If you’ve been following our postings on the blog over the past year, you’ll probably have seen quite a lot of activity around big data and Hadoop and in particular, what these technologies bring to the world of Oracle Business Intelligence, Oracle Data Warehousing and Oracle Data Integration. For anyone who’s not had a chance to read the posts and articles, the three links below are a great introduction to what we’ve been up to:
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...)
Over the past couple of years Rittman Mead have been broadening our skills and competencies out from core OBIEE, ODI and Oracle data warehousing into the new “emerging” analytic platforms: R and database advanced analytics, Hadoop, cloud and clustered/distributed systems. As we talked about in the recent series of updated Oracle Information Management Reference Architecture blog posts and my initial look at the Oracle Big Data SQL product, our customers are increasingly looking to (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...)
Oracle announced their Big Data SQL product a couple of weeks ago, which effectively extends Exadata’s query-offloading to Hadoop data sources. I covered the launch a few days afterwards, focusing on how it implements Exadata’s SmartScan on Hive and NoSQL data sources and provides a single metadata catalog over both relational, and Hadoop, data sources. In a Twitter conversation later in the day though, I made the comment that in my opinion, the biggest (more...)
Permission issues is one of the key error , while setting up Hadoop Cluster, while debugging some error found below table on http://hadoop.apache.org/ . It’s a good scorecard to keep handy.
The following table lists various paths on HDFS and local filesystems (on all nodes) and recommended permissions:
Oracle launched their Oracle Big Data SQL product earlier this week, and it’ll be of interest to anyone who saw our series of posts a few weeks ago about the updated Oracle Information Management Reference Architecture, where Hadoop now sits alongside traditional Oracle data warehouses to provide what’s termed a “data reservoir”. In this type of architecture, Hadoop and its underlying technologies HDFS, Hive and schema-on-read databases provide an extension to the more structured (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...)
A PDF version of the article can be downloaded here http://www.proligence.com/art/oracle_scene_summ14_hadoop.pdf
Hi Fellow Big Data Admirers ,
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...)
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...)