The document discusses OrientDB, a multi-model NoSQL database that supports document, key-value, and graph structures. It highlights several of OrientDB's features, including its support for relationships without joins, complex types, ACID transactions, and its RESTful HTTP interface. The document also briefly describes OrientDB's indexing, security, multi-master replication, and use of a graph database model.
Webinar: General Technical Overview of MongoDBMongoDB
MongoDB is the leading open-source, document database. In this webinar we'll dive into the technical details of MongoDB by first mapping it from relational concepts. Next we'll discuss an example data model and associated query functionality using commands pulled straight from the MongoDB shell. Finally, we'll delve into some of the deployment functionality provided by MongoDB including solutions for data redundancy, node failover and auto-sharding.
This document discusses MongoDB replica sets, which allow for data replication across multiple nodes for redundancy and high availability. It covers the replica set lifecycle including creation, initialization, elections, failures and recoveries. It also discusses configuration options, roles of primary and secondary nodes, operational considerations like maintenance and upgrades, and using replica sets across multiple data centers for disaster recovery. Replica sets allow for increased data durability, continuous availability and scalability compared to single node deployments.
This document discusses how to create a domain-specific language (DSL) using Ruby. It begins with an introduction to DSLs and examples of external and internal DSLs. It then demonstrates how to build a DSL for configuring Meetup groups by parsing a configuration file using Ruby's instance_eval method. Key points are that instance_eval interprets a string as Ruby code in the context of an object, and using it with a block changes the default receiver inside the block. The document provides sample code for loading the configuration and implementing setter methods to configure the Meetup object.
The document describes Pfm, a PaaS for online game development that provides an easy and inexpensive environment for coding, hosting, and scaling online games. Pfm uses Lua scripting with asynchronous RPC between Lua VMs to allow object interactions across a distributed key-value store. It aims to reduce the costs and difficulties of developing and operating online games.
For the first time this year, 10gen will be offering a track completely dedicated to Operations at MongoSV, 10gen's annual MongoDB user conference on December 4. Learn more at MongoSV.com
Sharding allows you to distribute load across multiple servers and keep your data balanced across those servers. This session will review MongoDB’s sharding support, including an architectural overview, design principles, and automation.
This document summarizes a presentation about MongoDB replication and replica sets. The key points are:
- Replica sets allow for redundancy and avoid downtime in the event of failures through automatic failover.
- Replica sets involve multiple nodes where one is primary and others are secondaries. They replicate operations from the primary oplog.
- Configuration options allow controlling priorities, hidden nodes for analytics, and slave delay for delayed consistency.
- Writing concerns like write acknowledgement, journal sync, and replication allow balancing consistency and availability.
- Operational considerations include rolling upgrades to avoid downtime and topology choices based on data center configuration.
Hadoop provides high availability through replication of data across multiple nodes. Replication handles data integrity through checksums and automatic re-replication of corrupt blocks. Rack failures are reduced by dual networking and more replication bandwidth. NameNode failures are rare but cause downtime, so Hadoop 1 adds cold failover of Namenodes using VMware HA or RedHat HA. Hadoop 2 introduces live failover of Namenodes using a quorum journal manager to eliminate single points of failure. Full stack high availability adds monitoring and restart of all services.
The document outlines an approach to scalable network services in Java using event-driven and non-blocking I/O. It discusses using the reactor pattern to handle I/O events asynchronously by dispatching tasks to handlers. This allows for high performance by reducing blocking and leveraging available resources like CPUs. It provides examples of how this can be implemented using Java's NIO APIs including channels, buffers, selectors and selection keys.
Webinar: General Technical Overview of MongoDBMongoDB
MongoDB is the leading open-source, document database. In this webinar we'll dive into the technical details of MongoDB by first mapping it from relational concepts. Next we'll discuss an example data model and associated query functionality using commands pulled straight from the MongoDB shell. Finally, we'll delve into some of the deployment functionality provided by MongoDB including solutions for data redundancy, node failover and auto-sharding.
This document discusses MongoDB replica sets, which allow for data replication across multiple nodes for redundancy and high availability. It covers the replica set lifecycle including creation, initialization, elections, failures and recoveries. It also discusses configuration options, roles of primary and secondary nodes, operational considerations like maintenance and upgrades, and using replica sets across multiple data centers for disaster recovery. Replica sets allow for increased data durability, continuous availability and scalability compared to single node deployments.
This document discusses how to create a domain-specific language (DSL) using Ruby. It begins with an introduction to DSLs and examples of external and internal DSLs. It then demonstrates how to build a DSL for configuring Meetup groups by parsing a configuration file using Ruby's instance_eval method. Key points are that instance_eval interprets a string as Ruby code in the context of an object, and using it with a block changes the default receiver inside the block. The document provides sample code for loading the configuration and implementing setter methods to configure the Meetup object.
