Towards automatic detection and prioritization of pre-logging overhead: a case study of hadoop ecosystem

Chen, Zhi; Han, Junxiao; Yin, Jianwei

doi:10.1007/s10515-021-00317-7

Cited by 3 publications

(2 citation statements)

References 36 publications

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“…For merchants, the recommendation system can also record customer information and can also carry out corresponding business promotion activities to customers through the platform and lay the foundation for recooperation with customers [8]. In order to better attract customers, help customers find the products they need and improve the quality of sales, and product recommendation systems are gradually being applied to e-commerce websites [9]. The recommendation system plays a role similar to that of a shopping guide in the e-commerce system.…”

Section: Introductionmentioning

confidence: 99%

Precision Marketing Optimization Model of e-Commerce Platform Based on Collaborative Filtering Algorithm

2022

Wireless Communications and Mobile Computing

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e-commerce mode shows great modern commercial value. In particular, online shopping has become a fashion and trend for people because of its convenience and rapidness. How to find the information users that need accurately and quickly in the increasing network information and recommend products is a big problem. Although precision marketing was mainly used in e-commerce activities in the past, due to factors such as the technical basis and data analysis ability at that time, there was not enough technical ability and theoretical basis to deeply mine and make use of the existing data. The collaborative filtering algorithm is one of the most widely used and successful recommendation techniques, but it has obvious defects. In this paper, the nearest neighbor collaborative filtering recommendation algorithm based on statistical eigenvalue classification is proposed in the collaborative filtering algorithm. By calculating the similarity between items, the user’s rating of unrated items is preliminarily predicted, the nearest neighbor of items is formed, and the classified cluster of items is formed. The matrix is filled by the similarity between related items. The cold treatment problem is solved under the optimization of the ant colony algorithm. In the experiment of the model, the optimization rate for the cold start problem is 87.3%.

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Section: Introductionmentioning

confidence: 99%

Precision Marketing Optimization Model of e-Commerce Platform Based on Collaborative Filtering Algorithm

2022

Wireless Communications and Mobile Computing

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“…In addition to the basic core components of Hadoop, they include the Distributed Coordination Service -Zookeeper; the Distributed Column-Storage Database -HBase; the Workflow Scheduling System -Oozie; and the Data Warehouse -Hive. Moreover, there are various distributed computing architectures, such as the data batch processing framework Spark and the data stream processing framework Storm (Ravichandran, 2017;Zhi et al, 2022;Islam et al, 2012;Thusoo et al, 2009;Zaharia et al, 2012;Cha & Wachowicz, 2015).…”

Section: Architecturementioning

confidence: 99%

A distributed data processing scheme based on Hadoop for synchrotron radiation experiments

Zhang,

Dai,

Sun

et al. 2024

J Synchrotron Radiat

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With the development of synchrotron radiation sources and high-frame-rate detectors, the amount of experimental data collected at synchrotron radiation beamlines has increased exponentially. As a result, data processing for synchrotron radiation experiments has entered the era of big data. It is becoming increasingly important for beamlines to have the capability to process large-scale data in parallel to keep up with the rapid growth of data. Currently, there is no set of data processing solutions based on the big data technology framework for beamlines. Apache Hadoop is a widely used distributed system architecture for solving the problem of massive data storage and computation. This paper presents a set of distributed data processing schemes for beamlines with experimental data using Hadoop. The Hadoop Distributed File System is utilized as the distributed file storage system, and Hadoop YARN serves as the resource scheduler for the distributed computing cluster. A distributed data processing pipeline that can carry out massively parallel computation is designed and developed using Hadoop Spark. The entire data processing platform adopts a distributed microservice architecture, which makes the system easy to expand, reduces module coupling and improves reliability.

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A literature review and existing challenges on software logging practices

Batoun,

Sayagh,

Aghili

et al. 2024

Empir Software Eng

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Towards automatic detection and prioritization of pre-logging overhead: a case study of hadoop ecosystem

Cited by 3 publications

References 36 publications

Precision Marketing Optimization Model of e-Commerce Platform Based on Collaborative Filtering Algorithm

Precision Marketing Optimization Model of e-Commerce Platform Based on Collaborative Filtering Algorithm

A distributed data processing scheme based on Hadoop for synchrotron radiation experiments

A literature review and existing challenges on software logging practices

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