Patents by Inventor Amit Ganesh
Amit Ganesh has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20210286611Abstract: Techniques for artificial intelligence driven configuration management are described herein. In some embodiments, a machine-learning process determines a feature set for a plurality of deployments of a software resource. Based on varying values in the feature set, the process clusters each of the plurality of deployments into a cluster of a plurality of clusters. Each cluster of the plurality of clusters comprises one or more nodes and each node of the one or more nodes corresponds to at least a subset of values of the feature set that are detected in at least one deployment of the plurality of deployments of the software resource. The process determines a representative node for each cluster of the plurality of clusters. An operation may be performed based on the representative node for at least one cluster.Type: ApplicationFiled: May 27, 2021Publication date: September 16, 2021Applicant: Oracle International CorporationInventors: Dustin Garvey, Amit Ganesh, Uri Shaft, Prasad Ravuri, Long Yang, Sampanna Shahaji Salunke, Sumathi Gopalakrishnan, Timothy Mark Frazier, Shriram Krishnan
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Patent number: 11113250Abstract: Techniques for activity tracking, data classification, and in-database archiving are described. Activity tracking refers to techniques that collect statistics related to user access patterns, such as the frequency or recency with which users access particular database elements. The statistics gathered through activity tracking can be supplied to data classification techniques to automatically classify the database elements or to assist users with manually classifying the database elements. Then, once the database elements have been classified, in-database archiving techniques can be employed to move database elements to different storage tiers based on the classifications. However, although the techniques related to activity tracking, data classification, and in-database archiving may be used together as described above; each technique may also be practiced separately.Type: GrantFiled: August 19, 2019Date of Patent: September 7, 2021Assignee: Oracle International CorporationInventors: Liang Guo, Vivekanandhan Raja, Amit Ganesh, Joshua Gould
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Patent number: 11023221Abstract: Techniques for artificial intelligence driven configuration management are described herein. In some embodiments, a machine-learning process determines a feature set for a plurality of deployments of a software resource. Based on varying values in the feature set, the process clusters each of the plurality of deployments into a cluster of a plurality of clusters. Each cluster of the plurality of clusters comprises one or more nodes and each node of the one or more nodes corresponds to at least a subset of values of the feature set that are detected in at least one deployment of the plurality of deployments of the software resource. The process determines a representative node for each cluster of the plurality of clusters. An operation may be performed based on the representative node for at least one cluster.Type: GrantFiled: April 21, 2020Date of Patent: June 1, 2021Assignee: Oracle International CorporationInventors: Dustin Garvey, Amit Ganesh, Uri Shaft, Prasad Ravuri, Long Yang, Sampanna Shahaji Salunke, Sumathi Gopalakrishnan, Timothy Mark Frazier, Shriram Krishnan
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Publication number: 20210149847Abstract: A method, apparatus, and system for policy driven data placement and information lifecycle management in a database management system are provided. A user or database application can specify declarative policies that define the movement and transformation of stored database objects. The policies are associated with a database object and may also be inherited. A policy defines, for a database object, an archiving action to be taken, a scope, and a condition before the archiving action is triggered. Archiving actions may include compression, data movement, table clustering, and other actions to place the database object into an appropriate storage tier for a lifecycle phase of the database object. Conditions based on access statistics can be specified at the row level and may use segment or block level heatmaps. Policy evaluation occurs periodically in the background, with actions queued as tasks for a task scheduler.Type: ApplicationFiled: January 26, 2021Publication date: May 20, 2021Inventors: Vineet Marwah, Hariharan Lakshmanan, Ajit Mylavarapu, Prashant Gaharwar, Amit Ganesh
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Patent number: 10949403Abstract: A method, apparatus, and system for policy driven data placement and information lifecycle management in a database management system are provided. A user or database application can specify declarative policies that define the movement and transformation of stored database objects. The policies are associated with a database object and may also be inherited. A policy defines, for a database object, an archiving action to be taken, a scope, and a condition before the archiving action is triggered. Archiving actions may include compression, data movement, table clustering, and other actions to place the database object into an appropriate storage tier for a lifecycle phase of the database object. Conditions based on access statistics can be specified at the row level and may use segment or block level heatmaps. Policy evaluation occurs periodically in the background, with actions queued as tasks for a task scheduler.Type: GrantFiled: March 14, 2013Date of Patent: March 16, 2021Assignee: ORACLE INTERNATIONAL CORPORATIONInventors: Vineet Marwah, Hariharan Lakshmanan, Ajit Mylavarapu, Prashant Gaharwar, Amit Ganesh
