用于远程ROOT数据分析的客户端透明缓存
Client-side transparent caching for remote ROOT data analysis
- Massachusetts Institute of Technology（麻省理工学院）
- CERN（欧洲核子研究组织）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
针对高能物理远程ROOT数据分析的网络延迟问题，提出透明客户端缓存uCache，经基准测试可显著提升后续分析速度，1TB缓存可满足10-20TB数据集需求。
AI中文摘要：
高能物理分析中，当物理学家优化算法、测试新想法时，往往会重复处理相同数据。由于数据日益从远程存储读取，每次迭代都会受网络延迟影响，且依赖网络带宽与共享存储吞吐量，这些指标在负载下会大幅波动。我们提出uCache（xrd-ucache），这是一款透明客户端缓存，作为XRootD客户端插件实现，无需服务器端部署，也无需修改分析代码。它利用分析机器上的本地存储作为网络与内存间的缓存层，仅存储分析实际读取的数据，还可将缓存数据重建为分支对齐、重新压缩的形式，消除后续迭代的大部分输入/输出与解压缩开销。我们采用Analysis Grand Challenge顶夸克对分析，使用经zlib和LZMA压缩的公开CMS Open Data对该缓存进行基准测试。与直接读取相比，填充缓存基本无额外开销；后续迭代从字节缓存读取速度提升1.6-8.8倍，从重新压缩缓存读取速度提升2.1-15.7倍。对于典型分析，1TB缓存可满足10-20TB数据集的需求，当远程数据源负载过重或地理距离较远时，改进效果最显著。
英文摘要：
High-energy physics analyses often process the same data as physicists refine algorithms and test new ideas. With data increasingly read from remote storage, each iteration is subject to network latency and depends on network bandwidth and shared-storage throughput, which can vary substantially under load. We present uCache (xrd-ucache), a transparent client-side cache implemented as an XRootD client plugin that requires neither server-side deployment nor changes to analysis code. It uses local storage on the analysis machine as a cache layer between the network and memory. The cache stores only the data actually read by an analysis. It can also rebuild cached data into a branch-aligned, recompressed form, eliminating most of the input/output and decompression costs of subsequent passes. We benchmark the cache using the Analysis Grand Challenge top quark pair analysis on public CMS Open Data compressed with zlib and LZMA. Filling the cache adds essentially no overhead compared with a direct read. Subsequent passes are 1.6-8.8 times faster from the byte cache and 2.1-15.7 times faster from the recompressed cache. For a typical analysis, a 1 TB cache suffices for datasets of 10-20 TB. The largest improvements occur when the remote data source is heavily loaded or geographically distant.
