OrigoDB is an in-memory database toolkit that allows writing and data to exist in the same process. It uses write-ahead command logging and snapshots for persistence. The document discusses OrigoDB's architecture, data modeling approaches, testing strategies, hosting options, and configuration capabilities like different persistence modes and kernels. It provides examples of using OrigoDB for various applications and demonstrates its immutability and server capabilities.
A system to record query performance of XQuery statements running on the BaseX http:basex.org XML database. It uses Angular on the client side and RESTXQ on the server.
Mongo DB: Fundamentals & Basics/ An Overview of MongoDB/ Mongo DB tutorials
The document discusses MongoDB, an open-source document database. It provides an overview of MongoDB, including what it is, why it is used, its basic concepts like databases, collections, and documents, and how it compares to a relational database. It also covers MongoDB commands for creating and dropping collections, inserting, querying, and updating documents.
Rapid prototyping using azure functions - A walk on the wild side
My presentation at the 2016 Miwaukee .NET conference.
Talked about how I leveraged Azure Functions to rapidly prototype a product.
http://www.mkedotnet.com/sessions/azure-functions/
Working with MongoDB as MySQL DBA. Comparing commands from MongoDB to MySQL, similarities and differences. Exploring replication features, failover and recovery, adjusting the variables and checking status and using DML, DDL with different storage engines
This document provides an introduction to MongoDB, a popular document-oriented database. It discusses how MongoDB stores data in flexible, JSON-like documents rather than rigid tables. It also covers MongoDB's features like replication, sharding, indexing, querying, map-reduce functions and how it provides a scalable and flexible alternative to traditional relational databases. The document also discusses some of the theoretical underpinnings of non-relational databases like MongoDB, including the CAP theorem and ACID versus BASE models of data consistency.
This document summarizes YoctoDB, an embedded Java library for horizontally partitioned immutable databases developed by Yandex to power its classified search services. It provides very low latency and high throughput for indexing and querying large datasets by using an immutable data model with field-based filtering and sorting. It has improved performance versus Lucene for Yandex's auto search workloads, reducing latency percentiles and CPU usage. YoctoDB's data model and implementation provide benefits like simplified concurrency, fast reindexing, and no need for garbage collection tuning.
Putting the Go in MongoDB: How We Rebuilt The MongoDB Tools in Go
With the release of MongoDB 3.0, the tools (mongodump, mongoimport, mongotop, etc) have been completely re-designed and re-written in Go to improve maintainability and performance. In this section, we'll give an architectural overview of the tools, describe how we used Go's native capacities to improve their parallelism, and also take a deep technical dive into their internals. We'll discuss performance, usability and integration improvements and share advanced techniques for power users. With a better understanding of how the tools work, you should feel comfortable effectively using and contributing to the tools.
This document provides an overview and introduction to MongoDB including:
- MongoDB installation using yum or binary, roles in MongoDB, and how to create users
- Basic MongoDB commands like use, show dbs, and dropDatabase
- Tracing slow queries using the database profiler and viewing results in the system.profile collection
- Important monitoring commands like db.serverStatus(), currentOp(), db.stats(), and replica set commands like rs.status() and rs.printReplicationInfo()
Use of No-SQL databases in web applications is becoming increasingly common. In part this is because they work well with rapid application development due to their schema-less nature. And partly because they scale well in a cloud-based environment without too much effort.
MongoDB is one of the many No-SQL database technologies available today. It's schema-less nature works very well with rapid application development nature of ColdFusion. Unlike other No-SQL databases, it offers the ability run arbitrary queries against databases without having to first write map-reduce functions. It also has some other interesting features like capped collections with asynchronous write ability.
In this session, Indy takes you through some common use-cases for considering MongoDB with ColdFusion applications, contrasting it with other No-SQL databases like CouchDB. And he shares his experiences of using it with cloud-based ColdFusion applications. The aim of the session is to provide an overview of using MongoDB with ColdFusion so that you have another tool to consider when working on your next web application.
This was presented at CFObjective, Melbourne, November 17-18, 2011.
Hekaton is SQL Server's in-memory optimized database engine for online transaction processing (OLTP) workloads. It uses lock-free data structures, multi-version concurrency control, and compiled Transact-SQL queries to provide high performance and scalability. Transaction logging and continuous checkpointing ensure data durability. Hekaton tables and indexes are optimized for memory residency, with hash indexes and Bw-tree indexes to support efficient lookups and updates.
CBDW2014 - NoSQL Development With Couchbase and ColdFusion (CFML)
NoSQL document stores are reinventing the way we design our databases and cache layers. Couchbase server is a unique offering with unparalleled performance, automatic replication and failover. In this session, we'll talk about how to get started with Couchbase using the open source CFML SDK as well as native caching via the Railo Couchbase Extension.
FITC presents: Mobile & offline data synchronization in Angular JS
Save 10% off ANY FITC event with discount code 'slideshare'
See our upcoming events at www.fitc.ca
OVERVIEW
Are you building mobile or web applications with AngularJS and wish they would work when you were offline? You can read, send and delete mail from your mobile email client when you are offline, why not from your AngularJS app? AngularJS is completely agnostic when it comes to creating your data models. Let’s explore what is required to allow your application to be useful to your users even without an internet connection.
INTENDED AUDIENCE - BEGINNER - INTERMEDIATE
This presentation is for developers that know they are looking for offline and data synchronization capabilities. Or, possibly for managers that wish to have a greater understanding of what their options are in AngularJS to create such functionality.
