HADOOPONLINE TRAINING IN AMEERPET

  • Email: info@sandsys.net
  • Mobile No: 9573408188
  • Street: mytrivanam, ameerpet,greenhouse bulding
  • City: HYDERABAD
  • State: Andhra Pradesh
  • Zip/Postal Code: 500038
  • Listed: June 23, 2016 3:31 pm
  • Expires: This ad has expired
HADOOPONLINE TRAINING IN AMEERPET
hadoop

Description

Hadoop classroom/online with job oriented best coaching in Sandsys with live projects by Real-Time experts and low fees.
Course Name Hadoop
Demo Classes Morning & Evening In Week Days
Venue Sandsys Technologies
Address
Trainer Having 8+ years of experience

MODE OF TRAINING : NORMAL TRACK FAST TRACK ONLINE
DURAION : 45 DAYS 25 DAYS 30 Days
DAILY SESSION : 1hr 30min 2hr 30min 1hr 30min
LAB SESSION : 7AM – 9PM
HARDCOPY OF MATERIAL AND SOFTWARES
REAL-TIME PROJECT WITH EXPLANATION

100% JOB ASSURANCE

Hadoop COURSE CONTENT

Table of Contents- With Real Time Faculty
1. Basics of Parallel Programming (4 hours)
a. Multi-Threading
b. Open MP (Open Multiprocessing)and MPI (Message Passing Interface)
c. Performance tuning and optimization
i. Matrix Multiplication
ii. Unique word count problem
2. Distributed computing concepts (2 hours)
3. Hadoop Overview (6 hours)
a. Why Hadoop?
b. Brief history of hadoop
c. Architecture of Hadoop
d. Overview of HDFS (Hadoop Distributed File System) and MR (Map Reduce) framework
e. Overview of problems solved by Hadoop
i. Data Mining
ii. Web Mining
iii. Natural Language Processing
iv. K-means clustering
v. Sentimental Analysis
4. Map Reduce Programming Model (8 hours)
a. Details of execution of Map Reduce frame work
b. Word count problem solved using MapReduce programming model.
c. Data Mining on Wikipedia data set.
5. Hadoop ecosystem (2 hours)
6. Hadoop Programming Languages (4 hours)
a. Pig
b. Hadoop Pipes (C++)
c. Hadoop Streaming
d. Hadoop and R
7. Distributed data base concepts (4 hours)
a. RDBMS v/s NoSQL DB
b. Overview of HBase and Cassandra

8. Advance MapReduce Programming (chaining Mapper and Reducer)
9. Case Studies
A. Data Mining on Wikipedia data set using
a. Batch Mode Processing (MR )
b. Using Hive
c. Using HBase and Hive
B. Web Mining using Apache Nutch, Apache Solr and Hadoop
C. Web Log processing using Flume and Hadoop
D. Complex Event processing using Flume, Hadoop and EPL ( Event Processing Language)
E. Integrating Hadoop and RDBMS
Prerequisites:
(1) Hands-on Core java programming / C++/ R/Python
(2) Hands on parallel/multithreaded programming
(3) Query Language (SQL or EPL) (Optional)

Ad Reference ID: 13656c1b35c699ab

 

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