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The paper is devoted to the evaluation of various hashing algorithms for improving the efficiency of information retrieval in big data management systems. The performance of the following widely used hashing algorithms was evaluated on the test big data base: 32-bit cyclic redundancy check CRC32, 128-bit MD2, MD4, MD5, 160-bit RIPEMD, 160-bit SHA-1, 256-bit SHA, double SHA-256, 384-bit SHA, 512-bit SHA, RIPEMD-160 with subsequent SHA-256 as used in Bitcoin. The most efficient hashing algorithm significantly outperforming the others is the CRC32 algorithm. A comparative analysis of double hashing algorithms was performed. Two new double hashing algorithms are considered: RIPEMD160 + MD4, SHA256 + MD4. Comparative analysis of the performance of double hashing algorithms: RIPEMD160 + MD4, SHA256 + MD4 with Double SHA256 and RIPEMD160 + SHA256 algorithms showed comparable performance on large amounts of data.

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Improving the Performance of Big Data Management Systems Using Hashing

  • 会议论文

  • 发表日期：

    2026年

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  • Sergei Ivanov,
  • Lubov Ivanova

摘要

The paper is devoted to the evaluation of various hashing algorithms for improving the efficiency of information retrieval in big data management systems. The performance of the following widely used hashing algorithms was evaluated on the test big data base: 32-bit cyclic redundancy check CRC32, 128-bit MD2, MD4, MD5, 160-bit RIPEMD, 160-bit SHA-1, 256-bit SHA, double SHA-256, 384-bit SHA, 512-bit SHA, RIPEMD-160 with subsequent SHA-256 as used in Bitcoin. The most efficient hashing algorithm significantly outperforming the others is the CRC32 algorithm. A comparative analysis of double hashing algorithms was performed. Two new double hashing algorithms are considered: RIPEMD160 + MD4, SHA256 + MD4. Comparative analysis of the performance of double hashing algorithms: RIPEMD160 + MD4, SHA256 + MD4 with Double SHA256 and RIPEMD160 + SHA256 algorithms showed comparable performance on large amounts of data.