The document describes Pfm, a PaaS for online game development that provides an easy and inexpensive environment for coding, hosting, and scaling online games. Pfm uses Lua scripting with asynchronous RPC between Lua VMs to allow object interactions across a distributed key-value store. It aims to reduce the costs and difficulties of developing and operating online games.
For the first time this year, 10gen will be offering a track completely dedicated to Operations at MongoSV, 10gen's annual MongoDB user conference on December 4. Learn more at MongoSV.com
Sharding allows you to distribute load across multiple servers and keep your data balanced across those servers. This session will review MongoDB’s sharding support, including an architectural overview, design principles, and automation.
This document summarizes a presentation about MongoDB replication and replica sets. The key points are:
- Replica sets allow for redundancy and avoid downtime in the event of failures through automatic failover.
- Replica sets involve multiple nodes where one is primary and others are secondaries. They replicate operations from the primary oplog.
- Configuration options allow controlling priorities, hidden nodes for analytics, and slave delay for delayed consistency.
- Writing concerns like write acknowledgement, journal sync, and replication allow balancing consistency and availability.
- Operational considerations include rolling upgrades to avoid downtime and topology choices based on data center configuration.
Hadoop provides high availability through replication of data across multiple nodes. Replication handles data integrity through checksums and automatic re-replication of corrupt blocks. Rack failures are reduced by dual networking and more replication bandwidth. NameNode failures are rare but cause downtime, so Hadoop 1 adds cold failover of Namenodes using VMware HA or RedHat HA. Hadoop 2 introduces live failover of Namenodes using a quorum journal manager to eliminate single points of failure. Full stack high availability adds monitoring and restart of all services.
The document outlines an approach to scalable network services in Java using event-driven and non-blocking I/O. It discusses using the reactor pattern to handle I/O events asynchronously by dispatching tasks to handlers. This allows for high performance by reducing blocking and leveraging available resources like CPUs. It provides examples of how this can be implemented using Java's NIO APIs including channels, buffers, selectors and selection keys.
Cassandra is a structured storage system designed to run on a peer-to-peer network. It was created to handle large amounts of data and requests across many servers. Cassandra provides high availability, eventual consistency, incremental scalability and low administration costs. It uses a decentralized architecture with dynamic data modeling and optimized for writes. Data is replicated across multiple nodes for fault tolerance and linear read and write scalability.
Scaling web applications with cassandra presentationMurat Çakal
This document provides an introduction and overview of Cassandra, including:
- Cassandra is a distributed database modeled after Amazon Dynamo and Google Bigtable that is highly scalable and fault tolerant.
- It is used by many large companies for applications that require fast writes, high availability, and elastic scalability.
- Cassandra's data model uses a column-oriented design organized into keyspaces, column families, rows, and columns. It also supports super columns.
- The document discusses Cassandra's features like tunable consistency levels, replication, and its data distribution using consistent hashing.
- An overview of Cassandra's Thrift API and basic operations like get, batch mutate, and
This document provides information about servlets and the servlet API. It defines a servlet as a Java program that runs on a web server and responds to client requests. It discusses how servlets use interfaces like Servlet, ServletConfig, and ServletContext to access configuration and context information. It also describes how HTTPServlet handles HTTP requests and responses using methods like doGet and doPost. The document explains the servlet lifecycle of initialization, processing requests via service(), and destruction. It provides examples of using the HttpRequest and HttpResponse interfaces to read request data and send responses.
This document provides information about Java Database Connectivity (JDBC) and how to connect Java applications to databases. It discusses the four types of JDBC drivers, the interfaces in the JDBC API including DriverManager, Connection, Statement, and ResultSet. It also provides examples of registering drivers, establishing a database connection, executing queries, and closing the connection in five steps.
This document provides information about networking basics including client-server computing, sockets, TCP, UDP, ports, proxies, and internet addressing. It discusses how client-server computing uses clients and servers, how sockets provide endpoints for communication, and how TCP and UDP are used for reliable and unreliable data transmission respectively. It also covers common port numbers, how proxies cache requests and act as intermediaries, and how internet addresses are represented in IPv4 and IPv6 formats. The document is intended as a teaching aid for a class on advanced Java programming and networking concepts.
A Locality Sensitive Hashing Filter for Encrypted Vector DatabasesJunpei Kawamoto
This document describes a locality sensitive hashing (LSH) filter for encrypted vector databases. The LSH filter allows cloud servers to filter database tuples without decrypting encrypted data, improving query efficiency. A whitening transformation is applied to encrypted vectors before inserting them into the LSH index to reduce skew in the vector space. When a query is received, the server computes the LSH of the encrypted query vector to identify candidate tuple groups for similarity checking based on the LSH hash values. Tuples with low estimated similarity are skipped, while those with high similarity have their actual encrypted similarity computed.
