Tag Archive for 'Hadoop'

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WANdisco Non-Stop NameNode Removes Hadoop’s Single Point of Failure

We’re pleased to announce the release of the WANdisco Non-Stop NameNode, the only 100% uptime solution for Apache Hadoop. Built on our Non-Stop patented technology, Hadoop’s NameNode is no longer a single point of failure, delivering immediate and automatic failover and recovery whenever a server goes offline, without any downtime or data loss.

“This announcement demonstrates our commitment to enterprises looking to deploy Hadoop in their production environments today,” said David Richards, President and CEO of WANdisco. “If the NameNode is unavailable, the Hadoop cluster goes down. With other solutions, a single NameNode server actively supports client requests and complex procedures are required if a failure occurs. The Non-Stop NameNode eliminates those issues and also allows for planned maintenance without downtime. WANdisco provides 100% uptime with unmatched scalability and performance.”

Additional benefits of Non-Stop NameNode include:

  • Every NameNode server is active and supports simultaneous read and write requests.
  • All servers are continuously synchronized.
  • Automatic continuous hot backup.
  • Immediate and automatic recovery after planned or unplanned outages, without the need for administrator intervention.
  • Protection from “split-brain” where the backup server becomes active before the active server is completely offline. This can result in data corruption.
  • Full support for HBase.
  • Works with Apache Hadoop 2.0 and CDH 4.1.

“Hadoop was not originally developed to support real-time, mission critical applications, and thus its inherent single point of failure was not a major issue of concern,” said Jeff Kelly, Big Data Analyst at Wikibon. “But as Hadoop gains mainstream adoption, traditional enterprises rightly are looking to Hadoop to support both batch analytics and mission critical apps. With WANdisco’s unique Non-Stop NameNode approach, enterprises can feel confident that mission critical applications running on Hadoop, and specifically HBase, are not at risk of data loss due to a NameNode failure because, in fact, there is no single NameNode. This is a major step forward for Hadoop.”

You can learn more about the Non-Stop NameNode at the product page, where you can also claim your free trial.

If you’d like to get first-hand experience of the Non-Stop NameNode and are attending the Strata Conference in Santa Clara this week, you can find us at booth 317, where members of the WANdisco team will be doing live demos of Non-Stop NameNode throughout the event.

WANdisco Announces Non-Stop Hadoop Alliance Partner Program

We’re pleased to announce the launch of our Non-Stop Alliance Partner Program to provide Industry, Technology and Strategic Partners with the competitive advantage required to compete and win in the multi-billion dollar Big Data market.

There are three partner categories:

  • For Industry Partners, which include consultants, system integrators and VARs, the program provides access to customers who are ready to deploy and the competitive advantage necessary to grow business through referral and resale tracks.
  • For Technology and Strategic Partners, including software and hardware vendors, the program accelerates time-to-market through Non-Stop certification and reference-integrated solutions.
  • For Strategic Partners, the program offers access to WANdisco’s non-stop technology for integrated Hadoop solutions (OEM and MSP)

Founding Partners participating in the Non-Stop Alliance Partner Program include Hyve Solutions and SUSE.

“Hyve Solutions is excited to be a founding member of WANdisco’s Non-Stop Alliance Partner Program,” said Steve Ichinaga, Senior Vice President and General Manager of Hyve Solutions. “The integration of WANdisco and SUSE’s technology with Hyve Solutions storage and server platforms gives enterprise companies an ideal way to deploy Big Data environments with non-stop uptime quickly and effectively into their datacenters.”

“Linux is the undisputed operating system of choice for high performance computing. For two decades, SUSE has provided reliable, interoperable Linux and cloud infrastructure solutions to help top global organizations achieve maximum performance and scalability,” said Michael Miller, vice president of global alliances and marketing, SUSE.  “We’re delighted to be a Non-Stop Strategic Technology Founding Partner to deliver highly available Hadoop solutions to organizations looking to solve business challenges with emerging data technologies.”

Find out more about joining the WANdisco Non-Stop Alliance Partner Program or view our full list of partners.

Hadoop Console: Simplified Hadoop for the Enterprise

We are pleased to announce the latest release in our string of Big Data announcements: the WANdisco Hadoop Console (WHC.) WHC is a plug-and-play solution that makes it easy for enterprises to deploy, monitor and manage their Hadoop implementations, without the need for expert HBase or HDFS knowledge.

