  In this paper, we analyze some basic features of SPARQL queries coming from
our practical world in a statistical way. These features include three
statistic features such as the occurrence frequency of triple patterns,
fragments, well-designed patterns and four semantic features such as
monotonicity, non-monotonicity, weak monotonicity (old solutions are still
served as parts of new solutions when some new triples are added) and
satisfiability. All these features contribute to characterize SPARQL queries in
different dimensions. We hope that this statistical analysis would provide some
useful observation for researchers and engineers who are interested in what
practical SPARQL queries look like, so that they could develop some practical
heuristics for processing SPARQL queries and build SPARQL query processing
engines and benchmarks. Besides, they can narrow the scope of their problems by
avoiding those cases that do possibly not happen in our practical world.
