Algorithms For Dummies

 Struggling with Big Data

You discover how data streams is like consuming tap water: Opening the tap lets 

you store the water in cups or drinking bottles, or you can use it for cooking, 

scrubbing food, cleaning plates, or washing hands. In any case, most or all of the 

water is gone, yet it proves very useful and indeed vital.

Analyzing streams with the right recipe

Streaming  data  needs  streaming  algorithms,  and  the  key  thing  to  know  about 

streaming algorithms is that, apart a few measures that it can compute exactly, 

a streaming algorithm necessarily provides approximate results. The algorithm 

output is almost correct, guessing not the precisely right answer, but close to it.

When dealing with streams, you clearly have to concentrate only on the measures 

of interest and leave out many details. You could be interested in a statistical mea-

surement, such as mean, minimum, or maximum. Moreover, you could want to 

count elements in the stream or distinguish old information from new. There are 

many algorithms to use, depending on the problem, yet the recipes always use the 

same ingredients. The trick of cooking the perfect stream is to use one or all of 

these algorithmic tools as ingredients: