Lightweight Monitoring of Distributed Streams

2018 ◽  
Vol 43 (2) ◽  
pp. 1-37 ◽  
Author(s):  
Arnon Lazerson ◽  
Daniel Keren ◽  
Assaf Schuster
Keyword(s):  
2012 ◽  
Vol 59 (2) ◽  
pp. 1-25 ◽  
Author(s):  
Graham Cormode ◽  
S. Muthukrishnan ◽  
Ke Yi ◽  
Qin Zhang

2017 ◽  
Vol 7 (1.1) ◽  
pp. 237
Author(s):  
MD. A R Quadri ◽  
B. Sruthi ◽  
A. D. SriRam ◽  
B. Lavanya

Java is one of the finest language for big data because of its write once and run anywhere nature. The new release of java 8 introduced few strategies like lambda expressions and streams which are helpful for parallel computing. Though these new strategies helps in extracting, sorting and filtering data from collections and arrays, still there are problems with it. Streams cannot properly process with the large data sets like big data. Also, there are few problems associated while executing in distributed environment. The new streams introduced in java are restricted to computations inside the single system there is no method for distributed computing over multiple systems. And streams store data in their memory and therefore cannot support huge data sets. Now, this paper cope with java 8 behalf of massive data and deed in distributed environment by providing extensions to the Programming model with distributed streams. The distributed computing of large data programming models may be consummated by introducing distributed stream frameworks.


2015 ◽  
Vol 8 (5) ◽  
pp. 545-556 ◽  
Author(s):  
Arnon Lazerson ◽  
Izchak Sharfman ◽  
Daniel Keren ◽  
Assaf Schuster ◽  
Minos Garofalakis ◽  
...  
Keyword(s):  

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