大数据管理:概念,技术与挑战 Page 1 大数据管理:概念,技术与挑战 孟小峰慈祥 (中国人民大学信息
学院北京100872) Big Data Management: Concepts, Techniques and Challenges Meng …

In the last two decades, the continuous increase of computational power has produced an
overwhelming flow of data which has called for a paradigm shift in the computing …

Context: In recent years, the valuable knowledge that can be retrieved from petabyte scale
datasets–known as Big Data–led to the development of solutions to process information …

In this paper, we review the background and state-of-the-art of big data. We first introduce
the general background of big data and review related technologies, such as could …

Recent technological advancements have led to a deluge of data from distinctive domains
(eg, health care and scientific sensors, user-generated data, Internet and financial …

Many" big data" applications must act on data in real time. Running these applications at
ever-larger scales requires parallel platforms that automatically handle faults and stragglers …

We present Resilient Distributed Datasets (RDDs), a distributed memory abstraction that lets
programmers perform in-memory computations on large clusters in a fault-tolerant manner …

Many important “big data” applications need to process data arriving in real time. However,
current programming models for distributed stream processing are relatively low-level, often …

Storm has emerged as a promising computation platform for stream data processing. In this
paper, we first show inefficiencies of the current practice of Storm scheduling and challenges …

Kineograph is a distributed system that takes a stream of incoming data to construct a
continuously changing graph, which captures the relationships that exist in the data feed. As …