Summary generation for a distributed graph database

A computer-implemented method of applying a set of summaries of a partitioned graph database, the method comprising:

• obtaining a partitioned graph database and a generated set of summaries of the partitioned graph database;
• receiving, by the partitioned graph database, a query having one or more basic graph patterns;
• for each basic graph pattern, identifying one or more partitions of the set of partitions based on the generated set of summaries, wherein the one or more partitions comprise all RDF tuples of the obtained partitioned graph database that answer the query;
• and
• executing the received query on the identified one or more partitions of the set,
• wherein the partitioned graph database is generated by generating a summary of a graph database having a set of RDF tuples including:
• obtaining the graph database, and
• generating a probabilistic extract of information of the graph database including:
• a set of probabilistic filters, each probabilistic filter of the set determining if at least one RDF tuple, existing in the graph database, corresponds to a respective basic graph pattern of the probabilistic filter with a possibility of false positive and with no false negative,
• metadata defining a role for each probabilistic filter of the set, and
• a value indicating a respective number of RDF tuples in the graph database for each predicate,
• thereby obtaining the summary of the graph database,
• wherein the graph database is a partitioned graph database having a set of partitions, and
• wherein the generating further includes generating a probabilistic extract of information for each partition of the partitioned graph database.

A system comprising:

• a processor coupled to a memory, the memory having recorded thereon instructions for generating a summary of a graph database having a set of RDF tuples that when executed by the processor cause the processor be configured to:
• obtain the graph database, and
• generate a probabilistic extract of information of the graph database including:
• a set of probabilistic filters, each probabilistic filter of the set determining if at least one RDF tuple, existing in the graph database, corresponds to a respective basic graph pattern of the probabilistic filter with a possibility of false positive and with no false negative,
• metadata defining a role for each probabilistic filter of the set, and
• a value indicating a respective number of RDF tuples in the graph database for each predicate,
• thereby obtaining the summary of the graph database.