|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.
JFrog has announced a powerful technology for managing software packages from development into production. JFrog Artifactory 4 represents disruptive innovation in its groundbreaking ability to help development and DevOps teams deliver increasingly complex solutions on ever-shorter deadlines across multiple platforms JFrog Artifactory 4 establishes a new category – the Universal Artifact Repository – that reflects JFrog's unique commitment to enable faster software releases through the first pla...
Oct. 7, 2015 03:00 PM EDT Reads: 553
Saviynt Inc. has announced the availability of the next release of Saviynt for AWS. The comprehensive security and compliance solution provides a Command-and-Control center to gain visibility into risks in AWS, enforce real-time protection of critical workloads as well as data and automate access life-cycle governance. The solution enables AWS customers to meet their compliance mandates such as ITAR, SOX, PCI, etc. by including an extensive risk and controls library to detect known threats and b...
Oct. 7, 2015 03:00 PM EDT Reads: 101
Ten years ago, there may have been only a single application that talked directly to the database and spit out HTML; customer service, sales - most of the organizations I work with have been moving toward a design philosophy more like unix, where each application consists of a series of small tools stitched together. In web example above, that likely means a login service combines with webpages that call other services - like enter and update record. That allows the customer service team to writ...
Oct. 7, 2015 02:45 PM EDT Reads: 335
Several years ago, I was a developer in a travel reservation aggregator. Our mission was to pull flight and hotel data from a bunch of cryptic reservation platforms, and provide it to other companies via an API library - for a fee. That was before companies like Expedia standardized such things. We started with simple methods like getFlightLeg() or addPassengerName(), each performing a small, well-understood function. But our customers wanted bigger, more encompassing services that would "do ...
Oct. 7, 2015 02:30 PM EDT Reads: 539
Clearly the way forward is to move to cloud be it bare metal, VMs or containers. One aspect of the current public clouds that is slowing this cloud migration is cloud lock-in. Every cloud vendor is trying to make it very difficult to move out once a customer has chosen their cloud. In his session at 17th Cloud Expo, Naveen Nimmu, CEO of Clouber, Inc., will advocate that making the inter-cloud migration as simple as changing airlines would help the entire industry to quickly adopt the cloud wit...
Oct. 7, 2015 01:30 PM EDT Reads: 605
The APN DevOps Competency highlights APN Partners who demonstrate deep capabilities delivering continuous integration, continuous delivery, and configuration management. They help customers transform their business to be more efficient and agile by leveraging the AWS platform and DevOps principles.
Oct. 7, 2015 01:15 PM EDT Reads: 116
Our guest on the podcast this week is Jason Bloomberg, President at Intellyx. When we build services we want them to be lightweight, stateless and scalable while doing one thing really well. In today's cloud world, we're revisiting what to takes to make a good service in the first place. Listen in to learn why following "the book" doesn't necessarily mean that you're solving key business problems.
Oct. 7, 2015 12:00 PM EDT Reads: 2,195
Apps and devices shouldn't stop working when there's limited or no network connectivity. Learn how to bring data stored in a cloud database to the edge of the network (and back again) whenever an Internet connection is available. In his session at 17th Cloud Expo, Bradley Holt, Developer Advocate at IBM Cloud Data Services, will demonstrate techniques for replicating cloud databases with devices in order to build offline-first mobile or Internet of Things (IoT) apps that can provide a better, ...
Oct. 7, 2015 11:45 AM EDT Reads: 486
Culture is the most important ingredient of DevOps. The challenge for most organizations is defining and communicating a vision of beneficial DevOps culture for their organizations, and then facilitating the changes needed to achieve that. Often this comes down to an ability to provide true leadership. As a CIO, are your direct reports IT managers or are they IT leaders? The hard truth is that many IT managers have risen through the ranks based on their technical skills, not their leadership ab...
Oct. 7, 2015 11:00 AM EDT Reads: 857
Despite all the talk about public cloud services and DevOps, you would think the move to cloud for enterprises is clear and simple. But in a survey of almost 1,600 IT decision makers across the USA and Europe, the state of the cloud in enterprise today is still fraught with considerable frustration. The business case for apps in the real world cloud is hybrid, bimodal, multi-platform, and difficult. Download this report commissioned by NTT Communications to see the insightful findings – registra...
