Welcome!

@BigDataExpo Authors: Pat Romanski, Elizabeth White, Liz McMillan, Leon Adato, Kevin Benedict

Blog Feed Post

Big Data Needs a Better Network

Earlier this week I had some interesting conversations with @davehusak. Where the conversation started early in the day with a discussion on overlay networks and what network functions are performed where and in what context, later in the afternoon the discussion moved to networking solutions (and specifically Plexxi solutions) for big data applications.

It’s easy to jump to Hadoop or similarly structured cluster computing applications (Spark, Storm, or a long list of others) as the definition of a big data application. With all its simplicity for the overall distribution of work, Hadoop is a fairly tough network problem to solve if you want to do anything more than “throw bandwidth at the problem”. And when you do throw bandwidth at the problem, the extreme burstiness of the traffic will still significantly drag down the performance of the overall solution. And for many, CPU cycles to reduce the data is not the biggest challenge, storage and movement of data throughout a big data cluster is the biggest pain point. Intel has done a fine job providing compute firepower that far outpaces the evolution of network capacity.

The network plays a significant factor in several stages of a Hadoop solution cycle. It starts with chopping the to-be-analyzed data into chunks and distributing it across the datanodes. Hadoop has a notion of a rack and it has some basic intelligence when placing data and jobs that work on that data. By default the data will be replicated 3 times across at least 2 racks, if racks have been defined. The data to be distributed is easily in the 100s of Gigabytes or even Terabytes, so triple that data is being moved throughout the Hadoop cluster to the datanodes.

Once distributed, the actual Map jobs are launched against that data, these are the tasks that take the data and perform a first pass mapping into (in its most basic form) <key, value> tuples. Again here there is an attempt to have jobs work on local data, where local can be defined as local to the server that has that chunk of data or local to the rack, in an attempt to avoid as much cross rack communication as possible. This is based on the assumption that cross rack communication is much more constrained and aggregated and therefore more prone to congestion and packet loss.

Once the mapper jobs complete their task, the results of the mapping exercise is sent to reducers. Reducers take the <key, value> information and essentially tally the results. This transfer is the most taxing part of a Hadoop cycle on the network. Since most Hadoop mapping jobs run the same function on a similar sized dataset, that first set of mappers will all complete their task at about the same time and will all start sending their results to the same set of reducers, creating 1) a lot of traffic and 2) a lot of traffic to the same set of destinations.  Depending on the amount of data, mappers and compute nodes, this cycle repeats (the next set of mapping jobs are fired off) and at the end of each cycle a very significant spike in network traffic appears. At the very end, all results are brought together for one last spike in traffic. Each one of these network events is a source of significant congestion.

Many variables contribute to the overall performance of the Hadoop solution. What is the relationship between the chunks of data and the amount of servers and jobs? How many reducers are used? Where are the reducers in relation to the mappers? Is the Map function compute heavy or I/O heavy? How aggressive is the speculative scheduling that allows the same data to be worked on by multiple mappers?

With that many variables that can be tuned, and with so many variables different from one analysis to the next, it is hard to imagine that a single network design or implementation provides the best supporting infrastructure. There are assumptions in Hadoop placement of data and jobs that can easily be altered. The basic concept of a rack can easily expanded into a multi layer locality definition. With the right tools in the network, the definition of a rack, or even the locality and closeness of nodes in a cluster or virtual cluster can be adjusted according to the analysis to be completed.

We tend to give our applications variables to tune its performance based on what the network provides. It is time that the network adjusts itself based on the application needs. In a clustered application like Hadoop, there is lots of knowledge and even some predictability of network traffic. Wouldn’t that make for a great opportunity to infuse the network with some of that knowledge and have it morph itself to provide the best possible service? And Hadoop is not unique, cluster compute framework almost all carefully track placement of data and compute jobs, which makes them all great candidates to share some of that information with a smart network.

There are far simpler big data needs and applications that can and should be supported by flexible networks. Storage networks are still often separated from data networks for performance reasons and fear of interference. If you could actually separate the various types of data with logically or even physically different paths in the same network, would you still?