Apache con 2012 taking the guesswork out of your hadoop infrastructureSteve Watt
This document discusses profiling a Hadoop cluster to determine infrastructure needs. It describes instrumenting a cluster running a 10TB TeraSort workload using the SAR tool to collect CPU, memory, I/O, and network metrics from each node. The results show the I/O subsystem was underutilized at 10% while CPU utilization was high, indicating the workload was not I/O bound. Memory metrics showed a high percentage of cached data, meaning the CPUs were not waiting on memory. Profiling workloads in this way helps right-size Hadoop infrastructure.
The document discusses MongoDB and Spring Data integration. It provides examples of creating, querying, and commenting on documents using Spring Data and MongoDB. It also covers topics like replication, sharding, and eventual consistency in MongoDB.
Apache Cassandra in Bangalore - Cassandra Internals and Performanceaaronmorton
Cassandra internals and performance was presented. The key points covered include:
1) Cassandra has a layered architecture with APIs, a Dynamo layer, and a database layer. The Dynamo layer implements the Dynamo paper and handles replication and failure handling.
2) The database layer includes the memtable, SSTables, commit log and more. It handles writes, flushes, compactions and reads from storage.
3) A number of performance tests were shown measuring the impact of configuration parameters like memtable flush queue size, commit log sync period, and secondary indexes on write and read latency. Bloom filters, compactions and concurrency were also discussed.
This document discusses cache and concurrency considerations for Apache Cassandra. It covers metrics and monitors for cache performance, how the JVM performs in big data systems, examples of Cassandra in real-world systems like Facebook and Twitter, techniques for achieving fast writes and reads, and tools for optimizing performance. It emphasizes locality, non-blocking collections, and techniques for handling garbage collection and compactions efficiently.
The document provides an overview of how modern websites work. It discusses how clients and servers communicate over the internet using protocols like IP and URLs. Key concepts explained include DNS for translating names to IP addresses, HTTP for exchanging web pages, and HTML/CSS for structuring and styling web page content. JavaScript is also introduced for adding interactive behaviors to web pages. The document then touches on newer technologies like cloud computing which abstracts servers into on-demand services.
Cassandra is a structured storage system designed to run on a peer-to-peer network. It was created to handle large amounts of data and requests across many servers. Cassandra provides high availability with eventual consistency and incremental scalability. It uses a column-oriented data model and optimizes for writes over reads. Data is partitioned and replicated across nodes and gossip protocols are used for membership and failure detection.
A sprint thru Python's Natural Language ToolKit, presented at SFPython on 9/14/2011. Covers tokenization, part of speech tagging, chunking & NER, text classification, and training text classifiers with nltk-trainer.
The document describes a distributed C/C++ compile system (DCC) built on Coord, an open source distributed computing platform. DCC allows compiling C/C++ code across multiple machines. It uses Coord's master-worker model to distribute compile jobs and Coord's space-based architecture to coordinate the machines. The system aims to reduce compile times by leveraging idle resources. It generates jobs from makefiles then schedules and executes them in a distributed manner for load balancing. A user interface is also mentioned.
MongoDB is a document-oriented database that stores data in flexible, JSON-like documents. It supports features like replication, auto-sharding, and indexing. The document discusses using MongoDB with Ameba Pico's photo tagging service, including initial implementation with one shard, expanding to multiple shards as user numbers grow over time, and repairing and upgrading shards over time to support the increasing load.
This document provides an overview of JRuby, which is a Ruby implementation that runs on the Java Virtual Machine (JVM). It discusses key aspects of JRuby like its compatibility with Ruby, access to Java libraries, integration with Java code, and usage in applications like Rails. Specific topics covered include JRuby fundamentals, dynamic typing, classes and modules, mixins, Java integration features, testing Java code from Ruby, and calling Ruby from Java using JSR-223.
This document discusses working with COM (Component Object Model) components in BIS. It provides an overview of what COM is, BIS's COM client interface using commands like @CCC, @CCP, @CCG, and @CCI. It also covers writing your own COM components in VB or C++ and working with existing COM components like email using CDONTS.NewMail and Excel using Excel.Application.
Apache Cassandra is a scalable, fault-tolerant database that has found its way into more than 25% of the Fortune 100 and continues to enjoy significant adoption in the marketplace. In this talk we'll introduce you to Cassandra, explore some of its internals, and discuss CQL (the SQL-like query language for Cassandra). We'll finish by talking about how some companies are using it for services you probably interact with in your daily life. You'll leave with all the tools you need to start exploring Cassandra on your own.
Emociones básicas en los niños y como educarlas para tener un mejor control de ellas y les ayuden a obtener un desempeño satisfactorio en la escuela y en su vida diaria.
Cassandra is a structured storage system designed to run on a peer-to-peer network. It was created to handle large amounts of data and requests across many servers. Cassandra provides high availability, eventual consistency, incremental scalability and low administration costs. It uses a decentralized architecture with dynamic data modeling and optimized for writes. Data is replicated across multiple nodes for fault tolerance and linear read and write scalability.
