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Chunk List: Concurrent Data Structures
arXiv - CS - Databases Pub Date : 2021-01-01 , DOI: arxiv-2101.00172 Daniel Szelogowski
arXiv - CS - Databases Pub Date : 2021-01-01 , DOI: arxiv-2101.00172 Daniel Szelogowski
Chunking data is obviously no new concept; however, I had never found any
data structures that used chunking as the basis of their implementation. I
figured that by using chunking alongside concurrency, I could create an
extremely fast run-time in regards to particular methods as searching and/or
sorting. By using chunking and concurrency to my advantage, I came up with the
chunk list - a dynamic list-based data structure that would separate large
amounts of data into specifically sized chunks, each of which should be able to
be searched at the exact same time by searching each chunk on a separate
thread. As a result of implementing this concept into its own class, I was able
to create something that almost consistently gives around 20x-300x faster
results than a regular ArrayList. However, should speed be a particular issue
even after implementation, users can modify the size of the chunks and
benchmark the speed of using smaller or larger chunks, depending on the amount
of data being stored.
中文翻译:
块列表:并行数据结构
分块数据显然不是什么新概念。但是,我从未发现过任何使用分块作为实现基础的数据结构。我发现通过在并发中使用分块,可以在搜索和/或排序等特定方法方面实现极快的运行时间。通过利用分块和并发的优势,我想到了分块列表-一种基于动态列表的数据结构,该结构将大量数据分成特定大小的分块,每个分块都应可以在同一时间进行搜索通过在单独的线程上搜索每个块。通过将这个概念实现到自己的类中,我能够创建出比常规ArrayList几乎始终如一的快20到300倍的结果。然而,
更新日期:2021-01-05
中文翻译:
块列表:并行数据结构
分块数据显然不是什么新概念。但是,我从未发现过任何使用分块作为实现基础的数据结构。我发现通过在并发中使用分块,可以在搜索和/或排序等特定方法方面实现极快的运行时间。通过利用分块和并发的优势,我想到了分块列表-一种基于动态列表的数据结构,该结构将大量数据分成特定大小的分块,每个分块都应可以在同一时间进行搜索通过在单独的线程上搜索每个块。通过将这个概念实现到自己的类中,我能够创建出比常规ArrayList几乎始终如一的快20到300倍的结果。然而,