Last week I attended Oracle OpenWorld 2014, and it was an outstanding event filled with great people, awesome sessions, and a few outstanding notable experiences.
Personally I thought the messaging behind the conference itself wasn’t as amazing and upbeat as OpenWorld 2013, but that’s almost to be expected. Last year there was a ton of buzz around the introduction of Oracle 12c, Big Data was a buzzword that people were totally excited (more...)
I will give a presentation on 24 September at the Jury’s Inn in Dublin on the next generation of Big Data 2.0 tools and architecture.
Over the last two years there have been significant changes and improvements in the various Big Data frameworks. With the release of Yarn (Hadoop 2.0) the most popular of these platforms now allows you to run mixed workloads. Gone are the days when Hadoop was only good for (more...)
For an organization to respond in real-time it needs to acquire or develop systems
that can respond in real-time. Such systems need to be able to rapidly
determine that a response is required and determine also what the
appropriate and relevant response should be – they need to decide when
and how to act. These kinds of decision-making systems are known as
Decision Management Systems. To ensure that a response is delivered in
real-time, more (more…)
Both ODI and the Hadoop ecosystem share a common design philosophy. Bring the processing to the data rather than the other way around. Sounds logical, doesn’t it? Why move Terabytes of data around your network if you can process it all in the one place. Why invest millions in additional servers and hardware just to transform and process your data?
In the ODI world this approach is known as ELT. ELT is a marketing concept (more...)
You may have wondered why we were quiet over the last couple of weeks? Well, we locked ourselves into the basement and did some research and a couple of projects and PoCs on Hadoop, Big Data, and distributed processing frameworks in general. We were also looking at Clickstream data and Web Analytics solutions. Over the next couple of weeks we will update our website with our new offerings, products, and services. The article below summarises (more...)
In every change there are hype machines that over play and sages who call doom. Into the Big Data arena steps David Searls to proclaim that Big Data is a myth and simply hype which is set to burst in an article over at ZDNet.
But big data, he said, is nothing more than the myth that collecting vast amounts of data can help companies know customers better than those customers even know
My paper on NoSQL and Big Data won the Editor’s Choice award at ODTUG Kscope14. Here are some key points from the paper: The relational camp made serious mistakes that limited the performance and usefulness of the relational model. NoSQL is based on the incorrect premise that tables in the relational model must be mapped to […]
Oracle Scene (the publication of United Kingdom Oracle Users Group) has published my article "Hadoop for Oracle Professionals", where I have attempted, like many others, to demystify the terms such as Hadoop, Map/Reduce and Flume. If you were interested in Big Data and what all comes with understanding it, you might find it useful.
I'm going to state a sacrilegious position for a moment: the quality of data isn't a primary goal in Master Data Management
Now before the perfectly correct 'Garbage In, Garbage Out' statement let me explain. Data Quality is certainly something that MDM can help with but its not actually the primary aim of MDM.
MDM is about enabling collaboration, collaboration is about the cross-reference
There is a massive amount of IT hype that is focused on what people see, its about the agile delivery of interfaces, about reporting, visualisation and interactional models. If you could weight hype then it is quite clear that 95% of all IT is about this area. Its why we need development teams working hand-in-hand with the business, its why animations and visualisation are massively important.
Scoop, Flume, PIG, Zookeeper. Do these mean anything to you? If they do then the odds are you are looking at Hadoop. The thing is that while that was cool a few years ago it really is time to face it that HDFS is a commodity, Map Reduce is interesting but not feasible for most users and the real question is how we turn all that raw data in HDFS into something we can actually (more...)
With big data and analytics playing an influential role helping organizations achieve a competitive advantage, IT managers are advised not to deploy big data in silos but instead to take a holistic approach toward it and define a base reference architecture even before contemplating positioning the necessary tools.
My latest print media article (5th in the series) for CIO magazine (ITNEXT) talks extensively about need of reference architecture in (more...)
Over the last few years there has been a trend of increased spending on BI, and that trend isn't going away. The analyst predictions however have, understandably, been based on the mentality that the choice was between a traditional EDW/DW model or Hadoop. With the new 'Business Data Lake' type of hybrid approach its pretty clear that the shift is underway for all vendors to have a hybrid
As Hive metastore is getting into the center of nervous system for the different type of SQL engines like Shark and Impala. It getting equally difficult to distinguish type of table created in Hive metastore. Eg. if we create a impala table using impala shell you will see the same table on hive prompt and vice versa. See the below example
Step 1 : “Create Table” in Impala Shell and “Show Table” (more...)
While building a data flow for replacing one of the EDW’ workflow using Big Data technology stack , came across some interesting findings and issues. Due to UPSERT ( INSERT new records or UPDATE existing records depending) nature of data we had to use Hbase, but to expose the outbound feed we need to do some calculation on HBase and publish that to Hive as external. Even though conceptually , its easy to create an (more...)
While looking into HBase performance issue, one of the suggestion was to have more region for a larger table. There was some confusion around, “Region” vs “RegionServer” . While doing some digging, found a simple text written below.
The basic unit of scalability and load balancing in HBase is called a region. Regions are essentially contiguous ranges of rows stored together. They are dynamically split by the system when they become too large. Alternatively, they may (more...)
With increasing data volume , in HDFS space could be continued challenge. While running into some space related issue, following command came very handy, hence thought of sharing with extended virtual community.
hadoop dfsadmin -report
Post running the command, below is the result, it takes all the nodes in the cluster and gives the detail break-up based on the space availability and spaces used.
"Real-time" its a word that gets thrown about a lot in IT and its worth documenting a few of the different ways it gets used
This is what Real-time Java was created to address (along with Soft Real-time) what is this? Easiest way to say it is that often in Hard Real-time environments the following statement is true
If it doesn't finish in X milliseconds then people might die