Hadoop

Hadoop

With a large data footprint is generated by Internet, Mobile, IOT world, traditional database systems can't process fast enough the large dataset and generate meaningful value out of it. In addition, security and reliability are the main challenges in handling the big data.

Hadoop provides the ability to store and process large datasets quickly. It's a distributed computing processing model processes bigdata fast. As we add more computing nodes, you get more processing power.

Hadoop as defined by Apache Foundation -

The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly available service on top of a cluster of computers, each of which may be prone to failures.

Hadoop echo system consists of Hadoop common (libraries/modules), Hadoop YARN (cluster management), HDFS (Hadoop Distributed File System) and MapReduce (distributed processing) of Hadoop Ecosystem. HDFS is a foundational storage layer where the data resides with required replica copies for the dataset. HDFS relies upon the resilient master slave architecture with name node, data node and secondary data nodes.

The most popular data access components for Hadoop echo system are Pig and Hive for large data processing and SQL like syntax data access layer respectively. Sqoop and Flame are known for the data integration with external systems. HBASE is a NoSQL database built on HDFS to provide random access capabilities on the large dataset and uses MapReduce for the batch computation.

 

What BDS can help you?

Architect and build a fault tolerance architecture for all the components of Hadoop echo system. As the BDS consists of wide range of data technology experts, it would be easy for us to build and manage any complex Hadoop echo system, and integration with other data storage infrastructure.

Provide the administration activities for overall Hadoop infrastructure including but not limited to deployment, node maintenance and configuration management.

Our support team members are skilled with DevOps tools and processes. All the members are having a strong knowledge on Linux/Unix platform with high degree confidence on the popular Continuous Integration tools such as GitHub, Jenkins, Puppet, Ansible and Nagios.

Our dedicated Hadoop DevOps team provide 24X7 global support model with strict SLAs