  Semantic Web applications require querying available RDF Data with high
performance and reliability. However, ensuring both data availability and
performant SPARQL query execution in the context of public SPARQL servers are
challenging problems. Queries could have arbitrary execution time and unknown
arrival rates. In this paper, we propose SaGe, a preemptive server-side SPARQL
query engine. SaGe relies on a preemptable physical query execution plan and
preemptable physical operators. SaGe stops query execution after a given slice
of time, saves the state of the plan and sends the saved plan back to the
client with retrieved results. Later, the client can continue the query
execution by resubmitting the saved plan to the server. By ensuring a fair
query execution, SaGe maintains server availability and provides high query
throughput. Experimental results demonstrate that SaGe outperforms the state of
the art SPARQL query engines in terms of query throughput, query timeout and
answer completeness.
