Patents by Inventor Jaiprakash Ganpatrao Chimanchode

Jaiprakash Ganpatrao Chimanchode 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).

  • Control versioning of temporal tables to reduce data redundancy
    Patent number: 11874811
    Abstract: Control versioning of records in a temporal table is provided to reduce data redundancy. New Data Definition Language (DDL) syntax is provided to make individual columns within a table sensitive or insensitive to whether new row versions are generated when Database Manipulation Language (DML) statements operate on the table. The database parser and back-end data processors are configured to create the table with the user-defined versioning attributes and to manage versioning of the rows without requiring additional programming.
    Type: Grant
    Filed: December 28, 2018
    Date of Patent: January 16, 2024
    Assignee: Teradata US, Inc.
    Inventors: Stephen Molini, Bhashyam Ramesh, Jaiprakash Ganpatrao Chimanchode, Sai Pavan Kumar Pakala, Pratik Patodi, Dhrubajyoti Roy, Todd Walter
  • Control Versioning of Temporal Tables to Reduce Data Redundancy
    Publication number: 20200210395
    Abstract: Control versioning of records in a temporal table is provided to reduce data redundancy. New Data Definition Language (DDL) syntax is provided to make individual columns within a table sensitive or insensitive to whether new row versions are generated when Database Manipulation Language (DML) statements operate on the table. The database parser and back-end data processors are configured to create the table with the user-defined versioning attributes and to manage versioning of the rows without requiring additional programming.
    Type: Application
    Filed: December 28, 2018
    Publication date: July 2, 2020
    Inventors: Stephen Molini, Bhashyam Ramesh, Jaiprakash Ganpatrao Chimanchode, Sai Pavan Kumar Pakala, Pratik Patodi, Dhrubajyoti Roy, Todd Walter
  • PREDICTIVE QUERY PARSING TIME AND OPTIMIZATION
    Publication number: 20200183936
    Abstract: A query is preprocessed for features identified by a Data Manipulation Language (DML) in the text of the query. A machine-learning algorithm uses the features as input and provides as output a predicted query parsing execution time needed by a query parser to parse the query. The predicted query parsing time is provided as input to a query optimizer. The query optimizer uses the predicted query parsing time as a factor in optimizing a query execution plan for the query. Subsequently, the query execution plan is executed against a database as the query.
    Type: Application
    Filed: December 10, 2018
    Publication date: June 11, 2020
    Inventors: Bhashyam Ramesh, Jaiprakash Ganpatrao Chimanchode, Naveen Thaliyil Sankaran, Jitendra Yasaswi Bharadwaj Katta