Using different scheduling polices can affect the system performance in Hadoop architecture. In Hadoop architecture, the default scheduling policy is First-In-First-Out (FIFO). However, the FIFO scheduler simply schedule jobs according to their arrival time and does not consider any other factors that may have great impact on system performance. As a result, using FIFO cannot achieve good enough performance in Hadoop. In this paper, we propose a novel scheduling algorithm, called FSSL (FIFO with Shared-Scan and Locality-aware). FSSL is a scheduling policy based on FIFO and take locality of required data and data sharing probability between jobs into account. Such that the jobs which need the same data can be gathered and easily batch processed, and thus reduce the overhead of transferring data between data nodes and computations nodes. The results show that FSSL scheduling polity can improve system performance about 65% compared to FIFO scheduling policy.