Click here to close now.

Welcome!

Java Authors: Liz McMillan, Yeshim Deniz, Elizabeth White, Carmen Gonzalez, Navrup Johal

Related Topics: Java, Microservices Journal, Virtualization

Java: Article

Dataflow Programming: A Scalable Data-Centric Approach to Parallelism

Dataflow allows developers to easily take advantage of today’s multicore processors

There are two major drivers behind the need to embrace parallelism: the dramatic shift to commodity multicore CPUs, and the striking increase in the amount of data being processed by the applications that run our enterprises. These two factors must be addressed by any approach to parallelism or we will find ourselves falling short of resolving the crisis that is upon us. While there are data-centric approaches that have generated interest, including Map-Reduce, dataflow programming is arguably the easiest parallel strategy to adopt for the millions of developers trained in serial programming.

The blog gives a nice summary of why parallel processing is important.

Hardware Support for Parallelism
Let's start with an overview of the supported parallelism available today in modern processors. First there is processor-level parallelism involving instruction pipelining and other techniques handled by the processor. These are all optimized by compilers and runtime environments such as the Java Virtual Machine. This goodness is available to all developers without much effort on our part.

Recently commodity multicore processors have brought parallelism into the mainstream. As we move into many-core systems, we now have available essentially a "cluster in a box." But, software has lagged behind hardware in the area of parallelism. As a result, many of today's multicore systems are woefully under-utilized. We need a paradigm shift to a new programming model that embraces this high level of parallelism from the start, making it easy for developers to create highly scalable applications. However, focusing only on cores doesn't take into account the whole system. Data-intensive applications by definition have significant amounts of I/O operations. A parallel programming model must take into account parallelizing I/O operations with compute. Otherwise we'll be unable to build applications that can keep the multicore monster fed and happy.

Virtualization is a popular way to divvy up multicore machines. This is essentially treating a single machine as multiple, separate machines. Each virtual slice has its function to provide and each operates somewhat independently. This works well for splitting up IT types of functions such as email servers, and web servers. But it doesn't help with the problem of crunching big data. For big data types of problems, taking advantage of the whole machine, the "cluster in a box," is imperative.

Scale-out, using multiple machines to execute big data jobs, is another way to implement parallelism. This technique has been around for ages and is seeing new instantiations in systems such as Hadoop, built on the Map-Reduce design pattern. Scaling out to large cluster systems certainly has its advantages and is absolutely required for the Internet-scale data problem. It does however introduce inefficiencies that can be critical barriers to full utilization in smaller cluster configurations (less than 100-node size clusters).

The Next Step for Hadoop
In a talk on Hadoop, Jeff Hammerbacher stated, "More programmer-friendly parallel dataflow languages await discovery, I think. MapReduce is one (small) step in that direction." His talk is summarized in this blog. As Jeff points out, Map-Reduce is a great first step, but is lacking as a programming model. Integrating dataflow with the scale-out capabilities available in frameworks such as Hadoop offers the next big step in handling big data.

Dataflow Programming
Dataflow architecture is based on the concept of using a dataflow graph for program execution. A dataflow graph consists of nodes that are computational elements. The edges in a dataflow graph provide data paths between nodes. A dataflow graph is directed and acyclic (DAG). Figure 1 provides a snapshot of an executing dataflow application. Note how all of the nodes are executing in parallel, flowing data in a pipeline fashion.

Figure 1

Nodes in the graph do work by reading data from their input flow(s), transforming the data and pushing the results to their outputs. Nodes that provide connectivity may have only input or output flows. A graph is constructed by creating nodes and linking their data flows together. Once a graph is constructed and executed, the connectivity nodes begin reading data and pushing it downstream. Downstream consumers read the data, process it and send their results downstream. This results in pipeline parallelism, allowing each node in the graph to run in parallel as the pipeline begins to fill.

