Performance Optimization of Data Structures in Big Data Storage and Retrieval
With the advent of the big data era,the performance optimization of data structures in large-scale data storage and retrieval has become particularly crucial.This paper aims to explore and analyze the storage and retrieval performance of different data structures in the context of big data and proposes corresponding optimization strategies.Firstly,the paper introduces the basic concepts and characteristics of big data,as well as the significance of data structures in big data applications.Subsequently,it analyzes the applications and limitations of common data structures such as tree structures,graph structures,hash structures,etc.,in large-scale data storage and retrieval.Furthermore,the paper proposes several optimization methods tailored to specific data structures,including improved algorithms,data compression,parallel processing,etc.,to enhance storage efficiency and retrieval speed.Finally,the effectiveness of these optimization strategies is experimentally validated.This research holds significant theoretical and practical value in guiding the real-world applications of large-scale data storage and retrieval.
big datadata structuresstorage optimizationretrieval performancealgorithm improvement
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