Unexpectedly, the rise of serverless computing has also collaterally started the
“democratization” of massive-scale data parallelism. This new trend heralded by PyWren …

In recent years ad hoc parallel data processing has emerged to be one of the killer
applications for Infrastructure-as-a-Service (IaaS) clouds. Major Cloud computing …

Unexpectedly, the rise of serverless computing has also collaterally started the"
democratization" of massive-scale data parallelism. This new trend heralded by PyWren …

MapReduce is one of the most widely used programming models for analysing large-scale
datasets, ie Big Data. In recent years, serverless computing and, in particular, Functions as a …

Cloud computing aims to give users virtually unlimited pay-per-use computing resources
without the burden of managing the underlying infrastructure. We present a new job …

Cloud datacenters are becoming increasingly heterogeneous with respect to the hardware
on which virtual machine (VM) instances are hosted. As a result, ostensibly identical …

MapReduce as a service enjoys wide adoption in commercial clouds today [3],[23]. But most
cloud providers just deploy native Hadoop [24] systems on their cloud platforms to provide …

As the volume of data to be processed in a timely manner soars, the scale of computing and
storage systems has much trouble keeping up with such a rate of explosive data growth. A …

Distributed data processing framework MapReduce is increasingly deployed in Clouds to
leverage the pay-per-usage cloud computing model. Popular Hadoop MapReduce …

MapReduce has become a popular model for data-intensive computation in recent years. By
breaking down each job into small map and reduce tasks and executing them in parallel …