Parallel Decompression of Gzip-Compressed Files and Random Access to DNA Sequences

Mael Kerbiriou, R. Chikhi
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引用次数: 9

Abstract

Decompressing a file made by the gzip program at an arbitrary location is in principle impossible, due to the nature of the DEFLATE compression algorithm. Consequently, no existing program can take advantage of parallelism to rapidly decompress large gzip-compressed files. This is an unsatisfactory bottleneck, especially for the analysis of large sequencing data experiments. Here we propose a parallel algorithm and an implementation, pugz, that performs fast and exact decompression of any text file. We show that pugz is an order of magnitude faster than gunzip, and 5x faster than a highly-optimized sequential implementation (libdeflate). We also study the related problem of random access to compressed data. We give simple models and experimental results that shed light on the structure of gzip-compressed files containing DNA sequences. Preliminary results show that random access to sequences within a gzip-compressed FASTQ file is almost always feasible at low compression levels, yet is approximate at higher compression levels.
并行解压缩gzip压缩文件和随机访问DNA序列
由于DEFLATE压缩算法的性质,在任意位置解压缩gzip程序生成的文件原则上是不可能的。因此,没有现有的程序可以利用并行性来快速解压缩大型gzip压缩文件。这是一个令人不满意的瓶颈,特别是对于大型测序数据实验的分析。在这里,我们提出了一个并行算法和pugz实现,它可以对任何文本文件执行快速而精确的解压缩。我们证明pugz比gunzip快一个数量级,比高度优化的顺序实现(libdeflate)快5倍。我们还研究了随机存取压缩数据的相关问题。我们给出了简单的模型和实验结果,揭示了包含DNA序列的gzip压缩文件的结构。初步结果表明,在低压缩级别下,对gzip压缩的FASTQ文件中的序列的随机访问几乎总是可行的,而在较高的压缩级别下则近似可行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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