{"title":"Ludo哈希:实用网络系统的紧凑、快速和动态键值查找","authors":"Shouqian Shi, Chen Qian","doi":"10.1145/3393691.3394198","DOIUrl":null,"url":null,"abstract":"Key-value lookup engines running in fast memory are crucial components of many networked and distributed systems such as packet forwarding, virtual network functions, content distribution networks, distributed storage, and cloud/edge computing. These lookup engines must be memory-efficient because fast memory is small and expensive. This work presents a new key-value lookup design, called Ludo Hashing, which costs the least space (3.76 + 1.05 ι bits per key-value item for ι-bit values) among known compact lookup solutions including the recently proposed partial-key Cuckoo and Bloomier perfect hashing. In addition to its space efficiency, Ludo Hashing works well with most practical systems by supporting fast lookups, fast updates, and concurrent writing/reading. We implement Ludo Hashing and evaluate it with both micro-benchmark and two network systems deployed in CloudLab. The results show that in practice Ludo Hashing saves 40% to 80%+ memory cost compared to existing dynamic solutions. It costs only a few GB memory for 1 billion key-value items and achieves high lookup throughput: over 65 million queries per second on a single node with multiple threads.","PeriodicalId":188517,"journal":{"name":"Abstracts of the 2020 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Ludo Hashing: Compact, Fast, and Dynamic Key-value Lookups for Practical Network Systems\",\"authors\":\"Shouqian Shi, Chen Qian\",\"doi\":\"10.1145/3393691.3394198\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Key-value lookup engines running in fast memory are crucial components of many networked and distributed systems such as packet forwarding, virtual network functions, content distribution networks, distributed storage, and cloud/edge computing. These lookup engines must be memory-efficient because fast memory is small and expensive. This work presents a new key-value lookup design, called Ludo Hashing, which costs the least space (3.76 + 1.05 ι bits per key-value item for ι-bit values) among known compact lookup solutions including the recently proposed partial-key Cuckoo and Bloomier perfect hashing. In addition to its space efficiency, Ludo Hashing works well with most practical systems by supporting fast lookups, fast updates, and concurrent writing/reading. We implement Ludo Hashing and evaluate it with both micro-benchmark and two network systems deployed in CloudLab. The results show that in practice Ludo Hashing saves 40% to 80%+ memory cost compared to existing dynamic solutions. It costs only a few GB memory for 1 billion key-value items and achieves high lookup throughput: over 65 million queries per second on a single node with multiple threads.\",\"PeriodicalId\":188517,\"journal\":{\"name\":\"Abstracts of the 2020 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems\",\"volume\":\"36 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Abstracts of the 2020 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3393691.3394198\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Abstracts of the 2020 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3393691.3394198","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Ludo Hashing: Compact, Fast, and Dynamic Key-value Lookups for Practical Network Systems
Key-value lookup engines running in fast memory are crucial components of many networked and distributed systems such as packet forwarding, virtual network functions, content distribution networks, distributed storage, and cloud/edge computing. These lookup engines must be memory-efficient because fast memory is small and expensive. This work presents a new key-value lookup design, called Ludo Hashing, which costs the least space (3.76 + 1.05 ι bits per key-value item for ι-bit values) among known compact lookup solutions including the recently proposed partial-key Cuckoo and Bloomier perfect hashing. In addition to its space efficiency, Ludo Hashing works well with most practical systems by supporting fast lookups, fast updates, and concurrent writing/reading. We implement Ludo Hashing and evaluate it with both micro-benchmark and two network systems deployed in CloudLab. The results show that in practice Ludo Hashing saves 40% to 80%+ memory cost compared to existing dynamic solutions. It costs only a few GB memory for 1 billion key-value items and achieves high lookup throughput: over 65 million queries per second on a single node with multiple threads.