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Big Data – Apache Spark zamena
za Hadoop ili ne?
Darko Marjanović
Founder @Hadoop Srbija
CEO @Things Solver
darko@hadoop-srbija.com
darko@thingsolver.com
Agenda
• Big Data
• Hadoop
• Apache Spark
• Hadoop i/ili Spark
2
Big Data - Šta je to?
• Big Data predstavlja podatke koji pristižu velikom
brzinom i one su količine koja prevazilazu
mogućnosti tradicionalnog softvera za skladištenje,
obradu i upravljanje podacima.
• Big Data je sve ono što ne može da stane u Excel.
3
Big Data - Dimenzije
4
Big Data - Izvori podataka
• Društvene mreže (Twitter, Facebook…)
• Email, HTML, Click Stream
• Slike, Video, Logovi, Senzorski podaci
• Relacione Baze podataka
5
Big Data - Izvori podataka
6http://wikibon.org/wiki/v/Big_Data_in_the_Aviation_Industry
Big Data - Neki primeri
• Google
• Facebook
• …
7
Arhitektura Big Data Aplikacije
10
Hadoop
• Hadoop Common
• HDFS
• MapReduce
• YARN
11
HDFS
12
MapReduce
13
Hadoop ekosistem
• MapReduce (Java, Python, C#…)
• Pig (ETL…)
• Hive, Tajo (Hadoop DWH alat)
• Spark (10x brži MapReduce), Flink
• Storm (Streaming)
• R
• Flume, Sqoop
• …
14
Apache Spark
• Apache Spark je platforma za big data obradu, sa
ugrađenim modulima za mašinsko učenje, SQL,
streaming i graf obradu.
15
Apache Spark - Osnovni
koncepti
• RDD (Resilient Distributed Datasets )
• Kolekcija objekta rasprostranjenih kroz klaster, u RAM-u ili
na disku
• Automatski oporavak
• Praralelizam
• Operacije
• Lazy transformacije (Map, Filter, groupBy…)
• Akcije (count, collect, save…)
16
Apache Spark memorija?
• Obrada u memoriji
• Premeštanje na disk ako podaci ne mogu da stanu u
memoriju
17
Razvoj Spark Aplikacija
• Java, Scala, Python
• Batch, Streaming, Interactive
• Standalone, YARN…
• Izvori podataka (HDFS, Hive, Cassandra, HBase..)
• SparkSQL, Streaming, MLib, GraphX
18
Primer: Senzorski podaci
19
Primer: Hive
20
Flink, Spark konkurencija
21
Hadoop i Spark
• Hadoop HDFS skladište podataka
• Spark VS MapReduce
• Spark na YARN-u
• 2015. Hortonworks ubacio Spark u HDP
22
Da li je potreban Hadoop ako
se koristi Spark?
• Ne ako se koristi u “standalone” modu
• Klaster zahteva neki “shared file system”, ne mora
HDFS
23databricks.com
Hive(MapReduce) vs Spark
test
• Hive = 52.54s
• Spark(Scala) = 4.1s
• Spark(Python) = 26.7s
24
Spark Prednosti
• Problemi koji se rešavaju pomoću više iteracija
• Mašinsko učenje
• Analitika u realnom vremenu
• Brži razvoj jednostavnih aplikacija
25www.techweekeurope.co.uk
Spark VS MapReduce
• Cena
• Količina podataka
• Vreme na tržištu
• Integracija sa ostalim sistemima
26
Spark zamena za Hadoop?
• Hadoop VS Spark
• HDFS VS Spark
• YARN VS Spark
• MapReduce VS Spark ?
• Hadoop i Spark
27
Korisni linkovi
• hadoop-srbija.com
• hortonworks.com
• spark.apache.org
• http://goo.gl/ej5CIJ
• hadoop.apache.org
28
Big Data – Apache Spark zamena
za Hadoop ili ne?
Darko Marjanović
Founder @Hadoop Srbija
CEO @Things Solver
darko@hadoop-srbija.com
darko@thingsolver.com

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Big data apache spark zamena za hadoop ili ne?