This innovative Big Data solution offers enterprise users:

  • An S3-enabled HDFS option for securely migrating from Amazon’s public cloud to a private in-house cloud
  • An intuitive UI that makes it easy to install, monitor and manage Hadoop clusters
  • Full support for Amazon S3 features (metadata tagging, data object versioning, snapshots, etc.)
  • The option to implement WHC in either a virtual or physical server environment.
  • Improved server efficiency
  • Full support for HBase

“WANdisco is addressing important issues with this product including the need to simplify Hadoop implementation and management as well as public to private cloud migration,” said John Webster, senior partner at storage research firm Evaluator Group. “Enterprises that may have been on the fence about bringing their cloud applications private can now do so in a way that addresses concerns about both data security and costs.”

More information about WHC is available from the WANdisco Hadoop Console product page. Interested parties can also download our Big Data whitepapers and datasheets, or request a free trial of WHC. Professional support for our Big Data solutions is also available.

This latest Big Data announcement follows the launch of our WANdisco Distro, the world’s first production-ready version of Apache Hadoop 2.

Running the SLive Test on WANdisco Distro

The SLive test is a stress test designed to simulate distributed operations and load on the NameNode by utilizing the MapReduce paradigm. It was designed by Konstantin Shvachko and introduced into the Apache Hadoop project in 2010 by him and others. It is now one of the many stress tests we ran here at WANdisco in testing our distribution, WANdisco Distro (WDD).

You can read the original paper about how this test works here:
https://issues.apache.org/jira/secure/attachment/12448004/SLiveTest.pdf
You can view the associated Apache JIRA for the introduction of this test here:
https://issues.apache.org/jira/browse/HDFS-708

This blog will provide a short tutorial on how you can run the SLive test on your own cluster of Hadoop 2 and YARN / MapReduce. Before we begin, please make sure you are logged in as the ‘hdfs’ user:

su – hdfs

The first order of business is to become familiar with the parameters supported by the stress test.

The percentage of operation distribution parameters:
-create <num> -delete <num> -rename <num> -read <num>  -append <num> -ls <num> -mkdir <num>

Stress test property parameters:
-blockSize <min,max> -readSize <min,max> -writeSize <min,max> -files <total>

The first set of parameters controls “how many of this kind of operation do you want?”. For example, if you want to simulate just a create and delete scenario, with no reads or writes, you would run the test with -create 50 -delete 50 (or any other percentages that add up to 100) and set the others in that first set to 0, or just don’t specify them and the test will automatically set them to 0.

The second set of parameters controls properties that extend throughout the entire test. “How many files do you want to make?,” “What is the biggest and smallest that you want each block in the file to be?” They can be ignored for the most part, except for “-blockSize”. Using the default block size, which is 64 megabytes, may cause your run of the SLive test to take longer. In order to make this a speedy tutorial, we will use small block sizes. Please note that block sizes must be in multiples of 512 bytes. We will use 4096 bytes in this tutorial.

There are other parameters available, but they are not necessary in order to provide a basic understanding and run of this stress test. You can refer to the document at the top of this entry if your curiosity of the other parameters is getting the best of you, or you can run:

hadoop org.apache.hadoop.fs.slive.SliveTest –help

The second step is to understand how to run the test. Although it is advised NOT to do this just yet, you can make the following call to instantly run the test with default parameters by executing the following command:

hadoop org.apache.hadoop.fs.slive.SliveTest

However, since we have no initial data within the cluster, you should notice that most, if not all, of the operations in the report are failures. Run the following to initialize the cluster with 10,000 files, all with a tiny 4096 byte block size, in order to achieve a quick run of the SLive test:

hadoop org.apache.hadoop.fs.slive.SliveTest -create 100 -delete 0 -rename 0 -read 0 -append 0 -ls 0 -mkdir 0 -blockSize 4096,4096 -files 10000

On a cluster with 1 NameNode and 3 DataNodes, running this command should take no longer  than about 3 – 4 minutes. If it is taking too long, you can try re-running with a lower “-files” parameter number and/or a smaller “-blockSize” parameter as well.

After you have initialized the cluster with data, you will need to delete the output directory that your previous SLive test run had created:

hadoop fs -rmr /test/slive/slive/output

You will need to do this after every time you have run an SLive test; otherwise your next run attempt will fail, telling you that the output directory for your requested run already exists.

