from when a user submits a query to when they receive ranked search results.
Key Areas to Cover
In your architectural design, ensure you address at least the following aspects:
- Document Discovery and Fetching: How web pages are identified and retrieved from the internet.
- Document Processing and Indexing: The methods for parsing, processing, and indexing documents. This should include considerations for data structures like an inverted index, as well as strategies for sharding and replication.
- User Query Processing: How a user's query is handled, including understanding and normalization techniques.
- Efficient Document Retrieval: Strategies for quickly identifying and retrieving candidate documents relevant to a query.
- Result Ranking: How search results are ordered by relevance. You may optionally discuss the use of Machine Learning (ML) models for ranking.
- System Qualities: How low latency, scalability, and fault tolerance are ensured throughout the system.
- User Interaction Logging: Mechanisms for recording user interactions to facilitate future system improvements and model training.
Scope
Focus on the high-level architecture, major components, and data flow. Detailed APIs or specific code implementations are not required.