Blockchain Data Index Method Based on Improved Red-black Tree

With the expansion of blockchain applications, the volume of data stored by each blockchain node is also on the rise. However, the current blockchain architecture faces challenges related to high storage demands and inefficient access. Presently, blockchain systems primarily support basic query modes, such as block and transaction retrieval via transaction hashing, lacking support for additional attributes like transaction value and transaction time. To address these issues, this paper proposes a three layer index method combining red-black tree and Bloom filter. Through testing and analysis, this method enhances query versatility while maintaining high performance levels.