This paper investigates data compression that simultaneously allows local decoding and local update. The main result is a universal compression scheme for memoryless sources with the following features. The rate can be made arbitrarily close to the entropy of the underlying source, contiguous fragments of the source can be recovered or updated by probing or modifying a number of codeword bits that is on average linear in the size of the fragment, and the overall encoding and decoding complexity is quasilinear in the blocklength of the source. In particular, the local decoding or update of a single message symbol can be performed by probing or modifying on average a constant number of codeword bits. This latter part improves over previous best known results for which local decodability or update efficiency grows logarithmically with blocklength.

中文翻译：

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大数据压缩的本地解码和更新

本文研究了同时允许本地解码和本地更新的数据压缩。主要结果是具有以下特征的无记忆源的通用压缩方案。速率可以任意接近底层源的熵，源的连续片段可以通过探测或修改平均为片段大小线性的多个码字位来恢复或更新，以及整体编码并且解码复杂度在源的块长度中是拟线性的。特别地，单个消息符号的本地解码或更新可以通过探测或修改平均恒定数量的码字比特来执行。后一部分改进了先前最著名的结果，其中局部可解码性或更新效率随块长度呈对数增长。