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23rd International Conference on Languages, Compilers, and Tools for Embedded System (LCTES)

作者： Zheng, Yi Fixelle, Joshua Challapalle, Nagadastagiri Huo, Pingyi Shen, Zhaoyan Shao, Zili Stan, Mircea Narayanan, Vijaykrishnan Penn State Univ University Pk PA 16802 USA Univ Virginia Charlottesville VA USA Shandong Univ Jinan Peoples R China Chinese Univ Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9781450392662

key-value databases are widely used to store the features or metadata generated from the neural network based video processing platforms. Due to the large volumes of video data, these databases use solid state drives (SSDs) as the primary data storage platform, and user query-based filtering, and retrieval operations on data incur large volume of data movement between the SSD and the host processor. In this paper, we present an in-SSD key-value database which uses the embedded CPU core, and DRAM memory on the SSD to support various queries with predicates and reduce the data movement between SSD and host processor significantly. We augment the SSD flash translation layer with key-value database functions and auxiliary data structures to support the user queries using the embedded core and DRAM memory on SSD. The proposed key-value store prototype on the Cosmos plus OpenSSD board reduces data movement between host processor and SSD by 14.57 x, achieves an application-level speedup by 1.16 x, and reduced energy consumption by 56 % across different types of user queries.

关键词： key-value database SSD video metadata video features data movement

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Bucket-Based Expiration Algorithm: Improving Eviction Efficiency for In-Memory key-value database

Bucket-Based Expiration Algorithm: Improving Eviction Effici...

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International Symposium on Memory Systems (MEMSYS)

作者： Xie, Guochao Chung, Yeh-Ching Chinese Univ Hong Kong Shenzhen Peoples R China

ISBN: (纸本)9781450388993

Evicting expired keys for an in-memory key-value database is essential to save its memory resources and control its memory usage not exceeding its memory limit. Existing randomized expiration algorithms randomly sample keys from the key space associated with expiration, evict all expired ones and proceed to the next iteration if the proportion of expired keys exceeds a pre-defined threshold. The randomized algorithm has been adopted by Redis currently. In this paper, we present a novel approach, a hybrid algorithm combining a deterministic one using buckets and a randomized one inherited from Redis expiration algorithm, to improve the efficiency of eviction of expired keys. For the main part, we adopt a deterministic algorithm to discretize the expiration timestamps into buckets and evict keys bucket by bucket;if time permitted, we also run the Redis expiration algorithm after finishing the deterministic part. Furthermore, our experiment using Redis randomized algorithm as the baseline shows that our algorithm is more effective in reducing memory usage with an acceptable impact on the overall throughputs.

关键词： Eviction algorithm Expiration Redis key-value database In-Memory Storage

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Bucket-Based Expiration Algorithm: Improving Eviction Efficiency for In-Memory key-value database 2020

Bucket-Based Expiration Algorithm: Improving Eviction Effici...

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The International Symposium on Memory Systems

作者： Guochao Xie Yeh-Ching Chung The Chinese University of Hong Kong Shenzhen China

ISBN: (纸本)9781450388993

Evicting expired keys for an in-memory key-value database is essential to save its memory resources and control its memory usage not exceeding its memory limit. Existing randomized expiration algorithms randomly sample keys from the key space associated with expiration, evict all expired ones and proceed to the next iteration if the proportion of expired keys exceeds a pre-defined threshold. The randomized algorithm has been adopted by Redis currently. In this paper, we present a novel approach, a hybrid algorithm combining a deterministic one using buckets and a randomized one inherited from Redis expiration algorithm, to improve the efficiency of eviction of expired keys. For the main part, we adopt a deterministic algorithm to discretize the expiration timestamps into buckets and evict keys bucket by bucket; if time permitted, we also run the Redis expiration algorithm after finishing the deterministic part. Furthermore, our experiment using Redis randomized algorithm as the baseline shows that our algorithm is more effective in reducing memory usage with an acceptable impact on the overall throughputs.

关键词： Expiration In-Memory Storage Eviction algorithm key-value database Redis

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A Comparative Study of Relational database and key-value database for Big Data Applications

A Comparative Study of Relational Database and Key-Value Dat...

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International Electrical Engineering Congress (iEECON)

作者： Puangsaijai, Wittawat Puntheeranurak, Sutheera King Mongkuts Inst Technol Ladkrabang Fac Engn Bangkok Thailand

ISBN: (纸本)9781509046669

Nowadays, Demands of web scale are in increasing and growing rapidly. Mobile applications, web technologies, social media always generates unstructured data that had lead to the advent of various NoSQL databases. Therefore, Big data applications are necessary to have an efficient technology to collect these data. However, a relational database is the traditional database that always uses in many applications and still has more valuable to play a significant role in the current information system. The main characteristics of NoSQL databases are schema-free, no relationship, no need to join as a relational database. The business organization expects that NoSQL database has better performance than a relational database. In This paper, we aim to compare the performance of Redis, which is a key-value database, one kind of NoSQL database, and MariaDB, which is a popular relational database. We designed a set of experiments with a large amount of data and compared the efficiency of the insert, update, delete and select transactions from various aspects on the same dataset. We measure the processing time of each transaction to evaluate the comparison. The results have shown that Redis has better runtime performance for insert, delete, update transaction under a specific condition or complex queries. MariaDB still is good for some conditions especially when we have a small data. Our study can help to choose a database that will be suitable for the real world applications because relational databases and NoSQL databases have different strengths and weakness.

