  Pregel is a popular distributed computing model for dealing with large-scale
graphs. However, it can be tricky to implement graph algorithms correctly and
efficiently in Pregel's vertex-centric model, especially when the algorithm has
multiple computation stages, complicated data dependencies, or even
communication over dynamic internal data structures. Some domain-specific
languages (DSLs) have been proposed to provide more intuitive ways to implement
graph algorithms, but due to the lack of support for remote access --- reading
or writing attributes of other vertices through references --- they cannot
handle the above mentioned dynamic communication, causing a class of Pregel
algorithms with fast convergence impossible to implement.
  To address this problem, we design and implement Palgol, a more declarative
and powerful DSL which supports remote access. In particular, programmers can
use a more declarative syntax called chain access to naturally specify dynamic
communication as if directly reading data on arbitrary remote vertices. By
analyzing the logic patterns of chain access, we provide a novel algorithm for
compiling Palgol programs to efficient Pregel code. We demonstrate the power of
Palgol by using it to implement several practical Pregel algorithms, and the
evaluation result shows that the efficiency of Palgol is comparable with that
of hand-written code.

Distributed, Parallel, and Cluster Computing