This article proposes to improve Apache Hadoop scheduling through the usage of context-awareness. Apache Hadoop is the most popular implementation of the MapReduce paradigm for distributed computing, but its design doesn't adapt automatically to computing nodes' context and capabilities. By introducing context-awareness into Hadoop, we intent to dynamically adapt its scheduling to the execution environment. This is a necessary feature in the context of pervasive grids, which are heterogeneous, dynamic and shared environments. The solution has been incorporated into Hadoop and evaluated through controlled experiments. The experiments demonstrate that context-awareness provides comparative performance gains, especially when part of the resources disappear during execution.