You can now run the default test, which performs an equal distribution of creates, deletes, reads, and other operations across the cluster:

hadoop org.apache.hadoop.fs.slive.SliveTest

Or you can specify the parameters of your own choosing and customize your own load to stress test with! That is the purpose of the test, after all. Enjoy!

Here are the results obtained from our own in-house run of the SLive test for you to compare your own results with. I ran the following command after initialization:

hadoop org.apache.hadoop.fs.slive.SliveTest -blockSize 4096,4096 -files 10000

And I got the following results:

13/02/11 11:00:36 INFO slive.SliveTest: Reporting on job:
13/02/11 11:00:36 INFO slive.SliveTest: Writing report using contents of /test/slive/slive/output
13/02/11 11:00:36 INFO slive.SliveTest: Report results being placed to logging output and to file /home/hdfs/part-0000
13/02/11 11:00:36 INFO slive.ReportWriter: Basic report for operation type AppendOp
13/02/11 11:00:36 INFO slive.ReportWriter: ————-
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “bytes_written” = 4317184
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “failures” = 1
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “files_not_found” = 365
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “milliseconds_taken” = 59813
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “op_count” = 1420
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “successes” = 1054
13/02/11 11:00:36 INFO slive.ReportWriter: Rate for measurement “bytes_written” = 0.067 MB/sec
13/02/11 11:00:36 INFO slive.ReportWriter: Rate for measurement “op_count” = 23.741 operations/sec
13/02/11 11:00:36 INFO slive.ReportWriter: Rate for measurement “successes” = 17.622 successes/sec
13/02/11 11:00:36 INFO slive.ReportWriter: ————-
13/02/11 11:00:36 INFO slive.ReportWriter: Basic report for operation type CreateOp
13/02/11 11:00:36 INFO slive.ReportWriter: ————-
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “bytes_written” = 1490944
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “failures” = 1056
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “milliseconds_taken” = 19029
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “op_count” = 1420
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “successes” = 364
13/02/11 11:00:36 INFO slive.ReportWriter: Rate for measurement “bytes_written” = 0.053 MB/sec
13/02/11 11:00:36 INFO slive.ReportWriter: Rate for measurement “op_count” = 74.623 operations/sec
13/02/11 11:00:36 INFO slive.ReportWriter: Rate for measurement “successes” = 19.129 successes/sec
13/02/11 11:00:36 INFO slive.ReportWriter: ————-
13/02/11 11:00:36 INFO slive.ReportWriter: Basic report for operation type DeleteOp
13/02/11 11:00:36 INFO slive.ReportWriter: ————-
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “failures” = 365
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “milliseconds_taken” = 4905
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “op_count” = 1420
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “successes” = 1055
13/02/11 11:00:36 INFO slive.ReportWriter: Rate for measurement “op_count” = 289.501 operations/sec
13/02/11 11:00:36 INFO slive.ReportWriter: Rate for measurement “successes” = 215.087 successes/sec
13/02/11 11:00:36 INFO slive.ReportWriter: ————-
13/02/11 11:00:36 INFO slive.ReportWriter: Basic report for operation type ListOp
13/02/11 11:00:36 INFO slive.ReportWriter: ————-
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “dir_entries” = 1167
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “files_not_found” = 1145
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “milliseconds_taken” = 536
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “op_count” = 1420
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “successes” = 275
13/02/11 11:00:36 INFO slive.ReportWriter: Rate for measurement “dir_entries” = 2177.239 directory entries/sec
13/02/11 11:00:36 INFO slive.ReportWriter: Rate for measurement “op_count” = 2649.254 operations/sec
13/02/11 11:00:36 INFO slive.ReportWriter: Rate for measurement “successes” = 513.06 successes/sec
13/02/11 11:00:36 INFO slive.ReportWriter: ————-
13/02/11 11:00:36 INFO slive.ReportWriter: Basic report for operation type MkdirOp
13/02/11 11:00:36 INFO slive.ReportWriter: ————-
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “milliseconds_taken” = 5631
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “op_count” = 1420
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “successes” = 1420
13/02/11 11:00:36 INFO slive.ReportWriter: Rate for measurement “op_count” = 252.175 operations/sec
13/02/11 11:00:36 INFO slive.ReportWriter: Rate for measurement “successes” = 252.175 successes/sec
13/02/11 11:00:36 INFO slive.ReportWriter: ————-
13/02/11 11:00:36 INFO slive.ReportWriter: Basic report for operation type ReadOp
13/02/11 11:00:36 INFO slive.ReportWriter: ————-
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “bad_files” = 1
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “bytes_read” = 25437917184
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “chunks_unverified” = 0
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “chunks_verified” = 3188125200
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “files_not_found” = 342
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “milliseconds_taken” = 268754
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “op_count” = 1420
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “successes” = 1077
13/02/11 11:00:36 INFO slive.ReportWriter: Rate for measurement “bytes_read” = 90.265 MB/sec
13/02/11 11:00:36 INFO slive.ReportWriter: Rate for measurement “op_count” = 5.284 operations/sec
13/02/11 11:00:36 INFO slive.ReportWriter: Rate for measurement “successes” = 4.007 successes/sec
13/02/11 11:00:36 INFO slive.ReportWriter: ————-
13/02/11 11:00:36 INFO slive.ReportWriter: Basic report for operation type RenameOp
13/02/11 11:00:36 INFO slive.ReportWriter: ————-
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “failures” = 1165
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “milliseconds_taken” = 1130
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “op_count” = 1420
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “successes” = 255
13/02/11 11:00:36 INFO slive.ReportWriter: Rate for measurement “op_count” = 1256.637 operations/sec
13/02/11 11:00:36 INFO slive.ReportWriter: Rate for measurement “successes” = 225.664 successes/sec
13/02/11 11:00:36 INFO slive.ReportWriter: ————-
13/02/11 11:00:36 INFO slive.ReportWriter: Basic report for operation type SliveMapper
13/02/11 11:00:36 INFO slive.ReportWriter: ————-
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “milliseconds_taken” = 765862
13/02/11 11:00:36 INFO slive.ReportWriter: Measurement “op_count” = 9940
13/02/11 11:00:36 INFO slive.ReportWriter: Rate for measurement “op_count” = 12.979 operations/sec
13/02/11 11:00:36 INFO slive.ReportWriter: ————-

