BEGIN:VCALENDAR
VERSION:2.0
PRODID:icalendar-ruby
CALSCALE:GREGORIAN
BEGIN:VEVENT
DTSTAMP:20260707T065437Z
UID:7274429f-793f-4b62-ac37-66fe9b4308e5
DTSTART:20181119T070000Z
DTEND:20181120T140000Z
DESCRIPTION:Description\n\nWith the rapid growth in data volume that is bei
 ng used in data analysis tasks\, it gets more and more challenging for the
  user to process it using standard methods. One typically runs into into s
 everal problems - low memory/cpu\, waiting forever for a job to complete o
 r starting all over again if a job fails. Enter Spark\, a high-performance
  distributed computing framework\, which allows us to tackle big-data prob
 lems by distributing the workload across a cluster of machines. The two da
 y course addresses the technical architecture and use cases of Spark\, wri
 ting Spark code using Python\, using Spark's machine learning library to p
 erform ML based tasks. Then\, we would be looking at the methods for runni
 ng a spark cluster on a cloud based infrastructure\, along with ways to ma
 nage and fine tune your cluster. The course will also demonstrate how to w
 ork with real-time data streams.\n\nThe first day includes the overview\, 
 architectural concepts\, programming with Spark's fundamental data structu
 re (RDD) and Spark's Machine Learning library. The second day focuses on t
 he analysis of data by running SQL queries in Spark\, working with real-ti
 me data streams and how to setup and manage a spark cluster.\n\nLearning o
 utcome\n\nAfter the course the participants should be able to write simple
  to intermediate programmes in Spark using RDD and dataframes. \n\nIntende
 d Audience and Prerequisites\n\nThe course is intended for researchers\, s
 tudents\, and professionals with programming skills\, preferably in Python
 \, as the exercises are in Python. Some knowledge of SQL is also recommend
 ed.\n \n\nPlease NOTE: This is not a regular programming course\, partici
 pants would be expected to learn emerging concepts in the field of big dat
 a / distributed processing\, which might be completely different from the 
 concepts of a general programming language.\n\nAgenda\n\nDay 1\, Monday 19
 .11\n\n   09.00 – 09.45    Overview and architechture of Spark\n	 
   09:45 – 10.30    Basics of RDDs and Demo\n	   10.30 – 10.45 
    Coffee break\n	   10.45 – 11.30    RDD: Transformations and Ac
 tions\n	   11.30 – 12.00    Exercises\n	   12.00 – 13.00    
 Lunch\n	   13.00 – 13.30    Word Count Example\n	   13.30 – 14.
 00    Exercises\n	   14.00 – 14.30    Short overviewof Machine l
 earning library of Spark\n	   14.30 – 14.45    Coffee break\n	   
 14.45 – 15.30    Exercises\n	   15.30 – 15.45    Wrap-up and f
 urther topics\n	   15.45 – 16.00    Summary of the first day &amp\;
  exercises walk-through\nDay 2\, Tuesday\, 20.11\n\n   09.00 – 09.30 
    Spark Dataframes and SQL Overview\n	   09:30 – 10.15    Exercis
 es\n	   10.15 – 10.30    Coffee break\n	   10.30 – 10.45    Da
 taframes and SQL (contd.)\n	   10.45 – 12.00    Exercises\n	   12
 .00 – 13.00    Lunch\n	   13.00 – 14.00    Setting up a Spark 
 cluster\n	   14.00 – 14.30    Exercises\n	   14.00 – 14.30  
   Best practices and other useful stuff\n	   14.30 – 14.45    Coff
 ee break\n	   14.45 – 15.00    Brief overview of Spark Streaming\n	
    15.00 – 15.15    Demo: Processing live twitter stream data\n	 
   15.15 – 16.00    Summary of the course &amp\; exercises walk-throu
 gh \nLecturers:  \n\nApurva Nandan (CSC\, lecturer)\, Juha Hulkkonen (CSC
 \, teaching assistant)\n\nLanguage:   EnglishPrice:          Fr
 ee of charge\n\nhttps://events.prace-ri.eu/event/785/
SUMMARY:Analysing large datasets with Apache Spark @ CSC
URL;VALUE=URI:https://events.prace-ri.eu/event/785/
END:VEVENT
END:VCALENDAR