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Agenda & Intervenants
Introduction
Alter Way in 2 slides
Alter Way in 2 slides
Elasticsearch in 1 slide 
• More than 11 million downloads 
• 650,000 New Downloads per Month 
• 1000s of Mission Critical Implementations 
• Top Investors: Benchmark Capital, Index 
Ventures 
• Seasoned Executive Team 
– Founded by Creator of Elasticsearch 
– Seasoned Executives from SpringSource
Les enjeux de la recherche à 
l’ère du BigData
Big Data in Todayʼs Business and Technology 
Environment : some significant figures 
• 2.7 Zetabytes of data exist in the digital universe today. (=1 billion Terabytes) 
• 235 Terabytes of data has been collected by the U.S. Library of Congress in 
April 2011. 
• Facebook stores, accesses, and analyzes 30+ Petabytes of user generated 
data. 
• Akamai analyzes 75 million events per day to better target advertisements. 
• Walmart handles more than 1 million customer transactions every hour, 
which is imported into databases estimated to contain more than 2.5 petabytes 
of data. 
• The largest AT&T database boasts titles including the largest volume of data in 
one unique database (312 terabytes) and the second largest number of rows in 
a unique database (1.9 trillion), which comprises AT&Tʼ’s extensive calling 
records. 
• Hadoop : 
– 94% of Hadoop users perform analytics on large volumes of data not 
possible before 
– 88% analyze data in greater detail; 
– while 82% can now retain more of their data.
The Rapid Growth of Unstructured Data 
• YouTube users upload 48 hours of new video every minute of the 
day. 
• 500+ new websites are created every minute of the day. 
• Brands and organizations on Facebook receive 34,722 Likes every 
minute of the day. 
• 100 terabytes of data uploaded daily to Facebook. 
• According to Twitterʼ’s own research in early 2012, it sees roughly 
175 million tweets every day, and has more than 465 million 
accounts. 
• 30 Billion pieces of content shared on Facebook every month. 
Data production will be 44 times greater in 2020 than it was in 2009.
Big Data & Real Business Issues 
• 25+ % of decision‐makers surveyed predict that data volumes in their 
companies will rise by more than 60% by the end of 2014, with the 
average of all respondents anticipating a growth of no less than 42 %. 
• 40% projected growth in global data generated per year vs. 5% growth in 
global IT spending. 
• According to estimates, the volume of business data worldwide, across all 
companies, doubles every 1.2 years. 
– Poor data can cost businesses 20%–35% of their operating revenue. 
– Bad data or poor data quality costs US businesses $600 billion annually. 
• 75+ % of decision-makers surveyed anticipate significant impacts in the 
domain of storage systems as a result of the “Big Data” phenomenon. 
• We anticipate a new challenge : to be able to Search and Analyse all 
those datas … in real time !
Elasticsearch 
A solution already in production 
with significant french 
implementations 
Revolutionizing Data Search and 
Analytics 
Richard Maurer– SEMEA Territory Manager
Purpose of Elasticsearch 
• Organize data and make it easily accessible 
– Through powerful search and analytics 
– Easily consumable (even for non-data scientists) 
– Elegantly handles extremely large data volumes 
– Delivers results in real time 
• Technology stack agnostic 
• Used across all market verticals
Features of Elasticsearch 
• Structured & unstructured search 
• Advanced analytics capabilities 
• Unmatched performance 
• Real-time results 
• Highly scalable 
• User friendly installation and maintenance
Elasticsearch 1.4: a solution 
production ready 
• Real time data Indexation 
• Distributed 
• High Availability 
• Schema Free 
• Real Time Data Analytics 
• Multi Tenancy 
• Much more….
