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CALSCALE:GREGORIAN
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DTSTAMP:20260708T214338Z
UID:84491177-b514-4f15-929c-f21783e41ba2
DTSTART:20191127T070000Z
DTEND:20191128T140000Z
DESCRIPTION:Description\n\n\nData is everywhere and with the rapid growth i
 n data volume that is being used in data analysis tasks\, it gets more and
  more challenging for the user to process it using standard methods. One t
 ypically runs into several problems - low memory or cpu\, waiting forever 
 for a job to complete or starting all over again if a job fails. Enter Spa
 rk\, a high-performance distributed computing framework\, which allows us 
 to tackle big-data problems by distributing the workload across a cluster 
 of machines. Say goodbye to all those painful workloads forever.\n\nThe tw
 o day course addresses the technical architecture and use cases of Spark\,
  writing Spark code using Python\, using Spark's machine learning library 
 to perform ML based tasks. Then\, we would be looking at the methods for r
 unning a spark cluster on CSC's container cloud Rahti\, along with ways to
  manage and fine tune your cluster. The course will also demonstrate how t
 o work with real-time data as well.\n\nThe first day includes the overview
 \, architectural concepts\, programming with Spark's fundamental data stru
 cture (RDD) and Spark's Machine Learning library. The second day focuses o
 n the analysis of data by running SQL queries in Spark\, working with real
 -time data streams and how to setup and manage a spark cluster.\n\nPlease 
 NOTE: This is not a regular programming course\, participants would be exp
 ected to learn emerging concepts in the field of big data / distributed pr
 ocessing\, which might be completely different from the concepts of a gene
 ral programming language.\n\n\nLearning outcome\n\n\nAfter the course the 
 participants should be able to write simple to intermediate programmes in 
 Spark using RDD and dataframes.\n\n\nIntended Audience and Prerequisites\n
 \n\nThe course is intended for researchers\, students\, and professionals 
 with programming skills\, preferably in Python\, as the exercises are in P
 ython. Some knowledge of SQL is also recommended.\n\nIMPORTANT: THIS IS A 
 BEGINNERS COURSE FOR SPARK\n\nIf you are already familiar with it\, please
  have a look at the agenda or email us to know more\, whether the course c
 ontent suits you or not.\n\n\nAgenda\n\nDay 1\, Wednesday 27.11\n\n\n	  
  09.00 – 09.45    Overview and architecture of Spark\n	   09:45 – 
 10.30    Basics of RDDs and Demo\n	   10.30 – 10.45    Coffee br
 eak\n	   10.45 – 11.30    RDD: Transformations and Actions\n	   1
 1.30 – 12.00    Exercises\n	   12.00 – 13.00    Lunch\n	   1
 3.00 – 13.30    Word Count Example\n	   13.30 – 14.00    Exerc
 ises\n	   14.00 – 14.30    Short overview of Machine learning libra
 ry of Spark\n	   14.30 – 14.45    Coffee break\n	   14.45 – 15.
 30    Exercises\n	   15.30 – 15.45    Wrap-up and further topics
 \n	   15.45 – 16.00    Summary of the first day &amp\; exercises wa
 lk-through\n\n\nDay 2\, Thursday\, 28.11\n\n\n	   09.00 – 09.30    S
 park Dataframes and SQL Overview\n	   09:30 – 10.15    Exercises\n	
    10.15 – 10.30    Coffee break\n	   10.30 – 10.45    Datafra
 mes and SQL (contd.)\n	   10.45 – 12.00    Exercises\n	   12.00 
 – 13.00    Lunch\n	   13.00 – 14.00    Setting up a Spark clus
 ter\n	   14.00 – 14.30    Exercises\n	   14.00 – 14.30    Be
 st practices and other useful stuff\n	   14.30 – 14.45    Coffee br
 eak\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-through \n\
 n\n\n\n\nLecturers:  \n\nApurva Nandan (CSC\, lecturer)\, Anni Pyysing (C
 SC\, teaching assistant)\n\nLanguage:   English\nPrice:        
   Free of charge\nhttps://events.prace-ri.eu/event/930/
SUMMARY:Big Data Analysis with Apache Spark @ CSC
URL;VALUE=URI:https://events.prace-ri.eu/event/930/
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