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Tunis big data_meetup__21_nov2015__aymenzaafouri

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LEK stack: Logstash, ElasticSearch, Kibana

Published in: Data & Analytics
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Tunis big data_meetup__21_nov2015__aymenzaafouri

  1. 1. @AymenZaafouri Tunis Big Data Meetup 21/11/2015 – Cogite Coworking Space 1 LEK stack : Logstash, ElasticSearch, Kibana Tunis Big Data Meetup
  2. 2. Aymen ZAAFOURI Ingénieur en statistique et analyse de l’information Promotion 2014 Mastère spécialisé « Informatique décisionnelle » Promotion 2015 Data Scientist 2Tunis Big Data Meetup
  3. 3. • Logstash • ElasticSearch • Kibana • ES - Hadoop • Autres produits Tunis Big Data Meetup 3
  4. 4. Logstash collecte, analyse et stockage de logs. Tunis Big Data Meetup 4
  5. 5. Log ? Tunis Big Data Meetup 5 Log = Timestamp + Données
  6. 6. Input Filter Output Logstash o Version 2.0 o Il est développé en Java, sous licence Apache 2.0. o Input: Syslog, IMAP, SGBD, IRC ,Twitter,… o Filter: Standardisation des dates, Suppression des événements, … o Output: ElasticSearch, MangoDB, Redis, … Tunis Big Data Meetup 6
  7. 7. Logstash + Twitter = ? Tunis Big Data Meetup 7
  8. 8. ElasticSearch Moteur de recherche Tunis Big Data Meetup 8
  9. 9. o 17 000 Commits (32 000 pour LEK) o 35 000 000 Téléchargements o 120 User groups dans 80 villes o ElasticSearch est utilisé en production par: o Wikipedia o NASA o Mozilla (300 millions d’événements par jour) o Verizon ( 500 billion de documents) Tunis Big Data Meetup 9
  10. 10. o Moteur de recherche: – Moteur d’indexation de document – Moteur de recherche sur les index o Limites de la recherche SQL (% - Like): – Pas de tolérance aux « Fotes » de frappe – Performances désastreuses sur des millions de ligne Tunis Big Data Meetup 10
  11. 11. Mots-clés o Le mapping: l’équivalent du schéma dans une base de données relationnelle. o Un index: Un peu comme une base de données sur un SGBD relationnel. o Les types: l’équivalent des tables dans un système relationnel. o Les documents: comme les lignes dans une base de données relationnelle. Les documents sont stockés au format JSON et ont un index, un type et un id en plus des données. Tunis Big Data Meetup 11
  12. 12. Points forts o Simple mise en place. o Rapide : Les recherches sont traitées en quasi temps réel grâce à la parallélisation des traitements. o Scalable : peut être distribué et plusieurs instances (nodes) peuvent communiquer entre-elles dans un même cluster. o Efficace : L’utilisation des bases NoSQL documentaires. Les données sont automatiquement répliquées. o Accessible : API REST Tunis Big Data Meetup 12
  13. 13. Sense Tunis Big Data Meetup 13
  14. 14. Sense Tunis Big Data Meetup 14
  15. 15. Kibana Outil de visualisation Tunis Big Data Meetup 15
  16. 16. Kibana • Kibana est une interface web permettant de rechercher des infos stockées dans ElasticSearch Tunis Big Data Meetup 16 Indexation Requête Résultats
  17. 17. Kibana Tunis Big Data Meetup 17
  18. 18. Kibana Tunis Big Data Meetup 18
  19. 19. ES for Hadoop Tunis Big Data Meetup 19
  20. 20. ES for Hadoop Tunis Big Data Meetup 20 o On peut accéder à Elasticsearch comme si les données existent sur HDFS. o Les jobs sont exécutés sur les mêmes machines que les shards Elasticsearch, ce qui permet d’éliminer le trafic réseau et d’avoir une meilleure performance, grâce à la proximité des données.
  21. 21. Autres produits Tunis Big Data Meetup 21
  22. 22. Tunis Big Data Meetup 22
  23. 23. Merci pour votre attention 23Tunis Big Data Meetup
  24. 24. Restons en contact ! 24 @AymenZaafouri aymenzaafouri aymen@zaafouri.fr Tunis Big Data Meetup

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