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Petit dejeuner
13 Mars 2014
Hotel Intercontinental
elasticsearch@alterway.fr
stephane.vincent@alterway.fr
Agenda & Intervenants
Introduction
Alter Way in 2 slides
Alter Way in 2 slides
Elasticsearch in 1 slide
• More than 6 million downloads
• 450,000 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 Todayʼ’s 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 !
Présentation des
fonctionnalités
d’Elasticsearch, Logstash,
Kibana et Marvel
StartUp
search = like % ?
SELECT 	

doc.*, pays.* 	

FROM 	

doc, pays	

WHERE 	

doc.pays_code = pays.code AND	

doc.date_doc > to_date('2011-12', 'yyyy-mm') AND 	

doc.date_doc < to_date('2012-01', 'yyyy-mm') AND 	

lower(pays.libelle) = 'france' AND 	

lower(doc.commentaire) LIKE ‘%produit%' AND
lower(doc.commentaire) LIKE ‘%david%';
StartUp
Moteur de recherche ?
elasticsearch ?
plug & play
REST/JSON
scalable
Apache 2 license
Lucene
elasticsearch
Start…
$ wget https://download.elasticsearch.org/elasticsearch/
elasticsearch/elasticsearch-1.0.0.tar.gz!
$ tar -xf elasticsearch-1.0.0.tar.gz!
$ ./elasticsearch-1.0.0/bin/elasticsearch!
[INFO ][node ][Ghost Maker] {1.0.0}[5645]: initializing
… and play!
$ curl -XPUT localhost:9200/sessions/session/1 -d '{!
"title" : "Elasticsearch",!
"subtitle" : "Make sense of your (BIG) data !",!
"date" : "2014-02-13T16:30:00",!
"tags" : [ "elasticsearch", "elosi", "cloud" ],!
"speaker" : [{!
"first_name" : "David", !
"last_name" : "Pilato" !
}]!
}'
Search!
$ curl -XPOST http://localhost:9200/sessions/session/_search -d'
{
"query": {
"multi_match": {
"query": "elasticsearch elosi david",
"fields": [ "title^2", "speaker.first_name" ]
}
},
"post_filter": {
"range": {
"date": {
"from": "2014-02-13",
"to": "2014-02-14"
}
}
}
}'
StartUp
Compute?
$ curl -XPOST 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": "11/02/2014", "doc_count": 1 },
{ "key_as_string": "12/02/2014", "doc_count": 2 },
{ "key_as_string": "13/02/2014", "doc_count": 3 }
]
Compute!
Let’s make sense of …
• logs	

• twitter	

• github	

• marketing data	

• ...	

• your data	

• your big data
{
"name":"Pilato David",
"dateOfBirth":"1971-12-26",
"gender":"male",
"marketing":{
"fashion":334,
"music":3363,
"hifi":2351
},
"address":{
"country":"France",
"countrycode":"FR",
"city":"Paris"
}
}
Let’s make sense of …
• logs	

• twitter	

• github	

• marketing data	

• ...	

• your data	

• your big data
démo
#mstechdays #elasticsearch StartUp
MAKE SENSE OF YOUR (BIG) DATA!
let’s inject some marketing documents…
ELASTICSEARCH
Elastique ? Distribué ?
StartUp
Distributed indices
node 1
orders
products
1 2
3 4
1 2
$ curl -XPUT localhost:9200/orders -d '{!
"settings.index.number_of_shards" : 4,!
"settings.index.number_of_replicas" : 1!
}'
$ curl -XPUT localhost:9200/products -d '{!
"settings.index.number_of_shards" : 2,!
"settings.index.number_of_replicas" : 0!
}'
StartUp
Distributed indices
node 1
orders
products
1 2
3 4
1 2
node 2
$ ./elasticsearch-1.0.0/bin/elasticsearch!
[INFO ][node ][Armageddon] {1.0.0}[5645]: initializing

[INFO ][cluster.service][Armageddon] detected_master [Ghost Maker]
StartUp
Distributed indices
node 1
orders
products
1
4
1
node 2
orders
products
2
3
2
2
3
1
4
2
3
2
StartUp
node 3
Distributed indices
node 1
orders
products
1
4
1
node 2
orders
products
2
3
2
2
3
1
4
$ ./elasticsearch-1.0.0/bin/elasticsearch!
[INFO ][node ][Karnak] {1.0.0}[5645]: initializing

