Blockchain Index Structure for Phantom Read Prevention
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Solution Overview
Problem
Current blockchain solutions, such as Hyperledger Fabric, face performance issues due to phantom read errors during non-critical range queries, which can lead to transaction failures and hinder concurrent transactions.
Innovation Solution
An index structure is built on top of the blockchain ledger, allowing peers to query the index instead of the ledger for non-critical queries, thereby avoiding phantom read errors by omitting data read from the index structure in the read set.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If range queries are executed on the blockchain ledger to retrieve data, then the queries can access the actual stored values, but phantom read errors occur causing false denials and transaction failures
Solution Approach 1:
The patent introduces an index structure as an intermediary layer between query operations and the blockchain ledger. This index stores key information without storing full values, allowing queries to check for phantom reads without accessing actual data values. The index acts as a mediator that filters out phantom read errors before they reach the ledger, thus maintaining query accuracy while improving transaction throughput by preventing false denials.
Solution Approach 2:
The patent segments the query validation process into two parts: first checking the index structure for potential phantom reads, then accessing the ledger only for critical queries. This segmentation allows non-critical queries to be resolved quickly using the index, while maintaining reliability by still accessing the ledger when necessary. The segmentation separates the phantom detection function from the data retrieval function.
2Reliability
If the read set includes all values read from the blockchain ledger, then phantom read errors can be detected, but non-critical queries cause false denials and reduce transaction performance
Solution Approach 1:
The patent applies local quality by treating different types of queries differently. Critical queries that affect transaction validity include their read values in the read set for phantom detection, while non-critical queries that do not affect validity exclude their read values from the read set. This localized differentiation maintains reliability for critical operations while reducing complexity and false denials for non-critical operations. The index structure enables this selective approach by providing phantom detection capability without requiring full value inclusion in the read set.
Data Source
AI summary
An example operation may include one or more of storing an index structure that comprises an index of keys from a blockchain ledger, where the keys are stored as nodes in the index structure, receiving a blockchain request for data stored on the blockchain ledger, reading a set of keys of a non-critical query included in the blockchain request from the nodes in the index structure, and generating and storing a read set for the blockchain request which does not include values for the set of keys of the non-critical query.