The invention discloses a
big data task
scheduling system and method. The
big data task scheduling method comprises the following steps that: a task configuration module acquires a task configuration command, and configures a task parameter according to the task configuration command; a task scheduling center node generates an
executable task according to the task parameter, performs statistics to obtain the number of tasks running on the task running node and a
data source, and controls a
concurrency degree of the tasks according to the
task number and a preset threshold value, so that the
task number is small than the preset threshold value; and task distribution is performed when the
concurrency degree of the tasks is in a preset threshold value range and satisfies dependence, and the task running node runs the
executable task allocated by the task scheduling center node. In the method, the
concurrency degree of current tasks is obtained by statistics, and whether the number of run tasks exceeds the preset threshold value or not is judged to determine whether to continue issuing the
executable task or not, so that over high
system load caused by simultaneous running of excessive tasks is avoided. Through adoption of the
system and the method, the concurrency degree of
big data tasks is controlled, so that the running efficiency of the big data tasks is ensured.