MinHash LSH in Milvus: The Secret Weapon for Fighting Duplicates in LLM Training Data

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Introduces and details the implementation of MinHash LSH indexing in Milvus 2.6 for approximate data deduplication. Explains the underlying concepts of MinHash (shingling, hashing) and LSH (banding technique) for efficient near-duplicate detection. Describes the native integration within Milvus, including the MINHASH_LSH index type, JACCARD metric, and distributed architecture support. Provides practical guidance on generating MinHash signatures and using Milvus SDK for schema creation, index building, and data insertion for deduplication tasks.