American Express Travel Related Services Company, Inc.

Nitish Sharma

Arindam Chatterjee

Swatee Singh

Pratap Singh Rathore

Shourya Roy

Mohammad Torkzahrani

Brian C Rosenfield

Sastry Vsm Durvasula

Sandeep Bose

Balaji Balaraman

Shubham Arora

Manoj Kumar Rana

Rahul Ghosh

Krishnaprasad Narayanan

Pratap Singh Singh Rathore

Lakshman Chaitanya

Pratyush Kotturu

Priya Narayana

Disclosed are various embodiments for garbage collection for object-based storage systems. A first set of objects stored by an object storage service that have been accessed within a previously defined date range is identified. Then, a second set of objects stored by the object storage service is identified based at least in part on a relationship to one or more objects in the first set of objects. Next, a third set of objects stored by the object storage service that have been created prior to a predefined date is identified. Then, a subset of objects which are members of the third set of objects and not members of the first set of objects or the second set of objects is identified. Finally, a retention action is performed on individual members of the subset of objects based at least in part on a retention policy.

Garbage collection for object-based storage systems

A system for generating graphical relationship maps is disclosed. The system may receive a search request. The system may generate a relationship map data based on linked data elements of at least one of a structured data set, an unstructured data set, and a hybrid data set comprising structured and unstructured data. The system may display a graphical relationship map including an entity type icon based on the relationship map data and the search request.

Systems and methods for generating graphical relationship maps

At least some embodiments are directed to a system that receives from an online portal loaded in a computing device, a user request to instantiate a server cluster in a hybrid computer network. The system authenticates and redirects the user request to a selected computer network configured in the hybrid computer network. The system instantiates the server cluster in the selected computer network causing the server cluster to initiate a microservice agent during bootup. The system sends a command to the server cluster to initiate the execution of a process and receives from the microservice agent event data associated with the process. The system inputs the event data into a trained machine learning model to determine a first execution state of the process and sends a command to change the first execution state of the process to a second execution state.

Computer-based systems for management of big data development platforms based on machine learning techniques and methods of use thereof

A system for data migration is disclosed. The system may receive a migration request comprising a source file path and a target file location. The system may capture source file metadata based on the source file path and the migration request. The system may transfer a source file from a first data environment to an intermediate data environment via a first transfer process. The system may transfer the source file from the intermediate data environment to a second data environment via a second transfer process.

Seamless data movement and metadata management in a hybrid cloud setting using a configurable micro services based architecture

A system may receive a query configured to access a column in a data table. The data table may be in a flat file in a big data storage format. The system may detect the language type of the query and validate the query against the syntax of the language type. The system may also validate an access permission for data in the data table. The access permission may be stored in a permissions database. The system may generate a temporary table including the column with the temporary table configured to support the language type. The system may execute the query against the temporary table to generate a query result based on the temporary table as though it were the underlying data table. The system may enforce column-level or row-level access permissions by excluding columns or rows from the temporary table.

Converting a language type of a query

At least some embodiments are directed to a system that receives from an online portal loaded in a computing device, a user request to instantiate a server cluster in a hybrid computer network. The system authenticates and redirects the user request via a proxy service to a selected computer network configured in the hybrid computer network. The system instantiates the server cluster in the selected computer network causing the server cluster to initiate a microservice agent during bootup. The system sends a command to the server cluster to initiate the execution of a process and receives from the microservice agent event data associated with the process. The system inputs the event data into a trained machine learning model to determine a first execution state of the process and sends a command to change the first execution state of the process to a second execution state.

A system may read an input file having an input file size and including a first record and a second record. The first and second record may each have a record length. The system may parse the input file into a first split file and a second split file, with the first split file including the first record and the second split file including the second record. The system may distribute the first split file to a first node to generate a first output file and the second split file to a second node to generate a second output file. Any number of additional split files may be distributed to generate any number output files. The system may combine the output files to generate a converted data file.

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Scottsdale, AZ, United States of America

Nitish Sharma