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About Plamen Jeliazkov

WANdisco Joins Fusion-io Technology Alliance Program

WANdisco is excited to announce its partnership with Fusion-io. Following the launch of our first Big Data offering, the world’s first production-ready Apache Hadoop 2 distro, we’ve joined Fusion-io’s Technology Alliance Program. This program focuses on working with leaders in strategic market segments to deliver proven solutions, access to resources and expertise to enhance the value of technology offerings.

“With rapid growth in big data demands around the world, customers require proven solutions and expertise that deliver Hadoop availability with no downtime or data loss,” said Tyler Smith, Fusion-io’s Vice President of Alliances. “WANdisco is a valuable addition to our Technology Alliance Program as we work together to fulfill the market demand for innovative and proven big data solutions.”

As mentioned, this partnership news follows the launch of WANdisco Distro (WDD), a fully tested, production-ready version of Apache Hadoop, based on the most recent Hadoop release. WDD lays the foundation for WANdisco’s upcoming enterprise Hadoop solutions, including the WANdisco Hadoop Console, a comprehensive, wizard-driven management dashboard and the Non-Stop NameNode, which combines our patented replication technology with open source Hadoop to deliver optimum performance, scalability and availability on a 24-by-7 basis.

You can find out more about the Technology Alliance announcement by reading the press release, or visiting Fusion-io’s Technology Alliance Program webpage.

New Webinar Replay: The Future of Big Data for the Enterprise

You may have heard that we’ve just launched the world’s first production-ready Apache Hadoop 2 distro. This WANdisco Distro (WDD) is a fully tested, production-ready version of Apache Hadoop, based on the most recent Hadoop release. We’re particularly excited, as the release of WDD lays the foundation for our upcoming enterprise Hadoop solutions. If you want to find out more about WANdisco’s plans for big data, the replay of our ‘The Future of Big Data for the Enterprise’ webinar is now available.

This webinar is led by WANdisco’s Chief Architect of Big Data, Dr. Konstantin Shvachko, and Jagane Sundar, our Chief Technology Officer and Vice President of Engineering for Big Data. Jagane and Konstantin were part of the original Apache Hadoop team, and have unparalleled expertise in Big Data.

This 30 minute webinar replay covers:

  • The cross-industry growth of Hadoop in the enterprise.
  • The new “Active-Active Architecture” for Apache Hadoop that improves performance.
  • Solving the fundamental issues of Hadoop: usability, high availability, HDFS’s single-point of failure and disaster recovery.
  • How WANdisco’s active-active replication technology will alleviate these issues by adding high-availability, data replication and data security to Hadoop, taking a fundamentally different approach to Big Data.

