Seminars

Abstract: We consider the problem of computing a conjunctive query on a large database in a parallel setting with p servers. Unlike traditional query processing, the complexity is no longer dominated by the number of disk accesses. Typically, a query is evaluated by a sufficiently large number of servers such that the entire data can be kept in the main memory of these servers. The dominant cost becomes that of communicating data and synchronizing among the servers.
I will present some interesting results in [1, 2, 3, 4] dealing with the communication complexity of massively parallel computation of a query. The computation is performed in "rounds".
First, I will present the Massively Parallel Communication (MPC) model to analyze the tradeoff between the number of rounds and the amount of communication required in a massively parallel computing environment.
Then I will present the HyperCube (HC) algorithm that computes a full conjunctive query q in one round.
I will discuss the communication complexity [2]. The main result is the optimal load O(m/p1/τ ) where τ is the fractional vertex cover of the hypergraph of q and m the input data size.

References
[1] Parallel Evaluation of Conjunctive Queries. Paris Koutris, Dan Suciu PODS2011
[2] Communication Steps for Parallel Query Processing. Paul Beame, Paris Koutris, Dan Suciu PODS2013
[3] Skew in Parallel Query Processing. Paul Beame, Paris Koutris Dan Suciu PODS'2014
[4] Worst-Case Optimal Algorithms for Parallel Query Processing. Paris Koutris, Paul Beame, Dan Suciu ICDT2016

Abstract:
The challenge that we tackle in this thesis is the problem of how to answer
XPath queries on XML streams with low latency, full coverage, high time
efficiency, and low memory costs. We first propose to approximate earli-
est query answering for navigational XPath queries by compilation to early
nested word automata. It turns out that this leads to almost optimal la-
tency and memory consumption. Second, we contribute a formal semantics
of XPath 3.0. It is obtained by mapping XPath to the new query language
λXP that we introduce. We then show how to compile λXP queries to net-
works of early nested word automata, and develop streaming algorithms for
the latter. Thereby we obtain a streaming algorithm that indeed covers all of
XPath 3.0. Third, we develop an algorithm for projecting XML streams with
respect to the query defined by an early nested word automaton. Thereby
we are able to make our streaming algorithms highly time efficient. We have
implemented all our algorithms with the objective to obtain an industrially
applicable streaming tool. It turns out that our algorithms outperform all
previous approaches in time efficiency, coverage, and latency.