Daniel Zen, CEO, Zen Digital
Daniel Zen is the CEO of Zen Digital, founder of the New York AngularJS Meetup, a frequent lecturer, and a former consultant for Google, Pivotal Labs and various Fortune 500 companies. Zen Digital uses Agile techniques to move projects forward while continuously integrating new code and ideas, producing elegant frontend experiences and efficient backend systems for web and mobile applications.
This document discusses using BaseX, an XML database, for web applications. It describes GraphXQ, which uses RESTXQ and Graphviz to visualize graphs. It also describes CellarXQ, an Angular.js single page application that uses BaseX and OAuth for user authentication and data storage. Finally, it shows how to create a chatbot using BaseX, Node.js and Socket.io that passes messages to an XQuery script for processing.
The document discusses various MongoDB command line tools and how to use them. It provides examples of using core tools like mongo, mongod, and mongostat to get database information and view performance metrics. Other tools covered include mongodump for backups, mongorestore for restores, mongoexport for data exports, and bsondump for document conversions. Third party tools like automongobackup and mongolog are also mentioned.
The document discusses MongoDB's new aggregation framework, which provides a declarative pipeline for performing data aggregation operations on complex documents. The framework allows users to describe a chain of operations without writing JavaScript. It will offer high-performance operators like $match, $project, $unwind, $group, $sort, and computed expressions to reshape and analyze document data without the overhead of JavaScript. The aggregation framework is nearing release and will support sharding by forwarding pipeline operations to shards and combining results.
Silicon Valley JUG - How to generate customized java 8 code from your database
The best code is the one you never need to write. Using code generation and automated builds you can minimize the risk of human error when developing software, but how do you maintain control over code when large parts of it is handed over to a machine? In this tutorial, you will learn how to use open-source software to create and control code automation. You will see how you can generate a completely object-oriented domain model by automatically analyzing your database schemas. Every aspect of the process is transparent and configurable, giving you as a developer 100% control of the generated code. This will not only increase your productivity, but also help you build safer and more maintainable Java applications.
How to generate customized java 8 code from your database
Did you know that database classes, that require many lines of Java and SQL code, may be replaced with a single line of Java 8 code? In this tutorial session you will learn how to use standard Java 8 Streams as an alternative to traditional Object Relational Mappers (ORM). We will use the open-source tool Speedment to show how development speed can be increased and how the application code can be more concise and run faster.
Running Airflow Workflows as ETL Processes on Hadoop
While working with Hadoop, you'll eventually encounter the need to schedule and run workflows to perform various operations like ingesting data or performing ETL. There are a number of tools available to assist you with this type of requirement and one such tool that we at Clairvoyant have been looking to use is Apache Airflow. Apache Airflow is an Apache Incubator project that allows you to programmatically create workflows through a python script. This provides a flexible and effective way to design your workflows with little code and setup. In this talk, we will discuss Apache Airflow and how we at Clairvoyant have utilized it for ETL pipelines on Hadoop.
JavaOne2016 - How to Generate Customized Java 8 Code from Your Database [TUT4...
The best code is the one you never need to write. Using code generation and automated builds, you can minimize the risk of human error when developing software, but how do you maintain control over code when large parts of it are handed over to a machine? In this tutorial, you will learn how to use open source software to create and control code automation. You will see how you can generate a completely object-oriented domain model by automatically analyzing your database schemas. Every aspect of the process is transparent and configurable, giving you, as a developer, 100 percent control of the generated code. This will not only increase your productivity but also help you build safer, more maintainable Java applications and is a perfect solution for Microservices.
How to JavaOne 2016 - Generate Customized Java 8 Code from Your Database [TUT...
The best code is the one you never need to write. Using code generation and automated builds, you can minimize the risk of human error when developing software, but how do you maintain control over code when large parts of it are handed over to a machine? In this tutorial, you will learn how to use open source software to create and control code automation. You will see how you can generate a completely object-oriented domain model by automatically analyzing your database schemas. Every aspect of the process is transparent and configurable, giving you, as a developer, 100 percent control of the generated code. This will not only increase your productivity but also help you build safer, more maintainable Java applications and is a perfect solution for Microservices.
The document provides an introduction to Typesafe Activator and the Play Framework. It discusses how Activator is a tool that helps developers get started with the Typesafe Reactive Platform and Play applications. It also covers some core features of Play like routing, templates, assets, data access with Slick and JSON, and concurrency with Futures, Actors, and WebSockets.
This is from a 2 hour talk introducing in-memory databases. First a look at traditional RDBMS architecture and some of it's limitations, then a look at some in-memory products and finally a closer look at OrigoDB, the open source in-memory database toolkit for NET/Mono.
This document discusses various technologies related to architectures, frameworks, infrastructure, services, data stores, analytics, logging and metrics. It covers Java 8 features like lambda expressions and method references. It also discusses microservices, Spring Boot basics and features, Gradle vs Maven, Swagger, AngularJS, Gulp, Jasmine, Karma, Nginx, CloudFront, Couchbase, Lambda Architecture, logging with Fluentd and Elasticsearch, metrics collection with Collectd and Statsd, and visualization with Graphite and Grafana.
This document summarizes the experiences of operating Rails websites at stable scale. It discusses using virtualization to run multiple websites on a single server. It provides tips for optimizing performance including database tuning, adding indexes, log rotation, and restarting Mongrel processes periodically. New Rails sites are launched using the newest framework versions and different web servers like Passenger are tested for performance.