Scaling web applications with cassandra presentationMurat Çakal
This document provides an introduction and overview of Cassandra, including:
- Cassandra is a distributed database modeled after Amazon Dynamo and Google Bigtable that is highly scalable and fault tolerant.
- It is used by many large companies for applications that require fast writes, high availability, and elastic scalability.
- Cassandra's data model uses a column-oriented design organized into keyspaces, column families, rows, and columns. It also supports super columns.
- The document discusses Cassandra's features like tunable consistency levels, replication, and its data distribution using consistent hashing.
- An overview of Cassandra's Thrift API and basic operations like get, batch mutate, and
This document provides information about servlets and the servlet API. It defines a servlet as a Java program that runs on a web server and responds to client requests. It discusses how servlets use interfaces like Servlet, ServletConfig, and ServletContext to access configuration and context information. It also describes how HTTPServlet handles HTTP requests and responses using methods like doGet and doPost. The document explains the servlet lifecycle of initialization, processing requests via service(), and destruction. It provides examples of using the HttpRequest and HttpResponse interfaces to read request data and send responses.
This document provides information about Java Database Connectivity (JDBC) and how to connect Java applications to databases. It discusses the four types of JDBC drivers, the interfaces in the JDBC API including DriverManager, Connection, Statement, and ResultSet. It also provides examples of registering drivers, establishing a database connection, executing queries, and closing the connection in five steps.
This document provides information about networking basics including client-server computing, sockets, TCP, UDP, ports, proxies, and internet addressing. It discusses how client-server computing uses clients and servers, how sockets provide endpoints for communication, and how TCP and UDP are used for reliable and unreliable data transmission respectively. It also covers common port numbers, how proxies cache requests and act as intermediaries, and how internet addresses are represented in IPv4 and IPv6 formats. The document is intended as a teaching aid for a class on advanced Java programming and networking concepts.
A Locality Sensitive Hashing Filter for Encrypted Vector DatabasesJunpei Kawamoto
This document describes a locality sensitive hashing (LSH) filter for encrypted vector databases. The LSH filter allows cloud servers to filter database tuples without decrypting encrypted data, improving query efficiency. A whitening transformation is applied to encrypted vectors before inserting them into the LSH index to reduce skew in the vector space. When a query is received, the server computes the LSH of the encrypted query vector to identify candidate tuple groups for similarity checking based on the LSH hash values. Tuples with low estimated similarity are skipped, while those with high similarity have their actual encrypted similarity computed.
Apache con 2012 taking the guesswork out of your hadoop infrastructureSteve Watt
This document discusses profiling a Hadoop cluster to determine infrastructure needs. It describes instrumenting a cluster running a 10TB TeraSort workload using the SAR tool to collect CPU, memory, I/O, and network metrics from each node. The results show the I/O subsystem was underutilized at 10% while CPU utilization was high, indicating the workload was not I/O bound. Memory metrics showed a high percentage of cached data, meaning the CPUs were not waiting on memory. Profiling workloads in this way helps right-size Hadoop infrastructure.
The document discusses MongoDB and Spring Data integration. It provides examples of creating, querying, and commenting on documents using Spring Data and MongoDB. It also covers topics like replication, sharding, and eventual consistency in MongoDB.
Apache Cassandra in Bangalore - Cassandra Internals and Performanceaaronmorton
Cassandra internals and performance was presented. The key points covered include:
1) Cassandra has a layered architecture with APIs, a Dynamo layer, and a database layer. The Dynamo layer implements the Dynamo paper and handles replication and failure handling.
2) The database layer includes the memtable, SSTables, commit log and more. It handles writes, flushes, compactions and reads from storage.
3) A number of performance tests were shown measuring the impact of configuration parameters like memtable flush queue size, commit log sync period, and secondary indexes on write and read latency. Bloom filters, compactions and concurrency were also discussed.
This document discusses cache and concurrency considerations for Apache Cassandra. It covers metrics and monitors for cache performance, how the JVM performs in big data systems, examples of Cassandra in real-world systems like Facebook and Twitter, techniques for achieving fast writes and reads, and tools for optimizing performance. It emphasizes locality, non-blocking collections, and techniques for handling garbage collection and compactions efficiently.
The document provides an overview of how modern websites work. It discusses how clients and servers communicate over the internet using protocols like IP and URLs. Key concepts explained include DNS for translating names to IP addresses, HTTP for exchanging web pages, and HTML/CSS for structuring and styling web page content. JavaScript is also introduced for adding interactive behaviors to web pages. The document then touches on newer technologies like cloud computing which abstracts servers into on-demand services.
Cassandra is a structured storage system designed to run on a peer-to-peer network. It was created to handle large amounts of data and requests across many servers. Cassandra provides high availability with eventual consistency and incremental scalability. It uses a column-oriented data model and optimizes for writes over reads. Data is partitioned and replicated across nodes and gossip protocols are used for membership and failure detection.
