Stream Processing Languages in the Big Data Era

被引：17
|
作者：
Hirzel, Martin [1 ]
Baudart, Guillaume [1 ]
Bonifati, Angela [2 ]
Della Valle, Emanuele [3 ]
Sakr, Sherif [4 ]
Vlachou, Akrivi [5 ]
机构：
[1] IBM Res, Armonk, NY 10504 USA
[2] Lyon 1 Univ, Lyon, France
[3] Politecn Milan, Milan, Italy
[4] Univ Tartu, Tartu, Estonia
[5] Univ Piraeus, Piraeus, Greece
来源：
SIGMOD RECORD | 2018年 / 47卷 / 02期
基金：
欧盟地平线“2020”;
关键词：
QUERY LANGUAGE; SEMANTICS; SYSTEM; MODEL;
D O I：
10.1145/3299887.3299892
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper is a survey of recent stream processing languages, which are programming languages for writing applications that analyze data streams. Data streams, or continuous data flows, have been around for decades. But with the advent of the big-data era, the size of data streams has increased dramatically. Analyzing big data streams yields immense advantages across all sectors of our society. To analyze streams, one needs to write a stream processing application. This paper showcases several languages designed for this purpose, articulates underlying principles, and outlines open challenges.
引用
收藏
页码：29 / 40
页数：12
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