This chapter discusses software development security. It covers topics like programming concepts, compilers and interpreters, procedural vs object-oriented languages, application development methods like waterfall vs agile models, databases, object-oriented design, assessing software vulnerabilities, and artificial intelligence techniques. The key aspects are securing the entire software development lifecycle from initial planning through operation and disposal, using secure coding practices, testing for vulnerabilities, and continually improving processes.
Title: Sista: Improving Cog’s JIT performance
Speaker: Clément Béra
Thu, August 21, 9:45am – 10:30am
Video Part1
https://www.youtube.com/watch?v=X4E_FoLysJg
Video Part2
https://www.youtube.com/watch?v=gZOk3qojoVE
Description
Abstract: Although recent improvements of the Cog VM performance made it one of the fastest available Smalltalk virtual machine, the overhead compared to optimized C code remains important. Efficient industrial object oriented virtual machine, such as Javascript V8's engine for Google Chrome and Oracle Java Hotspot can reach on many benchs the performance of optimized C code thanks to adaptive optimizations performed their JIT compilers. The VM becomes then cleverer, and after executing numerous times the same portion of codes, it stops the code execution, looks at what it is doing and recompiles critical portion of codes in code faster to run based on the current environment and previous executions.
Bio: Clément Béra and Eliot Miranda has been working together on Cog's JIT performance for the last year. Clément Béra is a young engineer and has been working in the Pharo team for the past two years. Eliot Miranda is a Smalltalk VM expert who, among others, has implemented Cog's JIT and the Spur Memory Manager for Cog.
The document discusses various topics related to software development security including programming concepts, compilers and interpreters, procedural vs object-oriented programming, software development lifecycles, agile development methods, database security, and object-oriented design. It also covers assessing software security through vulnerabilities, maturity models, and testing as well as artificial intelligence techniques.
This document discusses replacing the use of $GLOBALS['TYPO3_DB'] with Doctrine DBAL for database queries in TYPO3 extensions. Doctrine DBAL provides a database abstraction layer that supports multiple database vendors, whereas $GLOBALS['TYPO3_DB'] only supports MySQL. Migrating to Doctrine DBAL offers benefits like a more reliable industry standard and easier API. The document provides examples of common queries like select, insert, update using the Doctrine query builder and highlights best practices for security and restrictions. $GLOBALS['TYPO3_DB'] will be removed in TYPO3 8 LTS, so extensions need to migrate to Doctrine DB
The document discusses various topics related to software development security including programming concepts, compilers and interpreters, procedural vs object-oriented programming, application development methods like waterfall vs agile, database security concepts, and assessing software vulnerabilities. It provides an overview of machine code, source code, and assembly language. It also describes compilers and interpreters, top-down vs bottom-up programming, open source vs proprietary software, and the software development lifecycle (SDLC) process.
Adding Support for Networking and Web Technologies to an Embedded System
These are the slides for a presentation we gave at Device Developer Conference 2014 in the UK. The presentation discusses the work done, experiences, and lessons learnt from adding an open source TCP/IP network stack and web server to an existing industrial control system running on an ARM Cortex M3-based processor from TI.
The presentation covers the following:
· Integrating the network stack into the existing software base
· Configuring and using the network stack and web server
· Adding support for HTTP basic authentication to restrict user access
· Using HTTP to remotely access the target system and retrieve operational data
· Debugging hints and tips
· Pitfalls to avoid and other lessons learnt
This document summarizes a presentation on using Azure Databricks to predict flight delays. It introduces Databricks, which has environments for SQL, data science/engineering, and machine learning. For the flight prediction scenario, historical flight data is loaded into Databricks and a decision tree model is trained to predict delays. The model is then used to score new flight data and results are analyzed in Power BI.
During 4 days, I presented a training session for the .Net team in Business & Decision Tunisia about Asp.net MVC.
In this training we talked about:
MVC as a design pattern the history and the utility
Microsoft’s approach in Asp.net MVC
What's new in MVC 4
Data Access in Asp.net MVC
How to secure an Asp.net application
Dependency Injection in Asp.net MVC
The document discusses the Model-View-Controller (MVC) design pattern, which separates an application's data (model), user interface (view), and logic that manipulates data and controls the application flow and behavior (controller). MVC promotes loose coupling, separation of concerns, testability, and reusable code. The key components - model, view, and controller - and their roles are defined. ASP.NET MVC framework is introduced as an alternative to Web Forms that follows the MVC pattern.
ZZ BC#7 asp.net mvc practice and guideline by NineMvp
This document provides an overview and agenda for an ASP.NET MVC practice and guidelines session. The agenda includes discussing MVC programming fundamentals like models, views, controllers and routes. It also covers NuGet, Entity Framework Code First, common UI libraries, the repository pattern, application layer architecture and dependency injection principles. The session includes demonstrations of these various ASP.NET MVC and software design topics.
DISQUS is a comment system that handles high volumes of traffic, with up to 17,000 requests per second and 250 million monthly visitors. They face challenges in unpredictable spikes in traffic and ensuring high availability. Their architecture includes over 100 servers split between web servers, databases, caching, and load balancing. They employ techniques like vertical and horizontal data partitioning, atomic updates, delayed signals, consistent caching, and feature flags to scale their large Django application.
Alluxio Webinar | 10x Faster Trino Queries on Your Data Platform
Alluxio Webinar
June. 18, 2024
For more Alluxio Events: https://www.alluxio.io/events/
Speaker:
- Jianjian Xie (Staff Software Engineer, Alluxio)
As Trino users increasingly rely on cloud object storage for retrieving data, speed and cloud cost have become major challenges. The separation of compute and storage creates latency challenges when querying datasets; scanning data between storage and compute tiers becomes I/O bound. On the other hand, cloud API costs related to GET/LIST operations and cross-region data transfer add up quickly.