A sprint thru Python's Natural Language ToolKit, presented at SFPython on 9/14/2011. Covers tokenization, part of speech tagging, chunking & NER, text classification, and training text classifiers with nltk-trainer.
The document describes a distributed C/C++ compile system (DCC) built on Coord, an open source distributed computing platform. DCC allows compiling C/C++ code across multiple machines. It uses Coord's master-worker model to distribute compile jobs and Coord's space-based architecture to coordinate the machines. The system aims to reduce compile times by leveraging idle resources. It generates jobs from makefiles then schedules and executes them in a distributed manner for load balancing. A user interface is also mentioned.
MongoDB is a document-oriented database that stores data in flexible, JSON-like documents. It supports features like replication, auto-sharding, and indexing. The document discusses using MongoDB with Ameba Pico's photo tagging service, including initial implementation with one shard, expanding to multiple shards as user numbers grow over time, and repairing and upgrading shards over time to support the increasing load.
This document provides an overview of JRuby, which is a Ruby implementation that runs on the Java Virtual Machine (JVM). It discusses key aspects of JRuby like its compatibility with Ruby, access to Java libraries, integration with Java code, and usage in applications like Rails. Specific topics covered include JRuby fundamentals, dynamic typing, classes and modules, mixins, Java integration features, testing Java code from Ruby, and calling Ruby from Java using JSR-223.
This document discusses working with COM (Component Object Model) components in BIS. It provides an overview of what COM is, BIS's COM client interface using commands like @CCC, @CCP, @CCG, and @CCI. It also covers writing your own COM components in VB or C++ and working with existing COM components like email using CDONTS.NewMail and Excel using Excel.Application.
Apache Cassandra is a scalable, fault-tolerant database that has found its way into more than 25% of the Fortune 100 and continues to enjoy significant adoption in the marketplace. In this talk we'll introduce you to Cassandra, explore some of its internals, and discuss CQL (the SQL-like query language for Cassandra). We'll finish by talking about how some companies are using it for services you probably interact with in your daily life. You'll leave with all the tools you need to start exploring Cassandra on your own.
Emociones básicas en los niños y como educarlas para tener un mejor control de ellas y les ayuden a obtener un desempeño satisfactorio en la escuela y en su vida diaria.
Детский сад Планета детства» — это:
Группы по 12-15 малышей от 1,3 до 7 лет
Авторские педагогические программы для вашего ребенка
Уютный интерьер и специальное детское меню
Возможность посещения садика 3 раза в неделю
Группа кратковременного пребывания до 13.00
Группы выходного дня. Няня на час и т.д.
La historia trata de un patito feo que nació en una familia de patitos hermosos. Sus hermanos y su madre se burlaban de él por ser diferente. Sin embargo, cuando creció se convirtió en un hermoso cisne. La historia enseña que debemos aceptarnos a nosotros mismos aunque seamos diferentes y no dejarnos afectar por las críticas de los demás.
El documento describe las cuatro partes básicas de una computadora de escritorio: el monitor, que muestra la información y resultados; el teclado, que contiene teclas para ingresar datos; el mouse, dispositivo para navegar en la interfaz gráfica; y la CPU, parte central que procesa funciones y almacena información. El estudiante debe dibujar o colorear estas partes y identificar la CPU.
Los primeros instrumentos para realizar cálculos fueron el ábaco, inventado probablemente en China, y la máquina de calcular creada por Wilhelm Schickard en 1623. Más adelante, figuras como Blaise Pascal, Gottfried Leibniz y Charles Babbage hicieron contribuciones fundamentales al desarrollo de las primeras calculadoras mecánicas y sentaron las bases conceptuales de la computadora moderna. Joseph Marie Jacquard revolucionó la industria textil aplicando tarjetas perforadas para controlar telares, anticipando el uso de tarjetas
El documento describe la creación de un nuevo Departamento de Gestión Integral de Riesgos en el Ministerio de Agricultura de Chile. El departamento tiene como objetivo gestionar de manera integral los riesgos en el sector agropecuario, como desastres naturales y emergencias agrícolas. Se compone de tres subdepartamentos: Información, Monitoreo y Prevención; Desarrollo y Promoción de Herramientas de Gestión de Riesgos; y Atención a Desastres Naturales. El documento también solicita la nominación de contrapartes en las regiones y servic
IAB Europe Webinar Deck: Building more Meaningful Consumer Relationships with...IAB Europe
This webinar provides insight into how native advertising enables both publishers and advertisers to build more meaningful consumer relationships. It also outlines the key stakeholders involved in native advertising and content marketing and their key roles and responsibilities.
ACC uses on-board sensors to automatically adjust vehicle speed to maintain a safe distance from vehicles ahead without external infrastructure. CACC further extends this automation by utilizing information from fixed infrastructure like satellites and roadside beacons, or mobile infrastructure on other vehicles, to cooperatively control vehicle speed and distance. The document appears to provide information about ACC and CACC systems including their operation and components.
