Big Data and Hadoop Training in Hyderabad
The Apache Hadoop software library is a framework that allows 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.Big data and Hadoop are the two kinds of the promising technologies that can analyze, curate, and manage the data.
Algorithm Class is one of the best Hadoop Online Training Institutes in Hyderabad and Big Data Online Training Institutes in Hyderabad. Big Data Training in Hyderabad on Hadoop and Big data provides knowledge and technical skills needed to become an efficient developer in Hadoop technology. We teach with live industry based applications.
Algorithm Training Institute is one of the Best Hadoop Training Institutes in Hyderabad. Here the trainers are highly qualified with 15+ years of real-time IT experience. The Big Data Hadoop Training in Hyderabad consists of more programming rather than theory.
Big Data Training in Hyderabad at Algorithm Class Training Institute covers topics from beginner level to advanced level. It is one of the Best Hadoop Training Institutes in Hyderabad.
Finally, by the end of Hadoop Course in Hyderabad, you can be confident with Big Data and Hadoop Tehnology. Due to our trainers, practical sessions, and 1-1 care we are better than Hadoop Training in Hyderabad Gachibowli, Hadoop Training in KPHB, Hadoop Training Institutes in Hderabad KPHB, Big Data Hadoop Training in Kukatpally, Hadoop Training Institutes in Ameerpet, Big Data Training Institutes in Hyderabad
Trainer Details:
Duration: 45hrs
Mode : Online and Class Room
Course Content:
|
SNO |
topic |
|
1 |
Course Introduction |
|
2 |
Introduction to Big Data & Hadoop |
|
3 |
HDFS |
|
4 |
YARN |
|
5 |
Map Reduce |
|
6 |
Scoop |
|
7 |
Introduction to HIVE and Impala |
|
8 |
Working with HIVE |
|
9 |
Working with Impala |
|
10 |
Types of Data Formats |
|
11 |
Advanced HIVE Concepts & Data file partitioning |
|
12 |
Apache Flume |
|
13 |
Hbase |
|
14 |
Pig |
|
15 |
Basics of Apache Spark |
|
16 |
RDD’s in Spark |
|
17 |
Implementing Spark Applications |
|
18 |
Spark Parellel Processing |
|
19 |
RDD Optimization |
|
20 |
Spark Algorithm |
|
21 |
Spark SQL |