AdMap: a framework for advertising using MapReduce pipeline

Abhay Chaudhary, K R Batwada Batwada, Namita Mittal, Emmanuel S. Pilli

Abstract


There is a vast collection of data for consumers due to tremendous development in digital marketing. For their ads or for consumers to validate nearby services which already are upgraded to the dataset systems, consumers are more concerned with the amount of data. Hence there is a void formed between the producer and the client. To fill that void, there is the need for a framework which can facilitate all the needs for query updating of the data. The present systems have some shortcomings by a vast number of information that each time lead to decision tree-based approach. A systematic solution to the automated incorporation of data into a Hadoop distributed file system (HDFS) warehouse (Hadoop file system) includes a data hub server, a generic data charging mechanism and a metadata model. In our model framework, the database would be able to govern the data processing schema. In the future, as a variety of data is archived, the datalake will play a critical role in managing that data. To order to carry out a planned loading function, the setup files immense catalogue move the datahub server together to attach the miscellaneous details dynamically to its schemas.

Keywords


Advertising; Advertising and publishing; Data lake; Data warehouse; Hadoop distributed file system Map reduce

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DOI: https://doi.org/10.11591/csit.v3i2.p82-93

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Computer Science and Information Technologies
ISSN: 2722-323X, e-ISSN: 2722-3221

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