Abstract: Provided are data processing apparatus and methods for predicting a pattern frequency thereof. The data processing apparatus includes: a storage unit adapted to store a preset graph pattern, an occurrence frequency of the preset graph pattern, and information on actual data nodes corresponding to each node which belongs to the graph pattern; and a control unit adapted to compare the preset graph pattern with a graph pattern to be searched to perform a graph search, and when the preset graph pattern is not included in the graph to be searched, search for a node shared by two different preset graph patterns which are stored in the storage unit to perform the graph search. By this configuration, it is possible to predict a level of an intermediate result to optimize a graph query and effectively calculate sizes of various graphs patterns while making a capacity of a memory small.

Abstract: Provided are a data processing apparatus and a data mapping method thereof. The data processing apparatus according to an present invention includes: a storage unit adapted to store relational data; a mapping unit adapted to store mapping information for mapping a schema of a relational database having the relational data stored therein to a node or an edge of a graph database; and a control unit adapted to convert the relational data into graph data by the mapping unit. By this configuration, it is possible to easily transfer the data of the relational database into the graph database, query the relational database using a query language used in a graph data model, and visualize the relational database in a graph represented by a node and an edge.

Abstract: Provided are data processing apparatus and methods for predicting a pattern frequency thereof. The data processing apparatus includes: a storage unit adapted to store a preset graph pattern, an occurrence frequency of the preset graph pattern, and information on actual data nodes corresponding to each node which belongs to the graph pattern; and a control unit adapted to compare the preset graph pattern with a graph pattern to be searched to perform a graph search, and when the preset graph pattern is not included in the graph to be searched, search for a node shared by two different preset graph patterns which are stored in the storage unit to perform the graph search. By this configuration, it is possible to predict a level of an intermediate result to optimize a graph query and effectively calculate sizes of various graphs patterns while making a capacity of a memory small.