Data management

Management system

Quantum mechanics

Big data

Context (archaeology)

World Wide Web

Analytics

Biology

Smart city

Embedded system

Computer security

Scheduling (production processes)

The Internet

Economics

Data mining

Computer science

Data processing

Distributed computing

Paleontology

Physics

Database

Internet of Things

Management

Operations management

Data science

Personalization

Data analysis

Volume (thermodynamics)

Future Generation Computer Systems

The unbroken amplification of a versatile urban setup is challenged by huge Big Data processing. Understanding the voluminous data generated in a smart urban environment for decision making is a challenging task. Big Data analytics is performed to obtain useful insights about the massive data. The existing conventional techniques are not suitable to get a useful insight due to the huge volume of data. Big Data analytics has attracted significant attention in the context of large-scale data computation and processing. This paper presents a Hadoop-based architecture to deal with Big Data loading and processing. The proposed architecture is composed of two different modules, i.e., Big Data loading and Big Data processing. The performance and efficiency of data loading is tested to propose a customized methodology for loading Big Data to a distributed and processing platform, i.e., Hadoop. To examine data ingestion into Hadoop, data loading is performed and compared repeatedly against different decisions. The experimental results are recorded for various attributes along with manual and traditional data loading to highlight the efficiency of our proposed solution. On the other hand, the processing is achieved using YARN cluster management framework with specific customization of dynamic scheduling. In addition, the effectiveness of our proposed solution regarding processing and computation is also highlighted and decorated in the context of throughput.

Urban data management system: Towards Big Data analytics for Internet of Things based smart urban environment using customized Hadoop