[INFO ][cluster.service][Karnak] detected_master [Ghost Maker]
StartUp
node 3
products
orders
Distributed indices
node 1
orders
products
1
4
1
node 2
orders
products
2
33
2
2
3
1
4 3
1
4
elasticsearch.
elasticsearch
kibana
logstash
Marvel
Elasticsearch 1.0 : une
solution prête pour la
production !
Revolutionizing Data Search
and Analytics
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
User: GitHub
Searches 20TB of data, 1.3 billion files and 130
lines of code using Elasticsearch
User: Foursquare
Searches 50,000,000 venues every day using
Elasticsearch
User: Fog Creek Software
Searches 40,000,000,000 (40 billion) lines of code
in real-time using Elasticsearch
User: StumbleUpon
Delivers millions of recommendations every day
using Elasticsearch
Example: Email Archiving
Email Archiving of 2 Petabytes of data across 100’s of servers
Big data, structured and unstructured
Example: Support Agents
Custom Support – Search, Facets, and Reports
Real time metrics
What’s new in ES 1.0
• Snapshot & Restore
• Distributed Percolation
• Aggregations
• Much more….
Unprecedented Uptake
Elasticsearch has more than 6 Million downloads
… and 450,000 more each month
Cumulative
Users
User Raves
Chris Cowan @uhduh
I’m in love with @elasticsearch! I want to use it for everything right now!
Alain Richardt @alaincxs
Moving ffrom #solr to # Elasticsearch is like upgrading from a Reliant Robin to a McLaren
F1
Pete Connolly @peteconnolly
Two really useful and productive days of training from @kimchy and @uboness all
about #elasticsearch. Best training course in years
Cyril Lacôte @clacote
#ElasticSearch is the s*&t. Amazingly simple and powerful. Open source is awesome.
That's made my day.
Logan Lowell @fractaloop
Tweaking @elasticsearch for huge indexes can be fun. I'm very glad the IRC channel is
so helpful too.
Product Offerings:
Support Throughout Your Project
1. Core Elasticsearch Training
2. Development and Production Support
1: Training
Core Elasticsearch Training
• Two day classroom training
• Delivered by Elasticsearch developers
1. Worldwide Public Courses
2. Onsite Training Course
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
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?
Github projects
• Many
project
s
• Great
activity
• Many
langua
ges
Clients
Scripting Plugins Language
Why it ‘s easy
• One to
many
• Zero
conf
• Cloud
oriente
d
• Scalab
Start Small Grow Big
Where / How can you use
ElasticSearch?
VIA
Centralized Log Storage (eg.)
…
CMS Search Engine
• Faceting
• Fuzzy Search
• Speed
• Auto Completion
• Geo Search
• Log Analysis
Ecommerce Enhanced Search
Engine
• REST based
• Memory and I/O efficient
• Adaptive I/O
• Map/Reduce API support
• Pig support
• Hive support
• = elasticsearch-hadoop
Combining Hadoop & ElasticSearch
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
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) en
version 1.0 est prête pour la 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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Elasticsearch : petit déjeuner du 13 mars 2014

