|By Roger Gaskell||
|September 7, 2011 09:30 AM EDT||
Is MapReduce the Holy Grail answer to the pressing problem of processing, analyzing and making sense of large and growing data volumes? Certainly it has potential in this arena, but there is a distressing gap between the amount of hype this technology - and its spinoffs - has received and the number of professionals who actually know how to integrate and make best use of it.
Industry watchers say it's just a matter of time before MapReduce sweeps through the enterprise data warehouse (EDW) market the same way open source technologies like Linux have done. In fact, in a recent blog post, Forrester's James Kobielus proclaimed that most EDW vendors will incorporate support for MapReduce's open source cousin Hadoop into the heart of their architectures to enable open, standards-based data analytics on massive amounts of data.
So, no more databases, just MapReduce? I'm not so sure. But don't misunderstand. It's not that MapReduce isn't an effective way to analyze data in some cases. The big names in Internet business are all using it - Facebook, Google, Amazon, eBay et al - so it must be good, right? But it's worth taking a more measured view based both on the technical and the practical business merits. I believe that the two technologies are not so mutually exclusive; that they will work hand-in-hand and, in some cases, MapReduce will be integrated into the relational database (RDBMS).
Google certainly has proven that MapReduce excels at making sense out of the exabytes of unstructured data on the web, which it should, given that MapReduce was designed from the outset for manipulating very large data sets. MapReduce in this sense provides a way to put structure around unstructured data. We humans prefer structure; it's in our DNA. Without structure, we have no real way of adding value to the data. Unstructured data analytics is something of an oxymoron for a pattern-seeking hominid.
MapReduce helps us put structure around the unstructured so we can then make sense of it. It creates an environment wherein a data analyst can write two simple functions, a "mapper" and a "reducer," to perform the actual data manipulation, returning a result that is at once both an analysis of the data it has just mapped and summarized, as well as the structure for further analysis that will help provide insight into the data. Whether that further analysis is done in a MapReduce environment might be the more appropriate question.
From an infrastructure standpoint, MapReduce excels where performance and scalability are challenges. Applications written using the MapReduce framework are automatically parallelized, making it well suited to a large infrastructure of connected machines. As it scales applications across lots of servers made up of lots of nodes, the MapReduce framework also provides built-in query fault tolerance so that whatever hardware component might fail, a query would be completed by another machine. Further, MapReduce and its open source brethren can perform functions not possible in standard SQL (click-stream sessionization, nPath, graph production of potentially unbounded length in SQL).
What's not to love? At a basic level I believe the MapReduce framework is an inefficient way of analyzing data for the vast majority of businesses. The aforementioned capabilities of MapReduce are all well and good, provided you have a Google-like business replete with legions of programmers and vast amounts of server and memory capacity. Viewed from this perspective, it makes perfect sense that Google developed and used MapReduce: because it could. It had a huge and growing resource in its farms of custom-made servers, as well as armies of programmers constantly looking for new ways to take advantage of that seemingly infinite hardware (and the data collected on it), to do cool new things.
Similarly, the other high-profile adopters and advocates are also IT-savvy, IT-heavy companies and, like Google, have the means and ongoing incentive to get a MapReduce framework tailored to their particular needs and reap the benefits. Would a mid-size firm know how? It seems doubtful. While it has claimed that MapReduce is easy to use, even for programmers without experience with distributed systems, I know from field experience with customers that it does, in fact, take some pretty experienced folks to make best use of it.
Projects like Hive, Google Sawzall, Yahoo Pig and companies like Cloudera all, in essence, attempt to make the MapReduce paradigm easier for lesser experts to use and, in fact, make it behave for the end user more like a parallel database. But this raises the question: Why? It seems to be a bit of re-inventing the wheel. IT-heavy is not how most businesses operate today, especially in these economic times. The dot-com bubble is long over. Hardware budgets are limited and few companies relish the idea of hiring teams of programming experts to maintain even a valuable IT asset such as their data warehouse. They'd rather buy an off-the-shelf tool designed from the ground up to do high-speed data analytics.
Like MapReduce, commercially available massively parallel processing databases specifically built for rapid, high volume data analytics will provide immense data scale and query fault tolerance. They also have a proven track record of customer deployments and deliver equal if not better performance on Big Data problems. Perhaps as important, today's next-generation MPP analytic databases give businesses the flexibility to draw on a deep pool of IT labor skilled in established conventions such as SQL.
As mentioned earlier, unstructured data seems like a natural for MapReduce analysis. A rising tide of chatter is focused on the increasing problem - and importance - of unstructured data. There is more than a bit of truth to this. As the Internet of everything becomes more and more a reality, data is generated everywhere; but our experience to date is that businesses are most interested in data derived from the transactional systems they've wired their businesses on top of, where structure is a given.
