Oracle International Corporation

Petr Koupy

Sungpack Hong

Hassan Chafi

Vasileios Trigonakis

Thomas Manhardt

Siegfried Depner

Jinsu Lee

Vlad Ioan Haprian

Jean-Pierre Lozi

Iraklis Psaroudakis

Arnaud Delamare

Nicholas Roth

Stefan Kaestle

Abderrahmane Melhaoui

Jinsoo Lee

Techniques herein minimally communicate between computers to repartition a graph. In embodiments, each computer receives a partition of edges and vertices of the graph. For each of its edges or vertices, each computer stores an intermediate representation into an edge table (ET) or vertex table. Different edges of a vertex may be loaded by different computers, which may cause a conflict. Each computer announces that a vertex resides on the computer to a respective tracking computer. Each tracking computer makes assignments of vertices to computers and publicizes those assignments. Each computer that loaded conflicted vertices transfers those vertices to computers of the respective assignments. Each computer stores a materialized representation of a partition based on: the ET and vertex table of the computer, and the vertices and edges that were transferred to the computer. Edges stored in the materialized representation are stored differently than edges stored in the ET.

Method of distributed graph loading for minimal communication and good balance via lazy materialization and directory indirection using indexed tabular representation

In an embodiment, a computer of a cluster of computers receives graph logic that specifies a sequence of invocations, including a current invocation and a next invocation, of parallelism operations that can detect whether the graph logic should prematurely terminate. The computer initiates, on the computers of the cluster, execution of the graph logic to process a distributed graph. Before the current invocation, the graph logic registers reversion logic for a modification of the distributed graph that execution of the graph logic has caused. During the current invocation, it is detected that the graph logic should prematurely terminate. Execution of the graph logic on the cluster is terminated without performing the next invocation in the sequence of invocations. The reversion logic reverses the modification of the distributed graph to restore consistency. The distributed graph is retained in volatile memory of the cluster for reuse such as relaunch of the graph logic.

Methodology for fast and seamless task cancelation and error handling in distributed processing of large graph data

Techniques are described herein for evaluating graph processing tasks using a multi-stage pipelining communication mechanism. In a multi-node system comprising a plurality of nodes, each node of said plurality of nodes executes a respective communication agent object. The respective communication agent object comprises: a sender lambda function is configured to perform sending operations and generate source messages based on the sender operations. An intermediate lambda function is configured to read source messages marked for a node, perform intermediate operations based on the source messages and generate intermediate messages based on the intermediate operations. A final receiver lambda function configured to: read intermediate messages marked for said each node, perform final operations based on the intermediate messages and generate a final result based on the final operations.

Multi-stage pipelining for distributed graph processing

Techniques are described herein for early pruning of potential graph query results. Specifically, based on determining that property values of a path through graph data cannot affect results of a query, the path is pruned from a set of potential query solutions prior to fully exploring the path. Early solution pruning is performed on prunable queries that project prunable functions including MIN, MAX, SUM, and DISTINCT, the results of which are not tied to a number of paths explored for query execution. A database system implements early solution pruning for a prunable query based on intermediate results maintained for the query during query execution. Specifically, when a system determines that property values of a given potential solution path cannot affect the query results reflected in intermediate results maintained for the query, the path is discarded from the set of possible query solutions without further exploration of the path.

Optimizing graph queries by performing early pruning

Techniques are described herein for asynchronous execution of queries on statically replicated graph data. In an embodiment, a graph is partitioned among a plurality of computers executing the graph querying engine. One or more high-degree vertices of the graph are each replicated in each graph partition. The partitions, including the replicated high-degree vertices, are loaded in memory of the plurality of computers. To execute a query, a query plan is generated based on the query. The query plan specifies a plurality of operators and an order for the plurality of operators. The order is such that if an operator requires data generated by another operator, then the other operator is ordered before the operator in the query plan. Replicated copies of a vertex is visited if matches made by subsequent operator(s) are limited by data unique to the replicated vertices.

Fast distributed graph query engine

Growing community of inventors

Blansko, Czechia

Petr Koupy