null
(Ed.)
Hybrid Transactional and Analytical Processing
(HTAP) systems have become popular in the past decade. HTAP
systems allow running transactional and analytical processing
workloads on the same data and hardware. As a result, they
suffer from workload interference. Despite the large body of
existing work in HTAP systems and architectures, none of the
existing work has systematically analyzed workload interference
for HTAP systems.
In this work, we characterize workload interference for HTAP
systems. We show that the OLTP throughput drops by up to
42% due to sharing the hardware resources. Partitioning the
last-level cache (LLC) among the OLTP and OLAP workloads
can significantly improve the OLTP throughput without hurting
the OLAP throughput. The OLAP throughput is significantly
reduced due to sharing the data. The OLAP execution time is
exponentially increased if the OLTP workload generates fresh
tuples faster than the HTAP system propagates them. Therefore,
in order to minimize the workload interference, HTAP systems
should isolate the OLTP and OLAP workloads in the shared
hardware resources and should allocate enough resources to fresh
tuple propagation to propagate the fresh tuples faster than they
are generated.
more »
« less