Unprecedented Uptake 
Elasticsearch has more than11 Million downloads 
… and 650,000 more each month 
Cumulative
French Users
French Use Cases 
Bouygues Telecom: 
Uses Elasticsearch in their Big Data Platform. Cut their web resolution time by 10X 
Daily Motion: 
Indexing their 20 million Videos on Elasticsearch. On production for over 2 years 
Voyages SNCF 
They have recently announced ES has being live on their “Usine Logicielle” 
Fotolia: 
Search Engine made on Elasticsearch, to access 24 Million Images, move over to ES 
Orange: 
With over 1.2 billion docs, looking at better solution and cost reduction
Product Offerings: 
Support Throughout Your Project 
1. Core Elasticsearch Training (2 days) 
2. ELK Workshop (1 day) 
3. Development and Production Support 
4. Marvel, Monitoring of your ES clusters
2: Support
Resources 
• www.elasticsearch.com 
• www.elasticsearch.org 
• User Groups: 
http://www.elasticsearch.org/community/forum/ 
• Contact: 
Richard Maurer 
Territory Manager 
Richard.maurer@elasticsearch.com
MAKE SENSE OF YOUR (BIG) DATA! 
David Pilato 
Technical advocate! 
! 
elasticsearch. 
@dadoonet
StartUp 
data ?
StartUp
StartUp
StartUp
StartUp
StartUp
StartUp 
BIG data ?
StartUp 
BIG data ?
35.000.000.000.000.000 mb 
Source: http://www.csc.com/insights/flxwd/78931-big_data_just_beginning_to_explode 
StartUp
StartUp 
Source: http://www.domo.com/learn/data-never-sleeps-2
StartUp 
search = like % ? 
SELECT ! 
doc.*, country.* ! 
FROM ! 
doc, country! 
WHERE ! 
doc.country_code = country.code AND! 
doc.date_doc > to_date('2011-12', 'yyyy-mm') AND ! 
doc.date_doc < to_date('2012-01', 'yyyy-mm') AND ! 
lower(country.name) = 'france' AND ! 
lower(doc.comment) LIKE ‘%product%' AND 
lower(doc.comment) LIKE ‘%david%';
StartUp 
Search engine ?
elasticsearch ? 
StartUp 
plug & play 
REST/JSON 
scalable 
Apache 2 license 
Lucene 
elasticsearch
Start… 
$ wget https://download.elasticsearch.org/elasticsearch/ 
elasticsearch/elasticsearch-1.1.1.tar.gz! 
$ tar -xf elasticsearch-1.1.1.tar.gz! 
$ ./elasticsearch-1.1.1/bin/elasticsearch! 
[INFO ][node ][Ghost Maker] {1.1.1}[5645]: initializing
… and play! 
$ curl -XPUT localhost:9200/sessions/session/1 -d '{! 
"title" : "Elasticsearch",! 
"subtitle" : "Make sense of your (BIG) data !",! 
"date" : "2014-05-20T10:30:00",! 
"tags" : [ "elasticsearch", "alterway", "bigdata" ],! 
"speakers" : [{! 
"first_name" : "David", ! 
"last_name" : "Pilato" ! 
}]! 
}'
Search! 
$ curl http://localhost:9200/sessions/session/_search -d' 
{ 
"query": { 
"multi_match": { 
"query": "elasticsearch alterway david", 
"fields": [ "title^3", "tags^2", "speakers.first_name" ] 
} 
}, 
"post_filter": { 
"range": { 
"date": { 
"from": "2014-05-01", 
"to": "2014-06" 
} 
} 
} 
}'
StartUp 
Compute?
Compute! 
$ curl http://localhost:9200/sessions/session/_search -d' 
{ 
"query": { ... }, 
"aggs": { 
"by_date": { 
"date_histogram": { 
"field": "date", 
"interval": "day", 
"format" : "dd/MM/yyyy" 
} 
} 
} 
}' 
"by_date": [ 
{ "key_as_string": "03/04/2014", "doc_count": 1 }, 
{ "key_as_string": "12/04/2014", "doc_count": 2 }, 
{ "key_as_string": "16/04/2014", "doc_count": 3 } 
]
Let’s make sense of … 
• logs! 
• twitter! 
• github! 
• marketing data! 
• ...! 
• your data! 
• your big data 
#mstechdays #elasticsearch StartUp
Let’s make sense of … 
• logs! 
• twitter! 
• github! 
• marketing data! 
• ...! 
• your data! 