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Publication number: 20210073680Abstract: Techniques are described for applying what-f analytics to simulate performance of computing resources in cloud and other computing environments. In one or more embodiments, a plurality of time-series datasets are received including time-series datasets representing a plurality of demands on a resource and datasets representing performance metrics for a resource. Based on the datasets at least one demand propagation model and at least one resource prediction model are trained. Responsive to receiving an adjustment to a first set of one or more values associated with a first demand: (a) a second adjustment is generated for a second set of one or more values associated with a second demand; and (b) a third adjustment is generated for a third set of one or more values that is associated with the resource performance metric.Type: ApplicationFiled: September 22, 2020Publication date: March 11, 2021Applicant: Oracle International CorporationInventors: Dustin Garvey, Sampanna Shahaji Salunke, Uri Shaft, Amit Ganesh, Sumathi Gopalakrishnan
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Patent number: 10915830Abstract: Techniques are described for generating predictive alerts. In one or more embodiments, a seasonal model is generated, the seasonal model representing one or more seasonal patterns within a first set of time-series data, the first set of time-series data comprising data points from a first range of time. A trend-based model is also generated to represent trending patterns within a second set of time-series data comprising data points from a second range of time that is different than the first range of time. A set of forecasted values is generated based on the seasonal model and the trend-based model. Responsive to determining that a set of alerting thresholds has been satisfied based on the set of forecasted values, an alert is generated.Type: GrantFiled: July 6, 2017Date of Patent: February 9, 2021Assignee: Oracle International CorporationInventors: Dustin Garvey, Sampanna Shahaji Salunke, Uri Shaft, Amit Ganesh, Sumathi Gopalakrishnan
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Patent number: 10855548Abstract: Techniques are disclosed for summarizing, diagnosing, and correcting the cause of anomalous behavior in computing systems. In some embodiments, a system identifies a plurality of time series that track different metrics over time for a set of one or more computing resources. The system detects a first set of anomalies in a first time series that tracks a first metric and assigns a different respective range of time to each anomaly. The system determines whether the respective range of time assigned to an anomaly overlaps with timestamps or ranges of time associated with anomalies from one or more other time series. The system generates at least one cluster that groups metrics based on how many anomalies have respective ranges of time and/or timestamps that overlap. The system may preform, based on the cluster, one or more automated actions for diagnosing or correcting a cause of anomalous behavior.Type: GrantFiled: February 15, 2019Date of Patent: December 1, 2020Assignee: Oracle International CorporationInventors: Dustin Garvey, Neil Goodman, Sampanna Shahaji Salunke, Brent Arthur Enck, Sumathi Gopalakrishnan, Amit Ganesh, Timothy Mark Frazier
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Patent number: 10838933Abstract: A method, apparatus, and system for periodic performance optimization through heatmap based management of an in-memory area are provided. A heatmap is maintained to track database accesses, and a sliding most recent time window of the heatmap is externalized to a desired granularity level to provide access statistics regarding candidate elements to be possibly placed in the in-memory area. Initially and on a periodic basis, an appropriate knapsack algorithm is chosen based on an analysis on the computational costs versus the benefits of applying various knapsack algorithms for the candidate elements. Using the chosen algorithm in conjunction with a selected performance model, an optimized configuration of the in-memory area is determined. The optimized configuration indicates a set of elements chosen from the candidate elements, optionally specified with compression levels.Type: GrantFiled: October 23, 2015Date of Patent: November 17, 2020Assignee: Oracle International CorporationInventors: Vineet Marwah, Amit Ganesh, Hariharan Lakshmanan, Prashant Gaharwar, Dhruvil Shah
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Patent number: 10817803Abstract: Techniques are described for applying what-f analytics to simulate performance of computing resources in cloud and other computing environments. In one or more embodiments, a plurality of time-series datasets are received including time-series datasets representing a plurality of demands on a resource and datasets representing performance metrics for a resource. Based on the datasets at least one demand propagation model and at least one resource prediction model are trained. Responsive to receiving an adjustment to a first set of one or more values associated with a first demand: (a) a second adjustment is generated for a second set of one or more values associated with a second demand; and (b) a third adjustment is generated for a third set of one or more values that is associated with the resource performance metric.Type: GrantFiled: June 2, 2017Date of Patent: October 27, 2020Assignee: Oracle International CorporationInventors: Dustin Garvey, Sampanna Shahaji Salunke, Uri Shaft, Amit Ganesh, Sumathi Gopalakrishnan
