Oracle International Corporation

Oracle America, Inc.

Vitaly Bychkov

Prabhu Thukkaram

Hoyong Park

Dmitrii Markovskii

Gyorgy Geiszter

Péter Gordos

Dmitrii Andreevich Strizhikozin

Sandeep Bishnoi

Iuliia Shmeleva

Alexandre De Castro Alves

Ilya Sergeyevich Shikalov

Natalia Nikiforova

Vladimir Yaroslavskiy

Michael C Frisino

Sergey V Lunegov

Elena Ivanova

Techniques for processing data streaming from one or more event sources in order to recreate a database table with database transactions for real-time analytics. An exemplary technique includes receiving a stream of events comprising change data for a table attribute, populating an in-memory table with the change data based on a token associated with an operation type and a mapping of a first attribute and a second attribute to a key attribute of the in-memory table, executing a continuous query on the change data for the key attribute of the in-memory table to generate events comprising data for a third attribute, and outputting the events having an output shape comprising the third attribute, where the events include the data for the third attribute.

Recreating an OLTP table and reapplying database transactions for real-time analytics

Systems and methods described herein are directed towards a flexible event ingestion framework. In some examples, an input source comprising information that identifies a plurality of events may be identified. Additionally, in some examples, an adapter for ingesting the information of the input source may be implemented. At least one additional component for modifying the adapter may be received. The adapter may be modified by implementing the at least one additional component with a transport component and a mapper component as part of ingesting the information. Further, a tuple for at least a first event may be generated based at least in part on the modified adapter, and the tuple may be provided to an event server.

Flexible event ingestion framework in an event processing system

A distributed event processing system is disclosed that receives continuous data streams, registers a continuous query against the data streams, and continuously executes the query as new data appears in the streams. In certain embodiments, the distributed event processing system deploys and executes applications (e.g., event processing applications) by distributing the execution of the application on a cluster of machines within the system. In certain embodiments, the system provides users with the ability to specify logical rules in an application. The system processes the logical rules by generating a DAG of transformations representing the logical rules and converts the DAG of transformations into a logical rules Resilient Distributed Dataset (RDD) DAG of transformations. The system processes events in an event batch against the RDD DAG of transformations to generate a set of output results for the user.

Integrating logic in micro batch based event processing systems

A distributed event processing system is disclosed that receives continuous data streams, registers a continuous query against the data streams, and continuously executes the query as new data appears in the streams. In certain embodiments, the distributed event processing system deploys and executes applications (e.g., event processing applications) by distributing the execution of the application on a cluster of machines within the system. In certain embodiments, the system receive updates to an application, processes the updated application against a continuous stream of data, and continuously generates updated results to a user. In certain embodiments, the system reduces delays associated with application deployment and execution when updates to an application are received. The system enables a user to view results pertaining to an updated application quickly without experiencing the typical deployment and execution delays that occur when updates to an application are made.

Framework for the deployment of event-based applications

Techniques for implementing logical queries in a distributed stream processing system using automatic branching and joins. An exemplary technique includes determining a query is a logical query. The logical query includes two or more summaries based on different groups configured to execute in a single query stage of a stream analytics application. The technique further includes converting the logical query into one or more physical queries. The one or more physical queries are separated into individual query stages, and each of the query stages includes a summary from the two or more summaries that is based on an associated group. The technique further includes generating a directed acyclic graph for the one or more physical queries. The directed acyclic graph includes a physical query transformation for each of the individual query stages.

Logical queries in a distributed stream processing system

Systems and methods described herein are directed towards a test data generator. In some examples, a reference polygon may be received from an application. Additionally a control parameter may be received from the application. Two points on a map may be selected and a path between the two points may be generated. Additional points may be created along the path and test may be generated by processing the additional points. The test data may be provided to the application.

Pattern-based automated test data generation

Some event ordering requirements can be determined based on continuous event processing queries. Other event ordering requirements can be determined based on distribution flow types being used to distribute events from event streams to node executing the queries. Events from event streams can be ordered according to ordering semantics that are based on a combination of all of these event ordering requirements. Additionally, virtual computing nodes can be associated with constraints, and computing processors can be associated with capabilities. Virtual computing nodes for processing event streams can be assigned to execute on various computing processors based on both these constraints and capabilities. Additionally, for each of several events in an event stream, a ratio between a total latency and a communication latency can be for determined. Based on an average of these ratios, a quantity of reducing nodes that will be involved in a map-reduce operation can be selected.

Visually exploring and analyzing event streams

Systems and methods ('utility') for sorting a plurality of complex objects are provided herein. The utility may include a sorting algorithm that sorts references to the complex objects, rather than the complex objects themselves, such that the need to copy and swap complex objects in their locations in memory is reduced. Further, the sorting algorithm may utilize a recursive divide and conquer process, using multiple pivot elements at each sorting level. For example, the sorting algorithm is based on a modified Quicksort algorithm that uses multiple pivot elements at each level to sort an array of references that point to complex objects.

Multi-interval quicksort algorithm for complex objects

A method for software development that includes receiving, by a computing resource broker, a request to perform a software development operation on a software program using a computing resource, wherein the request is from an integrated development environment (IDE) used to develop the software program, obtaining an authentication protocol for the computing resource from a repository managed by the computing resource broker, authenticating with the computing resource using the authentication protocol, wherein the computing resource broker is authenticated to use the computing resource, sending a request to perform the software development operation to the computing resource, receiving a result of performing the software development operation from the computing resource, and sending the result to the IDE, wherein the result is displayed to a developer of the software program.

Growing community of inventors

Foster City, CA, United States of America

Vitaly Bychkov