Handling Conditional Queries on Hyperledger Fabric Efficiently

As a popular consortium blockchain platform, Hyperledger Fabric has received increasing attention recently. When conducting quer-ies that meet some specific conditions on such platform, we need to search ledger data which usually has multiple attributes. Although efficiently handling conditional queries can be leveraged to support various use-cases, it presents significant challenges as data on Hyperledger Fabric is organized on file-system and exposed via limited API. To tackle the problem, we propose the following novel methods in this paper. In the first one, we use all conditions of the query to create composite keys before executing it. To further improve the performance of conditional queries on Fabric, we build an index called AUP in the second method, where we also study the update of AUP during transactions. The extensive experiments conducted on the real-world dataset demonstrate that the proposed methods can achieve high performance in terms of efficiency and memory cost.