Semih Salihoğlu
YOU?
Author Swipe
View article: Optimizing differentially-maintained recursive queries on dynamic graphs
Optimizing differentially-maintained recursive queries on dynamic graphs Open
Differential computation (DC) is a highly general incremental computation/view maintenance technique that can maintain the output of an arbitrary and possibly recursive dataflow computation upon changes to its base inputs. As such, it is a…
View article: Making RDBMSs Efficient on Graph Workloads Through Predefined Joins
Making RDBMSs Efficient on Graph Workloads Through Predefined Joins Open
Joins in native graph database management systems (GDBMSs) are predefined to the system as edges, which are indexed in adjacency list indices and serve as pointers. This contrasts with and can be more performant than value-based joins in R…
View article: The future is big graphs
The future is big graphs Open
Ensuring the success of big graph processing for the next decade and beyond.
View article: Graphsurge
Graphsurge Open
This paper presents the design and implementation of a new open-source view-based graph analytics system called Graphsurge. Graphsurge is designed to support applications that analyze multiple snapshots or views of a large-scale graph. Use…
View article: Accurate Summary-based Cardinality Estimation Through the Lens of Cardinality Estimation Graphs
Accurate Summary-based Cardinality Estimation Through the Lens of Cardinality Estimation Graphs Open
We study two classes of summary-based cardinality estimators that use statistics about input relations and small-size joins in the context of graph database management systems: (i) optimistic estimators that make uniformity and conditional…
View article: A+ Indexes: Tunable and Space-Efficient Adjacency Lists in Graph Database Management Systems
A+ Indexes: Tunable and Space-Efficient Adjacency Lists in Graph Database Management Systems Open
Graph database management systems (GDBMSs) are highly optimized to perform fast traversals, i.e., joins of vertices with their neighbours, by indexing the neighbourhoods of vertices in adjacency lists. However, existing GDBMSs have system-…
View article: Columnar Storage and List-based Processing for Graph Database Management Systems
Columnar Storage and List-based Processing for Graph Database Management Systems Open
We revisit column-oriented storage and query processing techniques in the context of contemporary graph database management systems (GDBMSs). Similar to column-oriented RDBMSs, GDBMSs support read-heavy analytical workloads that however ha…
View article: Integrating Column-Oriented Storage and Query Processing Techniques into Graph Database Management Systems
Integrating Column-Oriented Storage and Query Processing Techniques into Graph Database Management Systems Open
Column-oriented RDBMSs, which support traditional read-heavy analytics workloads, employ a specific set of storage and query processing techniques for scalability and performance, such as positional tuple IDs, column-specific compression, …
View article: Box Covers and Domain Orderings for Beyond Worst-Case Join Processing
Box Covers and Domain Orderings for Beyond Worst-Case Join Processing Open
Recent beyond worst-case optimal join algorithms Minesweeper and its generalization Tetris have brought the theory of indexing and join processing together by developing a geometric framework for joins. These algorithms take as input an in…
View article: The Future is Big Graphs! A Community View on Graph Processing Systems
The Future is Big Graphs! A Community View on Graph Processing Systems Open
Graphs are by nature unifying abstractions that can leverage interconnectedness to represent, explore, predict, and explain real- and digital-world phenomena. Although real users and consumers of graph instances and graph workloads underst…
View article: Box Covers and Domain Orderings for Beyond Worst-Case Join Processing
Box Covers and Domain Orderings for Beyond Worst-Case Join Processing Open
Recent beyond worst-case optimal join algorithms Minesweeper and its generalization Tetris have brought the theory of indexing and join processing together by developing a geometric framework for joins. These algorithms take as input an in…
View article: Optimizing subgraph queries by combining binary and worst-case optimal joins
Optimizing subgraph queries by combining binary and worst-case optimal joins Open
We study the problem of optimizing subgraph queries using the new worst-case optimal join plans. Worst-case optimal plans evaluate queries by matching one query vertex at a time using multi-way intersections. The core problem in optimizing…
View article: Distributed Evaluation of Subgraph Queries Using Worstcase Optimal LowMemory Dataflows
Distributed Evaluation of Subgraph Queries Using Worstcase Optimal LowMemory Dataflows Open
We study the problem of finding and monitoring fixed-size subgraphs in a continually changing large-scale graph. We present the first approach that (i) performs worst-case optimal computation and communication, (ii) maintains a total memor…
View article: It's All a Matter of Degree: Using Degree Information to Optimize Multiway Joins
It's All a Matter of Degree: Using Degree Information to Optimize Multiway Joins Open
We optimize multiway equijoins on relational tables using degree information. We give a new bound that uses degree information to more tightly bound the maximum output size of a query. On real data, our bound on the number of triangles in …