Recently we had one requirement wherein we had to merge the files post Map and Reducer job. Since the file needed to be given to the outbound team outside of Hadoop development team, having these files on local system would have been ideal. The customer IT team worked with cloudera and gave us a mount point using a utility/concept called “mountableHDFS” aka FUSE (Filesystem in Userspace) .
mountableHDFS, helps allowing HDFS to be mounted (more...)
During one of the sizing exercise the ask for server capacity was more than the actual usage of cluster . Knowing the data and usage, I was not convinced that we should be asking for more memory space. That triggered the thought of
Conceptually FSIMG file is the balancesheet of all the file and their existence and location. If somehow we could read the metadata withing the file and make sence out of it, than it could help (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.
Permissions for both HDFS and local fileSystem paths
The following table lists various paths on HDFS and local filesystems (on all nodes) and recommended permissions:
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...)
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.
Configured Capacity: 13965170479105 (12.70 TB)
Present Capacity: 4208469598208 (more...)
Past few months I have been meeting with clients and discussing their potential need of Big Data. The discuss gets to the bottom of , do they really need the Big Data ? The below link to my ITNext article talks about As big data goes bigger,IT managers are challenged with the task of identifying data that qualifies for big and finding appropriate solutions to process it.
Click Here To Read Full Article (more...)
While doing a comparison analysis for building a reference architecture for Big Data technology stumbled on a very impressive Open source Big Data Technology mashup . Thanks to http://www.bigdata-startups.com/ . The most impressive part of this mashup is breaking the whole Big Data operational paradigm into multiple stages and giving available opensource technology.
Hope This Helps
Sunil S Ranka
“Superior BI is the antidote to Business Failure”