Dataflow provides a computational model. A dataflow graph must first be constructed before it can be executed. This leads to a very nice modularity: creating building blocks (nodes) that can be plugged together in an endless number of ways to create complex applications. This model is analogous to the UNIX shell model. With the UNIX shell, you can string together multiple commands that are pipelined for execution. Each command reads its input, does something with the data and writes to its output. The commands operate independently in the sense that they don't care what is upstream or downstream from them. It is up to the pipeline composer (the end user) to create the pipeline correctly to process the data as wanted. Dataflow is very similar to this model, but provides more capabilities.

The dataflow architecture provides flow control. Flow control prevents fast producers from overrunning slower consumers. Flow control is inherent in the way dataflow works and puts no burden on the programmer to deal with issues such as deadlock or race conditions.

Dataflow is focused on data parallelism. As such, it is not a great fit for all computational problems. But as has become evident over the past few years, there are many domains of parallel problems and one solution or architecture will not solve all problems for all domains. Dataflow provides a different programming paradigm for most developers, so it requires a bit of a shift in thinking to a more data-centric way of designing solutions. But once that shift takes place, dataflow programming is a natural way to express data-centric solutions.

Dataflow Programming and Actors
Dataflow programming and the Actor model available in languages such as Scala and Erlang share many similarities. The Actor model provides for independent actors to communicate using message passing. Within an actor, pattern matching is used to allow an actor determine how to handle a message. Messages are generally asynchronous, but synchronous behavior with flow control can be built on top of the Actor model with some effort.

 

In general, the Actor model is best used for task parallelism. For example, Erlang was originally developed within the telecom industry for building non-stop control systems. Dataflow is data centric and therefore well suited for big data processing tasks.

Dataflow Goodness
As just mentioned, dataflow programming is a different paradigm and so it does require somewhat of a shift in design thinking. This is not a critical issue as the concepts around dataflow are easy to grasp, which is a very important point. A parallel framework that provides great multicore utilization but takes months if not years to master is not all that helpful. Dataflow programming makes the simple things easy and the hard tasks possible.

Dataflow applications are simple to express. Dataflow uses a composition programming model based on a building blocks approach. This leads to very modular designs that provide a high amount of reuse.

Dataflow does a good job of abstracting the details of parallel development. This is important as all of the lower level tools for parallel application development are available today in frameworks such as the java.util.concurrent library available in the JDK. However, these libraries are low-level and require a high degree of expertise to use them correctly. They rely on shared state that must be protected using synchronization techniques that can lead to race conditions, deadlocks and extremely hard-to-debug problems.

Being based on a shared-nothing, immutable message passing architecture makes dataflow a simplified programming model. The nodes within a dataflow graph don't have to worry about using synchronization techniques to produce shared memory. They are lock-free so deadlock and race conditions are not a worry either. The dataflow architecture inherently handles these conditions, allowing the developer to focus on their job at hand. Since the data streams are immutable, this allows multiple readers to attach to the output node. This feature provides more flexibility and reuse in the programming model.

The immutability of the data flows also limits the side effects of nodes within a dataflow program. Nodes within a dataflow graph can only communicate over dataflow channels. By following this model, you are assured that no global state or state of other nodes can be affected by a node. Again, this helps to simplify the programming model. Developing new nodes is free of most of the worries normally involved with parallel programming.

The dataflow programming model is functional in style. Each node within a graph provides a very specific, continuous function on its input data. Programs are built by stitching these functions together in various ways to create complex applications.

Dataflow-based architecture elegantly takes advantage of multicore processors on a single machine (scale up). It's also a good architecture for scaling out to multiple machines. Nodes that run across machine boundaries can communicate over data channels using network sockets. This provides the same simple, flexible dataflow programming model in a distributed configuration.

Dataflow and Big Data
The inherent pipeline parallelism built into dataflow programming makes dataflow great for datasets ranging from thousands to billions of records. Applications written using dataflow techniques can scale easily to extremely large data sizes, generally without much strain on the memory system as a dataflow application will eventually enter into a steady state of memory consumption. The overall amount of data pumped through the application doesn't affect that steady state memory size.

