Vmware, Inc.

Oracle International Corporation

Mirza Mohsin Beg

Sundeep Tiyyagura

A Christer Sabelstrom

Charles P Sum

Sai Samrat Karlapudi

Jae Young Yoon

Ramsés V Morales

Konstantinos Morfonios

Shashank Pedamallu

James W Cooley

Sufian A Dar

Tyler J Curtis

Venkat Gujjula

Shefali Dubey

Anshu Bansal

Michael Patrick Colena

Mihai Budiu

Serdar Kadioglu

Samir Sebbah

Leonid Ryzhyk

Manish Roy

Pooja Khandelwal

The present disclosure relates generally to techniques for processing asynchronous queries across multiple data cores including secondary data cores stored in the secondary storage system in a distributed computing system. Data from secondary data cores are recovered to new data cores generated in the data plane in order to be accessible for searching. Using this technique, asynchronous queries are run in parallel allowing the client to dynamically manage the queries and receive notifications when results are available.

Asynchronous queries on secondary data cores in a distributed computing system

A computer implemented processing service for efficient streaming of data input from one or more sources to one or more receivers is disclosed. The processing service includes a schema manager that receives commands from a tenant of the data stream processing service. The processing service includes a processing services gateway that validates the data and sends the data to a transformation processor. The transformation processor receives the data and parses the data into the one or more data formats in accordance with the instructions and sends the data in the one or more data formats to an egress service. The egress service outputs the data in the one or more data formats to the one or more receivers, each receiver receiving the data in a data pipeline in one of the one or more formats.

Processes and systems for dataflow routing based on data types and transformations

Techniques for ingesting data streams to a distributed-computing system using a multi-directional data ingestion pipeline are provided. In one embodiment, a method for ingesting data streams includes, at a client gateway, receiving a plurality of messages; assigning the plurality of messages to one or more data streams; obtaining stream routing configurations; and identifying one or more receivers. The method further includes determining whether at least one of the one or more data streams is to be delivered to one or more receivers operating in the first computing environment; and if so, delivering the at least one of the one or more data streams to the one or more receivers operating in the first computing environment. The method further includes delivering the one or more data streams to a data ingress gateway operating in a second computing environment.

Secure multi-directional data pipeline for data distribution systems

The present disclosure relates generally to techniques for processing asynchronous queries across multiple data cores including secondary data cores stored in the secondary storage system in a distributed computing system. Secondary data cores are recovered in the data plane from secondary storage in order to be accessible for searching. Using this technique, asynchronous queries are run in parallel allowing the client to dynamically manage the queries and receive notifications when results are available.

Techniques for data ingestion by a distributed-computing system are provided. In one embodiment, data received from one or more data sources is processed at a management node of the distributed-computing system. The data is generated by one or more components of an information processing system external to the distributed-computing system. The data is stored at the management plane. The management plane selects, from a plurality of data cores, a data core to ingest the data. The plurality of data cores are stored across one or more data plane containers of a data plane of the distributed-computing system. The management plane processes the data to generate one or more event records corresponding to the data. The one or more event records are sent to the selected data core, which causes the data plane to store the one or more event records in the selected data core.

Data ingestion by distributed-computing systems

Disclosed is a system, method, and computer program product for analyzing sets of data in an efficient manner, such that analytics can be effectively performed over that data. Classification operations can be performed to generate groups of similar log records. This permits classification of the log records in a cohesive and informative manner.

Method and system for implementing efficient classification and exploration of data

In a computer-implemented method for performing alert notification on streaming textual data, streaming textual data is received. A plurality of copies of the streaming textual data is generated, wherein a first copy of the streaming textual data is transmitted to an ingestion service for persistent storage at a data plane and a second copy of the streaming textual data is transmitted to an alert evaluation service for performing alert evaluation on the streaming textual data, such that the ingestion service and the alert evaluation service are performed independently. The streaming textual data is evaluated by the alert evaluation service to detect an alert. Responsive to detecting an alert at the alert evaluation service, a notification of the alert is generated.

Alert notification on streaming textual data

Techniques for splitting a time-range query into sub-queries for serial execution are provided. In one embodiment, a user query is received requesting items within a time range from a database. The time range is divided into a plurality of time periods within the time range. Sub-queries defining respective time periods of the plurality of time periods are generated from the user query, and a first sub-query is executed. The first sub-query defines a first time period of the plurality of time periods, where the first time period is a most-recent time period or a least-recent time period among the plurality of time periods. If it is determined that a number of items obtained from executing the first sub-query is greater than or equal to a predetermined result target, then the items obtained from executing the first sub-query are provided and subsequent sub-queries are not executed.

Splitting a time-range query into multiple sub-queries for serial execution

Techniques for splitting a query into native query operations and post-processing operations are provided. In one embodiment, a user query including a plurality of search parameters is received. Expressions representing the plurality of search parameters in the user query are determined. A first subset and a second subset of the expressions are identified. Each expression of the first subset corresponds to one of a plurality of native query operations executable by a database platform, and each expression of the second subset corresponds to one of a plurality of predefined post-processing operations not executable by the database platform. A database query is generated based on one or more expressions of the first subset, and a post-processing query is generated based on each expression in the second subset. The database query is executed by the database platform, then the post-processing query is executed on the results from database platform.

Splitting a query into native query operations and post-processing operations

Techniques for splitting a time-range query into sub-queries for parallel execution are provided. In one embodiment, a user query requesting items from a database is received. A total number of items in the database that correspond to a time range of the user query is determined. Based on the total number of items, target values are determined. Each target value represents a target number of items in the database to be assigned to a respective sub-query. Based on the target values, a plurality of time periods within the time range are determined. Each time period corresponds to a respective set of items in the database platform, and a total number of items in the respective set of items corresponds to a respective target value. Sub-queries defining respective time periods of the plurality of time periods are then generated from the user query and executed in parallel.

Growing community of inventors

Foster City, CA, United States of America

Mirza Mohsin Beg