Quand la gestion des données de nos applications web dépasse la simple persistance dans une base de données relationnelle (type SGBD), l’utilisation de technologies alternatives dites « NoSql » est nécessaire. Nous aborderons les 4 grandes familles de NoSql (Key/Value, Document, Column-oriented et Graph) ainsi que leur intégration dans des applications PHP.
This XML Prague 2015 Pre-conference presentations shows practical usage of linked data sources. These sources can help to: enrich content with entities, add link to external data sources, use the enriched content in question answering, machine translation or other scenarios. The aim is to show the practical application of linked data sources in XML tooling. The presentation is an update and provides outcomes of the related session held at XML Prague 2014.
This XML Prague 2015 Pre-conference presentations shows practical usage of linked data sources. These sources can help to: enrich content with entities, add link to external data sources, use the enriched content in question answering, machine translation or other scenarios. The aim is to show the practical application of linked data sources in XML tooling. The presentation is an update and provides outcomes of the related session held at XML Prague 2014.
CouchBase Lite is a native NoSQL database for Android (mobile) that enables JSON data and document storage, replication and conflict management. We will show you how we use it to get our data updated, distributed and in the format that suits us best.
Presto, an open source distributed SQL engine originally built at Facebook, has a rapidly growing community of developers and users. In this talk, speakers from both Facebook and Teradata, will discuss technical details of some of the recent developments such as integration with Hadoop ecosystem (YARN/Slider and Ambari), security features (Kerberos), enabling BI tools via JDBC/ODBC drivers, new connectors (Redis, MongoDB) and storage engines (Raptor) as well as improvements in performance and ANSI SQL coverage. In addition, we will present a few use cases and major new users that leverage interactive SQL capabilities Presto offers. Finally, we will present our roadmap for the next year.
See the video at https://youtu.be/wMy3LXuTb0U
On-Demand RDF Graph Databases in the CloudMarin Dimitrov
slides from the S4 webinar "On-Demand RDF Graph Databases in the Cloud"
RDF database-as-a-service running on the Self-Service Semantic Suite (S4) platform: http://s4.ontotext.com
video recording of the talk is available at http://info.ontotext.com/on-demand-rdf-graph-database
BDM8 - Near-realtime Big Data Analytics using ImpalaDavid Lauzon
Quick overview of all informations I've gathered on Cloudera Impala. It describes use cases for Impala and what not to use Impala for. Presented at Big Data Montreal #8 at RPM Startup Center.
People like graphs. In nowadays they use facebook social graph search to find ex-girlfriend/boyfriends of their sweet hearts, or to search for a new love. Moreover - companies use graphs to evaluate the internal communication effectiveness or to design the enterprise network scheme. In all those tasks the simple questions arise - what type of data storage should be used to solve the problem in the most effective and easy? Graph databases!
BDM9 - Comparison of Oracle RDBMS and Cloudera Impala for a hospital use caseDavid Lauzon
High-level use case description of one department of a hospital, and comparisons of two solutions : 1) Big data solution using Cloudera Impala; and 2) Traditional RDBMS solution using Oracle DB.
CouchBase Lite is a native NoSQL database for Android (mobile) that enables JSON data and document storage, replication and conflict management. We will show you how we use it to get our data updated, distributed and in the format that suits us best.
Presto, an open source distributed SQL engine originally built at Facebook, has a rapidly growing community of developers and users. In this talk, speakers from both Facebook and Teradata, will discuss technical details of some of the recent developments such as integration with Hadoop ecosystem (YARN/Slider and Ambari), security features (Kerberos), enabling BI tools via JDBC/ODBC drivers, new connectors (Redis, MongoDB) and storage engines (Raptor) as well as improvements in performance and ANSI SQL coverage. In addition, we will present a few use cases and major new users that leverage interactive SQL capabilities Presto offers. Finally, we will present our roadmap for the next year.
See the video at https://youtu.be/wMy3LXuTb0U
On-Demand RDF Graph Databases in the CloudMarin Dimitrov
slides from the S4 webinar "On-Demand RDF Graph Databases in the Cloud"
RDF database-as-a-service running on the Self-Service Semantic Suite (S4) platform: http://s4.ontotext.com
video recording of the talk is available at http://info.ontotext.com/on-demand-rdf-graph-database
BDM8 - Near-realtime Big Data Analytics using ImpalaDavid Lauzon
Quick overview of all informations I've gathered on Cloudera Impala. It describes use cases for Impala and what not to use Impala for. Presented at Big Data Montreal #8 at RPM Startup Center.