The newly introduced Trino file system cache by Alluxio aims to overcome the above challenges. In this session, Jianjian will dive into Trino data caching strategies, the latest test results, and discuss the multi-level caching architecture. This architecture makes Trino 10x faster for data lakes of any scale, from GB to EB.
What you will learn:
- Challenges relating to the speed and costs of running Trino in the cloud
- The new Trino file system cache feature overview, including the latest development status and test results
- A multi-level cache framework for maximized speed, including Trino file system cache and Alluxio distributed cache
- Real-world cases, including a large online payment firm and a top ridesharing company
- The future roadmap of Trino file system cache and Trino-Alluxio integration
Break data silos with real-time connectivity using Confluent Cloud Connectors
Connectors integrate Apache Kafka® with external data systems, enabling you to move away from a brittle spaghetti architecture to one that is more streamlined, secure, and future-proof. However, if your team still spends multiple dev cycles building and managing connectors using just open source Kafka Connect, it’s time to consider a faster and cost-effective alternative.
Top 10 Tips To Get Google AdSense For Your Website
Lots of bloggers are using Google AdSense now. It’s getting really popular. With AdSense, bloggers can make money by showing ads on their websites. Read this important article written by the experienced designers of the best website designing company in Delhi –
You may all know that JSON is a subset of JavaScript, but… Did you know that HTML5 implements NoSQL databases? Did you know that JavaScript was recommended for REST by HTTP co-creator Roy T. Fielding himself? Did you know that map & reduce are part of the native JavaScript API? Did you know that most NoSQL solutions integrate a JavaScript engine? CouchDB, MongoDB, WakandaDB, ArangoDB, OrientDB, Riak…. And when they don’t, they have a shell client which does. The story of NoSQL and JavaScript goes beyond your expectations and opens more opportunities than you might imagine… What better match could you find than a flexible and dynamic language for schemaless databases? Isn’t an event-driven language what you’ve been waiting for to manage consistency? When NoSQL doesn’t come to JavaScript, JavaScript comes to NoSQL. And does it very well.
Evolution of MonogDB Sharding and Its Best Practices - Ranjith A - Mydbops TeamMydbops
The document discusses the evolution of MongoDB sharding from versions 3.6 to 5.0. It provides an overview of MongoDB sharding architecture including shards, mongos, and config servers. It describes the different types of sharding such as hashed sharding and ranged sharding. It also discusses important sharding concepts like choosing an appropriate shard key and the use of zones. Finally, it outlines major new features introduced in each version related to modifying shard keys, refining shard keys, and resharding collections.
Benchx: An XQuery benchmarking web application Andy Bunce
A system to record query performance of XQuery statements running on the BaseX http:basex.org XML database. It uses Angular on the client side and RESTXQ on the server.
Mongo DB: Fundamentals & Basics/ An Overview of MongoDB/ Mongo DB tutorialsSpringPeople
The document discusses MongoDB, an open-source document database. It provides an overview of MongoDB, including what it is, why it is used, its basic concepts like databases, collections, and documents, and how it compares to a relational database. It also covers MongoDB commands for creating and dropping collections, inserting, querying, and updating documents.
Rapid prototyping using azure functions - A walk on the wild sideSamrat Saha
My presentation at the 2016 Miwaukee .NET conference.
Talked about how I leveraged Azure Functions to rapidly prototype a product.
http://www.mkedotnet.com/sessions/azure-functions/
Working with MongoDB as MySQL DBA. Comparing commands from MongoDB to MySQL, similarities and differences. Exploring replication features, failover and recovery, adjusting the variables and checking status and using DML, DDL with different storage engines
This document provides an introduction to MongoDB, a popular document-oriented database. It discusses how MongoDB stores data in flexible, JSON-like documents rather than rigid tables. It also covers MongoDB's features like replication, sharding, indexing, querying, map-reduce functions and how it provides a scalable and flexible alternative to traditional relational databases. The document also discusses some of the theoretical underpinnings of non-relational databases like MongoDB, including the CAP theorem and ACID versus BASE models of data consistency.
This document summarizes YoctoDB, an embedded Java library for horizontally partitioned immutable databases developed by Yandex to power its classified search services. It provides very low latency and high throughput for indexing and querying large datasets by using an immutable data model with field-based filtering and sorting. It has improved performance versus Lucene for Yandex's auto search workloads, reducing latency percentiles and CPU usage. YoctoDB's data model and implementation provide benefits like simplified concurrency, fast reindexing, and no need for garbage collection tuning.
Putting the Go in MongoDB: How We Rebuilt The MongoDB Tools in GoMongoDB
With the release of MongoDB 3.0, the tools (mongodump, mongoimport, mongotop, etc) have been completely re-designed and re-written in Go to improve maintainability and performance. In this section, we'll give an architectural overview of the tools, describe how we used Go's native capacities to improve their parallelism, and also take a deep technical dive into their internals. We'll discuss performance, usability and integration improvements and share advanced techniques for power users. With a better understanding of how the tools work, you should feel comfortable effectively using and contributing to the tools.
