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Representation of a query on input graph in Fig. 1a

Representation of a query on input graph in Fig. 1a

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Fig. 1: Sample input graph and its partitions
Figure 2: Representation of a query on input graph in Fig. 1a
Figure 3: Architecture of the PGQP System
Figure 4: Different Cases of Query Evaluation in Partitioned Graph
+6 Figure 5: Query answering in the PGQP System
Query Processing on Large Graphs: Approaches To Scalability and Response Time Trade Offs
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  • May 2019
With the advent of social networks and the web, the graph sizes have grown too large to fit in main memory precipitating the need for alternative approaches for an efficient, scalable evaluation of queries on graphs of any size. Here, we use the divide and conquer approach by partitioning a graph and process queries over partitions to obtain all or...
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Context 1
... is used as the graph on which a query is processed. Figure 2 illustrates the representation of a sample query -"Find all actors in the movie 'Beyond all boundaries' and year of its production". Cost-Based Plan Generation: As described in [6,10], a cost-based plan generation is used along the lines of relational approach to query processing where metadata collected from the database is used to estimate the cost of a query plan, we create a graph catalog which contains information that are relevant to plan generation in a graph database. ...
Context 2
... is used as the graph on which a query is processed. Figure 2 illustrates the representation of a sample query -"Find all actors in the movie 'Beyond all boundaries' and year of its production". Cost-Based Plan Generation: As described in [6,10], a cost-based plan generation is used along the lines of relational approach to query processing where metadata collected from the database is used to estimate the cost of a query plan, we create a graph catalog which contains information that are relevant to plan generation in a graph database. ...

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Figure 1: Sample input graph and its partitions
Figure 2: Representation of a query on input graph in Fig. 1a
Figure 3: Architecture of the PGQP System
Figure 4: Different Cases of Query Evaluation in Partitioned Graph
+2 Figure 5: Query answering in the PGQP System
Query processing on large graphs: Approaches to scalability and response time trade offs
Article
Full-text available
  • Sep 2019
Graphs, being an expressive data structure, have become increasingly important for modeling real-world applications, such as collaboration, different kinds of transactions, social networks, to name a few. With the advent of social networks and the web, the graph sizes have grown too large to fit in main memory precipitating the need for alternative...
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