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Patent number: 10789065Abstract: Techniques for analyzing, understanding, and remediating differences in configurations among many software resources are described herein. Machine learning processes are applied to determine a small feature set of parameters from among the complete set of parameters configured for each software resource. The feature set of parameters is selected to optimally cluster configuration instances for each of the software resources. Once clustered based on the values of the feature set of parameters, a graph is generated for each cluster of configuration instances that depicts the differences among the configuration instances within the cluster. An interactive visualization tool renders the graph in a user interface, and a management tool allows changes to the graph and changes to the configuration of one or more software resources.Type: GrantFiled: May 7, 2018Date of Patent: September 29, 2020Assignee: Oracle lnternational CorporationInventors: Dustin Garvey, Amit Ganesh, Timothy Mark Frazier, Shriram Krishnan, Sr., Uri Shaft, Prasad Ravuri, Sampanna Shahaji Salunke, Sumathi Gopalakrishnan
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Publication number: 20200267057Abstract: Techniques are disclosed for summarizing, diagnosing, and correcting the cause of anomalous behavior in computing systems. In some embodiments, a system identifies a plurality of time series that track different metrics over time for a set of one or more computing resources. The system detects a first set of anomalies in a first time series that tracks a first metric and assigns a different respective range of time to each anomaly. The system determines whether the respective range of time assigned to an anomaly overlaps with timestamps or ranges of time associated with anomalies from one or more other time series. The system generates at least one cluster that groups metrics based on how many anomalies have respective ranges of time and/or timestamps that overlap. The system may preform, based on the cluster, one or more automated actions for diagnosing or correcting a cause of anomalous behavior.Type: ApplicationFiled: February 15, 2019Publication date: August 20, 2020Applicant: Oracle International CorporationInventors: Dustin Garvey, Neil Goodman, Sampanna Shahaji Salunke, Brent Arthur Enck, Sumathi Gopalakrishnan, Amit Ganesh, Timothy Mark Frazier
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Publication number: 20200257663Abstract: A method, apparatus, and system for tracking row and object database activity into block level heatmaps is provided. Database activity including reads, writes, and creates can be tracked by a database management system at the finest possible level of granularity, or the row and object level. To efficiently record the tracked database activity, a two-part structure is described for writing the activity into heatmaps. A hierarchical in-memory component may use a dynamically allocated sparse pool of bitmap blocks. Periodically, the in-memory component is persisted to a stored representation component, sharable with multiple database instances, which may include consolidated last access times and/or a history of heatmap snapshots to reflect access over time. The heatmaps may then be externalized to database users and applications to provide and support a variety of features.Type: ApplicationFiled: April 28, 2020Publication date: August 13, 2020Inventors: Vineet Marwah, Sujatha Muthulingam, Amit Ganesh
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Publication number: 20200249931Abstract: Techniques for artificial intelligence driven configuration management are described herein. In some embodiments, a machine-learning process determines a feature set for a plurality of deployments of a software resource. Based on varying values in the feature set, the process clusters each of the plurality of deployments into a cluster of a plurality of clusters. Each cluster of the plurality of clusters comprises one or more nodes and each node of the one or more nodes corresponds to at least a subset of values of the feature set that are detected in at least one deployment of the plurality of deployments of the software resource. The process determines a representative node for each cluster of the plurality of clusters. An operation may be performed based on the representative node for at least one cluster.Type: ApplicationFiled: April 21, 2020Publication date: August 6, 2020Applicant: Oracle International CorporationInventors: Dustin Garvey, Amit Ganesh, Uri Shaft, Prasad Ravuri, Long Yang, Sampanna Shahaji Salunke, Sumathi Gopalakrishnan, Timothy Mark Frazier, Shriram Krishnan
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Patent number: 10678760Abstract: A method, apparatus, and system for tracking row and object database activity into block level heatmaps is provided. Database activity including reads, writes, and creates can be tracked by a database management system at the finest possible level of granularity, or the row and object level. To efficiently record the tracked database activity, a two-part structure is described for writing the activity into heatmaps. A hierarchical in-memory component may use a dynamically allocated sparse pool of bitmap blocks. Periodically, the in-memory component is persisted to a stored representation component, sharable with multiple database instances, which may include consolidated last access times and/or a history of heatmap snapshots to reflect access over time. The heatmaps may then be externalized to database users and applications to provide and support a variety of features.Type: GrantFiled: March 14, 2013Date of Patent: June 9, 2020Assignee: Oracle International CorporationInventors: Vineet Marwah, Sujatha Muthulingam, Amit Ganesh