This document provides an overview and introduction to MongoDB including:
- MongoDB installation using yum or binary, roles in MongoDB, and how to create users
- Basic MongoDB commands like use, show dbs, and dropDatabase
- Tracing slow queries using the database profiler and viewing results in the system.profile collection
- Important monitoring commands like db.serverStatus(), currentOp(), db.stats(), and replica set commands like rs.status() and rs.printReplicationInfo()
Use of No-SQL databases in web applications is becoming increasingly common. In part this is because they work well with rapid application development due to their schema-less nature. And partly because they scale well in a cloud-based environment without too much effort.
MongoDB is one of the many No-SQL database technologies available today. It's schema-less nature works very well with rapid application development nature of ColdFusion. Unlike other No-SQL databases, it offers the ability run arbitrary queries against databases without having to first write map-reduce functions. It also has some other interesting features like capped collections with asynchronous write ability.
In this session, Indy takes you through some common use-cases for considering MongoDB with ColdFusion applications, contrasting it with other No-SQL databases like CouchDB. And he shares his experiences of using it with cloud-based ColdFusion applications. The aim of the session is to provide an overview of using MongoDB with ColdFusion so that you have another tool to consider when working on your next web application.
This was presented at CFObjective, Melbourne, November 17-18, 2011.
Hekaton is SQL Server's in-memory optimized database engine for online transaction processing (OLTP) workloads. It uses lock-free data structures, multi-version concurrency control, and compiled Transact-SQL queries to provide high performance and scalability. Transaction logging and continuous checkpointing ensure data durability. Hekaton tables and indexes are optimized for memory residency, with hash indexes and Bw-tree indexes to support efficient lookups and updates.
CBDW2014 - NoSQL Development With Couchbase and ColdFusion (CFML)Ortus Solutions, Corp
NoSQL document stores are reinventing the way we design our databases and cache layers. Couchbase server is a unique offering with unparalleled performance, automatic replication and failover. In this session, we'll talk about how to get started with Couchbase using the open source CFML SDK as well as native caching via the Railo Couchbase Extension.
FITC presents: Mobile & offline data synchronization in Angular JSFITC
Save 10% off ANY FITC event with discount code 'slideshare'
See our upcoming events at www.fitc.ca
OVERVIEW
Are you building mobile or web applications with AngularJS and wish they would work when you were offline? You can read, send and delete mail from your mobile email client when you are offline, why not from your AngularJS app? AngularJS is completely agnostic when it comes to creating your data models. Let’s explore what is required to allow your application to be useful to your users even without an internet connection.
INTENDED AUDIENCE - BEGINNER - INTERMEDIATE
This presentation is for developers that know they are looking for offline and data synchronization capabilities. Or, possibly for managers that wish to have a greater understanding of what their options are in AngularJS to create such functionality.
Daniel Zen, CEO, Zen Digital
Daniel Zen is the CEO of Zen Digital, founder of the New York AngularJS Meetup, a frequent lecturer, and a former consultant for Google, Pivotal Labs and various Fortune 500 companies. Zen Digital uses Agile techniques to move projects forward while continuously integrating new code and ideas, producing elegant frontend experiences and efficient backend systems for web and mobile applications.
This document discusses using BaseX, an XML database, for web applications. It describes GraphXQ, which uses RESTXQ and Graphviz to visualize graphs. It also describes CellarXQ, an Angular.js single page application that uses BaseX and OAuth for user authentication and data storage. Finally, it shows how to create a chatbot using BaseX, Node.js and Socket.io that passes messages to an XQuery script for processing.
The document discusses various MongoDB command line tools and how to use them. It provides examples of using core tools like mongo, mongod, and mongostat to get database information and view performance metrics. Other tools covered include mongodump for backups, mongorestore for restores, mongoexport for data exports, and bsondump for document conversions. Third party tools like automongobackup and mongolog are also mentioned.
The document discusses MongoDB's new aggregation framework, which provides a declarative pipeline for performing data aggregation operations on complex documents. The framework allows users to describe a chain of operations without writing JavaScript. It will offer high-performance operators like $match, $project, $unwind, $group, $sort, and computed expressions to reshape and analyze document data without the overhead of JavaScript. The aggregation framework is nearing release and will support sharding by forwarding pipeline operations to shards and combining results.
Silicon Valley JUG - How to generate customized java 8 code from your databaseSpeedment, Inc.
The best code is the one you never need to write. Using code generation and automated builds you can minimize the risk of human error when developing software, but how do you maintain control over code when large parts of it is handed over to a machine? In this tutorial, you will learn how to use open-source software to create and control code automation. You will see how you can generate a completely object-oriented domain model by automatically analyzing your database schemas. Every aspect of the process is transparent and configurable, giving you as a developer 100% control of the generated code. This will not only increase your productivity, but also help you build safer and more maintainable Java applications.
How to generate customized java 8 code from your databaseSpeedment, Inc.
Did you know that database classes, that require many lines of Java and SQL code, may be replaced with a single line of Java 8 code? In this tutorial session you will learn how to use standard Java 8 Streams as an alternative to traditional Object Relational Mappers (ORM). We will use the open-source tool Speedment to show how development speed can be increased and how the application code can be more concise and run faster.
Running Airflow Workflows as ETL Processes on Hadoopclairvoyantllc
While working with Hadoop, you'll eventually encounter the need to schedule and run workflows to perform various operations like ingesting data or performing ETL. There are a number of tools available to assist you with this type of requirement and one such tool that we at Clairvoyant have been looking to use is Apache Airflow. Apache Airflow is an Apache Incubator project that allows you to programmatically create workflows through a python script. This provides a flexible and effective way to design your workflows with little code and setup. In this talk, we will discuss Apache Airflow and how we at Clairvoyant have utilized it for ETL pipelines on Hadoop.
