The invention discloses a method for anomaly detection in a MapReduce environment. The method comprises the following steps of: 1, acquiring performance index values of each slave node in the MapReduce environment, and transmitting the performance index values to a master node; 2, categorizing the acquired performance index values of each slave node according to the categories of performance indexes; 3, clustering each category of performance index values of each slave node by using a density-based clustering method; and 4, analyzing clustering results, and recording and outputting an obtained anomalous result. Algorithms are simple, and the method is low in complexity; and in a task execution process, reported data can be instantly analyzed and processed without waiting for the finishing of task execution, the anomalous result can be instantly output, and online detection can be realized, so that the method is high in real-time performance.