People like graphs. In nowadays they use facebook social graph search to find ex-girlfriend/boyfriends of their sweet hearts, or to search for a new love. Moreover - companies use graphs to evaluate the internal communication effectiveness or to design the enterprise network scheme. In all those tasks the simple questions arise - what type of data storage should be used to solve the problem in the most effective and easy? Graph databases!
BDM9 - Comparison of Oracle RDBMS and Cloudera Impala for a hospital use caseDavid Lauzon
High-level use case description of one department of a hospital, and comparisons of two solutions : 1) Big data solution using Cloudera Impala; and 2) Traditional RDBMS solution using Oracle DB.
This is an introduction to relational and non-relational databases and how their performance affects scaling a web application.
This is a recording of a guest Lecture I gave at the University of Texas school of Information.
In this talk I address the technologies and tools Gowalla (gowalla.com) uses including memcache, redis and cassandra.
Find more on my blog:
http://schneems.com
Slides from my talk at ACCU2011 in Oxford on 16th April 2011. A whirlwind tour of the non-relational database families, with a little more detail on Redis, MongoDB, Neo4j and HBase.
The past few years have seen an enormous growth in the popularity of graph databases, but what exactly is a graph database and how can I use one to gain deeper insights from my data?
In this session we will introduce JanusGraph, a highly scalable, transactional graph database with flexible backend storage options such as Apache HBase, Apache Cassandra, and Oracle Berkeley DB. We will begin with a brief introduction to graph databases and data models, common use cases, and the benefits of a relationship centric approach to analytics. We will follow with a more technical dive into the features and deployment options of JanusGraph, including accessing the graph with the Apache Tinkerpop API stack, manipulating it with the Blueprints API, and querying the graph with the Gremlin query language. Finally, we will look at how JanusGraph integrates with other technologies like Apache Spark as part of an overall analytics architecture.
Webinar: Enterprise Data Management in the Era of MongoDB and Data LakesMongoDB
With so much talk of how Big Data is revolutionizing the world and how a data lake with Hadoop and/or Spark will solve all your data problems, it is hard to tell what is hype, reality, or somewhere in-between.
In working with dozens of enterprises in varying stages of their enterprise data management (EDM) strategy, MongoDB enterprise architect, Matt Kalan, sees the same challenges and misunderstandings arise again and again.
In this session, he will explain common challenges in data management, what capabilities are necessary, and what the future state of architecture looks like. MongoDB is uniquely capable of filling common gaps in the data lake strategy.
This session also includes a live Q&A portion during which you are encouraged to ask questions of our team.
The presentation begins with an overview of the growth of non-structured data and the benefits NoSQL products provide. It then provides an evaluation of the more popular NoSQL products on the market including MongoDB, Cassandra, Neo4J, and Redis. With NoSQL architectures becoming an increasingly appealing database management option for many organizations, this presentation will help you effectively evaluate the most popular NoSQL offerings and determine which one best meets your business needs.
Similar to Ciel, mes données ne sont plus relationnelles (20)
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
3. 3
Association Française des Utilisateurs de PHP
• Crée en 2001
• Forum PHP ( 21 & 22 Novembre 2013 à Paris)
• AperoPHP et Rendez Vous
• Antennes Locale
• Président en 2009 www.afup.org
Association Francophone des utilisateurs de SYmfony
• Initié en 2010 par Hugo Hamon
• Pas encore une vraie association
• Sfpot mensuel avec conférence suivie d’un apéro
• Antenne à Marseille, Lyon ??
www.afsy.fr
4. 4
Elao
• Fondateur en 2005
• Lyon & Paris
• Agence Web Technique de 15 personnes
• Symfony depuis 2006
• Partenaire officiel SensioLabs
www.elao.com
10. Data Size
• 500 million page views a day
• ~3TB of new data to store a day
• Posts are about 50GB a day.
Follower list updates are about
2.7TB a day.
