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Doug Cutting: Hadoop dodged a Microsoft-Oracle stomping

Elephant daddy on breaking into mainstream IT

By Gavin Clarke, 27 Jun 2012

Interview We’ve all heard plenty about open source changing the dynamics of the tech industry and upsetting the old order. Open source, we’re told, is manifest destiny. Companies that ignore it will be consigned to history and CIOs who assert there’s no freebie code behind their firewalls are out of touch with devs happily humming to Tomcat, Apache, Linux and PHP. At least that's how the story goes.

One open-source success of recent years has been Hadoop, the Apache-licensed implementation of Google’s MapReduce, which quickly and efficiently processes petabytes of data using clusters of ordinary x86 servers.

MapReduce works by splitting up massive data-processing jobs into chunks to be processed locally and parallelising the computation (the map phase), and then re-combining the results (the reduce phase) at the end. It means you don’t need big, centralised servers like mainframes or SPARC servers; it's a gift to x86 computing.

In the eight years since Hadoop was first written by Doug Cutting and Mike Cafarella, it has found a home running, Facebook and Yahoo! – some of the biggest sites on the web – among others. In the last eight months alone, Hadoop has won the backing of Microsoft, IBM and Oracle – three of the biggest names in relational databases. The software giants are now supporting a piece of software that the NoSQL zealots believed would actually kill RDBMS.

Microsoft is writing connectors between its databases, Windows and Azure cloud and Hadoop with Hadoop start-up Hortonworks, while Oracle is marrying Hadoop with its open-source MySQL database and merging the result with some Sun Microsystems' server hardware to produce yet another Oracle appliance.

'I’m pleased they decided not to fight it [Hadoop] with some proprietary solution, but to join forces with the open source one' – Doug Cutting

Yet, with history apparently on his side, you'd be surprised to learn Cutting feared Oracle and Microsoft might try to stand up to Hadoop, with disastrous consequences for the ecosystem. He said he is "gratified" that the pair decided to come on board.

“I’m pleased they decided not to fight it [Hadoop] with some proprietary solution, but to join forces with the open source one,” Cutting told The Reg. “It means those would otherwise be two potential sources of serious competition and to grow the community with two companies as big and powerful as Oracle and Microsoft is tremendous.

“I’m really gratified they have elected not to [develop proprietary solutions]. It’s a good thing for Hadoop for sure... I no longer see a formidable competitor, which is a little frightening," Cutting said.

“[It’s] frightening and exciting at the same time because it’s something you have to worry about, to win them over and convince them that this is a better approach. It’s gratifying when you haven’t got to do that.”

Microsoft and Oracle could have forked Hadoop’s code, building versions of Hadoop tailored to their systems thereby splitting the community into those who support Hadoop for large communities of Oracle and SQL Server users, and everybody else.

Not possible you say? Oracle has played politics before to get its way – with disastrous results for open-source projects. Oracle pulled the open-source Solaris project, OpenSolaris, back in-house in 2010 – allowing the fledgling open-source effort that had been blessed and spun up by Sun to die. Oracle’s control of OpenOffice has produced the LibreOffice fork in 2011, while Oracle's reluctance to let go of the Hudson build management system saw almost the entire community leave to create the rival Jenkins.

The legacy of such actions: forked codebases and rival claims over which is the one "true" project. Oracle has the brands, but the community has the code.

Then there’s Microsoft. Redmond is a strategic friend to open source, supporting projects where they help sell more copies of Windows or at prevent lost sales. So far it has worked on Linux, MySQL, PHP, and cuddled up to Eclipse on Silverlight.

On big data, Microsoft had been building a Hadoop-esque architecture since 2006. Called Dryad, it would “efficiently” process huge data loads running on Windows HPC Server 2008 R2 and HPC Pack 2008 R2-based clusters with Service Pack 2. In November last year, however, Microsoft quietly announced that it no longer planned to pursue Dryad as a commercial product just as it announced Hadoop connectors to SQL Server and Windows Azure.

Microsoft and Oracle have muscle in RDBMS. Oracle sells half the planet’s relational databases in a market worth $29bn with Microsoft in third place. The more open-source friendly IBM – which announced Hadoop connectors to its DB2 database around the same time as Oracle – is second.

