Streaming applications process possibly infinite streams of data and often have both high throughput and low latency requirements. They are comprised of operator graphs that produce and consume data tuples. General streaming applications use stateful, selective, and user-defined operators. The stream programming model naturally exposes task and pipeline parallelism, enabling it to exploit parallel systems of all kinds, including large clusters. However, data parallelism must either be manually introduced by programmers, or extracted as an optimization by compilers. Previous data parallel optimizations did not apply to selective, stateful and user-defined operators. This article presents a compiler and runtime system that automatically extra...
We describe an approach to elastically scale the per-formance of a data analytics operator that is p...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
Various research communities have independently arrived at stream processing as a programming model ...
Streaming applications transform possibly infinite streams of data and often have both high throughp...
Stream processing applications use online analytics to ingest high-rate data sources, process them o...
This article addresses the profitability problem associated with auto-parallelization of general-pur...
The sheer scale of today\u27s data processing needs has led to a new paradigm of software systems ce...
There is an ever increasing rate of digital information available in the form of online data streams...
As multicore architectures enter the mainstream, there is a pressing demand for high-level programmi...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
Cataloged from PDF version of article.In this paper we study partitioning functions for stream proc...
Stream processing has a long history as a way of describing and implementing specific kinds of compu...
This tutorial starts with a survey of optimizations for streaming applications. The survey is organi...
The sheer scale of today\u27s data processing needs has led to a new paradigm of software systems ce...
Streaming APIs are becoming more pervasive in mainstream Object-Oriented programming languages. For ...
We describe an approach to elastically scale the per-formance of a data analytics operator that is p...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
Various research communities have independently arrived at stream processing as a programming model ...
Streaming applications transform possibly infinite streams of data and often have both high throughp...
Stream processing applications use online analytics to ingest high-rate data sources, process them o...
This article addresses the profitability problem associated with auto-parallelization of general-pur...
The sheer scale of today\u27s data processing needs has led to a new paradigm of software systems ce...
There is an ever increasing rate of digital information available in the form of online data streams...
As multicore architectures enter the mainstream, there is a pressing demand for high-level programmi...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
Cataloged from PDF version of article.In this paper we study partitioning functions for stream proc...
Stream processing has a long history as a way of describing and implementing specific kinds of compu...
This tutorial starts with a survey of optimizations for streaming applications. The survey is organi...
The sheer scale of today\u27s data processing needs has led to a new paradigm of software systems ce...
Streaming APIs are becoming more pervasive in mainstream Object-Oriented programming languages. For ...
We describe an approach to elastically scale the per-formance of a data analytics operator that is p...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
Various research communities have independently arrived at stream processing as a programming model ...