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Patent number: 10678788Abstract: Techniques are provided for storing in in-memory unit (IMU) in a lower-storage tier and copying the IMU to DRAM when needed for query processing. Techniques are also provided for copying IMUs to lower tiers of storage when evicted from the cache of higher tiers of storage. Techniques are provided for implementing functionality of IMUs within a storage system, to enable database servers to push tasks, such as filtering, to the storage system where the storage system may access IMUs within its own memory to perform the tasks. Metadata associated with a set of data may be used to indicate whether an IMU for the data should be created by the database server machine or within the storage system.Type: GrantFiled: October 21, 2016Date of Patent: June 9, 2020Assignee: Oracle International CorporationInventors: Roger D. Macnicol, Viral Shah, Xia Hua, Jesse Kamp, Shasank K. Chavan, Maria Colgan, Tirthankar Lahiri, Adrian Tsz Him Ng, Krishnan Meiyyappan, Amit Ganesh, Juan R. Loaiza, Kothanda Umamageswaran, Yiran Qin
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Patent number: 10664264Abstract: Techniques for artificial intelligence driven configuration management are described herein. In some embodiments, a machine-learning process determines a feature set for a plurality of deployments of a software resource. Based on varying values in the feature set, the process clusters each of the plurality of deployments into a cluster of a plurality of clusters. Each cluster of the plurality of clusters comprises one or more nodes and each node of the one or more nodes corresponds to at least a subset of values of the feature set that are detected in at least one deployment of the plurality of deployments of the software resource. The process determines a representative node for each cluster of the plurality of clusters. An operation may be performed based on the representative node for at least one cluster.Type: GrantFiled: July 23, 2018Date of Patent: May 26, 2020Assignee: Oracle International CorporationInventors: Dustin Garvey, Amit Ganesh, Uri Shaft, Prasad Ravuri, Long Yang, Sampanna Shahaji Salunke, Sumathi Gopalakrishnan, Timothy Mark Frazier, Shriram Krishnan
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Patent number: 10592230Abstract: Techniques are described herein for scalable clustering of target resources by parameter set. In some embodiments, a plurality of parameter sets of varying length are received, where a parameter set identifies attributes of a target resource. A plurality of signature vectors are generated based on the plurality of parameter sets such that the signature vectors have equal lengths. A signature vector may map to one or more parameter sets of the plurality of parameter sets. A plurality of clusters are generated based on the similarity between signature vectors. Operations may be performed on a target resource based on one or more nodes in the plurality of clusters.Type: GrantFiled: August 7, 2019Date of Patent: March 17, 2020Assignee: Oracle International CorporationInventors: Dustin Garvey, Timothy Mark Frazier, Shriram Krishnan, Uri Shaft, Amit Ganesh, Prasad Ravuri, Sampanna Shahaji Salunke, Sumathi Gopalakrishnan
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Publication number: 20190370229Abstract: Techniques for activity tracking, data classification, and in-database archiving are described. Activity tracking refers to techniques that collect statistics related to user access patterns, such as the frequency or recency with which users access particular database elements. The statistics gathered through activity tracking can be supplied to data classification techniques to automatically classify the database elements or to assist users with manually classifying the database elements. Then, once the database elements have been classified, in-database archiving techniques can be employed to move database elements to different storage tiers based on the classifications. However, although the techniques related to activity tracking, data classification, and in-database archiving may be used together as described above; each technique may also be practiced separately.Type: ApplicationFiled: August 19, 2019Publication date: December 5, 2019Inventors: Liang GUO, Vivekanandhan RAJA, Amit GANESH, Joshua GOULD
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Patent number: 10496396Abstract: Techniques are described herein for scalable clustering of target resources by parameter set. In some embodiments, a plurality of parameter sets of varying length are received, where a parameter set identifies attributes of a target resource. A plurality of signature vectors are generated based on the plurality of parameter sets such that the signature vectors have equal lengths. A signature vector may map to one or more parameter sets of the plurality of parameter sets. A plurality of clusters are generated based on the similarity between signature vectors. Operations may be performed on a target resource based on one or more nodes in the plurality of clusters.Type: GrantFiled: July 20, 2018Date of Patent: December 3, 2019Assignee: Oracle International CorporationInventors: Dustin Garvey, Timothy Mark Frazier, Shriram Krishnan, Uri Shaft, Amit Ganesh, Prasad Ravuri, Sampanna Shahaji Salunke, Sumathi Gopalakrishnan