From the course: LLM Foundations: Vector Databases for Caching and Retrieval Augmented Generation (RAG)

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Query and search in Milvus

Query and search in Milvus

From the course: LLM Foundations: Vector Databases for Caching and Retrieval Augmented Generation (RAG)

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Query and search in Milvus

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Query and such are key capabilities that any database needs to support. Let's explore what capabilities are available in Milvus in this regard. Let's start with queries. In queries, we extract entities using scalar field-based filtering. This is very similar to the retrieval process in RDBMS, where SQL statements are executed to extract data that match specific filter conditions. When running a query in Milvus, we can specify the output fields needed and the limits on the number of rows. We can also specify offsets, which is the number of rows to skip before returning the remaining data. This helps with pagination type queries. We can restrict the queries to specific partitions. This can be done by specifying the partition name in the query or using the partition key in the filter. For aggregations, only a count(*) feature is available. Other capabilities like sum or average are not available. Do note that the scalar querying capabilities are severely limited in Milvus when compared…

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