JavaOne2016 - How to Generate Customized Java 8 Code from Your Database [TUT4...Speedment, Inc.
The best code is the one you never need to write. Using code generation and automated builds, you can minimize the risk of human error when developing software, but how do you maintain control over code when large parts of it are handed over to a machine? In this tutorial, you will learn how to use open source software to create and control code automation. You will see how you can generate a completely object-oriented domain model by automatically analyzing your database schemas. Every aspect of the process is transparent and configurable, giving you, as a developer, 100 percent control of the generated code. This will not only increase your productivity but also help you build safer, more maintainable Java applications and is a perfect solution for Microservices.
How to JavaOne 2016 - Generate Customized Java 8 Code from Your Database [TUT...Malin Weiss
The best code is the one you never need to write. Using code generation and automated builds, you can minimize the risk of human error when developing software, but how do you maintain control over code when large parts of it are handed over to a machine? In this tutorial, you will learn how to use open source software to create and control code automation. You will see how you can generate a completely object-oriented domain model by automatically analyzing your database schemas. Every aspect of the process is transparent and configurable, giving you, as a developer, 100 percent control of the generated code. This will not only increase your productivity but also help you build safer, more maintainable Java applications and is a perfect solution for Microservices.
The document provides an introduction to Typesafe Activator and the Play Framework. It discusses how Activator is a tool that helps developers get started with the Typesafe Reactive Platform and Play applications. It also covers some core features of Play like routing, templates, assets, data access with Slick and JSON, and concurrency with Futures, Actors, and WebSockets.
This is from a 2 hour talk introducing in-memory databases. First a look at traditional RDBMS architecture and some of it's limitations, then a look at some in-memory products and finally a closer look at OrigoDB, the open source in-memory database toolkit for NET/Mono.
This document discusses various technologies related to architectures, frameworks, infrastructure, services, data stores, analytics, logging and metrics. It covers Java 8 features like lambda expressions and method references. It also discusses microservices, Spring Boot basics and features, Gradle vs Maven, Swagger, AngularJS, Gulp, Jasmine, Karma, Nginx, CloudFront, Couchbase, Lambda Architecture, logging with Fluentd and Elasticsearch, metrics collection with Collectd and Statsd, and visualization with Graphite and Grafana.
This document summarizes the experiences of operating Rails websites at stable scale. It discusses using virtualization to run multiple websites on a single server. It provides tips for optimizing performance including database tuning, adding indexes, log rotation, and restarting Mongrel processes periodically. New Rails sites are launched using the newest framework versions and different web servers like Passenger are tested for performance.
This chapter discusses software development security. It covers topics like programming concepts, compilers and interpreters, procedural vs object-oriented languages, application development methods like waterfall vs agile models, databases, object-oriented design, assessing software vulnerabilities, and artificial intelligence techniques. The key aspects are securing the entire software development lifecycle from initial planning through operation and disposal, using secure coding practices, testing for vulnerabilities, and continually improving processes.
Title: Sista: Improving Cog’s JIT performance
Speaker: Clément Béra
Thu, August 21, 9:45am – 10:30am
Video Part1
https://www.youtube.com/watch?v=X4E_FoLysJg
Video Part2
https://www.youtube.com/watch?v=gZOk3qojoVE
Description
Abstract: Although recent improvements of the Cog VM performance made it one of the fastest available Smalltalk virtual machine, the overhead compared to optimized C code remains important. Efficient industrial object oriented virtual machine, such as Javascript V8's engine for Google Chrome and Oracle Java Hotspot can reach on many benchs the performance of optimized C code thanks to adaptive optimizations performed their JIT compilers. The VM becomes then cleverer, and after executing numerous times the same portion of codes, it stops the code execution, looks at what it is doing and recompiles critical portion of codes in code faster to run based on the current environment and previous executions.
Bio: Clément Béra and Eliot Miranda has been working together on Cog's JIT performance for the last year. Clément Béra is a young engineer and has been working in the Pharo team for the past two years. Eliot Miranda is a Smalltalk VM expert who, among others, has implemented Cog's JIT and the Spur Memory Manager for Cog.
CISSP Prep: Ch 9. Software Development SecuritySam Bowne
The document discusses various topics related to software development security including programming concepts, compilers and interpreters, procedural vs object-oriented programming, software development lifecycles, agile development methods, database security, and object-oriented design. It also covers assessing software security through vulnerabilities, maturity models, and testing as well as artificial intelligence techniques.
This document discusses replacing the use of $GLOBALS['TYPO3_DB'] with Doctrine DBAL for database queries in TYPO3 extensions. Doctrine DBAL provides a database abstraction layer that supports multiple database vendors, whereas $GLOBALS['TYPO3_DB'] only supports MySQL. Migrating to Doctrine DBAL offers benefits like a more reliable industry standard and easier API. The document provides examples of common queries like select, insert, update using the Doctrine query builder and highlights best practices for security and restrictions. $GLOBALS['TYPO3_DB'] will be removed in TYPO3 8 LTS, so extensions need to migrate to Doctrine DB
The document discusses various topics related to software development security including programming concepts, compilers and interpreters, procedural vs object-oriented programming, application development methods like waterfall vs agile, database security concepts, and assessing software vulnerabilities. It provides an overview of machine code, source code, and assembly language. It also describes compilers and interpreters, top-down vs bottom-up programming, open source vs proprietary software, and the software development lifecycle (SDLC) process.
