Abstract
In the era of big data, interest in analysis andextraction of information from large data graphs is increasingrapidly. This paper examines the field of graph analytics fromsomewhat of a query processing point of view. Whether it bedetermination of shortest paths or finding patterns in a datagraph matching a query graph, the issue is to find interestingcharacteristics or information content from graphs. Many ofthe associated problems can be abstracted to problems onpaths or problems on patterns. Unfortunately, seemingly simpleproblems, such as finding patterns in a data graph matching aquery graph are surprisingly difficult. In addition, the iterativenature of algorithms in this field makes the simple MapReducestyle of parallel and distributed processing less effective. Still,the need to provide answers even for very large graphs isdriving the research. Progress, trends and directions for futureresearch are presented