The document discusses OrientDB's transition from a master-slave architecture to a new multi-master distributed architecture. The new architecture allows any node to read and write, improves scalability, and handles conflicts intelligently. It will be released in OrientDB version 1.0 in December 2011.
Spring one2gx2010 spring-nonrelational_dataRoger Xia
This document provides a summary of a talk on using Spring with NoSQL databases. The talk discusses the benefits and drawbacks of NoSQL databases, and how the Spring Data project simplifies development of NoSQL applications. It then provides background on the two speakers, Chris Richardson and Mark Pollack. The agenda outlines explaining why NoSQL, overviewing some NoSQL databases, discussing Spring NoSQL projects, and having demos and code examples.
Webinar Back to Basics 3 - Introduzione ai Replica SetMongoDB
Un set di repliche in MongoDB è un gruppo di processi che mantengono copie dei dati su diversi server di database. Assicurano ridondanza e disponibilità elevata e sono la base di tutte le distribuzioni in produzione di MongoDB.
This document provides an overview of Exchange Server 2007 availability solutions and introduces Exchange 2010 high availability features. Exchange Server 2007's single copy cluster provides little high availability and does not automatically recover from failures or protect data. Exchange 2010 improves on this with database availability groups that allow up to 16 replicated database copies across multiple servers for improved redundancy and recovery times. It also simplifies administration and supports stretching databases across different sites.
Running Neutron at Scale - Gal Sagie & Eran Gampel - OpenStack Day Israel 2016Cloud Native Day Tel Aviv
Dragonflow is an integral project in OpenStack that is designed to help OpenStack networking scale to thousands of compute nodes. It addresses limitations in Neutron's scalability, performance, and operability. Dragonflow uses a lightweight distributed SDN control plane architecture with pluggable database and publish-subscribe drivers. This allows it to distribute network services like DHCP, security groups, and DNAT across compute nodes for improved scalability and performance.
Security regarding NoSQL Databases Still remain a question.Not much research done these databases,this paper concentrates on some of the major NoSQL databases and their flaws
This document discusses JDBC (Java Database Connectivity), which defines how Java programs can access databases. It describes the four types of JDBC drivers that convert Java requests into protocols understood by different database systems. It also explains how to load JDBC drivers at runtime, make database connections using the DriverManager, execute SQL queries with Statement objects to retrieve ResultSets, and move between rows in a ResultSet using a cursor.
This presentation was given at the LDS Tech SORT Conference 2011 in Salt Lake City. The slides are quite comprehensive covering many topics on MongoDB. Rather than a traditional presentation, this was presented as more of a Q & A session. Topics covered include. Introduction to MongoDB, Use Cases, Schema design, High availability (replication) and Horizontal Scaling (sharding).
Key-value databases in practice Redis @ DotNetToscanaMatteo Baglini
This document provides an overview of Redis, an open source in-memory data structure store. It discusses how Redis can be used as a data store, cache, and message broker. It explains Redis' core abstractions like strings, hashes, lists, sets, sorted sets; persistence options; replication; and pub/sub functionality. The document also provides information about Redis' performance, clients, and how it is well-suited for caching, analytics, and real-time applications.
The document discusses trends in data, networking, and individualization. It then covers topics around scaling databases including scale-up (vertical scaling) and scale-out (horizontal scaling). It notes that NoSQL databases do not use a relational data model or SQL, instead supporting distributed and horizontal scalability with loose or no schema restrictions and different consistency models. Requirements for distributed systems like consistency, availability, and partition tolerance are discussed in relation to Brewer's CAP theorem from 2000.
Replication and sharding allow MongoDB databases to scale horizontally across commodity servers for high availability and increased performance. Replication duplicates data across multiple nodes so the application can continue running if a node fails. Sharding partitions data across nodes to distribute load and storage requirements. MongoDB supports combining replication within shards for redundancy and sharding to partition data across replicated shards, providing redundancy and scalability.
The document discusses several networking concepts:
- The OSI reference model created standardized layers for networking.
- Subnetting networks optimizes performance by dividing large networks into smaller logical subnets. Methods for determining subnet masks and allocating addresses are covered.
- RAID (redundant array of independent disks) systems provide data redundancy and improved performance through techniques like disk striping, mirroring, and parity. The various RAID levels trade off these properties differently.
- Active Directory and DNS are protocols for centralized network management and translation of names to network addresses respectively. DHCP dynamically allocates IP addresses to devices on a network. IOPS is a metric for storage performance.
This document summarizes techniques for scaling MongoDB deployments, including:
- Single server read/write scaling using techniques like denormalization, indexing, and restricting fields
- Scaling reads using master-slave replication and replica sets for improved availability and read scaling
- Scaling reads and writes using sharding to partition data across multiple servers and distribute load
Modeling Tricks My Relational Database Never Taught MeDavid Boike
In this session we will explore several modeling scenarios from my own experience that can easily be achieved using RavenDB, but difficult (if not nearly impossible) to build using a classic relational database. The focus will be on helping those accustomed to SQL Server or other relational databases learn good document modeling skills by example, with a summary of document modeling guidelines at the end.