• your big data 
{ 
"name":"Pilato David", 
"dateOfBirth":"1971-12-26", 
"gender":"male", 
"children":3, 
"marketing":{ 
"fashion":334, 
"music":3363, 
"hifi":2351 
}, 
"address":{ 
"country":"France", 
"city":"Paris", 
"location": [2.332395, 48.861871] 
} 
} 
#mstechdays #elasticsearch StartUp
démo 
MAKE SENSE OF YOUR (BIG) DATA! 
let’s inject some marketing documents… 
#mstechdays #elasticsearch StartUp
elasticsearch. 
elasticsearch 
kibana 
logstash 
Marvel
thanks 
@dadoonet
Comment insérer ElasticSearch 
dans votre Système d’Information 
et en tirer le meilleur parti
ElasticSearch to do What ?
STORE
SEARCH
ANALYZE
Are you ready to use 
ElasticSearch in your IT?
What you need to run it 
• Java 8 update 20 or later, or Java 7 update 55 or 
later 
• Only Oracle’s Java and the OpenJDK are 
supported.
Github projects 
• Many projects 
• Big activity 
• Many languages 
6 mois !
Clients
Scripting Plugins Language
Why it ‘s easy
• One to many 
• ~ Zero conf 
• Cloud oriented 
• Scalability DNA 
• Replication 
• Sharding 
• Distributed 
• Resilience 
• Snapshot 
• Restore 
Start Small Grow Big
• One to many 
• ~ Zero conf 
• Cloud oriented 
• Scalability DNA 
• Replication 
• Sharding 
• Distributed 
• Resilience 
• Snapshot 
• Restore 
Start Small Grow Big
Where / How can you use 
ElasticSearch?
Centralized Log Storage 1/2 
VIA
Centralized Log Storage 2/2
… 
CMS Search Engine
Ecommerce Enhanced Search 
Engine 
• Faceting 
• Fuzzy Search 
• Speed 
• Auto Completion 
• Geo Search 
• Log Analysis
Combining Hadoop & ElasticSearch 
• REST based 
• Memory and I/O efficient 
• Adaptive I/O 
• Map/Reduce API support 
• Pig support 
• Hive support 
 elasticsearch-hadoop
What Else ?
It’s up to you to decide what to build with ES
Analysis / Dasboards 
Some Examples
Kibana examples : IRC Activity
Kibana examples : Pfsense Monitoring
Kibana examples : Windows Events
Kibana examples : Inventory
Kibana examples : Syslog
Kibana examples : Web Activity
ES = No Limits
Conclusion
Conclusion 
• Il est temps de révolutionner la façon dont vous valorisez 
vos données : offrez Elasticsearch à vos applicatifs ! 
• La stack ELK (Elasticsearch, Logstash, Kibana) est déjà 
massivement utilisée en production ! 
• Faites vous accompagner pour bénéficier des bonnes 
pratiques et du support à tous les stades de votre projet : 
conception, développement, production
Questions / Réponses

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Séminaire Big Data Alter Way - Elasticsearch - octobre 2014

  • 1.
  • 4. Alter Way in 2 slides
  • 5. Alter Way in 2 slides
  • 6. Elasticsearch in 1 slide • More than 11 million downloads • 650,000 New Downloads per Month • 1000s of Mission Critical Implementations • Top Investors: Benchmark Capital, Index Ventures • Seasoned Executive Team – Founded by Creator of Elasticsearch – Seasoned Executives from SpringSource
  • 7. Les enjeux de la recherche à l’ère du BigData
  • 8. Big Data in Todayʼs Business and Technology Environment : some significant figures • 2.7 Zetabytes of data exist in the digital universe today. (=1 billion Terabytes) • 235 Terabytes of data has been collected by the U.S. Library of Congress in April 2011. • Facebook stores, accesses, and analyzes 30+ Petabytes of user generated data. • Akamai analyzes 75 million events per day to better target advertisements. • Walmart handles more than 1 million customer transactions every hour, which is imported into databases estimated to contain more than 2.5 petabytes of data. • The largest AT&T database boasts titles including the largest volume of data in one unique database (312 terabytes) and the second largest number of rows in a unique database (1.9 trillion), which comprises AT&Tʼ’s extensive calling records. • Hadoop : – 94% of Hadoop users perform analytics on large volumes of data not possible before – 88% analyze data in greater detail; – while 82% can now retain more of their data.
