1. A method for realizing graph processing based on a MapReduce architecture, comprising: receiving an input file of a graph processing job; predicting a MapReduce task execution time distribution of the graph processing job using an obtained MapReduce task degree-execution time relationship distribution and a degree distribution of the graph processing job, wherein the MapReduce task degree-execution time relationship distribution is a Map task degree-execution time relationship distribution and a Reduce task degree-execution time relationship distribution, both of which may be obtained from historical records of MapReduce tasks processing; and dividing the input file of the graph processing job into input data splits of MapReduce tasks according to the predicted MapReduce task execution time distribution of the graph processing job, wherein dividing the input file of the graph processing job into input data splits of MapReduce tasks according to the predicted MapReduce task execution time distribution of the graph processing job includes: detecting whether key-value pairs of nodes in the input file of the graph processing job are constructed with degrees of the nodes; responsive to detecting that the key-value pairs of nodes in the input file are constructed with degrees of the nodes, sorting the key-value pairs of the nodes according to the degrees of the nodes; and dividing the sorted key-value pairs of the nodes into input data splits of MapReduce tasks according to the predicted MapReduce task execution time distribution of the graph processing job, wherein the step of dividing the sorted key-value pairs of the nodes into input data splits of MapReduce tasks according to the predicted MapReduce task execution time distribution of the graph processing job comprises: equally dividing the sorted key-value pairs of the nodes into input data splits of the Map tasks according to the predicted Map task execution time distribution; equally dividing the sorted key-value pairs of the nodes into input data splits of the Reduce tasks according to the predicted Reduce task execution time distribution; and assigning, by a Job Tracker, the input data splits of the Map tasks to Map Task Trackers to execute and the input data splits of the Reduce tasks to Reduce Task Trackers to execute; executing, by the Map Task Trackers, the input data splits of the assigned Map tasks; and executing, by the Reduce task Trackers, the input data splits of the assigned Reduce tasks.