This document provides an overview of JDBC (Java Database Connectivity) including ODBC, the JDBC API, JDBC architecture and drivers, and the basic steps for using JDBC to connect to and query a database.
The document discusses various SQL Server concepts and features including:
1) Encrypted stored procedures, linked servers, Analysis Services features like OLAP and data mining models.
2) The Analysis Services repository stores metadata for cubes and data sources. SQL Service Broker allows asynchronous messaging between databases.
3) User-defined data types are based on system types and ensure columns store the same type of data. Data types like bit store 0, 1, or null values.
This summary provides an overview of the Nimbuzz architecture and technologies:
Nimbuzz is a communication platform that allows calling, messaging, and file sharing across mobile devices and computers using popular IM networks. It uses a microservices architecture with small, stateless services and external components communicating over XMPP. The platform is built on Ejabberd, an XMPP server written in Erlang, which provides features like concurrency, distribution, and high availability. Caching, database, and data processing best practices are employed to optimize performance for millions of daily users.
Open source technologies allow anyone to view, modify, and distribute source code freely. The key characteristics of open source are that it is free to use and modify. Anyone can improve open source code by adding new functionality. As more people contribute code, the potential uses of open source software grow beyond what the original creator intended. To be a web developer requires a passion for learning and skills with technologies like HTML, PHP, Linux, Apache, MySQL, and PHP (LAMP stack). Caching and NoSQL databases like MongoDB can improve performance of dynamic web applications.
This document discusses advanced replication in MongoDB replica sets. It begins by explaining the roles and configuration of replica set members, including primaries, secondaries, and arbiters. It then covers the implementation details of replication using an oplog and heartbeats between nodes. The rest of the document discusses best practices for maintenance, data center awareness using tagging, write concerns, and read preferences to control data distribution and failover.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
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2. Artem Orobets
Senior Java Developer
in ExigenServices
1.5 year in Java
OrientDB committer
Andrey Lomakin
Software Architect
in ExigenServices
6+ years JEE experience
OrientDB committer
3. OrientDB
=
best features of newest NoSQL
solutions
+
best features of Relational DBMS
+
True Graph engine
www.orientechnologies.com
4. Relationships
are direct links
no Relational JOINS to connect multiple tables
Load trees and graphs in few ms!
www.orientechnologies.com
5. Complex types
native support for collections, maps
(key/value)
and embedded documents
no more additional tables to handle them
www.orientechnologies.com
6. Schema-mixed
schema with mandatory and optional fields + constraints
the best of schema-less and schema-full modes
www.orientechnologies.com
14. Binary protocol
available for Java
and soon C, C++ and Ruby
www.orientechnologies.com
15. MVRB-Tree index
the best of B+Tree and RB-Tree
fast on browsing, low insertion cost
www.orientechnologies.com
16. Hooks
similar to triggers
catch events against records, database and transactions
implement custom cascade deletion algorithm
enforce constraints
www.orientechnologies.com
19. The actors
Leader Node Only 1 per Leader per cluster, checks other nodes and
notify changes to other Peer Nodes.
Any server node in the cluster. Has a permanent
Peer Node connection to the Leader Node
Clients are connected to Server Nodes no matter if Leader
Client
or Peer
Database Database, where data are stored
Synchronous mode replication.
Asynchronous mode replication.
20. Cluster auto-discovering
At start up each Server Node sends a IP Multicast message in broadcast to
discover if any Leader Node is available to join the cluster.
Server #1
(Leader) DB DB
DB DB
DB DB
Server #2
(Peer)
DB DB
DB DB
DB DB
21. One Leader Multiple Peers
The first node to start is always the Leader but in case of failure can be elected
any other.
