  Modern trends in data collection are bringing current mainstream techniques
for database query processing to their limits. Consequently, various novel
approaches for efficient query processing are being actively studied. One such
approach is based on hypertree decompositions (HDs), which have been shown to
carry great potential to process complex queries more efficiently and with
stronger theoretical guarantees. However, using HDs for query execution relies
on the difficult task of computing decompositions of the query structure, which
guides the efficient execution of the query. From theoretical results we know
that the performance of purely sequential methods is inherently limited, yet
the problem is susceptible to parallelisation.
  In this paper we propose the first algorithm for computing hypertree
decompositions that is well-suited for parallelisation. The proposed algorithm
log-k-decomp requires only a logarithmic number of recursion levels and
additionally allows for highly parallelised pruning of the search space by
restriction to balanced separators. We provide detailed experimental evaluation
over the HyperBench benchmark and demonstrate that our approach is highly
effective especially for complex queries.