It's not just Cutting, the father of Hadoop, who felt concern. Hortonworks, the start-up that spun out of Yahoo! last year with venture backing from Red Hat and JBoss investor Rob Bearden and competes with Cutting’s Cloudera, was also worried by what Microsoft and Oracle might do.

A thousand tiny elephants

Eric Baldeschwieler, Hortonworks’ chief technology officer, breathed what could be called a sigh of relief when Oracle last year announced its plans for a big data appliance using Hadoop. “It’s hugely validating of Hadoop, having all the major vendors coming in,” Baldeschwieler told The Reg at the time. “What we don’t want to see is thousands of flavours of Hadoop.”

Why did the giants suddenly turn friendly towards a technology that Cutting reckons will tread on the toes of their beloved RDBMS in about five years – when, as Cutting believes, it becomes an incumbent of mainstream enterprise IT?

“We are moving into a world where there’s lots of data,” Cutting says. “It [Hadoop] is not going to take over all software – there will be other technologies – but it’s going to become one of the mainstream staples in the next five to 10 years - maybe even sooner than that. It seems to be progressing pretty quickly.”

RDBMS grows up

The roots of competition with RDBMS are already there: Hadoop Pig is a data analysis program and Hive a data warehousing system. Cutting says parts of data warehousing and ETL might well be subsumed as these grow.

You laugh? Well, it’s not like RDBMS owns data analysis, data warehousing or ETL; these have only became synonymous with RDBMS because the software giants – Microsoft, Oracle and IBM – have poured vast sums of money into developing the tools that added value to their software by allowing them to take more workloads off the mainframe and midrange systems of the day. “There might be some battles where some existing technologies get incorporated into the big data sack,” Cutting says.

Co-existence, though, is the watchword as Cutting reckons Hadoop can find a new niche working with RDBMS. “The sweet spot for the growth is not to try to displace things like that but rather to attack problems people are having when they use those things. Over time the technologies could creep upstream and erode neighbouring technologies but, right now, there’s enough new stuff to keep us busy.”

'It’s getting better,' Baldeschwieler said of Hortonworks’ relationship with Cloudera. 'There’s name-calling in all open-source projects.'

The RDBMS giants, it seems, agree with Cutting's view that Hadoop won't compete for enterprise transactional loads such as payroll and inventory.

The other big reason Microsoft and Oracle have lowered their defences is that Hadoop will actually reinforce their positions and the position of RDBMS. Hadoop will bring larger numbers of developers to their databases. These devs will build applications for big data and the web that – in part – will use information held in RDBMS. Hadoop is built using open-source Java while the Avro project allows compiling in Java, C, C++, C sharp, Python and Ruby.

The big companies might be buying into Hadoop right now, but they could still pose problems and could help contribute to some kind of fragmentation down the road. That's because the RDBMS giants have taken sides: Microsoft has chosen to work with Hortonworks, formed in June 2011 with the engineering team who’d worked with Cutting on Hadoop but who’d remained at Yahoo!. IBM and Oracle, meanwhile, have gone with Cloudera, where Cutting is architect.

Cloudera and Hortonworks implement different modules of Hadoop in their distributions. You can compare the full list for Cloudera CDH here and Hortonworks' Data Platform here (warning PDF). Hortonworks has also added third-party software to its module mix: Talend's Open Studio.

There has already been tension between Cutting’s company and Hortonworks. They got in to a bloggy spat last year over who contributed which code to Apache (fixes versus new features).

At the time of the spat, Baldeschwieler told The Reg this was was business as usual for open source but he reckoned Hortonworks and Cloudera are united on the common cause of improving Hadoop. “It’s getting better,” Baldeschwieler said of Hortonworks’ relationship with Cloudera, adding: “There’s name-calling in all open-source projects...

“At this point,” he continued, “there’s an obvious consensus that Cloudera and Hortonworks are equally focused on making Hadoop better.”

Baldeschwieler called Hortonworks' partnership with Microsoft “an example of building a strong relationship to take Hadoop to more customers.”

Cutting hopes Hadoop can stay united using BigTop, which acts as a kind of reference model. BigTop is an Apache project that integrates core Hadoop with the Zookeeper, HBass, Hive, Pig, Mahout, Oozie, Sqoop, Flume and Whirr modules and with versions of Fedora, CentOS, Red Hat Enterprise Linux and SuSE Linux Ubuntu. The basis of BigTop is Cloudera’s CDH and the idea is that all future versions of CDH will come from BigTop.

