Performance Analysis of RDBMS and Hadoop Components with Their File Formats for the Development of Recommender Systems

Gupta, Anchal; Saxena, Merry; Gill, Rupali

doi:10.1109/i2ct.2018.8529480

Cited by 3 publications

(5 citation statements)

References 9 publications

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“…MySQL adalah sistem manajemen database relasional (RDBMS) berbasis SQL (Structured Query Language) yang bersifat open-source dengan model client-server [10]. Secara umum, MySQL adalah perangkat lunak yang berfungsi untuk membuat dan mengelola berbagai informasi yang ada pada database di dalam sebuah server dengan bahasa pemrograman SQL [11], [12].…”

Section: A Database Mysqlunclassified

Sistem Replikasi Basis Data berdasarkan MySQL menggunakan Container Docker

Sholihah¹,

Darujati²

2022

JTE

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This study aims to implement database replication using the master-slave technique. The main focus of this research is to run data replication on the master server so that it can be copied automatically on the slave server. Master-slave replication techniques aim to prevent data loss from system failure events or device damage on the main server. The concept of master-slave replication is to copy data from the master server database to the slave server so that users do not need to manually backup data from the database. Master-slave database replication is one of the features provided by the MySQL database application in the Docker container. Still, to run the replication system, some adjustments and configurations are required for the database application to establish a replication infrastructure automatically. In this study, the replication was run on a MySQL database application with 20 multimedia data files capacity of 100MB. Testing is done by entering data into the database on the master server. The test scenario in this study was to upload data and delete data. The test results show that the data changes automatically: the data on the slave server is the same as on the master server, even though the data on the master server has gone through data uploads and deletions. And vice versa, data changes made on the master server are also directly replicated on the slave server.

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Section: A Database Mysqlunclassified

Sistem Replikasi Basis Data berdasarkan MySQL menggunakan Container Docker

Sholihah¹,

Darujati²

2022

JTE

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“…CERN [12] had chosen four candidate technologies, ORC [13], Parquet [14], Kudu [15] and Avro [16] for this purpose. However, we have included other data file formats like Arrow [17] and text-based formats to this discussion for comprehensibility.…”

Section: Development Of Big Data Systems Requires Identificationmentioning

confidence: 99%

“…Existing literature discuss data formats for specific application areas like bioinformatics [4], recommender systems [13] and their usages in satellite image detection [18] or indoor air quality analysis [19]. Some papers provide an account of how compression can be performed using some formats like Parquet and Avro [20] and performance analysis of use-case with and without the use of these formats [17].…”

Section: Development Of Big Data Systems Requires Identificationmentioning

confidence: 99%

“…RCFile [27] is the most primitive column-based data file format and ORCFile is an optimized version of the same. Although, ORCFile [13] is considered apt for applications with ACID transactions and offers fast access with its indexing feature, Parquet is promoted by Cloudera [36] and is known to perform best with Spark [8]. The most advanced and recent file format in this category is CarbonData [30], but owing to its newer status, its compatibility with technologies is questionable.…”

Section: Datamentioning

confidence: 99%

“…The metadata is stored for each row split as the key and the corresponding data is kept as its value.  Optimized Row Columnar (ORC) File Format Optimized Row Columnar[13] is similar to Parquet and…”

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File Format s for Big Data Storage Systems

Khan*,

Alam*

2019

IJEAT

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Big data is one of the most influential technologies of the modern era. However, in order to support maturity of big data systems, development and sustenance of heterogeneous environments is requires. This, in turn, requires integration of technologies as well as concepts. Computing and storage are the two core components of any big data system. With that said, big data storage needs to communicate with the execution engine and other processing and visualization technologies to create a comprehensive solution. This brings the facet of big data file formats into picture. This paper classifies available big data file formats into five categories namely text-based, row-based, column-based, in-memory and data storage services. It also compares the advantages, shortcomings and possible use cases of available big data file formats for Hadoop, which is the foundation for most big data computing technologies. Lastly, it provides a discussion on tradeoffs that must be considered while choosing a file format for a big data system, providing a framework for creation for file format selection criteria.

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