  Many distributed applications adopt a partition/aggregation pattern to
achieve high performance and scalability. The aggregation process, which
usually takes a large portion of the overall execution time, incurs large
amount of network traffic and bottlenecks the system performance. To reduce
network traffic,some researches take advantage of network devices to commit
innetwork aggregation. However, these approaches use either special topology or
middle-boxes, which cannot be easily deployed in current datacenters. The
emerging programmable RMT switch brings us new opportunities to implement
in-network computation task. However, we argue that the architecture of RMT
switch is not suitable for in-network aggregation since it is designed
primarily for implementing traditional network functions. In this paper, we
first give a detailed analysis of in-network aggregation, and point out the key
factor that affects the data reduction ratio. We then propose SwitchAgg, which
is an innetwork aggregation system that is compatible with current datacenter
infrastructures. We also evaluate the performance improvement we have gained
from SwitchAgg. Our results show that, SwitchAgg can process data aggregation
tasks at line rate and gives a high data reduction rate, which helps us to cut
down network traffic and alleviate pressure on server CPU. In the system
performance test, the job-completion-time can be reduced as much as 50%