关键词： NoSQL database Redis key-value database Big data applications MariaDB

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A key-value Based Approach to Scalable Graph database 34th

A Key-Value Based Approach to Scalable Graph Database

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34th International Conference on database and Expert Systems Applications (DEXA)

作者： Zhao, Zihao Hu, Chuan Shen, Zhihong Mao, Along Ren, Hao Chinese Acad Sci Comp Network Informat Ctr Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China

ISBN: (纸本)9783031398469;9783031398476

An increasing number of applications are modeling data as property graphs. In various scenarios, the scale of data can differ significantly, ranging from thousands of nodes/relationships to tens of billions of nodes/relationships. While distributed native graph databases can cater to the management and query requirements of large-scale graph data sets, they tend to be relatively cumbersome for small-scale data sets. This motivates us to develop a lightweight, scalable graph database capable of handling data across different scales. In this paper, we propose a method for constructing a graph database based on key-value storage, outlining the process of mapping graph data to key-value storage and executing graph queries on the key-value storage. We implemented and open-sourced a graph database based on RocksDB, namely KVGDB, which can manage data in an embedded fashion and be easily scaled to distributed environments. Experimental results demonstrate that KVGDB can effectively meet the management and query requirements of graph data sets, even at the scale of billions of nodes/relationships.

关键词： Graph database Graph data key-value database

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Agent-Based Fault-Tolerance Mechanism for Distributed key-value database

Agent-Based Fault-Tolerance Mechanism for Distributed Key-Va...

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5th International Conference on Digital Home (ICDH)

作者： Wu Hui-Jun Lu Kai Li Gen Jiang Jin-Fei Wang Shuang-Xi Natl Univ Def Technol Sci & Technol Parallel & Distributed Proc Lab Changsha Hunan Peoples R China

ISBN: (纸本)9781479942848

Distributed key-value database is widely used in Web 2.0 applications and cloud computing environments. It overcomes the weak performance and bad scalability of traditional relational database. But fault in distributed system will lead to errors, then the high performance is useless. So we should build a fault tolerance mechanism. On the other hand, in many application scenarios, transactional operations are inevitable. Some existing key-value databases utilize two-phase commit protocol or optimistic concurrency control in transaction processing. But the problems are sing-node failure and high overhead in protocol processing. Meanwhile, users' programming becomes more error-prone. This paper designs a fault tolerance and recovery mechanism on DStageDB, which is a distributed key-value database. We design an agent-based transaction processing mechanism. The transaction processing speed is improved and less user intervention is needed.

关键词： fault-tolerance key-value database agent transaction

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Spatio-Temporal keyword Query Processing Based on key-value Stores

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DATA SCIENCE AND ENGINEERING 2025年第1期10卷 98-116页

作者： Li, Ruiyuan He, Xiang Sun, Yingying Jiang, Jun Shang, You Li, Guanyao Chen, Chao Chongqing Univ Coll Comp Sci Chongqing Peoples R China Chongqing Univ Start Spatio Temporal Art Lab Chongqing Peoples R China Chongqing City Vocat Coll Chongqing Peoples R China Guangzhou Urban Planning & Design Survey Res Inst Guangzhou Peoples R China

With the popularity of mobile devices and the development of location technology, there is an increasing amount of text data with spatial and temporal tags generated. Querying with spatial, temporal, and keyword constraints on such data, known as spatio-temporal keyword query (STK query), is of great significance. However, most existing STK query solutions rely on tree-based indexes designed for stand-alone architectures, which struggle to scale for big data. key-value stores, with the keys as their indexes, are designed for big data scenarios. On one hand, key-value stores can only support one-dimensional indexes initially, which makes them unsuitable for multi-dimensional STK queries. On the other hand, key-value stores put their indexes out of the memory, making it inevitable to trigger many unnecessary disk I/Os and slow down the query efficiency. To this end, based on key-value stores, we provide the first attempt by combining the in-memory index with on-disk index to efficiently support STK queries. Specifically, we design two-layer filters as the in-memory index, which enormously prunes unqualified spatio-temporal keyword combinations. An eviction policy is employed for the in-memory index, allowing it to support an infinite amount of data with limited memory usage. We deploy our solution on both HBase and Redis, conducting extensive experiments with two real and one synthetic datasets. The experimental results demonstrate that our solution achieves approximately twice the query efficiency of the state-of-the-art key-value based solutions, and is much more scalable than the tree-based competitor.