Not all dataflow operators are friendly when it comes to memory consumption. Many are designed specifically to load data into memory. For example a hash join operator may load one of its data sources into an in-memory index. This is the nature of the operator and must be taken into account when using it.

Being pipelined in nature also allows for great overlap of I/O and computational tasks. As mentioned earlier, this is an important "whole" application approach that is highly critical to success in building big data applications.

Dataflow systems are easily embeddable in the current commonly used systems. For instance, a dataflow-based application can easily be executed within the context of a Map-Reduce application. Experimentation with a dataflow-based platform named Pervasive DataRush has shown that the Hadoop system can be used to scale out an application using DataRush within each map step to help parallelize the mapper to take advantage of multicore efficiencies. Allowing each mapper to handle larger chunks of data allows the overall Map-Reduce application to run faster since each mapper is itself parallelized.

Summary
Dataflow is a software architecture that is based on the idea of continuous functions executing in parallel on data streams. It's focused on data-intensive applications, lending itself to today's big data challenges. Dataflow is easy to grasp and simple to express, and this design-time scalability can be as important as its run-time scalability.

Dataflow allows developers to easily take advantage of today's multicore processors and also fits well into a distributed environment. Tackling big data problems with dataflow is straightforward and ensures your applications will be able to scale in the future to meet the growing demands of your organization.

More Stories By Jim Falgout

Jim Falgout has 20+ years of large-scale software development experience and is active in the Java development community. As Chief Technologist for Pervasive DataRush, he’s responsible for setting innovative design principles that guide the company’s engineering teams as they develop new releases and products for partners and customers. He applied dataflow principles to help architect Pervasive DataRush.

Prior to Pervasive, Jim held senior positions with NexQL, Voyence Net Perceptions/KD1 Convex Computer, Sequel Systems and E-Systems. Jim has a B.Sc. (Cum Laude) in Computer Science from Nicholls State University. He can be reached at [email protected]

Comments (0)

Share your thoughts on this story.

Add your comment
You must be signed in to add a comment. Sign-in | Register

In accordance with our Comment Policy, we encourage comments that are on topic, relevant and to-the-point. We will remove comments that include profanity, personal attacks, racial slurs, threats of violence, or other inappropriate material that violates our Terms and Conditions, and will block users who make repeated violations. We ask all readers to expect diversity of opinion and to treat one another with dignity and respect.