  • 9. The Rapid Growth of Unstructured Data • YouTube users upload 48 hours of new video every minute of the day. • 500+ new websites are created every minute of the day. • Brands and organizations on Facebook receive 34,722 Likes every minute of the day. • 100 terabytes of data uploaded daily to Facebook. • According to Twitterʼ’s own research in early 2012, it sees roughly 175 million tweets every day, and has more than 465 million accounts. • 30 Billion pieces of content shared on Facebook every month. Data production will be 44 times greater in 2020 than it was in 2009.
  • 10. Big Data & Real Business Issues • 25+ % of decision‐makers surveyed predict that data volumes in their companies will rise by more than 60% by the end of 2014, with the average of all respondents anticipating a growth of no less than 42 %. • 40% projected growth in global data generated per year vs. 5% growth in global IT spending. • According to estimates, the volume of business data worldwide, across all companies, doubles every 1.2 years. – Poor data can cost businesses 20%–35% of their operating revenue. – Bad data or poor data quality costs US businesses $600 billion annually. • 75+ % of decision-makers surveyed anticipate significant impacts in the domain of storage systems as a result of the “Big Data” phenomenon. • We anticipate a new challenge : to be able to Search and Analyse all those datas … in real time !
  • 11. Elasticsearch A solution already in production with significant french implementations Revolutionizing Data Search and Analytics Richard Maurer– SEMEA Territory Manager
  • 12. Purpose of Elasticsearch • Organize data and make it easily accessible – Through powerful search and analytics – Easily consumable (even for non-data scientists) – Elegantly handles extremely large data volumes – Delivers results in real time • Technology stack agnostic • Used across all market verticals
  • 13. Features of Elasticsearch • Structured & unstructured search • Advanced analytics capabilities • Unmatched performance • Real-time results • Highly scalable • User friendly installation and maintenance
  • 14. Elasticsearch 1.4: a solution production ready • Real time data Indexation • Distributed • High Availability • Schema Free • Real Time Data Analytics • Multi Tenancy • Much more….
  • 15. Unprecedented Uptake Elasticsearch has more than11 Million downloads … and 650,000 more each month Cumulative
  • 17. French Use Cases Bouygues Telecom: Uses Elasticsearch in their Big Data Platform. Cut their web resolution time by 10X Daily Motion: Indexing their 20 million Videos on Elasticsearch. On production for over 2 years Voyages SNCF They have recently announced ES has being live on their “Usine Logicielle” Fotolia: Search Engine made on Elasticsearch, to access 24 Million Images, move over to ES Orange: With over 1.2 billion docs, looking at better solution and cost reduction
  • 18. Product Offerings: Support Throughout Your Project 1. Core Elasticsearch Training (2 days) 2. ELK Workshop (1 day) 3. Development and Production Support 4. Marvel, Monitoring of your ES clusters
  • 20. Resources • www.elasticsearch.com • www.elasticsearch.org • User Groups: http://www.elasticsearch.org/community/forum/ • Contact: Richard Maurer Territory Manager Richard.maurer@elasticsearch.com
  • 21. MAKE SENSE OF YOUR (BIG) DATA! David Pilato Technical advocate! ! elasticsearch. @dadoonet
  • 22.
  • 31. 35.000.000.000.000.000 mb Source: http://www.csc.com/insights/flxwd/78931-big_data_just_beginning_to_explode StartUp
  • 33.
