Cluster maintenance, commissioning & decommissioning data nodes.
    Installation and configuration of MapR/Hortonwork Hadoop cluster , Design & develop MapR DR setup, and manage data on MapR/ Hortonwork cluster
    End-to-end performance tuning of MapR clusters and Hadoop Map/Reduce routines against very large data sets, working with MapR cluster along with  MapR-Table(creation, import, export, scan, list)
    Managing & monitoring cluster.

    Performed data balancing on clusters

    Applications PROD Support as roaster and Hadoop Platform Support.

    Working on Name Node high availability customizing zookeeper services.

    Managing quotas to Mapr File System.

    Recovering from node failure and troubleshooting common hadoop cluster issues.

    Responsible for Mapr File system data rebalancing.

    Responsible for performing the backup and Restoration of data from MFS to SAN and Tapes as per Retention Policy.

Responsibilities:
?    Design, develop, and manage data on MapR/Hadoop cluster, Addition of node on MapR cluster End-to-end performance tuning of Hadoop clusters and Hadoop Map/Reduce routines against very large datasets
?    Hands on experience in installing, configuring and using ecosystem components like Hadoop MapReduce, HDFS, MapR-FS HBase, ZooKeeper, Oozie, Hive, Sqoop, Pig, Flume.
?    Monitor Hadoop cluster job performance and capacity planning, manage nodes on Hadoop cluster Installation, Hadoop Administration/development as well as Pig, Hive, HBase, MapR, Flume, Sqoop, implementing bash shell scripts to automate the services and processes on servers.
?    Administration of Linux Servers on Centos, Ubuntu
?    Managing application servers on different zones like Production & Staging.
?    Actively monitoring idle threads, JVM, CPU utilization, connection pools & Troubleshooting.
?    Hadoop cluster connectivity and security, Implement new Hadoop hardware infrastructure
?    HDFS support and

This project involves tracking network fault complaints from the customers. And also to examine information flows formally and informally within a customer complaint handling process, and to identify possible improvement areas to strengthen the network signal.
Data in the MYSQL database is transformed loaded into HDFS. Later this data is analysed using Hive that exposes data in HDFS in a Distributed Query enabled platform. Sqoop is used to extract data from internal