You can watch the full ‘The Future of Big Data for the Enterprise’ replay, along with our other webinars, at our Webinar Replays page.

WANdisco Launches World’s First Production-Ready Apache Hadoop 2 Distro

hadoop

We’re excited to announce the launch of our WANdisco Distro (WDD) a fully tested, production-ready version of Apache Hadoop 2. WDD is based on the most recent Hadoop release, includes all the latest fixes and undergoes the same rigorous quality assurance process as our enterprise software solutions.

The team behind WDD is led by Dr. Konstantin Boudnik, who is one of the original Hadoop developers, has been an Apache Hadoop committer since 2009 and served as a Hadoop architect with Yahoo! This dedicated team of Apache Hadoop development, QA and support professionals is focused exclusively on delivering the highest quality version of the software.

We are also now offering enterprise-class professional support for organizations deploying Hadoop clusters that utilize WDD. Delivered by our team of open source experts, WANdisco’s professional support for Hadoop includes online service request and case tracking, customer discussion forums, online access to service packs and patches, indemnification coverage, Hadoop cluster health checks, consulting and training and more. You can find out more about the available support options at www.wandisco.com/support/hadoop

We’re particularly excited to make this announcement, as WDD lays the foundation for our enterprise Hadoop solutions that deliver 24-by-7 availability, scalability and performance globally, without any downtime or data loss.

“This is one of a number of key Big Data product announcements WANdisco will be making between now and the upcoming Strata 2013 Big Data conference in Santa Clara, CA, February 26-28. It’s a great time for enterprises requiring a hardened, non-stop Hadoop,” said David Richards, CEO of WANdisco. “Only our patented active-active technology removes the single point of failure inherent in Hadoop and works locally and globally. We are excited to have Dr. Konstantin Boudnik, one of the original developers of Hadoop, leading this rollout.”

You can learn more about WDD at the official press release, or by visiting the Download WANdisco Distro webpage.

WANdisco Teams up with Cloudera

We’re pleased to announce that WANdisco is now an authorized member of the Cloudera Connect Partner Program. This program focuses on accelerating the innovative use of Apache Hadoop for a range of business applications.

“We are pleased to welcome WANdisco into the Cloudera Connect network of valued service and solution providers for Apache Hadoop and look forward to working together to bring the power of Big Data to more enterprises,” said Tim Stevens, Vice President of Business and Corporate Development at Cloudera. “As a trusted partner, we will equip WANdisco with the tools and resources necessary to support, manage and innovate with Apache Hadoop-based solutions.”

As a member of Cloudera Connect, we are proud to add Cloudera’s extensive tools, use case insight and resources to the expertise of our core Hadoop committers.

You can learn more about this program at Cloudera’s website and by reading the official announcement in full.

At WANdisco, we’re working on our Hadoop-based products, including WANdisco Non-Stop NameNode, which will enable each NameNode server to support simultaneous read and write requests, alongside balancing workload across servers for optimum scalability and performance.

You can learn more about Non-Stop NameNode, and our other upcoming Hadoop-based offerings at our Hadoop Big Data Products page.

WANdisco’s January Roundup

Happy new year from WANdisco!

This month we have plenty of news related to our move into the exciting world of Apache Hadoop. Not only did another veteran Hadoop developer join our ever-expanding team of experts, but we announced a partnership with Cloudera, and WANdisco CEO David Richards and Vice President of Big Data Jagane Sundar met with Wikibon’s lead analyst for an in-depth discussion on active-active big data deployments.

WANdisco big data

You may have heard that AltoStor founders and core Apache Hadoop creators, Dr. Konstantin Shvachko and Jagane Sundar joined WANdisco last year. Now we’re excited to announce that another veteran Hadoop developer has joined our Big Data team. Dr Konstantin Boudnik is the founder of Apache BigTop and was a member of the original Hadoop development team. Dr. Boudnik will act as WANdisco’s Director of Big Data Distribution, leading WANdisco’s Big Data team in the rollout of certified Hadoop binaries and graphical user interface. Dr. Boudnik will ensure quality control and stability of the Hadoop open source code.

In building our Big Data team, we’ve been seeking Hadoop visionaries and authorities who demonstrate leadership and originality,” said David Richards, CEO of WANdisco. “Konstantin Boudnik clearly fits that description, and we’re honored that he’s chosen to join our team. He brings great professionalism and distribution expertise to WANdisco.”

