Datasets that have random missing nodes in them are termed as Incomplete Big Data. While cleaned and complete datasets are preferred, having an algorithm to resolve queries on incomplete datasets are essential. In this paper we first survey these algorithms then we survey the different ways where MapReduce framework has been used to solve data problems. Additionally, we research methods to partition the data sets being fed into the framework. Finally, we suggest a method by which one algorithm of resolving incomplete dataset queries can be improved.
Volume 11 | 04-Special Issue
Pages: 912-916