jm + dc   2

_Airport Noise NIMBYism: An Empirical Investigation_
'Generally, a very small number of people account for a disproportionately high share of the total number
of noise complaints. In 2015, for example, 6,852 of the 8,760 complaints submitted to Ronald Reagan
Washington National Airport originated from one residence in the affluent Foxhall neighborhood of
northwest Washington, DC. The residents of that particular house called Reagan National to express irritation about aircraft noise an average of almost 19 times per day during 2015.'

Somebody needs help.
airports  noise  nimby  nimbyism  complaints  dc 
october 2016 by jm
_Dynamic Histograms: Capturing Evolving Data Sets_ [pdf]

Currently, histograms are static structures: they are created from scratch periodically and their creation is based on looking at the entire data distribution as it exists each time. This creates problems, however, as data stored in DBMSs usually varies with time. If new data arrives at a high rate and old data is likewise deleted, a histogram’s accuracy may deteriorate fast as the histogram becomes older, and the optimizer’s effectiveness may be lost. Hence, how often a histogram is reconstructed becomes very critical, but choosing the right period is a hard problem, as the following trade-off exists: If the period is too long, histograms may become outdated. If the period is too short, updates of the histogram may incur a high overhead.

In this paper, we propose what we believe is the most elegant solution to the problem, i.e., maintaining dynamic histograms within given limits of memory space. Dynamic histograms are continuously updateable, closely tracking changes to the actual data. We consider two of the best static histograms proposed in the literature [9], namely V-Optimal and Compressed, and modify them. The new histograms are naturally called Dynamic V-Optimal (DVO) and Dynamic Compressed (DC). In addition, we modified V-Optimal’s partition constraint to create the Static Average-Deviation Optimal (SADO) and Dynamic Average-Deviation Optimal (DADO) histograms.

(via d2fn)
via:d2fn  histograms  streaming  big-data  data  dvo  dc  sado  dado  dynamic-histograms  papers  toread 
may 2013 by jm

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