Another difficulty faces companies even as MapReduce becomes more integrated into the overall enterprise data analysis strategy. MapReduce is a framework. As the hype and interest have grown, MapReduce solutions are being created by database vendors in entirely non-standard and incompatible ways. This will further limit the likelihood that it will become the centerpiece of an EDW. Business has demonstrated time and again that it prefers open standards and interoperability.
Finally, I believe a move toward a programmer-centric approach to data analysis is both inefficient and contrary to all other prevailing trends of technology use in the enterprise. From the mobile workforce to the rise of social enterprise computing, the momentum is away from hierarchy. I believe this trend is the only way the problem of making Big Data actionable will be effectively addressed. In his classic book on the virtues of open source programming, The Cathedral and the Bazaar, Eric S. Raymond put forth the idea that open source was an effective way to address the complexity and density of information inherent in developing good software code. His proposition, "given enough eyeballs, all bugs are shallow," could easily be restated for Big Data as, "given enough analysts, all trends are apparent." The trick is - and really always has been - to get more people looking at the data. You don't achieve that end by centering your data analytics efforts on a tool largely geared to the skills of technical wizards.
MapReduce-type solutions as they currently exist are most effective when utilized by programmer-led organizations focused on maximizing their growing IT assets. For most businesses seeking the most efficient way to quickly turn their most valuable data into revenue generating insight, MPP databases will likely continue to hold sway, even as MapReduce-based solutions find a supporting role.
Today we can collect lots and lots of performance data. We build beautiful dashboards and even have fancy query languages to access and transform the data. Still performance data is a secret language only a couple of people understand. The more business becomes digital the more stakeholders are interested in this data including how it relates to business. Some of these people have never used a monitoring tool before. They have a question on their mind like “How is my application doing” but no id...
Dec. 3, 2016 05:15 PM EST Reads: 2,129
In IT, we sometimes coin terms for things before we know exactly what they are and how they’ll be used. The resulting terms may capture a common set of aspirations and goals – as “cloud” did broadly for on-demand, self-service, and flexible computing. But such a term can also lump together diverse and even competing practices, technologies, and priorities to the point where important distinctions are glossed over and lost.
Dec. 3, 2016 04:30 PM EST Reads: 1,460
Information technology is an industry that has always experienced change, and the dramatic change sweeping across the industry today could not be truthfully described as the first time we've seen such widespread change impacting customer investments. However, the rate of the change, and the potential outcomes from today's digital transformation has the distinct potential to separate the industry into two camps: Organizations that see the change coming, embrace it, and successful leverage it; and...
Dec. 3, 2016 03:15 PM EST Reads: 3,215
Monitoring of Docker environments is challenging. Why? Because each container typically runs a single process, has its own environment, utilizes virtual networks, or has various methods of managing storage. Traditional monitoring solutions take metrics from each server and applications they run. These servers and applications running on them are typically very static, with very long uptimes. Docker deployments are different: a set of containers may run many applications, all sharing the resource...
Dec. 3, 2016 02:15 PM EST Reads: 5,467
Join Impiger for their featured webinar: ‘Cloud Computing: A Roadmap to Modern Software Delivery’ on November 10, 2016, at 12:00 pm CST. Very few companies have not experienced some impact to their IT delivery due to the evolution of cloud computing. This webinar is not about deciding whether you should entertain moving some or all of your IT to the cloud, but rather, a detailed look under the hood to help IT professionals understand how cloud adoption has evolved and what trends will impact th...
Dec. 3, 2016 02:00 PM EST Reads: 2,476
Without lifecycle traceability and visibility across the tool chain, stakeholders from Planning-to-Ops have limited insight and answers to who, what, when, why and how across the DevOps lifecycle. This impacts the ability to deliver high quality software at the needed velocity to drive positive business outcomes. In his session at @DevOpsSummit 19th Cloud Expo, Eric Robertson, General Manager at CollabNet, showed how customers are able to achieve a level of transparency that enables everyone fro...
Dec. 3, 2016 01:45 PM EST Reads: 1,827
Internet of @ThingsExpo, taking place June 6-8, 2017 at the Javits Center in New York City, New York, is co-located with the 20th International Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world. @ThingsExpo New York Call for Papers is now open.
Dec. 3, 2016 01:00 PM EST Reads: 1,868
The 20th International Cloud Expo has announced that its Call for Papers is open. Cloud Expo, to be held June 6-8, 2017, at the Javits Center in New York City, brings together Cloud Computing, Big Data, Internet of Things, DevOps, Containers, Microservices 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 ...
Dec. 3, 2016 11:30 AM EST Reads: 2,085
You have great SaaS business app ideas. You want to turn your idea quickly into a functional and engaging proof of concept. You need to be able to modify it to meet customers' needs, and you need to deliver a complete and secure SaaS application. How could you achieve all the above and yet avoid unforeseen IT requirements that add unnecessary cost and complexity? You also want your app to be responsive in any device at any time. In his session at 19th Cloud Expo, Mark Allen, General Manager of...
