event

PACE Seminar

Presenter: Dr. Chi Xie

Date and Time: Friday October 4th 11:10 am – 12:10 pm

Location: CODA Room 114

Host: PACE

 

 

Title:  Pivotal Gemfire – A distributed, memory-based data management system

 

Abstract: 

Pivotal GemFire is a data management platform that provides real-time, consistent access to data-intensive applications throughout widely distributed cloud architectures. GemFire pools memory, CPU, network resources, and optionally local disk across multiple processes to manage application objects and behavior. It uses dynamic replication and data partitioning techniques to implement high availability, improved performance, scalability, and fault tolerance. In addition to being a distributed data container, GemFire is an in-memory data management system that provides reliable asynchronous event notifications and guaranteed message delivery.

 

  • Caches are an abstraction that describe a node in a GemFire distributed system. Application architects can arrange these nodes in peer-to-peer or client/server topologies. Within each cache, you define data regions. Data regions are analogous to tables in a relational database and manage data in a distributed fashion as name/value pairs. A replicated region stores identical copies of the data on each cache member of a distributed system. A partitioned region spreads the data among cache members. After the system is configured, client applications can access the distributed data in regions without knowledge of the underlying system architecture. You can define listeners to create notifications about when data has changed, and you can define expiration criteria to delete obsolete data from a region.
  • GemFire locators provide both member discovery and load-balancing services. You configure clients with a list of locator services and the locators maintain a dynamic list of member servers.
  • GemFire uses continuous querying to enable event-driven architectures. GemFire ties events and data together so that when an event is processed, the data required to process the event is available without additional queries to a disk-based database. Clients can subscribe to change notifications so that they can execute tasks when a specific piece of data changes.
  • In addition to peer-to-peer and client/server topologies, GemFire supports multi-site configurations that allow you to scale horizontally between disparate, loosely-coupled distributed systems over a wide geographically separated network. A wide-area network (WAN) is the main use case for the multi-site topology.

 

Biography:
Dr. Xie is a senior Member of Technical Staff Pivotal Software Inc. He recievd his PhD in Bioinformatics from the University of Georgia in 2012. He has 6 years of core Java and Java2EE experience with Eclipse IDE on web application development and on data processing algorithm development; 4 years of experience in development and testing of scientific analysis modules andJBPM/XML based workflow systems and web services on Windows and Linux/Unix; 3 years of Spring framework experience on bioinformatics projects and financial industrial projects, database systems, test experiences in supply chain industrial and financial industrial projects.
 

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Summary

Presenter: Dr. Chi Xie

Date and Time: Friday October 4th 11:10 am – 12:10 pm

Location: CODA Room 114

Host: PACE

 

 

Title:  Pivotal Gemfire – A distributed, memory-based data management system

 

Abstract: 

Pivotal GemFire is a data management platform that provides real-time, consistent access to data-intensive applications throughout widely distributed cloud architectures. GemFire pools memory, CPU, network resources, and optionally local disk across multiple processes to manage application objects and behavior. It uses dynamic replication and data partitioning techniques to implement high availability, improved performance, scalability, and fault tolerance. In addition to being a distributed data container, GemFire is an in-memory data management system that provides reliable asynchronous event notifications and guaranteed message delivery.

 

  • Caches are an abstraction that describe a node in a GemFire distributed system. Application architects can arrange these nodes in peer-to-peer or client/server topologies. Within each cache, you define data regions. Data regions are analogous to tables in a relational database and manage data in a distributed fashion as name/value pairs. A replicated region stores identical copies of the data on each cache member of a distributed system. A partitioned region spreads the data among cache members. After the system is configured, client applications can access the distributed data in regions without knowledge of the underlying system architecture. You can define listeners to create notifications about when data has changed, and you can define expiration criteria to delete obsolete data from a region.
  • GemFire locators provide both member discovery and load-balancing services. You configure clients with a list of locator services and the locators maintain a dynamic list of member servers.
  • GemFire uses continuous querying to enable event-driven architectures. GemFire ties events and data together so that when an event is processed, the data required to process the event is available without additional queries to a disk-based database. Clients can subscribe to change notifications so that they can execute tasks when a specific piece of data changes.
  • In addition to peer-to-peer and client/server topologies, GemFire supports multi-site configurations that allow you to scale horizontally between disparate, loosely-coupled distributed systems over a wide geographically separated network. A wide-area network (WAN) is the main use case for the multi-site topology.

 

Biography:
Dr. Xie is a senior Member of Technical Staff Pivotal Software Inc. He recievd his PhD in Bioinformatics from the University of Georgia in 2012. He has 6 years of core Java and Java2EE experience with Eclipse IDE on web application development and on data processing algorithm development; 4 years of experience in development and testing of scientific analysis modules andJBPM/XML based workflow systems and web services on Windows and Linux/Unix; 3 years of Spring framework experience on bioinformatics projects and financial industrial projects, database systems, test experiences in supply chain industrial and financial industrial projects.

Details

Friday
Oct 4 2019
12:10pm - 01:10pm

Contact: Organizer: PACE/ART/OIT Contact:  Nuyun Zhang, nuyun@gatech.edu

In campus calendar: Yes

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  • Workflow Status:Published
  • Created By:mweiner3
  • Created:10/02/2019
  • Modified By:mweiner3
  • Modified:10/02/2019

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