IR systems manage large-scale datasets through techniques designed to efficiently index, retrieve, and rank large amounts of data. One key approach is the use of indexing structures like inverted indices, which map terms to their occurrences in documents, allowing for fast lookups and retrieval.
To handle large volumes of data, distributed systems are often employed. These systems break data into smaller chunks and distribute them across multiple servers, allowing parallel processing and faster search results. Technologies like Hadoop and Elasticsearch are commonly used for scaling IR systems.
Additionally, optimized storage solutions and compression algorithms help reduce the physical space needed to store large datasets, making it easier to scale IR systems effectively.