Dec. 3, 2016 11:15 AM EST Reads: 1,637
"Dice has been around for the last 20 years. We have been helping tech professionals find new jobs and career opportunities," explained Manish Dixit, VP of Product and Engineering at Dice, in this SYS-CON.tv interview at 19th Cloud Expo, held November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA.
Dec. 3, 2016 09:30 AM EST Reads: 843
Application transformation and DevOps practices are two sides of the same coin. Enterprises that want to capture value faster, need to deliver value faster – time value of money principle. To do that enterprises need to build cloud-native apps as microservices by empowering teams to build, ship, and run in production. In his session at @DevOpsSummit at 19th Cloud Expo, Neil Gehani, senior product manager at HPE, discussed what every business should plan for how to structure their teams to delive...
Dec. 3, 2016 08:30 AM EST Reads: 1,367
Rapid innovation, changing business landscapes, and new IT demands force businesses to make changes quickly. In the eyes of many, containers are at the brink of becoming a pervasive technology in enterprise IT to accelerate application delivery. In this presentation, attendees learned about the: The transformation of IT to a DevOps, microservices, and container-based architecture What are containers and how DevOps practices can operate in a container-based environment A demonstration of how ...
Dec. 3, 2016 08:30 AM EST Reads: 766
As we enter the final week before the 19th International Cloud Expo | @ThingsExpo in Santa Clara, CA, it's time for me to reflect on six big topics that will be important during the show. Hybrid Cloud This general-purpose term seems to provide a comfort zone for many enterprise IT managers. It sounds reassuring to be able to work with one of the major public-cloud providers like AWS or Microsoft Azure while still maintaining an on-site presence.
Dec. 3, 2016 04:00 AM EST Reads: 2,734
Without lifecycle traceability and visibility across the tool chain, stakeholders from Planning-to-Ops have limited insight and answers to who, what, when, why and how across the DevOps lifecycle. This impacts the ability to deliver high quality software at the needed velocity to drive positive business outcomes. In his general session at @DevOpsSummit at 19th Cloud Expo, Phil Hombledal, Solution Architect at CollabNet, discussed how customers are able to achieve a level of transparency that e...
Dec. 3, 2016 02:15 AM EST Reads: 790
Much of the value of DevOps comes from a (renewed) focus on measurement, sharing, and continuous feedback loops. In increasingly complex DevOps workflows and environments, and especially in larger, regulated, or more crystallized organizations, these core concepts become even more critical. In his session at @DevOpsSummit at 18th Cloud Expo, Andi Mann, Chief Technology Advocate at Splunk, showed how, by focusing on 'metrics that matter,' you can provide objective, transparent, and meaningful f...
Dec. 3, 2016 01:45 AM EST Reads: 4,540
Between 2005 and 2020, data volumes will grow by a factor of 300 – enough data to stack CDs from the earth to the moon 162 times. This has come to be known as the ‘big data’ phenomenon. Unfortunately, traditional approaches to handling, storing and analyzing data aren’t adequate at this scale: they’re too costly, slow and physically cumbersome to keep up. Fortunately, in response a new breed of technology has emerged that is cheaper, faster and more scalable. Yet, in meeting these new needs they...
Dec. 3, 2016 12:15 AM EST Reads: 1,767
@DevOpsSummit taking place June 6-8, 2017 at Javits Center, New York City, is co-located with the 20th International Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world. @DevOpsSummit at Cloud Expo New York Call for Papers is now open.
Dec. 2, 2016 10:30 PM EST Reads: 1,743
Logs are continuous digital records of events generated by all components of your software stack – and they’re everywhere – your networks, servers, applications, containers and cloud infrastructure just to name a few. The data logs provide are like an X-ray for your IT infrastructure. Without logs, this lack of visibility creates operational challenges for managing modern applications that drive today’s digital businesses.
Dec. 2, 2016 08:00 PM EST Reads: 1,553
Keeping pace with advancements in software delivery processes and tooling is taxing even for the most proficient organizations. Point tools, platforms, open source and the increasing adoption of private and public cloud services requires strong engineering rigor – all in the face of developer demands to use the tools of choice. As Agile has settled in as a mainstream practice, now DevOps has emerged as the next wave to improve software delivery speed and output. To make DevOps work, organization...
Dec. 2, 2016 01:30 PM EST Reads: 5,713
In his session at 19th Cloud Expo, Claude Remillard, Principal Program Manager in Developer Division at Microsoft, contrasted how his team used config as code and immutable patterns for continuous delivery of microservices and apps to the cloud. He showed how the immutable patterns helps developers do away with most of the complexity of config as code-enabling scenarios such as rollback, zero downtime upgrades with far greater simplicity. He also demoed building immutable pipelines in the cloud ...
Dec. 1, 2016 09:00 PM EST Reads: 1,734