Simplified Maze of MachineLearning Algorithm
Hi All
Finally, I found something that I was looking for a long time, thought is would be very useful. A simplified maze of #MachineLearning #Algorithm feeling like Nirvana Today #MachinesWouldRuleWorld #AdvanceAnalytics
Hope this helps
Sunil S Ranka
“Superior Data Analytics is the antidote to Business Failure”

What is Oracle Business Intelligence Cloud Service ( BICS )
Recently we have been getting lots of traction on BICS , existing OBIEE customers been asking for BICS . In nutshell :
BI Cloud Service enables organisations of all sizes to quickly and cost effectively deploy business intelligence with the simplicity of the cloud..
Silent features of BICS :
- No need of software installation
- No need of software maintenance
- No upfront costs, low monthly subscription
- Customers can get started in hours
- 100% cloud based
- Robust reporting (more...)
Cloud Allergy – Clouds Security and Changing Notion
With my recent role as CTO/Advisor with www.analytos.com, during most of my conversation with Analytics leaders within the company, all are concern over security. At a recent conversation with another entrepreneur friend, one of his solution was stalled due to SQL injection issue on the cloud ( a valid concern , but is it valid ?) .
During my recent startup sting, cloud Allergy word was coined, and it did make sense, because allergies do exist and (more...)
Big Data – Tez, MR, Spark Execution Engine : Performance Comparison
There is no question that massive data is being generated in greater volumes than ever before. Along with the traditional data set, new data sources as sensors, application logs, IOT devices, and social networks are adding to data growth. Unlike traditional ETL platforms like Informatica, ODI, DataStage that are largely proprietary commercial products, the majority of Big ETL platforms are powered by open source.
With many execution engines, customers are always curious about their usage (more...)
Map Reduce: File compression and Processing cost
Recently while working with a customer we ran into an interesting situation concerning file compression and processing time. For a system like Hadoop, file compression has been always a good way to save on space, especially when Hadoop replicates the data multiple times.
All Hadoop compression algorithms exhibit a space/time trade-off: faster compression and decompression speeds usually come at the expense of space savings. For more details about how compression is used, see https://documentation.altiscale. (more...)
Accessing HDFS files on local File system using mountableHDFS – FUSE
Hi All
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...)
How to read HDFS fsImage file
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...)
Permissions for both HDFS and local fileSystem paths
Hi All,
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:
Filesystem | Path | User:Group | Permissions |
---|---|---|---|
local | dfs.namenode.name.dir | hdfs:hadoop | drwx—— |
local | dfs.datanode.data.dir | (more...) |