Also on the Big Data-front, CEO David Richards, and Vice President of Big Data Jagane Sundar, spoke to Wikibon’s lead analyst about our upcoming solution for active-active big data deployments.

We can take our secret sauce, which is this patented active-active replication algorithm, and apply it to Hadoop to make it bullet-proof for enterprise deployments,” said David Richards. “We have something coming out called the Non-Stop NameNode … that will ensure that Hadoop stays up 100% of the time, guaranteed.”

Watch the ‘WANdisco Hardening Hadoop for the Enterprise’ video in full, or read Wikibon’s Lead Big Data Analyst Jeff Kelly’s post about the upcoming Non-Stop NameNode.

Capping off our Big Data announcements, WANdisco is now an authorized member of the Cloudera Connect Partner Program. This program focuses on accelerating the innovative use of Apache Hadoop for a range of business applications.

We are pleased to welcome WANdisco into the Cloudera Connect network of valued service and solution providers for Apache Hadoop and look forward to working together to bring the power of Big Data to more enterprises,” said Tim Stevens, Vice President of Business and Corporate Development at Cloudera. “As a trusted partner, we will equip WANdisco with the tools and resources necessary to support, manage and innovate with Apache Hadoop-based solutions.”

As a member of Cloudera Connect, we are proud to add Cloudera’s extensive tools, use case insight and resources to the expertise of our core Hadoop committers.

You can learn more about this program at Cloudera’s website and by reading the official announcement in full.

apache subversion logo

On the Subversion side of things, the SVN community announced their first release of 2013, with an update to the Subversion 1.6 series.

Apache Subversion 1.6.20 includes some useful fixes for 1.6.x users:

  • Vary: header added to GET responses
  • Fix fs_fs to cleanup after failed rep transmission.
  • A fix for an assert with SVNAutoVersioning in mod_dav_svn

Full details on Apache Subversion 1.6.20 can be found in the Changes file. As always, the latest, certified binaries can be downloaded for free from our website, along with the latest release of the Subversion 1.7 series.

How many developers can a single Apache Subversion server support? In his recent blog post, James Creasy discussed how DConE replication technology can support Subversion deployments of 20,000 or more developers.

“While impressive, DConE is not magic,” writes James. “What DConE delivers is a completely fault tolerant, mathematically ideal coordination engine for performing WAN connected replication.”

In another new DConeE post, James explains where DConE fits into the ‘software engineering vs. computer science’ debate, and warns “in the world of distributed computing, you’d better come armed with deep knowledge of the science.”

Finally, WANdisco China, a Wholly Foreign Owned Enterprise was announced this month, following WANdisco’s first deal in China with major telecommunications equipment company Huawei. From this new office we’ll be providing sales, training, consulting and 24/7 customer support for WANdisco software solutions sold in China, and are excited to be expanding our activities within this region.

We view China as an emerging and high growth market for WANdisco,” said David Richards. “It was a natural progression to establish our Chengdu office as a WFOE and ramp up staff there as so many companies have operations in the country. We are excited about this announcement and look forward to the growth opportunities this brings.”

To keep up with all the latest WANdisco news, be sure to follow us on Twitter.

 

WANdisco Joins Hortonworks’ Technology Partner Program

We’re pleased to announce that WANdisco has joined the Hortonworks Technology Partner Program. This program aims to support and accelerate the growth of the Apache Hadoop ecosystem. As a part of the Hortonworks Technology Partner Program we will offer our Big Data products on the Hortonworks Data Platform which is powered by Apache Hadoop.

The Hortonworks Data Platform delivers an enterprise-class distribution of Apache Hadoop that is endorsed and adopted by some of the largest vendors in the IT ecosystem.

“We are pleased to welcome WANdisco into the Hortonworks Technology Partner Program,” said Mitch Ferguson, vice president of business development, Hortonworks. “We look forward to working with WANdisco to deliver innovative Apache Hadoop-based solutions for the enterprise.”

Our upcoming Big Data products will remove the single point of failure inherent in Hadoop, providing enterprises with non-stop availability and allowing servers to be taken offline for planned maintenance without interrupting user access.

“WANdisco is bringing active-active replication technology to enterprises for high-availability global Hadoop deployments,” said David Richards, WANdisco CEO. “Hortonworks Data Platform customers will greatly benefit from WANdisco non-stop Big Data solutions through this partnership.”

You can learn more at the official press release, or get more information on the Technology Partner Program at HortonWorks’ website.