First Things I do in the Hortonworks Sandbox

The Hortonworks Sandbox has been out for some time now and over that time a few versions have been released. I use the sandbox for demos, POCs and development work. In the interest of always using the latest and greatest I have had the opportunity to install a few new versions.  A pattern has emerged for me of changes and things that I do with the sandbox when a new version comes out. I thought sharing this list might be useful to others:

1. Snapshot it – I run a Mac Pro so I use VMware Fusion. One of the first things I do is snapshot my installation right after I install. I also make sure I take snapshots at key breakpoints over the working life of the instance including after installing packages and bookending projects. I like to be able to make all the changes I would like while experimenting with the sandbox and simply backing out of those changes quickly.

2. Modify the Network – The sandbox used to come preconfigured with two network adapters which was later reduced to one. Of course its up to you how you accomplish connecting the sandbox in general but I have found I like having my primary adapter to be on a host only network while adding a second adapter for external connections. This allows me to not only update the sandbox with new tutorials but also connect to various online repos and pull packages down via the command line as I see fit. I like to choose a static IP for my sandbox and make an entry in my local hosts file for name resolution that is consistent over time.

3. Install additional packages – I usually have a list of thing I like to use and install. This list might vary for you but some of my favorites include mlocate, R along with the R Hadoop Libraries, Mahout, flume, elastic search, Kibana. If you have other linux nodes you want to harness as a group I also recommend pdsh.

4. Swap SSH Keys – I dont like to keep typing passwords so I always make sure I create keys for user root and swap them with my host OS public key. Be sure to also change the default root password from “hadoop”.

5. Enable Ambari – There is a small script in home directory of root that you can run to enable Amabri called “”. Run this script and reboot. You will then have Ambari available at http://hostname:8080 with username admin and password admin while the standard Hue interface is available at http://hostname.

6. Check for new Tutorials – You can click the “About Hortonwork Hue” icon in the upper left hand corner and then click “Update” on the resulting page. You can check this every so often to make sure you have all the latest tutorials.

7. Enable NFS to HDFS – This is a little more involved but is possible. I will have a blog entry on the Hortonworks main site detailing the steps involved and I will like to it here. This gives you the ability to mount HDFS as an NFS mountable directory to your local workstation. This isnt really made for a transferring data at scale but is another very hand option up to a point.

8. Increase the amount of available memory – This is a no brainer. Turn up the amount of memory available to the sandbox to make your life easier. I have 16GB on my laptop so I have plenty to spare. If you don’t then try to find out if you can host this virtual somewhere with more memory available if possible. Lots of times administrators don’t mind giving you space to run a small VM like this. Try running the built in Hadoop benchmarks as you increase the hardware specs and see what happens.

9. Change the Ambari admin password – The default Ambari login is username Ambari with password set to Ambari. Make sure you change this immediately.

10. Add users including HDFS users – Its Linux so you can simply use “adduser” to add OS level users. Also add HDFS users and add a quotas. You can then simply use to add your hadoop users.

11. Connect Clients – I run a collection of clients including Talend Open Studio for Big Data, Tableau and Microsoft Excel powered by the Hortonworks ODBC driver. All these are pretty detailed and probably worthy of additional blog entries on each.

There are probably more things I am forgetting here but this is a good list of the basics that I touch when installing a new version of the Hortonworks Sandbox.

Arun talks Yarn

In case you werent there here is a link to Arun Murthy one of the founders of Hortonworks talking abour Yarn at Hadoop Summit 2013. This is a topic near and dear to my heart being that I have spent a good deal of my career working in HPC under the banners of workload management but also resource negotiation across nodes.

Don’t over think Hadoop.

I was watching TV yesterday and flipped past the film Moneyball on one of the movie channels. I had seen this movie before and I have heard all about the relationship to BI and Big Data. I guess for me I saw the central theme of that movie as disruption as it relates to innovation.

The disruptive power of not really needing high end hardware to build a supercomputer has the market scrambling to force Hadoop into a model that fits many years of coaching by industry giants. You have to have super high end hardware with many layers of backup, redundancy and failsafes. You have to come in on the weekend and neglect your family to “save the day” for some silly website powering someones else’s critical functionality. Stuck in a rut of selling high end nodes the thought of converting to disposability of slave nodes combined with the resiliency of the power that large numbers of slaves brings is disruptive to the entire industry selling into modern data warehouse powered businesses. Not needing Fiber or even 10GbE means networks are smaller, less expensive and closer to disposable. No need for virtualization you say? How can this be? Virtualization is good for everything isn’t it? Its faster, more dense and cost efficient right? Just ask your vendor. They will tell you all about it. Don’t even get me started on the eternal battle of share everything versus share nothing. I have argued for share nothing for many years in classic HPC to no avail. How else can sell massive network or cluster based storage? Query the market and you will find no end to the perversion of the original intent of Hadoop. Changes to the file system, replication level, placement of data into traditional databases and placement of MapReduce over the same. Hogwash. Buy nodes. Lots of them. Cheap ones with zero features for redundancy (no you don’t need two power supplies or 18 NIC cards and shouldn’t be paying more than $5k MAX). If they break beyond repair put them in the dumpster (or may be donate them to a good cause). Don’t over think Hadoop. Start using it and get educated. It will be disruptive and cause people to fear change (including in your own company) but at this stage much like “cloud” was a few years ago if you don’t have a strategy for Hadoop in place you are going to be sitting on your couch in October watching competitive company brand X win the world series of your field.