Cutting reckons BigTop will align CDH to the official Apache Hadoop project. While Cloudera has tried to align CDH to Apache releases, gaps have sometimes emerged as bugfixes and some features are back-ported to CDH that correspond to earlier versions of the Apache release, Cutting said.

Cutting doesn’t see fragmentation as a big problem but did note that fewer versions of Hadoop would be a good thing – it would make things easier for developers and, presumably, better for firms like Cloudera, which hopes to build a Hadoop business based upon the distro which the market likes the most. “Fewer distributions would make it easier for developers, since they'd have fewer combinations of versions to support,” Cutting said.

Coding inside the BigTop

To mean anything, however, BigTop, will need everybody – not just Cloudera – to support its development and to swallow up the code base into their distros. Currently, BigTop is rather Cloudera-centric. According to this blog post, and based on the Hortonworks HDP data sheet (warning PDF), Hortonworks is only "parts” of BigTop.

“We're hoping that other distributors will join us in collaborating on BigTop to further reduce any such fragmentation issues,” Cutting told The Reg. “We currently have lots of folks collaborating well on these projects who don't share a distribution. Ideally we'll all start collaborating through BigTop and the various distributions will interoperate easily.”

BigTop comes as Cutting reckons further changes are needed to help Hadoop hit its potential – and establish that footing it aims for in mainstream IT. Changes won't be big, he says. Instead, they will be refinements.

Name change, game changer

The last big change went to the very heart of Hadoop’s identity: the MapReduce engine was rewritten so there is a global resource manager and per-application master that manages different applications. The rewrite was called MapReduce 2.0 (MRv2) or YARN, and has been folded into Apache Hadoop 2.0 and Cloudera’s CDH 4.

MRv2 is designed to bring the power of Hadoop to applications outside of large datasets, such as graph-processing algorithms. "Graph" is the name given to software maps constructed by social networks such as Facebook and LinkedIn to connect people, to find out who knows whom and their relationships to each other.

'Right now we are getting the low-hanging fruit of the companies that are sophisticated users of technology and that have the most glaring big data problems,' – Doug Cutting

“Graph will be moved to shared node,” Cutting said. “So you can have a node for a time doing graph process and then a minute later running a task from a MapReduce job – there’d be time-sharing on the cluster at a finer level. It’s going tog give people better resource utilisation.”

Cutting wrote Hadoop while working on Nutch, a web search project. Nutch had used a lot of manual steps and lacked a framework that would automate large-scale data crunching. MapReduce provided the automation framework and two years later Cutting was hired by Yahoo!.

Despite improvements, Hadoop still remains relatively difficult for newcomers. More work is needed on vertical-specific apps, nice UIs and tools to integrate Hadoop with existing platforms, Cutting says.

Cutting, who today spends just a third of his time working on Hadoop, is focused on the need for broader language support. He spends the rest of his time working on Apache's Avro project, designed to make Hadoop “less of a Java shop”.

“[Java] gets you 90 per cent of the performance,” Cutting told us. “Over time, the last 10 per cent of performance might become more critical and as things stabilise, we might see more things move into C/C++. In Hadoop, several critical elements have been moved into C/C++. It would be nice if wasn’t just a Java world and we worked better with other languages, but it [Java] has been a good platform for the technology.”

Cutting is bullish on Hadoop's potential to become established in the mainstream in the next five to 10 years. MRv2 should help broaden Hadoop’s adoption among different sizes of user with different types of challenges, he says. "Making Hadoop easier" should accompany such changes, he added.

The old order liveth

“Right now we are getting the low-hanging fruit of the companies that are sophisticated users of technology and that have the most glaring big data problems. Over time we can take new classes of problems and support people more easily and do it more efficiently,” Cutting says.

Cutting said he is relieved Microsoft and Oracle are on board. In fact, he says, the will actually help Hadoop grow by adding more contributors. “We want to build a large community to develop the common software... the larger the community the more refined the tools will get. Users turn into contributors over time; the more users, the more contributors over time.”

As long as Cloudera and Hortonworks don’t become Cold War proxies to the giants, maybe this IS manifest destiny. Maybe more makers of proprietary software in the field of data and analytics should be worried.

By allying with Hadoop, though, Microsoft and Oracle have done more than reassure Cutting. They have ensured the survival of their RDBMS. ®

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