Adding Support for Networking and Web Technologies to an Embedded SystemJohn Efstathiades
These are the slides for a presentation we gave at Device Developer Conference 2014 in the UK. The presentation discusses the work done, experiences, and lessons learnt from adding an open source TCP/IP network stack and web server to an existing industrial control system running on an ARM Cortex M3-based processor from TI.
The presentation covers the following:
· Integrating the network stack into the existing software base
· Configuring and using the network stack and web server
· Adding support for HTTP basic authentication to restrict user access
· Using HTTP to remotely access the target system and retrieve operational data
· Debugging hints and tips
· Pitfalls to avoid and other lessons learnt
This document summarizes a presentation on using Azure Databricks to predict flight delays. It introduces Databricks, which has environments for SQL, data science/engineering, and machine learning. For the flight prediction scenario, historical flight data is loaded into Databricks and a decision tree model is trained to predict delays. The model is then used to score new flight data and results are analyzed in Power BI.
During 4 days, I presented a training session for the .Net team in Business & Decision Tunisia about Asp.net MVC.
In this training we talked about:
MVC as a design pattern the history and the utility
Microsoft’s approach in Asp.net MVC
What's new in MVC 4
Data Access in Asp.net MVC
How to secure an Asp.net application
Dependency Injection in Asp.net MVC
The document discusses the Model-View-Controller (MVC) design pattern, which separates an application's data (model), user interface (view), and logic that manipulates data and controls the application flow and behavior (controller). MVC promotes loose coupling, separation of concerns, testability, and reusable code. The key components - model, view, and controller - and their roles are defined. ASP.NET MVC framework is introduced as an alternative to Web Forms that follows the MVC pattern.
This document provides an overview and agenda for an ASP.NET MVC practice and guidelines session. The agenda includes discussing MVC programming fundamentals like models, views, controllers and routes. It also covers NuGet, Entity Framework Code First, common UI libraries, the repository pattern, application layer architecture and dependency injection principles. The session includes demonstrations of these various ASP.NET MVC and software design topics.
DISQUS is a comment system that handles high volumes of traffic, with up to 17,000 requests per second and 250 million monthly visitors. They face challenges in unpredictable spikes in traffic and ensuring high availability. Their architecture includes over 100 servers split between web servers, databases, caching, and load balancing. They employ techniques like vertical and horizontal data partitioning, atomic updates, delayed signals, consistent caching, and feature flags to scale their large Django application.
Alluxio Webinar | 10x Faster Trino Queries on Your Data PlatformAlluxio, Inc.
Alluxio Webinar
June. 18, 2024
For more Alluxio Events: https://www.alluxio.io/events/
Speaker:
- Jianjian Xie (Staff Software Engineer, Alluxio)
As Trino users increasingly rely on cloud object storage for retrieving data, speed and cloud cost have become major challenges. The separation of compute and storage creates latency challenges when querying datasets; scanning data between storage and compute tiers becomes I/O bound. On the other hand, cloud API costs related to GET/LIST operations and cross-region data transfer add up quickly.
The newly introduced Trino file system cache by Alluxio aims to overcome the above challenges. In this session, Jianjian will dive into Trino data caching strategies, the latest test results, and discuss the multi-level caching architecture. This architecture makes Trino 10x faster for data lakes of any scale, from GB to EB.
What you will learn:
- Challenges relating to the speed and costs of running Trino in the cloud
- The new Trino file system cache feature overview, including the latest development status and test results
- A multi-level cache framework for maximized speed, including Trino file system cache and Alluxio distributed cache
- Real-world cases, including a large online payment firm and a top ridesharing company
- The future roadmap of Trino file system cache and Trino-Alluxio integration
Break data silos with real-time connectivity using Confluent Cloud Connectorsconfluent
Connectors integrate Apache Kafka® with external data systems, enabling you to move away from a brittle spaghetti architecture to one that is more streamlined, secure, and future-proof. However, if your team still spends multiple dev cycles building and managing connectors using just open source Kafka Connect, it’s time to consider a faster and cost-effective alternative.
Lots of bloggers are using Google AdSense now. It’s getting really popular. With AdSense, bloggers can make money by showing ads on their websites. Read this important article written by the experienced designers of the best website designing company in Delhi –
Ansys Mechanical enables you to solve complex structural engineering problems and make better, faster design decisions. With the finite element analysis (FEA) solvers available in the suite, you can customize and automate solutions for your structural mechanics problems and parameterize them to analyze multiple design scenarios. Ansys Mechanical is a dynamic tool that has a complete range of analysis tools.
WhatsApp Tracker - Tracking WhatsApp to Boost Online Safety.pdfonemonitarsoftware
WhatsApp Tracker Software is an effective tool for remotely tracking the target’s WhatsApp activities. It allows users to monitor their loved one’s online behavior to ensure appropriate interactions for responsive device use.
Download this PPTX file and share this information to others.
A captivating AI chatbot PowerPoint presentation is made with a striking backdrop in order to attract a wider audience. Select this template featuring several AI chatbot visuals to boost audience engagement and spontaneity. With the aid of this multi-colored template, you may make a compelling presentation and get extra bonuses. To easily elucidate your ideas, choose a typeface with vibrant colors. You can include your data regarding utilizing the chatbot methodology to the remaining half of the template.
Seamless PostgreSQL to Snowflake Data Transfer in 8 Simple StepsEstuary Flow
Unlock the full potential of your data by effortlessly migrating from PostgreSQL to Snowflake, the leading cloud data warehouse. This comprehensive guide presents an easy-to-follow 8-step process using Estuary Flow, an open-source data operations platform designed to simplify data pipelines.