 

[Today's fun fact: An MLB baseball lasts on average 7 pitches. A google search asking how many baseballs are used in a single MLB season returns several pages worth of different answers. They must all be correct, it's on the Internet afterall.]

The post Big Data Needs a Better Network appeared first on Plexxi.

Read the original blog entry...

More Stories By Marten Terpstra

Marten Terpstra is a Product Management Director at Plexxi Inc. Marten has extensive knowledge of the architecture, design, deployment and management of enterprise and carrier networks.

@BigDataExpo Stories
With Cloud Foundry you can easily deploy and use apps utilizing websocket technology, but not everybody realizes that scaling them out is not that trivial. In his session at 21st Cloud Expo, Roman Swoszowski, CTO and VP, Cloud Foundry Services, at Grape Up, will show you an example of how to deal with this issue. He will demonstrate a cloud-native Spring Boot app running in Cloud Foundry and communicating with clients over websocket protocol that can be easily scaled horizontally and coordinate...
Any startup has to have a clear go –to-market strategy from the beginning. Similarly, any data science project has to have a go to production strategy from its first days, so it could go beyond proof-of-concept. Machine learning and artificial intelligence in production would result in hundreds of training pipelines and machine learning models that are continuously revised by teams of data scientists and seamlessly connected with web applications for tenants and users.
IT organizations are moving to the cloud in hopes to approve efficiency, increase agility and save money. Migrating workloads might seem like a simple task, but what many businesses don’t realize is that application migration criteria differs across organizations, making it difficult for architects to arrive at an accurate TCO number. In his session at 21st Cloud Expo, Joe Kinsella, CTO of CloudHealth Technologies, will offer a systematic approach to understanding the TCO of a cloud application...
SYS-CON Events announced today that Secure Channels, a cybersecurity firm, will exhibit at SYS-CON's 21st International Cloud Expo®, which will take place on Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. Secure Channels, Inc. offers several products and solutions to its many clients, helping them protect critical data from being compromised and access to computer networks from the unauthorized. The company develops comprehensive data encryption security strategie...
"With Digital Experience Monitoring what used to be a simple visit to a web page has exploded into app on phones, data from social media feeds, competitive benchmarking - these are all components that are only available because of some type of digital asset," explained Leo Vasiliou, Director of Web Performance Engineering at Catchpoint Systems, in this SYS-CON.tv interview at DevOps Summit at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
Connecting to major cloud service providers is becoming central to doing business. But your cloud provider’s performance is only as good as your connectivity solution. Massive Networks will place you in the driver's seat by exposing how you can extend your LAN from any location to include any cloud platform through an advanced high-performance connection that is secure and dedicated to your business-critical data. In his session at 21st Cloud Expo, Paul Mako, CEO & CIO of Massive Networks, wil...
Deep learning has been very successful in social sciences and specially areas where there is a lot of data. Trading is another field that can be viewed as social science with a lot of data. With the advent of Deep Learning and Big Data technologies for efficient computation, we are finally able to use the same methods in investment management as we would in face recognition or in making chat-bots. In his session at 20th Cloud Expo, Gaurav Chakravorty, co-founder and Head of Strategy Development ...
When shopping for a new data processing platform for IoT solutions, many development teams want to be able to test-drive options before making a choice. Yet when evaluating an IoT solution, it’s simply not feasible to do so at scale with physical devices. Building a sensor simulator is the next best choice; however, generating a realistic simulation at very high TPS with ease of configurability is a formidable challenge. When dealing with multiple application or transport protocols, you would be...
As businesses adopt functionalities in cloud computing, it’s imperative that IT operations consistently ensure cloud systems work correctly – all of the time, and to their best capabilities. In his session at @BigDataExpo, Bernd Harzog, CEO and founder of OpsDataStore, presented an industry answer to the common question, “Are you running IT operations as efficiently and as cost effectively as you need to?” He then expounded on the industry issues he frequently came up against as an analyst, and ...