Server #1
(Leader) DB DB
DBDB
DB DB
Server #2 Server #3
(Peer) (Peer)
DB DB
DBDB
DB DB DB DB
DBDB
DB
22. Security
To join a cluster the Server Node has to configure the cluster name and
password
Broadcast messages are encrypted using the password
Server #1
(Leader)
Server #2 Join the cluster
(Peer) ONLY
If knows the name
DB DB
DB DB
DB DB and password
23. Multiple clusters
Multiple separate clusters can coexist in the same network
Clusters can't see each others. Are separated boxes
What identify a cluster is name + password
Cluster 'A', password
'aaa'
Server #1 Cluster 'B', password
(Leader) 'bbb'
Server #2 Server #1
(Peer) (Leader)
Server #3
(Peer) Server #2
(Peer)
Server #3
(Peer)
25. Synchronous Replication
steps
Client #1
6) Sends back OK to Client
1) Update record #1
request 3) Propagates the
update
Server #1 Server #2
2) Update record to DB-1 5) Sends back OK to Server #1 4) update record to DB-2
DB-1 DB-2
26. Asynchronous Replication
Changes are propagated without waiting for the answer
Two databases could be not consistent in the range of few
ms
Server #1 Server #2
DB-1 DB-2
27. Asynchronous Replication
steps
(4a and 4b are executed in parallel)
Client #1
4a) Sends back OK to Client #1
1) Update record request
3) Propagates the update
Server #1 Server #2
2) Update record to DB-1 4b) update record to DB-2
DB-1 DB-2
28. Conflict Management
The conflicts resolution strategy can be plugged by
providing implementations of the
OReplicationConflictResolver interface
Server #2
Conflict Strategy DB-2
29. Conflict Management
Default strategy
Server #2
Default implementation:
Conflict mark is created
Default
and conflict should be Conflict
DB-2
resolved manually Strategy
Conflict Log
30. Graph Database model
wrapper on top of Document Database
Few simple concepts: Vertex, Edge,
Property and Index
www.orientechnologies.com
31. 2 different API
OGraphDatabase All APIs
Native, damn fast, not the most beautiful API are compatible
among them!
So use the
right one
for the right
case
OrientGraph
TinkerPop Blueprints, slowest but:
common to other impls, Gremlin, SPARQL
www.orientechnologies.com
32. TinkerPop technologies
sort of “standard” for GraphDB
a lot of free open-source projects
http://tinkerpop.com
www.orientechnologies.com
33. TinkerPop Blueprints
basic API to interact with GraphDB
implements transactional and
indexable property graph model
bidirectional edges
www.orientechnologies.com
34. TinkerPop Gremli
scripting language
easy to learn and understand
Used for operations against graphs
www.orientechnologies.com
36. Inheritance
OgraphVertex (V) OgraphEdge (E)
Person Works Reside Knows
Vehicle
Address :
Address
brand : BRANDS s
since : since : Date Level :
Date till : Date LEVELS
Custome Provider
r totBuyed :
totSold : float float
www.orientechnologies.com
37. Polymorphic SQL Query
List<ODocument> result = database.query( new
OSQLSynchQuery(
"select from Person where city.name = 'Rome'" ));
Queries are polymorphics
and subclasses of Person can be
part of result set
www.orientechnologies.com
38. Fetch plans
Choose what to fetch on query and vertexes/edges loading
Vertexes/Edges not fetched will be lazy-loaded on request
Optimizes network latency
www.orientechnologies.com
39. Fetch plans
Load only the root vertex
Vertex = *:1
Luca
|
| lives city
+---------> Vertex ------------> Vertex
| 10th street Italy
| knows
+--------->* [Vertex Vertex Vertex ]
[ Marko John Nicholas]
www.orientechnologies.com
40. Fetch plans
Load root + address
Vertex = *:1 lives:2
Luca
|
| lives city
+---------> Vertex ------------> Vertex
| 10th street Italy
| knows
+--------->* [Vertex Vertex Vertex ]
[ Marko John Nicholas]
www.orientechnologies.com
41. Fetch plans
Load root + all known
Vertex = *:1 knows:1
Luca
|
| lives city
+---------> Vertex ------------> Vertex
| 10th street Italy
| knows
+--------->* [Vertex Vertex Vertex ]
[ Marko John Nicholas]
www.orientechnologies.com
42. Fetch plans
Load up 3rd level of depth
Vertex = *:3
Luca
|
| lives city
+---------> Vertex ------------> Vertex
| 10th street Italy
| knows
+--------->* [Vertex Vertex Vertex ]
[ Marko John Nicholas]
www.orientechnologies.com
43. Console
ORIENT database v.1.0.0 www.orientechnologies.com
Type 'help' to display all the commands supported.
> connect remote:localhost/demo admin admin
Connecting to database [remote:localhost/demo] with user 'admin'...OK
> select from profile where nick.startsWith('L')
---+--------+--------------------+--------------------+--------------------+
#| REC ID |NICK |SEX |AGE |
---+--------+--------------------+--------------------+--------------------+
0| 10:0|Lvca |male |34
1| 10:3|Leo |male |22
2| 10:7|Luisa |female |27
3 item(s) found. Query executed in 0.013 sec(s).
> close
Disconnecting from the database [demo]...OK
> quit
www.orientechnologies.com
44. OrientDB Studio/SQL query
Resultset is editable and
changes are immediately
persistent!
www.orientechnologies.com
48. NuvolaBase.com (beta)
The first
Graph Database
on the Cloud
always available
few seconds to setup it
use it from app & mobile
www.orientechnologies.com
49. User’s reasons to chose
Only one graph DB with cloud computing
support, high flexibility of data format,
powerful data analyzes (SQL + Gremlin),
JDBC driver, huge reduction of integration
time, good technical support.