@ThingsExpo Stories
“In the past year we've seen a lot of stabilization of WebRTC. You can now use it in production with a far greater degree of certainty. A lot of the real developments in the past year have been in things like the data channel, which will enable a whole new type of application," explained Peter Dunkley, Technical Director at Acision, in this SYS-CON.tv interview at @ThingsExpo, held Nov 4–6, 2014, at the Santa Clara Convention Center in Santa Clara, CA.
WebRTC is an up-and-coming standard that enables real-time voice and video to be directly embedded into browsers making the browser a primary user interface for communications and collaboration. WebRTC runs in a number of browsers today and is currently supported in over a billion installed browsers globally, across a range of platform OS and devices. Today, organizations that choose to deploy WebRTC applications and use a host machine that supports audio through USB or Bluetooth can use Plantronics products to connect and transit or receive the audio associated with the WebRTC session.
The best mobile applications are augmented by dedicated servers, the Internet and Cloud services. Mobile developers should focus on one thing: writing the next socially disruptive viral app. Thanks to the cloud, they can focus on the overall solution, not the underlying plumbing. From iOS to Android and Windows, developers can leverage cloud services to create a common cross-platform backend to persist user settings, app data, broadcast notifications, run jobs, etc. This session provides a high level technical overview of many cloud services available to mobile app developers, includi...
SYS-CON Media announced today that @WebRTCSummit Blog, the largest WebRTC resource in the world, has been launched. @WebRTCSummit Blog offers top articles, news stories, and blog posts from the world's well-known experts and guarantees better exposure for its authors than any other publication. @WebRTCSummit Blog can be bookmarked ▸ Here @WebRTCSummit conference site can be bookmarked ▸ Here
There are lots of challenges in IoT around secure, scalable and business friendly infrastructure for enterprises. For large corporations, IoT implementations are one of the top priorities of the decade. All industries are seeing a competitive need to sustain by investing in IoT initiatives. The value addition comes from improved customer service, innovative product and additional revenue streams. The data from these IP-connected devices can be leveraged for a variety of business applications as well as responsive action controls. The various architectural building blocks of an IoT ...
SYS-CON Events announced today that Ciqada will exhibit at SYS-CON's @ThingsExpo, which will take place on June 9-11, 2015, at the Javits Center in New York City, NY. Ciqada™ makes it easy to connect your products to the Internet. By integrating key components - hardware, servers, dashboards, and mobile apps - into an easy-to-use, configurable system, your products can quickly and securely join the internet of things. With remote monitoring, control, and alert messaging capability, you will meet your customers' needs of tomorrow - today! Ciqada. Let your products take flight. For more inform...
Health care systems across the globe are under enormous strain, as facilities reach capacity and costs continue to rise. M2M and the Internet of Things have the potential to transform the industry through connected health solutions that can make care more efficient while reducing costs. In fact, Vodafone's annual M2M Barometer Report forecasts M2M applications rising to 57 percent in health care and life sciences by 2016. Lively is one of Vodafone's health care partners, whose solutions enable older adults to live independent lives while staying connected to loved ones. M2M will continue to gr...
Chuck Piluso will present a study of cloud adoption trends and the power and flexibility of IBM Power and Pureflex cloud solutions. Speaker Bio: Prior to Data Storage Corporation (DSC), Mr. Piluso founded North American Telecommunication Corporation, a facilities-based Competitive Local Exchange Carrier licensed by the Public Service Commission in 10 states, serving as the company's chairman and president from 1997 to 2000. Between 1990 and 1997, Mr. Piluso served as chairman & founder of International Telecommunications Corporation, a facilities-based international carrier licensed by t...
Dave will share his insights on how Internet of Things for Enterprises are transforming and making more productive and efficient operations and maintenance (O&M) procedures in the cleantech industry and beyond. Speaker Bio: Dave Landa is chief operating officer of Cybozu Corp (kintone US). Based in the San Francisco Bay Area, Dave has been on the forefront of the Cloud revolution driving strategic business development on the executive teams of multiple leading Software as a Services (SaaS) application providers dating back to 2004. Cybozu's kintone.com is a leading global BYOA (Build Your O...
As enterprises move to all-IP networks and cloud-based applications, communications service providers (CSPs) – facing increased competition from over-the-top providers delivering content via the Internet and independently of CSPs – must be able to offer seamless cloud-based communication and collaboration solutions that can scale for small, midsize, and large enterprises, as well as public sector organizations, in order to keep and grow market share. The latest version of Oracle Communications Unified Communications Suite gives CSPs the capability to do just that. In addition, its integration ...
