  Distributed transactions on high-overhead TCP/IP-based networks were
conventionally considered to be prohibitively expensive and thus were avoided
at all costs. To that end, the primary goal of almost any existing partitioning
scheme is to minimize the number of cross-partition transactions. However, with
the new generation of fast RDMA-enabled networks, this assumption is no longer
valid. In fact, recent work has shown that distributed databases can scale even
when the majority of transactions are cross-partition. In this paper, we first
make the case that the new bottleneck which hinders truly scalable transaction
processing in modern RDMA-enabled databases is data contention, and that
optimizing for data contention leads to different partitioning layouts than
optimizing for the number of distributed transactions. We then present Chiller,
a new approach to data partitioning and transaction execution, which aims to
minimize data contention for both local and distributed transactions. Finally,
we evaluate Chiller using various workloads, and show that our partitioning and
execution strategy outperforms traditional partitioning techniques which try to
avoid distributed transactions, by up to a factor of 2.
