Sign In

Communications of the ACM

Research highlights

Technical Perspective: Naiad


The Naiads in Greek mythology are the nymphs of fresh water. They are unpredictable and a bit scary, like big data, whose size has been exploding and continues to double every two years. Novel systems that process this data tsunami have been the focus of much research and development over the last decade. Many such big data processing systems are programmed through a workflow, where smaller programs with local state (nodes) are composed into bigger workflows through well-defined interfaces (edges). The resulting dataflows are then scaled to huge inputs through data parallelism (the execution of one node in the dataflow is scaled out across many servers), task parallelism (independent nodes in the dataflow are executed at the same time), and pipelining (a node later in the dataflow can already start its work based on partial output from its predecessors).

The most well-known class of such dataflow systems is based on the map-reduce pattern, enabling large-scale batch processing. These systems can process terabytes of data for preprocessing and cleaning, data transformation, model training and evaluation, and report generation, achieving high throughput while making the computation fault tolerant across hundreds of machines.


 

No entries found

Log in to Read the Full Article

Sign In

Sign in using your ACM Web Account username and password to access premium content if you are an ACM member, Communications subscriber or Digital Library subscriber.

Need Access?

Please select one of the options below for access to premium content and features.

Create a Web Account

If you are already an ACM member, Communications subscriber, or Digital Library subscriber, please set up a web account to access premium content on this site.

Join the ACM

Become a member to take full advantage of ACM's outstanding computing information resources, networking opportunities, and other benefits.
  

Subscribe to Communications of the ACM Magazine

Get full access to 50+ years of CACM content and receive the print version of the magazine monthly.

Purchase the Article

Non-members can purchase this article or a copy of the magazine in which it appears.
Sign In for Full Access
» Forgot Password? » Create an ACM Web Account
ACM Resources
Read CACM in a free mobile app!
Access the latest issue, plus archived issues and more
ACM Logo
  • ACM CACM apps available for iPad, iPhone and iPod Touch, and Android platforms
  • ACM Digital Library apps available for iOS, Android, and Windows devices
  • Download an app and sign in to it with your ACM Web Account
Find the app for your mobile device
ACM DL Logo