2026-10-14T21:05:05Z https://www.scidb.cn/oai

10.57760/sciencedb.09330 2023-07-07T09:09:29Z

2023-07-07 Dataset for recommendation-based auxiliary caching doi:10.57760/sciencedb.09330 en Track the nginx logs on the CDN cluster of a cloud vendor, obtain log records for 7 consecutive days, and use ELK to analyze and extract the data obtained by key fields. The data contains 7 days (from 2022.06.10 to 2022.06.16) of data, and the data of each day is divided into a separate folder. The files under each folder are described as follows:202206xx├── city2code.csv // Mapping table of popular cities to city codes├── df-1m-unique.csv // The data set used to train the recommendation model, the format is [clientid, contentid, value, timestamp]├── df-1m.csv├── group_uri_dict.json // uri grouping by time├── ip_city_dict.json // mapping of IP address with city code ├── request.csv // for generate requests，intercepted a request fragment for a continuous period of time├── summarize.txt // summary of log└── uri2code.csv // save the correspondence between uri and uri encoding auxiliary caching; recommendation; ttl caching; distributed system Zhaolin Ma Jiali You PUBLIC https://mit-license.org dataset Science Data Bank