关键词： Spatio-temporal data management key-value database Spatio-temporal keyword query Bloom filter

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A systematic literature review of authorization and access control requirements and current state of the art for different database models

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INTERNATIONAL JOURNAL OF WEB INFORMATION SYSTEMS 2024年第1期20卷 1-23页

作者： Mohamed, Aya Khaled Youssef Sayed Auer, Dagmar Hofer, Daniel Kueng, Josef Johannes Kepler Univ Linz Inst Applicat Oriented Knowledge Proc FAW Linz Austria Johannes Kepler Univ Linz Linz Inst Technol LIT Secure & Correct Syst Lab Linz Austria

PurposeData protection requirements heavily increased due to the rising awareness of data security, legal requirements and technological developments. Today, NoSQL databases are increasingly used in security-critical domains. Current survey works on databases and data security only consider authorization and access control in a very general way and do not regard most of today's sophisticated requirements. Accordingly, the purpose of this paper is to discuss authorization and access control for relational and NoSQL database models in detail with respect to requirements and current state of the ***/methodology/approachThis paper follows a systematic literature review approach to study authorization and access control for different database models. Starting with a research on survey works on authorization and access control in databases, the study continues with the identification and definition of advanced authorization and access control requirements, which are generally applicable to any database model. This paper then discusses and compares current database models based on these *** no survey works consider requirements for authorization and access control in different database models so far, the authors define their requirements. Furthermore, the authors discuss the current state of the art for the relational, key-value, column-oriented, document-based and graph database models in comparison to the defined ***/valueThis paper focuses on authorization and access control for various database models, not concrete products. This paper identifies today's sophisticated - yet general - requirements from the literature and compares them with research results and access control features of current products for the relational and NoSQL database models.

关键词： Authorization Access control Requirements Relational database NoSQL key-value database Column-oriented database Document-based database Graph database

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LayerBF: A Space Allocation Policy for Bloom Filter in LSM-Tree 7th

LayerBF: A Space Allocation Policy for Bloom Filter in LSM-T...

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7th Asia-Pacific Web (APWeb) and Web-Age Information Management (WAIM) International Joint Conference on Web and Big Data

作者： Li, Jiaoyang Fan, Zhixin Yue, Yinliang Yao, Zekun Liu, Jinzhou Zhou, Jiang Univ Chinese Acad Sci Sch Cyberspace Secur Beijing Peoples R China Chinese Acad Sci Inst Informat Engn Beijing Peoples R China Zhongguancun Lab Beijing 100080 Peoples R China

ISBN: (纸本)9789819723867;9789819723874

LSM-Tree based key-value stores commonly suffer from the issue of read amplification, as the retrieval of a particular key typically requires examination of multiple layers of SSTables. To enhance query performance, a bloom filter is commonly employed, although it is susceptible to the problem of false positives, which leads to additional I/Os. To mitigate the issue of false positives, the bloom filter size can be increased, but this in turn results in higher memory consumption. In response, we have developed LayerBF, a space allocation strategy for layered bloom filters. By leveraging access frequency, LayerBF dynamically allocates bits-per-key of bloom filters in each layer. Hotter layers are allocated a larger space, while colder layers are allocated a smaller space. This approach reduces the average false positive rate, improves storage read performance, and simultaneously minimizes memory consumption. We have implemented LayerBF in the widely used RocksDB key-value store and evaluated its performance with and without LayerBF on both hard disk drives (HDDs) and solid-state drives (SSDs). The evaluation results demonstrate that LayerBF improves read performance by 5% to 14% and reduces the false positive rate by 8% to 10%.

关键词： LSM-Tree Bloom Filter key-value database

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A Free-Space Adaptive Runtime Zone-Reset Algorithm for Enhanced ZNS Efficiency 23

A Free-Space Adaptive Runtime Zone-Reset Algorithm for Enhan...

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15th ACM Workshop on Hot Topics in Storage and File Systems (HotStorage)

作者： Byeon, Sungjin Ro, Joseph Jamil, Safdar Kang, Jeong-Uk Kim, Youngjae Sogang Univ Seoul South Korea Samsung Elect Co Suwon South Korea

ISBN: (纸本)9798400702242

While the state-of-the-art runtime zone-reset algorithm of the ZenFS in RocksDB is optimized for the performance of Zone Namespace (ZNS) SSDs, it does not take into account the lifetime constraint of ZNS SSDs. To address this issue, we present FAR, a Free-space Adaptive Runtime Zone-Reset algorithm for ZenFS, which dynamically adjusts the frequency of runtime zone-reset calls based on the available free-space in the ZNS SSD. We developed FAR with the ZenFS of RocksDB using a ZNS SSD prototype based on the Cosmos+ OpenSSD platform and compared it with the state-of-the-art runtime zone-reset algorithm used in ZenFS. Our extensive evaluations demonstrate that FAR improves the lifetime of ZNS SSD by 2x without compromising performance.

关键词： File System key-value database Solid State Drive

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