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Big data in practice using Hadoop

Nowadays everybody seems to be working with "big data". Do you also want to interrogate your several data sources (click streams, social media, relational data, sensor data, ...) and are you experiencing the shortcomings of traditional data tools? Maybe you are in need of distributed data stores like HDFS and a MapReduce infrastructure like Hadoop's.

This course builds on the concepts which are set forth in the Big data concepts course. you will get hands-on practice on linux with Apache Hadoop: HDFS, Yarn, Pig, and Hive. You learn how to implement robust data processing with an SQL-style interface which generates MapReduce jobs. You also learn to work with the graphical tools which allow for easy follow-up of the jobs and the workflows on the distributed Hadoop cluster.

After successful completion of the course, you will have sufficient basic expertise to set up a Hadoop cluster, to import data into HDFS, and to interrogate it clevery using MapReduce.

When you want to use Hadoop with Spark, you are referred to the course Big data in practice using Spark.

Schedule

datedur.lang.  location  price
09 Nov2NWoerden  (NL)1000 EUR  (exempt from VAT) 
20 Nov2?Leuven  (BE)1000 EUR  (excl. VAT) 
SESSION INFO AND ENROLMENT

Intended for

Whoever wants to start practising "big data": developers, data architects, and anyone who needs to work with big data technology.

Background

Familiarity with the concepts of data stores and more specifically of "big data" is necessary; see our course Big data concepts. Additionally, minimal knowledge of SQL, UNIX and Java are useful. Experience with a programming language (Java, PHP, Python, Perl, C++ or C#) is a must.

Main topics

Training method

Classroom instruction, with practical examples and supported by extensive practical exercises.

Duration

2 days.

Course leader

Peter Vanroose.

Global score

   
4.1/5 (based on 29 evaluations)

Reviews

     
Goed om een overzicht te krijgen (, )
     
Prima cursus, goede basis voor het opzetten hadoop kennis (, )
     
Wel ok, ik denk dat de algemene uitleg veel sneller kan. Soms veel focus op details die voor mij bijna irrelevant lijken. Kan ook aan mij liggen. (, )
     
Happy with the training even if I would spend less time on HDFS and MapReduce and more time in others components (Pig, Hive,...) (, )
     
Goede introductie (, )
     
Ik vond dit een zeer goede cursus. (, )
     
Een dag langer? (, )
     
Interessante kennismaking. Voor mij soms te veel theorie (, )
     
De meeste belangrijke punten zijn behandeld in de cursus. (, )
     
Zeer goede introductie (, )

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SESSION INFO AND ENROLMENT