10
12. Uniformity
• Semi-‐structured
data
• Different
data
lifecycle
• Store
more
data
about
each
en7ty
• Individualisa7on
&
decentraliza7on
of
content
genera7on
12
16. Column 1 : value
Column 2 : value
Column 3 : value
Key
Key
Key/Value Column-oriented
Field 1 : value
Field A : value
Field B : value
Field 2 : value
Node 1
Node 3
Node 2
Node 4
Node 5
Document
oriented
Graph
Key Value
Key Value
Key Value
Key Value
16
17. Column 1 : value
Column 2 : value
Column 3 : value
Key
Key
Key/Value Column-oriented
Field 1 : value
Field A : value
Field B : value
Field 2 : value
Node 1
Node 3
Node 2
Node 4
Node 5
Document
oriented
Graph
Key Value
Key Value
Key Value
Key Value
17
18. Key-value databases
• Inspired by Amazon’s Dynamo (2007)
• Global collection of key-value
• Big scalable HashMap
18
19. • Strengths
• Simple data model
• High performance
• Great at scaling out horizontally
• Weaknesses
• Simplistic data model
• Poor for complex data
19
Key-value databases
20. • Written in C - BSD License - 2009
• Very fast and light-weigth
• All data in memory
• Persistence
• Master/Slave Replication
• Used for caching, session or working
queue
20
Key-value databases
http://redis.io/
22. Column 1 : value
Column 2 : value
Column 3 : value
Key
Key
Key/Value Column-oriented
Field 1 : value
Field A : value
Field B : value
Field 2 : value
Node 1
Node 3
Node 2
Node 4
Node 5
Document
oriented
Graph
Key Value
Key Value
Key Value
Key Value
22
23. Document databases
• Inspired by IBM Lotus Notes/Domino
• Idem from Key/Value with value as a
document
• A document is a key-value collection
• Flexible schema
• Non-relational, data is de-normalized
23
24. Document databases
• Strengths
• Simple, powerful data model
• Good scaling, Easy/Auto sharding
• Usually “ACID” compliant
• Weaknesses
• Unsuited for interconnected data
• Query model limited to keys (and indexes)
24
25. Document databases
• Written in C++ - License AGPL - 2009
• JSON-style documents
• Full Index Support
• Fast In-Place Updates
• Auto-Sharding
• Replication & High Availability
• A lot of Connector
• Big Community
• Commercial Support
25
http://www.mongodb.org
26. Document databases
• Lotus Notes / Domino
• CouchDB
written in Erlang, Javascript for Query
• OrientDB
written in Java, relationship as graph
26
27. Column 1 : value
Column 2 : value
Column 3 : value
Key
Key
Key/Value Column-oriented
Field 1 : value
Field A : value
Field B : value
Field 2 : value
Node 1
Node 3
Node 2
Node 4
Node 5
Document
oriented
Graph
Key Value
Key Value
Key Value
Key Value
27
28. Graph databases
• Nodes with properties
• Named relationships with properties
• Focus on the data structure
• Direct pointer to its adjacent element and
no indexlookups are necessary
28
29. Graph databases
• Strengths
• Powerful data model
• Fast for connected data
• A new data architecture
• Weaknesses
• No Sharding : All data in one instance
• Using Node/Relation property for Query kill
performance
• A new data architecture
29
32. Column 1 : value
Column 2 : value
Column 3 : value
Key
Key
Key/Value Column-oriented
Field 1 : value
Field A : value
Field B : value
Field 2 : value
Node 1
Node 3
Node 2
Node 4
Node 5
Document
oriented
Graph
Key Value
Key Value
Key Value
Key Value
32
33. Column-oriented database
• A big table, with column families
• Data stored by column instead of row
• Build for distributed architecture
• Map-reduce for querying/processing
• Flexible schema
• Easy sharding (partitioning)
33
34. Column-oriented database
• Strengths
• Data model supports semi-structured data
• Naturally indexed (columns)
• Horizontally scalable – RW increase linearly
• Fault tolerant – no single point of failure
• Weaknesses
• Unsuited for interconnected data
34
35. Column-oriented database
• Java - Apache License 2 - 2008
• Developed by Facebook
• Decentralized
• Supports replication and multi data center
replication
• Scalability
• Fault-tolerant
• MapReduce support
http://cassandra.apache.org/
35
37. Conclusion
• Application architecture impact
• Store your data in the way you want to
query it
• Denormalize your data and try to keep
them up-to-date !
37