REAL TIME COMPUTING IN A HIGH PERFORMANCE CLUSTER.

2005 ◽  
Vol 38 (2) ◽  
pp. 32-39
Author(s):  
M. Palomera-Pérez ◽  
L. Almeida ◽  
H. Benítez-Pérez
2017 ◽  
Author(s):  
Christian Patauner ◽  
Roberto Biasi ◽  
Mario Andrighettoni ◽  
Gerald Angerer ◽  
Dietrich Pescoller ◽  
...  

Author(s):  
M. Palomera-Pérez ◽  
L. Almeida ◽  
H. Benítez-Pérez

2018 ◽  
Vol 173 ◽  
pp. 01019 ◽  
Author(s):  
Zonghuai Guo ◽  
Shiwang Ding

With the rapid development of the Internet, such as storm, s4, sparkstreaming and other large data real-time computing framework, is widely used in real-time monitoring, real-time recommendation, real-time transaction analysis and other systems for real-time consumption of data streams, Kafka messaging system has been widely deployed. Aiming at the problem that the Kafka cluster needs a lot of network overhead, disk overhead and memory consumption to ensure the reliability of the message, the clustering load is increased, and a replica adaptive synchronization strategy based on the message heat and replica update frequency is proposed. It is proved that the Kafka cluster can guarantee the reliability of the message, and it can significantly reduce the overhead of the resource and improve the throughput of the cluster by using the method of dynamically adjusting the replica synchronization to reduce the system resource consumption while ensuring the reliability of the message. to ensure the system availability and high performance.


Author(s):  
Jiyang Yu ◽  
Dan Huang ◽  
Siyang Zhao ◽  
Nan Pei ◽  
Huixia Cheng ◽  
...  

Author(s):  
Muhammad Faris Roslan ◽  
◽  
Afandi Ahmad ◽  
Abbes Amira ◽  
◽  
...  

Author(s):  
A. V. Bratulin ◽  
◽  
M. B. Nikiforov ◽  
A. I. Efimov ◽  
◽  
...  

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