  • 1. Petit dejeuner 13 Mars 2014 Hotel Intercontinental elasticsearch@alterway.fr stephane.vincent@alterway.fr
  • 4. Alter Way in 2 slides
  • 5. Alter Way in 2 slides
  • 6. Elasticsearch in 1 slide • More than 6 million downloads • 450,000 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 Todayʼ’s 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 !
  • 12. StartUp search = like % ? SELECT doc.*, pays.* FROM doc, pays WHERE doc.pays_code = pays.code AND doc.date_doc > to_date('2011-12', 'yyyy-mm') AND doc.date_doc < to_date('2012-01', 'yyyy-mm') AND lower(pays.libelle) = 'france' AND lower(doc.commentaire) LIKE ‘%produit%' AND lower(doc.commentaire) LIKE ‘%david%';
  • 14. elasticsearch ? plug & play REST/JSON scalable Apache 2 license Lucene elasticsearch
  • 15. Start… $ wget https://download.elasticsearch.org/elasticsearch/ elasticsearch/elasticsearch-1.0.0.tar.gz! $ tar -xf elasticsearch-1.0.0.tar.gz! $ ./elasticsearch-1.0.0/bin/elasticsearch! [INFO ][node ][Ghost Maker] {1.0.0}[5645]: initializing
  • 16. … and play! $ curl -XPUT localhost:9200/sessions/session/1 -d '{! "title" : "Elasticsearch",! "subtitle" : "Make sense of your (BIG) data !",! "date" : "2014-02-13T16:30:00",! "tags" : [ "elasticsearch", "elosi", "cloud" ],! "speaker" : [{! "first_name" : "David", ! "last_name" : "Pilato" ! }]! }'
  • 17. Search! $ curl -XPOST http://localhost:9200/sessions/session/_search -d' { "query": { "multi_match": { "query": "elasticsearch elosi david", "fields": [ "title^2", "speaker.first_name" ] } }, "post_filter": { "range": { "date": { "from": "2014-02-13", "to": "2014-02-14" } } } }'
  • 19. $ curl -XPOST 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": "11/02/2014", "doc_count": 1 }, { "key_as_string": "12/02/2014", "doc_count": 2 }, { "key_as_string": "13/02/2014", "doc_count": 3 } ] Compute!
  • 20. Let’s make sense of … • logs • twitter • github • marketing data • ... • your data • your big data
  • 22. démo #mstechdays #elasticsearch StartUp MAKE SENSE OF YOUR (BIG) DATA! let’s inject some marketing documents…
  • 24. StartUp Distributed indices node 1 orders products 1 2 3 4 1 2 $ curl -XPUT localhost:9200/orders -d '{! "settings.index.number_of_shards" : 4,! "settings.index.number_of_replicas" : 1! }' $ curl -XPUT localhost:9200/products -d '{! "settings.index.number_of_shards" : 2,! "settings.index.number_of_replicas" : 0! }'
  • 25. StartUp Distributed indices node 1 orders products 1 2 3 4 1 2 node 2 $ ./elasticsearch-1.0.0/bin/elasticsearch! [INFO ][node ][Armageddon] {1.0.0}[5645]: initializing
 [INFO ][cluster.service][Armageddon] detected_master [Ghost Maker]
  • 26. StartUp Distributed indices node 1 orders products 1 4 1 node 2 orders products 2 3 2 2 3 1 4 2 3 2
  • 27. StartUp node 3 Distributed indices node 1 orders products 1 4 1 node 2 orders products 2 3 2 2 3 1 4 $ ./elasticsearch-1.0.0/bin/elasticsearch! [INFO ][node ][Karnak] {1.0.0}[5645]: initializing
 [INFO ][cluster.service][Karnak] detected_master [Ghost Maker]
  • 28. StartUp node 3 products orders Distributed indices node 1 orders products 1 4 1 node 2 orders products 2 33 2 2 3 1 4 3 1 4
  • 30. Elasticsearch 1.0 : une solution prête pour la production ! Revolutionizing Data Search and Analytics
  • 31. 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
  • 32. Features of Elasticsearch • Structured & unstructured search • Advanced analytics capabilities • Unmatched performance • Real-time results • Highly scalable • User friendly installation and maintenance
  • 33. User: GitHub Searches 20TB of data, 1.3 billion files and 130 lines of code using Elasticsearch
  • 34. User: Foursquare Searches 50,000,000 venues every day using Elasticsearch
  • 35. User: Fog Creek Software Searches 40,000,000,000 (40 billion) lines of code in real-time using Elasticsearch
  • 36. User: StumbleUpon Delivers millions of recommendations every day using Elasticsearch
  • 37. Example: Email Archiving Email Archiving of 2 Petabytes of data across 100’s of servers Big data, structured and unstructured
  • 38. Example: Support Agents Custom Support – Search, Facets, and Reports Real time metrics
  • 39. What’s new in ES 1.0 • Snapshot & Restore • Distributed Percolation • Aggregations • Much more….
  • 40. Unprecedented Uptake Elasticsearch has more than 6 Million downloads … and 450,000 more each month Cumulative
  • 41. Users
  • 42. User Raves Chris Cowan @uhduh I’m in love with @elasticsearch! I want to use it for everything right now! Alain Richardt @alaincxs Moving ffrom #solr to # Elasticsearch is like upgrading from a Reliant Robin to a McLaren F1 Pete Connolly @peteconnolly Two really useful and productive days of training from @kimchy and @uboness all about #elasticsearch. Best training course in years Cyril Lacôte @clacote #ElasticSearch is the s*&t. Amazingly simple and powerful. Open source is awesome. That's made my day. Logan Lowell @fractaloop Tweaking @elasticsearch for huge indexes can be fun. I'm very glad the IRC channel is so helpful too.
  • 43. Product Offerings: Support Throughout Your Project 1. Core Elasticsearch Training 2. Development and Production Support
  • 44. 1: Training Core Elasticsearch Training • Two day classroom training • Delivered by Elasticsearch developers 1. Worldwide Public Courses 2. Onsite Training Course
  • 46. Resources • www.elasticsearch.com • www.elasticsearch.org • User Groups: http://www.elasticsearch.org/community/forum/ • Contact: Richard Maurer Territory Manager Richard.maurer@elasticsearch.com
  • 47. Comment insérer Elasticsearch dans votre système d’information et en tirer le meilleur parti !
  • 49. STORE
  • 52. Are you ready to use ElasticSearch in your IT?
  • 53. Github projects • Many project s • Great activity • Many langua ges
  • 56. Why it ‘s easy
  • 57. • One to many • Zero conf • Cloud oriente d • Scalab Start Small Grow Big
  • 58. Where / How can you use ElasticSearch?
  • 61. • Faceting • Fuzzy Search • Speed • Auto Completion • Geo Search • Log Analysis Ecommerce Enhanced Search Engine
  • 62. • REST based • Memory and I/O efficient • Adaptive I/O • Map/Reduce API support • Pig support • Hive support • = elasticsearch-hadoop Combining Hadoop & ElasticSearch
  • 63. It’s up to you to decide what to build with ES
  • 65. Kibana examples : IRC Activity
  • 66. Kibana examples : Pfsense Monitoring
  • 67. Kibana examples : Windows Events
  • 68. Kibana examples : Inventory
  • 70. ES = No Limits
  • 72. Conclusion • Il est temps de révolutionner la façon dont vous valorisez vos données : offrez Elasticsearch à vos applicatifs ! • La stack ELK (Elasticsearch, Logstash, Kibana) en version 1.0 est prête pour la production ! • Faites vous accompagner pour bénéficier des bonnes pratiques et du support à tous les stades de votre projet : conception, développement, production