Oct. 7, 2015 11:00 AM EDT Reads: 222
Application availability is not just the measure of “being up”. Many apps can claim that status. Technically they are running and responding to requests, but at a rate which users would certainly interpret as being down. That’s because excessive load times can (and will be) interpreted as “not available.” That’s why it’s important to view ensuring application availability as requiring attention to all its composite parts: scalability, performance, and security.
Oct. 7, 2015 11:00 AM EDT Reads: 371
“All our customers are looking at the cloud ecosystem as an important part of their overall product strategy. Some see it evolve as a multi-cloud / hybrid cloud strategy, while others are embracing all forms of cloud offerings like PaaS, IaaS and SaaS in their solutions,” noted Suhas Joshi, Vice President – Technology, at Harbinger Group, in this exclusive Q&A with Cloud Expo Conference Chair Roger Strukhoff.
Oct. 7, 2015 10:00 AM EDT Reads: 376
As we increasingly rely on technology to improve the quality and efficiency of our personal and professional lives, software has become the key business differentiator. Organizations must release software faster, as well as ensure the safety, security, and reliability of their applications. The option to make trade-offs between time and quality no longer exists—software teams must deliver quality and speed. To meet these expectations, businesses have shifted from more traditional approaches of d...
Oct. 7, 2015 08:45 AM EDT Reads: 162
As the world moves towards more DevOps and microservices, application deployment to the cloud ought to become a lot simpler. The microservices architecture, which is the basis of many new age distributed systems such as OpenStack, NetFlix and so on, is at the heart of Cloud Foundry - a complete developer-oriented Platform as a Service (PaaS) that is IaaS agnostic and supports vCloud, OpenStack and AWS. In his session at 17th Cloud Expo, Raghavan "Rags" Srinivas, an Architect/Developer Evangeli...
Oct. 7, 2015 08:00 AM EDT Reads: 133
What Is Emergent About Emergent Architecture? By @TheEbizWizard | @DevOpsSummit #DevOps #BigData #API
All we need to do is have our teams self-organize, and behold! Emergent design and/or architecture springs up out of the nothingness! If only it were that easy, right? I follow in the footsteps of so many people who have long wondered at the meanings of such simple words, as though they were dogma from on high. Emerge? Self-organizing? Profound, to be sure. But what do we really make of this sentence?
Oct. 7, 2015 08:00 AM EDT Reads: 381
Last month, my partners in crime – Carmen DeArdo from Nationwide, Lee Reid, my colleague from IBM and I wrote a 3-part series of blog posts on DevOps.com. We titled our posts the Simple Math, Calculus and Art of DevOps. I would venture to say these are must-reads for any organization adopting DevOps. We examined all three ascpects – the Cultural, Automation and Process improvement side of DevOps. One of the key underlying themes of the three posts was the need for Cultural change – things like t...
Oct. 7, 2015 05:00 AM EDT Reads: 314
There once was a time when testers operated on their own, in isolation. They’d huddle as a group around the harsh glow of dozens of CRT monitors, clicking through GUIs and recording results. Anxiously, they’d wait for the developers in the other room to fix the bugs they found, yet they’d frequently leave the office disappointed as issues were filed away as non-critical. These teams would rarely interact, save for those scarce moments when a coder would wander in needing to reproduce a particula...
Oct. 7, 2015 05:00 AM EDT Reads: 277
In today's digital world, change is the one constant. Disruptive innovations like cloud, mobility, social media, and the Internet of Things have reshaped the market and set new standards in customer expectations. To remain competitive, businesses must tap the potential of emerging technologies and markets through the rapid release of new products and services. However, the rigid and siloed structures of traditional IT platforms and processes are slowing them down – resulting in lengthy delivery ...
Oct. 7, 2015 05:00 AM EDT Reads: 989
In a report titled “Forecast Analysis: Enterprise Application Software, Worldwide, 2Q15 Update,” Gartner analysts highlighted the increasing trend of application modernization among enterprises. According to a recent survey, 45% of respondents stated that modernization of installed on-premises core enterprise applications is one of the top five priorities. Gartner also predicted that by 2020, 75% of
Oct. 7, 2015 04:00 AM EDT Reads: 274
It is with great pleasure that I am able to announce that Jesse Proudman, Blue Box CTO, has been appointed to the position of IBM Distinguished Engineer. Jesse is the first employee at Blue Box to receive this honor, and I’m quite confident there will be more to follow given the amazing talent at Blue Box with whom I have had the pleasure to collaborate. I’d like to provide an overview of what it means to become an IBM Distinguished Engineer.
Oct. 7, 2015 04:00 AM EDT Reads: 174