SYS-CON Events announced today that App2Cloud will exhibit at SYS-CON's 21st International Cloud Expo®, which will take place on Oct. 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. App2Cloud is an online Platform, specializing in migrating legacy applications to any Cloud Providers (AWS, Azure, Google Cloud).
Cloud resources, although available in abundance, are inherently volatile. For transactional computing, like ERP and most enterprise software, this is a challenge as transactional integrity and data fidelity is paramount – making it a challenge to create cloud native applications while relying on RDBMS. In his session at 21st Cloud Expo, Claus Jepsen, Chief Architect and Head of Innovation Labs at Unit4, will explore that in order to create distributed and scalable solutions ensuring high availa...
IoT is at the core or many Digital Transformation initiatives with the goal of re-inventing a company's business model. We all agree that collecting relevant IoT data will result in massive amounts of data needing to be stored. However, with the rapid development of IoT devices and ongoing business model transformation, we are not able to predict the volume and growth of IoT data. And with the lack of IoT history, traditional methods of IT and infrastructure planning based on the past do not app...
Internet-of-Things discussions can end up either going down the consumer gadget rabbit hole or focused on the sort of data logging that industrial manufacturers have been doing forever. However, in fact, companies today are already using IoT data both to optimize their operational technology and to improve the experience of customer interactions in novel ways. In his session at @ThingsExpo, Gordon Haff, Red Hat Technology Evangelist, shared examples from a wide range of industries – including en...
To get the most out of their data, successful companies are not focusing on queries and data lakes, they are actively integrating analytics into their operations with a data-first application development approach. Real-time adjustments to improve revenues, reduce costs, or mitigate risk rely on applications that minimize latency on a variety of data sources. Jack Norris reviews best practices to show how companies develop, deploy, and dynamically update these applications and how this data-first...
Intelligent Automation is now one of the key business imperatives for CIOs and CISOs impacting all areas of business today. In his session at 21st Cloud Expo, Brian Boeggeman, VP Alliances & Partnerships at Ayehu, will talk about how business value is created and delivered through intelligent automation to today’s enterprises. The open ecosystem platform approach toward Intelligent Automation that Ayehu delivers to the market is core to enabling the creation of the self-driving enterprise.
SYS-CON Events announced today that Grape Up will exhibit at SYS-CON's 21st International Cloud Expo®, which will take place on Oct. 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. Grape Up is a software company specializing in cloud native application development and professional services related to Cloud Foundry PaaS. With five expert teams that operate in various sectors of the market across the U.S. and Europe, Grape Up works with a variety of customers from emergi...
Detecting internal user threats in the Big Data eco-system is challenging and cumbersome. Many organizations monitor internal usage of the Big Data eco-system using a set of alerts. This is not a scalable process given the increase in the number of alerts with the accelerating growth in data volume and user base. Organizations are increasingly leveraging machine learning to monitor only those data elements that are sensitive and critical, autonomously establish monitoring policies, and to detect...
You know you need the cloud, but you’re hesitant to simply dump everything at Amazon since you know that not all workloads are suitable for cloud. You know that you want the kind of ease of use and scalability that you get with public cloud, but your applications are architected in a way that makes the public cloud a non-starter. You’re looking at private cloud solutions based on hyperconverged infrastructure, but you’re concerned with the limits inherent in those technologies.
SYS-CON Events announced today that Massive Networks will exhibit at SYS-CON's 21st International Cloud Expo®, which will take place on Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. Massive Networks mission is simple. To help your business operate seamlessly with fast, reliable, and secure internet and network solutions. Improve your customer's experience with outstanding connections to your cloud.
Because IoT devices are deployed in mission-critical environments more than ever before, it’s increasingly imperative they be truly smart. IoT sensors simply stockpiling data isn’t useful. IoT must be artificially and naturally intelligent in order to provide more value In his session at @ThingsExpo, John Crupi, Vice President and Engineering System Architect at Greenwave Systems, will discuss how IoT artificial intelligence (AI) can be carried out via edge analytics and machine learning techn...