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With the continual progress of information technology and marine observation methods, the volume of obtained marine environmental data has grown exponentially. Efficient data storage and indexed querying remain urgent challenges to be solved. To address this problem, this study proposes an HBase-based distributed storage and indexing method for global marine environmental data. The core contribution is an engineering optimization that introduces a novel TimeHash-SID-TID composite Row Key design, which effectively mitigates write hotspots while preserving spatio-temporal locality, thereby enabling efficient storage and query for massive marine datasets. To verify and evaluate the storage and query performance of the proposed approach, comparative experiments were designed against different data storage schemes and index construction methods. Experimental results show that the proposed method can effectively improve the storage and query efficiency of marine environmental data. The performance gains afforded by this method directly support data-intensive scientific tasks such as large-scale ocean circulation modeling and climate change analysis, while also enhancing the responsiveness of operational systems for marine hazard early warning.

A distributed storage and indexing approach for global marine environmental data