  • 34. StartUp search = like % ? SELECT ! doc.*, country.* ! FROM ! doc, country! WHERE ! doc.country_code = country.code AND! doc.date_doc > to_date('2011-12', 'yyyy-mm') AND ! doc.date_doc < to_date('2012-01', 'yyyy-mm') AND ! lower(country.name) = 'france' AND ! lower(doc.comment) LIKE ‘%product%' AND lower(doc.comment) LIKE ‘%david%';
  • 36. elasticsearch ? StartUp plug & play REST/JSON scalable Apache 2 license Lucene elasticsearch
  • 37. Start… $ wget https://download.elasticsearch.org/elasticsearch/ elasticsearch/elasticsearch-1.1.1.tar.gz! $ tar -xf elasticsearch-1.1.1.tar.gz! $ ./elasticsearch-1.1.1/bin/elasticsearch! [INFO ][node ][Ghost Maker] {1.1.1}[5645]: initializing
  • 38. … and play! $ curl -XPUT localhost:9200/sessions/session/1 -d '{! "title" : "Elasticsearch",! "subtitle" : "Make sense of your (BIG) data !",! "date" : "2014-05-20T10:30:00",! "tags" : [ "elasticsearch", "alterway", "bigdata" ],! "speakers" : [{! "first_name" : "David", ! "last_name" : "Pilato" ! }]! }'
  • 39. Search! $ curl http://localhost:9200/sessions/session/_search -d' { "query": { "multi_match": { "query": "elasticsearch alterway david", "fields": [ "title^3", "tags^2", "speakers.first_name" ] } }, "post_filter": { "range": { "date": { "from": "2014-05-01", "to": "2014-06" } } } }'
  • 41. Compute! $ curl http://localhost:9200/sessions/session/_search -d' { "query": { ... }, "aggs": { "by_date": { "date_histogram": { "field": "date", "interval": "day", "format" : "dd/MM/yyyy" } } } }' "by_date": [ { "key_as_string": "03/04/2014", "doc_count": 1 }, { "key_as_string": "12/04/2014", "doc_count": 2 }, { "key_as_string": "16/04/2014", "doc_count": 3 } ]
  • 42.
  • 43. Let’s make sense of … • logs! • twitter! • github! • marketing data! • ...! • your data! • your big data #mstechdays #elasticsearch StartUp
  • 44. Let’s make sense of … • logs! • twitter! • github! • marketing data! • ...! • your data! • your big data { "name":"Pilato David", "dateOfBirth":"1971-12-26", "gender":"male", "children":3, "marketing":{ "fashion":334, "music":3363, "hifi":2351 }, "address":{ "country":"France", "city":"Paris", "location": [2.332395, 48.861871] } } #mstechdays #elasticsearch StartUp
  • 45. démo MAKE SENSE OF YOUR (BIG) DATA! let’s inject some marketing documents… #mstechdays #elasticsearch StartUp
  • 48. Comment insérer ElasticSearch dans votre Système d’Information et en tirer le meilleur parti
  • 50. STORE
  • 53. Are you ready to use ElasticSearch in your IT?
  • 54. What you need to run it • Java 8 update 20 or later, or Java 7 update 55 or later • Only Oracle’s Java and the OpenJDK are supported.
  • 55. Github projects • Many projects • Big activity • Many languages 6 mois !
  • 58. Why it ‘s easy
  • 59. • One to many • ~ Zero conf • Cloud oriented • Scalability DNA • Replication • Sharding • Distributed • Resilience • Snapshot • Restore Start Small Grow Big
  • 60. • One to many • ~ Zero conf • Cloud oriented • Scalability DNA • Replication • Sharding • Distributed • Resilience • Snapshot • Restore Start Small Grow Big
  • 61. Where / How can you use ElasticSearch?
  • 64. … CMS Search Engine
  • 65. Ecommerce Enhanced Search Engine • Faceting • Fuzzy Search • Speed • Auto Completion • Geo Search • Log Analysis
  • 66. Combining Hadoop & ElasticSearch • REST based • Memory and I/O efficient • Adaptive I/O • Map/Reduce API support • Pig support • Hive support  elasticsearch-hadoop
  • 68. It’s up to you to decide what to build with ES
  • 69. Analysis / Dasboards Some Examples
  • 70. Kibana examples : IRC Activity
  • 71. Kibana examples : Pfsense Monitoring
  • 72. Kibana examples : Windows Events
  • 73. Kibana examples : Inventory
  • 75. Kibana examples : Web Activity
  • 76. ES = No Limits
  • 77.
  • 79. Conclusion • Il est temps de révolutionner la façon dont vous valorisez vos données : offrez Elasticsearch à vos applicatifs ! • La stack ELK (Elasticsearch, Logstash, Kibana) est déjà massivement utilisée en production ! • Faites vous accompagner pour bénéficier des bonnes pratiques et du support à tous les stades de votre projet : conception, développement, production