Elasticsearch
A presentation at BBL SNCF (Private Event) by David Pilato
Elastic Stack Overview Search. Observe. Protect.
$ curl http://localhost:9200/speaker/_doc/dpilato “nom” : “David Pilato” “jobs” : [ { “boite” : “SRA Europe (SSII)”, “mission” : “bon à tout faire”, “date” : “1995” } { “boite” : “SFR”, “mission” : “touche à tout”, “date” : “1997” } { “boite” : “e-Brands / Vivendi”, “mission” : “chef de projets”, “date”: “2000” } { “boite” : “DGDDI (douane)”, “mission” : “mouton à 5 pattes”, “date” : “2005” } { “boite” : “IDEO Technologies”, “mission” : “CTO”, “date” : “2012” } { “boite” : “elastic”, “mission” : “développeur”, “date” : “2013” } ] “passions” : [ “famille”, “job”, “deejay” ] “blog” : “http://david.pilato.fr/” “twitter” : [ “@dadoonet”, “@elasticfr” ] “email” : “david@pilato.fr } , , , , , , , , , ” , 2 { Who?
The Elastic Stack Reliably and securely take data from any source, in any format, then search, analyze, and visualize it in real time.
FILEBEAT MASTER (3) METRICBEA T PACKETBEAT WINGLOBEAT AUDITBEAT HEARTBEAT CUSTOM UI INGEST (X) Coordinating (X) DATA - HOT (X) FUNCTION BEAT KAFKA ELASTICSEARCH CLIENTS DATA - WARM (X) REDIS DATA STORE SOCIAL 4 WEB APIS SENSORS MESSAGING QUEUE WORKERS (2+) ALERTING (X) MACHINE LEARNING (2+) INSTANCES (X)
Deploy anywhere. Elastic Cloud SaaS Elastic Cloud Enterprise Elastic Cloud on Kubernetes Orchestration
CREATE TABLE use name VARCHAR(100) comments VARCHAR(1000 ) INSERT INSERT french INSERT INSERT INTO user VALUES (‘David Pilato’, ‘Developer at elastic’) INTO user VALUES (‘Malloum Laya’, ‘Worked with David at customs service’) INTO user VALUES (‘David Gageot’, ‘Engineer at Google’) INTO user VALUES (‘David David’, ‘Who is that guy?’); David ; ; ) ; , r 8 ; ( A typical search implementation…
Search on term INSERT INTO user VALUES (‘David Pilato’, ‘Developer at elastic’) Empty set (0,00 sec) David ; 9
Search like INSERT INTO user VALUES (‘David Pilato’, ‘Developer at elastic’) +———————+——————————-| name | comments +———————+——————————-| David Pilato | Developer at elastic | David Gageot | Engineer at Google | David David | Who is that guy? +———————+——————————— David ; + | | | + | + 10
Search for terms INSERT INTO user VALUES (‘David Pilato’, ‘Developer at elastic’) +———————+——————————-| name | comments +———————+——————————-| David Pilato | Developer at elastic +———————+——————————— David Pilato ; + | + | + 11
Search with inverted terms INSERT INTO user VALUES (‘David Pilato’, ‘Developer at elastic’) Empty set (0,00 sec SELECT * FROM user WHERE name LIKE “%Pilato%David%” Empty set (0,00 sec Pilato David ; ; ) ) 12
Search for terms INSERT INTO user VALUES (‘David Pilato’, ‘Developer at elastic’) name LIKE “%Pilato%” +———————+——————————-| name | comments +———————+——————————-| David Pilato | Developer at elastic +———————+——————————— Pilato David ; + | + | + 13
Search in two fields INSERT INTO user VALUES (‘David Pilato’, ‘Developer at elastic’) comments LIKE “%David%” +———————+——————————————————————| name | comments +———————+——————————————————————| David Pilato | Developer at elastic | Malloum Laya | Worked with David at french customs service | David Gageot | Engineer at Google | David David | Who is that guy? +———————+——————————————————————-+ David | | | | + | + ;
14
Search with typos INSERT INTO user VALUES (‘David Pilato’, ‘Developer at elastic’) Empty set (0,00 sec Dadid ; ) 16
Search with typos INSERT INTO user VALUES (‘David Pilato’, ‘Developer at elastic’) name LIKE “%D_did%” OR name LIKE “%Da_id%” OR name LIKE “%Dad_d%” OR name LIKE “%Dadi_%” +———————+——————————-| name | comments +———————+——————————-| David Pilato | Developer at elastic | David Gageot | Engineer at Google | David David | Who is that guy? +———————+———————————+
; | | | + | + 17
User Interface 19
Search engine? Moteur d’indexation de documents Moteur de recherche dans les index 20
Demo time!
3 solutions powered by 1 stack Elastic Enterprise Search Elastic Observability Elastic Security Kibana Elasticsearch Logstash Beats Elastic Stack
Elastic Enterprise Search Workplace Search App Search Site Search
ELASTIC ENTERPRISE SEARCH Search everything, anywhere Easily implement powerful, modern search experiences across your website, app, or digital workplace. Search it all, simply.
Elastic Observability Logs Metrics APM Uptime
ELASTIC OBSERVABILITY Unified visibility across your entire ecosystem Bring your logs, metrics, and traces together into a single stack so you can monitor, detect, and react to events with speed.
Elastic Security Endpoint SIEM
ELASTIC SECURITY Security how it should be: open Elastic Security integrates endpoint security and SIEM to give you prevention, collection, detection, and response capabilities for unified protection across your infrastructure.
Deploy anywhere. Elastic Cloud SaaS Elastic Cloud Enterprise Elastic Cloud on Kubernetes Orchestration
ELASTIC CLOUD Family of SaaS Offerings Easily launch, operate, and scale deployments on AWS, GCP, or Azure with a SaaS experience tailor-made for Elastic products and solutions.
ELASTIC CLOUD ENTERPRISE Centrally manage your Elastic deployments Provision, manage, and monitor Elastic products and solutions, at any scale, on any infrastructure, while managing everything from a single console.
ELASTIC CLOUD ON KUBERNETES Official Operator, and much more Simplify setup, upgrades, snapshots, scaling, high availability, security, and more when running Elastic products and solutions on Kubernetes.
Searching for Rides
Searching for Restaurants
Searching for Love
#ElasticStories
ElasticFR https://community.elastic.co/france @elasticfr discuss.elastic.co
Vous utilisez encore des requêtes SQL pour faire des recherches ? Vos utilisateurs vous reprochent de ne pas pouvoir chercher sur toutes les rubriques ? Votre temps de réponse moyen est supérieur à la demi-seconde avec seulement quelques millions de documents ? Il vous faut 3 jours pour produire des statistiques sur vos données ? Vous rêvez d’offrir une recherche “à la google” sur les données de votre SI ?
Ne cherchez plus ! Cette conférence est faite pour vous.
David présentera au cours du déjeuner pourquoi et comment il est passé de la recherche SQL à Elasticsearch en détaillant les apports de ce moteur par rapport à une solution pure Lucene :
- Pourquoi Elasticsearch ?
- L’indexation
- La recherche
- Les agrégations et le principe de navigation par facettes
- L’analyse de texte et le mapping
- La communauté
Resources
The following resources were mentioned during the presentation or are useful additional information.
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Kibana Demo Script
This is the Kibana script I’m starting from when doing the talk
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A video (in french) on the same topic
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SNCF
