Sampling in dynamic data streams and applications - Frahling, Indyk - 2005 () Citation Context ... consideration since many interesting graphs evolve with time, e.g., hyperlinks can be removed and tiresome friends can be de-friended. We note that dynamic geometric stream problems are well-...
In general, sampling types can be broken down into three main categories: falling stream, cross belt and auger. Falling Stream Sampling Systems are probably the largest category. They intercept sample material either from a free-falling stream of material or from a stream of material moving throug...
Stream sampling is the process of collecting a representative sample of the elements of a data stream. The sample is usually much smaller than the entire stream, but can be designed to retain many important characteristics of the stream, and can be used to estimate many important aggregates on...
M3 Aggregator is responsible for stream aggregation of indicators before they are stored in M3DB, and specifies the storage duration of indicators and the sampling interval of the calculation window according to the storagePolicy. M3 supports more flexible data intervals and more eigenvalues, including...
the importance of need for using biased sampling methods in these scenarios is fully dissertated.In addition to listing successful applications of sampling techniques in data mining,statistics estimating and stream mining up to now,we survey the application and development of sampling techniques,...
We consider SRS on continuously arriving data streams and statically stored data sets. We present a tight lower bound showing that any streaming algorithm for SRS over the entire stream must have, in the worst case, a variance that is \\(\\varOmega (r)\\) factor away from the optimal, ...
1. Create a Stream Table View First, you need to create a stream table viewair_stream, which reads data from the raw tableairand is used in the stream query. CREATE STREAM TABLE air_stream( time TIMESTAMP, station STRING, pressure DOUBLE, ...
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A sampling error can result even when no mistakes of any kind are made; sampling errors occur because no sample will ever perfectly match the data in the universe from which the sample is taken. Company XYZ will also want to avoidnon-sampling errors. Non-sampling errors are errors that resu...