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Hadoop training Kudlu Bangalore, apache hadoop bigdata training institutes Kudlu Bangalore

List of Best Hadoop training Kudlu Bangalore, apache hadoop training institutes Kudlu Bangalore, hadoop big data training Kudlu Bangalore with address, Phone numbers, course fee, student reviews and training course learning at Kudlu area in Bangalore City. As of June 23, 2018, We have total of 2 Hadoop training institutes in and around also near to Kudlu in Bangalore.

 

 

training institutes Systems Domain - Head Office
Bangalore - Jaya Nagar

 

Best Institute

 

Systems Domain - Head Office at Jaya Nagar - theory class	 photo_2887 Systems Domain - Head Office at Jaya Nagar - computer lab	 photo_2889 Systems Domain - Head Office at Jaya Nagar - center entrance	 photo_2888 
Address: Head Office, Jayanagar 3rd block, Lucky paradise building, 4th floor, Jaya Nagar, Bangalore-560011 google map of 8726
Established in the year 1997, System Domain is headquartered in Bangalore and has more than twelve training institutes located across India. Awarded an ISO 9001 in 2008 Systems Domain - Head Office provides placement Hadoop training in Kudlu , Hive, Apache Mahout, Apache HBase, Bigdata Hadoop, Apache Hadoop training classes at Jaya Nagar.
 
training institutes Amstar Technologies Pvt Lts
Bangalore - Kudlu
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training institute
Address: Ground Floor, A.M. Building, 7th Mile, A.M. Industrial Estate, Garvebhavipalaya, Kudlu Bangalore-560068
Amstar Technologies Pvt Lts provides placement Hadoop training in Kudlu , Bigdata Hadoop, Apache Hadoop training classes at Kudlu.
 
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Hadoop related Training courses in kudlu

 

 

 

 

 

 

 

 

Hadoop course Content / syllabus at kudlu, bangalore.

We gathered most widely used Hadoop course content used by training institutes in kudlu,bangalore. The Hadoop course syllabus covers basic to advanced level and it may vary based on Hadoop training classes offered in kudlu.

 

1 Introduction to Hadoop administration
1.1 HDFS design
1.2 HA Name node
1.3 Map reduce design
1.4 HAdoop daemons

2 Hadoop design consideration
2.1 Distributions &
2.2 versions
2.3 Planning
2.4 Hadoop in the cloud

3 Monitoring
3.1 Nagios
3.2 Gangila
3.3 JMX
3.4 logging
3.5 Clustering

4 Backup
4.1 Storage
4.2 Backup vs Disaster
4.3 recovery
4.4 Best practices

5 Optimization
5.1 Bottleneck
5.2 Preformance
5.3 File System
5.4 Worker Node
5.5 Networking
5.6 Comparisson

6 Troubleshooting
6.1 Data Node
6.2 Task Tracker
6.3 Job Tracker
6.4 Name Node

7 Security
7.1 Multi tenancy
7.2 Authentication &
7.3 Autherization
7.4 Kerberos
7.5 Security step by step

 

 

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