An Architect's vision

  We'll explore scenarios involving nested queries, aggregations, custom scoring, and hybrid queries that combine multiple search criteria. 1. Nested Queries ElasticSearch Example: ElasticSearch supports nested documents, which allows for querying on nested fields with complex conditions. Query: Find products where the product has a review with a rating of 5 and the review text contains "excellent". { "query": { "nested": { "path": "reviews", "query": { "bool": { "must": [ { "match": { "reviews.rating": 5 } }, { "match": { "reviews.text": "excellent" } } ] } } } } } Redis Limitation: Redis does not support nested documents natively. While you can store nested structures in JSON documents using the RedisJSON module, querying these nested structures with complex condi

  Reranking What is Reranking? Reranking is a process that takes initial search results and reorders them to improve their relevance. Imagine you have a list of search results. Reranking looks at these results and adjusts their order to better match what you’re looking for. How Does Reranking Work? After the initial search, the system examines the results and applies additional criteria to reorder them. For example, it might combine results from multiple searches using a technique like Reciprocal Rank Fusion (RRF), which adjusts the ranking based on how documents are scored across different searches. This helps in pushing the most relevant documents to the top of the list. Benefits of Reranking: Refined Results : It fine-tunes the list of results to better meet the user’s needs. Higher Quality : By considering multiple relevance signals, it ensures that the most pertinent documents are ranked higher. Hybrid Search What is Hybrid Search? Hybrid Search combines multiple search techniqu