Managing multiple data streams in R

02/18/2020
by   Mark P. J. van der Loo, et al.
0

It is often useful to tap secondary information from a running R script. Obvious use cases include logging, and profiling of time or memory consuption. Perhaps less obvious cases include tracking changes in R objects or collecting output of unit tests (assertions). In this paper we demonstrate an approach that abstracts collection and processing of such secondary information from the code in the running script. The approach is implemented in pure R, and allows users to control the secondary information stream stream without global side effects and without altering existing code. Although some elements of the approach discussed here have been applied in existing packages, the combination of elements proposed here appears thus far to have been overlooked.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
02/18/2020

A method for deriving information from running R code

It is often useful to tap information from a running R script. Obvious u...
research
11/17/2016

Stream Packing for Asynchronous Multi-Context Systems using ASP

When a processing unit relies on data from external streams, we may face...
research
11/24/2022

Highest-performance Stream Processing

We present the stream processing library that achieves the highest perfo...
research
03/28/2022

Efficient Algorithm for Deterministic Search of Hot Elements

When facing a very large stream of data, it is often desirable to extrac...
research
04/21/2023

Integrating Per-Stream Stat Tracking into Accel-Sim

Accel-Sim is a widely used computer architecture simulator that models t...
research
01/29/2020

The Rockerverse: Packages and Applications for Containerization with R

The Rocker Project provides widely-used Docker images for R across diffe...

Please sign up or login with your details

Forgot password? Click here to reset