The IoT Bootcamp is coming to Cloud Expo | @ThingsExpo on June 9-10 at the Javits Center in New York. Instructor. Registration is now available at http://iotbootcamp.sys-con.com/ Instructor Janakiram MSV previously taught the famously successful Multi-Cloud Bootcamp at Cloud Expo | @ThingsExpo in November in Santa Clara. Now he is expanding the focus to Janakiram is the founder and CTO of Get Cloud Ready Consulting, a niche Cloud Migration and Cloud Operations firm that recently got acquired by Aditi Technologies. He is a Microsoft Regional Director for Hyderabad, India, and one of the f...
The 17th International Cloud Expo has announced that its Call for Papers is open. 17th International Cloud Expo, to be held November 3-5, 2015, at the Santa Clara Convention Center in Santa Clara, CA, brings together Cloud Computing, APM, APIs, Microservices, Security, Big Data, Internet of Things, DevOps and WebRTC to one location. With cloud computing driving a higher percentage of enterprise IT budgets every year, it becomes increasingly important to plant your flag in this fast-expanding business opportunity. Submit your speaking proposal today!
While not quite mainstream yet, WebRTC is starting to gain ground with Carriers, Enterprises and Independent Software Vendors (ISV’s) alike. WebRTC makes it easy for developers to add audio and video communications into their applications by using Web browsers as their platform. But like any market, every customer engagement has unique requirements, as well as constraints. And of course, one size does not fit all. In her session at WebRTC Summit, Dr. Natasha Tamaskar, Vice President, Head of Cloud and Mobile Strategy at GENBAND, will explore what is needed to take a real time communications ...
Containers and microservices have become topics of intense interest throughout the cloud developer and enterprise IT communities. Accordingly, attendees at the upcoming 16th Cloud Expo at the Javits Center in New York June 9-11 will find fresh new content in a new track called PaaS | Containers & Microservices Containers are not being considered for the first time by the cloud community, but a current era of re-consideration has pushed them to the top of the cloud agenda. With the launch of Docker's initial release in March of 2013, interest was revved up several notches. Then late last...
Wearable technology was dominant at this year’s International Consumer Electronics Show (CES) , and MWC was no exception to this trend. New versions of favorites, such as the Samsung Gear (three new products were released: the Gear 2, the Gear 2 Neo and the Gear Fit), shared the limelight with new wearables like Pebble Time Steel (the new premium version of the company’s previously released smartwatch) and the LG Watch Urbane. The most dramatic difference at MWC was an emphasis on presenting wearables as fashion accessories and moving away from the original clunky technology associated with t...
SYS-CON Events announced today that Litmus Automation will exhibit at SYS-CON's 16th International Cloud Expo®, which will take place on June 9-11, 2015, at the Javits Center in New York City, NY. Litmus Automation’s vision is to provide a solution for companies that are in a rush to embrace the disruptive Internet of Things technology and leverage it for real business challenges. Litmus Automation simplifies the complexity of connected devices applications with Loop, a secure and scalable cloud platform.
In 2015, 4.9 billion connected "things" will be in use. By 2020, Gartner forecasts this amount to be 25 billion, a 410 percent increase in just five years. How will businesses handle this rapid growth of data? Hadoop will continue to improve its technology to meet business demands, by enabling businesses to access/analyze data in real time, when and where they need it. Cloudera's Chief Technologist, Eli Collins, will discuss how Big Data is keeping up with today's data demands and how in the future, data and analytics will be pervasive, embedded into every workflow, application and infra...
From telemedicine to smart cars, digital homes and industrial monitoring, the explosive growth of IoT has created exciting new business opportunities for real time calls and messaging. In his session at @ThingsExpo, Ivelin Ivanov, CEO and Co-Founder of Telestax, shared some of the new revenue sources that IoT created for Restcomm – the open source telephony platform from Telestax. Ivelin Ivanov is a technology entrepreneur who founded Mobicents, an Open Source VoIP Platform, to help create, deploy, and manage applications integrating voice, video and data. He is the co-founder of TeleStax, a...
As Marc Andreessen says software is eating the world. Everything is rapidly moving toward being software-defined – from our phones and cars through our washing machines to the datacenter. However, there are larger challenges when implementing software defined on a larger scale - when building software defined infrastructure. In his session at 16th Cloud Expo, Boyan Ivanov, CEO of StorPool, will provide some practical insights on what, how and why when implementing "software-defined" in the datacenter.
How is unified communications transforming the way businesses operate? In his session at WebRTC Summit, Arvind Rangarajan, Director of Product Marketing at BroadSoft, will discuss how to extend unified communications experience outside the enterprise through WebRTC. He will also review use cases across different industry verticals. Arvind Rangarajan is Director, Product Marketing at BroadSoft. He has over 19 years of experience in the telecommunications industry in various roles such as Software Development, Product Management and Product Marketing, applied across Wireless, Unified Communic...