An Optimal Solution of Storing and Processing Small Image Files on Hadoop
Lu Lu, Qiu Yan Feng · Procedia Computer Science · 2019
The rapid development of the Internet, especially mobile Internet, makes it much easier for people to make social contacts online. Nowadays they tend to spend more and more time on social network service, producing a lot of image files. This brings a challenge to traditional standalone framework on handing the continued increasing image files. Therefore, it is advisable to find a new way to face the challenge. Hadoop is a notable, widely-used project for distributed storage and computations with high efficiency, data integrity, reliability and fault tolerance. Hadoop Distributed File System and MapReduce are two primary subprojects respectively for big data storage and computations. However, Hadoop do not provide any interface for image processing. Worse, both Hadoop Distributed File System and MapReduce have trouble processing large amount of small files, decreasing efficiency of files access and distributed computations. This prevents us from performing images processing actions on Hadoop. This paper proposes a method to optimize small image files storage on Hadoop and self-defines an input/output format to enable Hadoop to process image files.