Storm is much more sophisticated then just filter-pipe pattern. It provides 1. Reliability: guarantees that every spout tuple will be fully processed. Actually it provides : at-most-once delivery(no ackers) , at-least-once delivery(ackers) and exactly-once (Trident) semantic for the message delivering/processing 2. Various types of tuples grouping 3. Scaling-out distributed system Vladi
On Sun, Nov 16, 2014 at 8:29 PM, Patrick Wiener <[email protected]> wrote: > So basically Storm’s core concept can be compared to > pipes-and-filters-pattern BUT provides a more „user-friendly“ framework > than e.g. a unix based pipes-and-filters processing. > > btw: I haven’t come across with TRIDENT yet. Just starting to dive deeper > into Storm as a potential technology for a real-time analytics architecture > (e.g. KAFKA+STORM+NODE+D3). > > Am 16.11.2014 um 17:06 schrieb Nathan Leung <[email protected]>: > > Storm supports fan outs, joins, various data groupings, and easier > scalability than the canonical Unix based pipes and filters processing. > On Nov 16, 2014 10:53 AM, "Andres Gomez Ferrer" <[email protected]> > wrote: > >> Firstly your thoughts are correct :), but do you know Trindet’s api? >> >> Trindet provides functions and filters equivalent to bolts >> >> ____________________________________________________________ >> Andrés Gómez >> *Developer* >> redborder.net / [email protected] >> mobile: +34 606224922 >> http://lnkd.in/sHnbJe >> >> <LogoEneo1-300x119.png> <LogoRedBorder.png> >> ____________________________________________________________ >> >> >> En 16 de noviembre de 2014 en 15:25:10, Patrick Wiener ( >> [email protected]) escrito: >> >> >> Hey everybody, >> >> I am working on a universities project towards a comparison towards >> pipes-and-filters-pattern and Storm. >> Since I am new to Storm and its topology and operating mode I hope you >> can help me evaluating my train of thoughts. >> >> *Bolts* can be considered as Filters, whereas the *Spout* equals >> the „Data Source“ (internal view) *pushing* tuples (data) to the >> downstream bolt. >> Finally the last bolt within the topology pushes tuples into a Data Sink, >> e.g. Redis. >> For the external view the Spout is also *pulling* (not shown in picture) >> from external sources such as Kafka. >> >> Overall, Spouts implement pull and push mechanism and Bolts only push >> mechanism >> >> I know this might seem trivial to you guys but i really hope for some >> constructive help. >> >> >> <34AC046A-F649-4A4E-9DA6-5FB7FE16868F> >> >> >