  • 1. Big Data – Apache Spark zamena za Hadoop ili ne? Darko Marjanović Founder @Hadoop Srbija CEO @Things Solver darko@hadoop-srbija.com darko@thingsolver.com
  • 2. Agenda • Big Data • Hadoop • Apache Spark • Hadoop i/ili Spark 2
  • 3. Big Data - Šta je to? • Big Data predstavlja podatke koji pristižu velikom brzinom i one su količine koja prevazilazu mogućnosti tradicionalnog softvera za skladištenje, obradu i upravljanje podacima. • Big Data je sve ono što ne može da stane u Excel. 3
  • 4. Big Data - Dimenzije 4
  • 5. Big Data - Izvori podataka • Društvene mreže (Twitter, Facebook…) • Email, HTML, Click Stream • Slike, Video, Logovi, Senzorski podaci • Relacione Baze podataka 5
  • 6. Big Data - Izvori podataka 6http://wikibon.org/wiki/v/Big_Data_in_the_Aviation_Industry
  • 7. Big Data - Neki primeri • Google • Facebook • … 7
  • 8.
  • 9.
  • 10. Arhitektura Big Data Aplikacije 10
  • 11. Hadoop • Hadoop Common • HDFS • MapReduce • YARN 11
  • 14. Hadoop ekosistem • MapReduce (Java, Python, C#…) • Pig (ETL…) • Hive, Tajo (Hadoop DWH alat) • Spark (10x brži MapReduce), Flink • Storm (Streaming) • R • Flume, Sqoop • … 14
  • 15. Apache Spark • Apache Spark je platforma za big data obradu, sa ugrađenim modulima za mašinsko učenje, SQL, streaming i graf obradu. 15
  • 16. Apache Spark - Osnovni koncepti • RDD (Resilient Distributed Datasets ) • Kolekcija objekta rasprostranjenih kroz klaster, u RAM-u ili na disku • Automatski oporavak • Praralelizam • Operacije • Lazy transformacije (Map, Filter, groupBy…) • Akcije (count, collect, save…) 16
  • 17. Apache Spark memorija? • Obrada u memoriji • Premeštanje na disk ako podaci ne mogu da stanu u memoriju 17
  • 18. Razvoj Spark Aplikacija • Java, Scala, Python • Batch, Streaming, Interactive • Standalone, YARN… • Izvori podataka (HDFS, Hive, Cassandra, HBase..) • SparkSQL, Streaming, MLib, GraphX 18
  • 22. Hadoop i Spark • Hadoop HDFS skladište podataka • Spark VS MapReduce • Spark na YARN-u • 2015. Hortonworks ubacio Spark u HDP 22
  • 23. Da li je potreban Hadoop ako se koristi Spark? • Ne ako se koristi u “standalone” modu • Klaster zahteva neki “shared file system”, ne mora HDFS 23databricks.com
  • 24. Hive(MapReduce) vs Spark test • Hive = 52.54s • Spark(Scala) = 4.1s • Spark(Python) = 26.7s 24
  • 25. Spark Prednosti • Problemi koji se rešavaju pomoću više iteracija • Mašinsko učenje • Analitika u realnom vremenu • Brži razvoj jednostavnih aplikacija 25www.techweekeurope.co.uk
  • 26. Spark VS MapReduce • Cena • Količina podataka • Vreme na tržištu • Integracija sa ostalim sistemima 26
  • 27. Spark zamena za Hadoop? • Hadoop VS Spark • HDFS VS Spark • YARN VS Spark • MapReduce VS Spark ? • Hadoop i Spark 27
  • 28. Korisni linkovi • hadoop-srbija.com • hortonworks.com • spark.apache.org • http://goo.gl/ej5CIJ • hadoop.apache.org 28
  • 29. Big Data – Apache Spark zamena za Hadoop ili ne? Darko Marjanović Founder @Hadoop Srbija CEO @Things Solver darko@hadoop-srbija.com darko@thingsolver.com