Discover how to seamlessly transfer your PostgreSQL data to Snowflake, leveraging Estuary Flow's intuitive interface and powerful real-time replication capabilities. Harness the power of both platforms to create a robust data ecosystem that drives business intelligence, analytics, and data-driven decision-making.
Key Takeaways:
1. Effortless Migration: Learn how to migrate your PostgreSQL data to Snowflake in 8 simple steps, even with limited technical expertise.
2. Real-Time Insights: Achieve near-instantaneous data syncing for up-to-the-minute analytics and reporting.
3. Cost-Effective Solution: Lower your total cost of ownership (TCO) with Estuary Flow's efficient and scalable architecture.
4. Seamless Integration: Combine the strengths of PostgreSQL's transactional power with Snowflake's cloud-native scalability and data warehousing features.
Don't miss out on this opportunity to unlock the full potential of your data. Read & Download this comprehensive guide now and embark on a seamless data journey from PostgreSQL to Snowflake with Estuary Flow!
Try it Free: https://dashboard.estuary.dev/register
2. Robert Friberg
• Design, build and maintain systems for clients at Devrex
• Trainer – Microsoft NET, SQL Server, java, perl, python, linux
• Machine learning, AI
• Squash fanatic
• @robertfriberg, robert@devrexlabs.com
3. Why?
Service
Layer
Domain
Layer
Data Access
Layer
Relational
Model
Views/SP’s
Build faster systems faster
4. What is OrigoDB?
• In-memory database toolkit
• Code and data in same process
• Write-ahead command logging and snapshots
• Open Source single DLL for NET/Mono
• Commercial server with mirror replication
5. How does it work?
.NET Process Storage
Handles queries and
commands, guards
model
Engine
1. AppendToLog
2. Execute
command
PlaceOrderCommand
Snapshot
Snapshot
Client code
passes commands
and queries
PlaceOrderCommand
NewCustomerCommand
IncreaseInventoryLevelCommand
PlaceOrderCommand
PlaceOrderCommand
time
In-memory
Model
6. Demand drives change
• Performance
• Data volume
• Scalability
• Availability
• Modeling
• NoSQL
• Big data
• Graph
• Real time analytics
• In-memory computing
• Column stores
One size (RDBMS) no longer fits all
Polyglot Persistence
7. B-trees and Transactions
LOG
• Fill factor
• Page splits
• Clustered index
• Checkpoint
DATA 64KB blocks w 8x8KB pages
Logical BTREE of 8kb data pages
In the buffer pool (cache)
Buffer
Manager
Transactions append inserted, deleted, original and modified pages to the LOG
8. When?
• Whenever data fits in RAM
• Alternative to general RDBMS OLAP/OLTP
• Complex models and transactions
• In-memory analytics
• Traceability requirements (complete history of events)
17. Silly Relational
[Serializable]
public class RelationalModel : Model
{
private DataSet _dataset;
public RelationalModel()
{
_dataset = new DataSet();
}
//... ExecuteQuery and ExecuteCommand omitted
}
19. Domain specific relational
[Serializable]
public class Model : Model
{
SortedDictionary<int,Customer> _customers;
SortedDictionary<int,Order> _orders;
SortedDictionary<int,Product> _products;
SortedDictionary<string,Customer> _customersByName;
}
[Serializable]
public class Order {
public int CustomerId; //foreign key vs. reference
}
20. JS interpreter hosting (V8)
[Serializable]
public class JurassicModel : Model
{
private ScriptEngine _scriptEngine;
public JurassicModel()
{
_scriptEngine = new ScriptEngine();
_scriptEngine.Execute("var model = {}");
}
//... ExecuteQuery and ExecuteCommand omitted
}
21. Commands
• Serial execution
• Exclusive access to the model
• Transition the model from one valid state to the next
s0 t s1 s2 1 t2
22. Command guidelines
• No side effects or external actions
• No external dependencies
• Unhandled exceptions trigger rollback (full restore)
• Call Command.Abort() to signal exception
23. The model is an object graph
TaskList
Task
Task
Task
TaskList
Task
Task
Task
Task
Category
Category
Category
Category
TaskModel
28. Automated Test alternatives
• Transparent testing of domain behavior: entities, model
• Test commands, queries, entities on model without engine
• Test with in-memory storage
• Full stack testing – slow, requires cleanup
29. In-memory storage
• Non persistent command journal and snapshots
• Mimics FileStore using MemoryStreams
• Tests serialization/identity issues
var config = EngineConfiguration.Create().ForIsolatedTest();
OR:
config.SetCommandStoreFactory(cfg => new InMemoryCommandStore(cfg));
config.SetSnapshotStoreFactory(cfg => new InMemorySnapshotStore(cfg));
33. Engine.For<M>()
• Returns IEngine<M>() or derivative
• Reuse based on EngineConfiguration.Location property
• Remote or in-process
• ILocalEngineClient<M>
• IRemoteEngineClient<M>
• Running engines are tracked by Config.Engines
35. x64 vs. x32
• Core Library compiled with AnyCPU
• x32 = 32-bit pointers, max 4GB
• x64 = 64-bit pointers
• Server ships with x64 and x32 binaries
36. IIS Hosting
• Disable application pool recycling
• Ensure single process, no farming or LB
• Litter controllers with Db.For<M>() / Engine.For<M>()
• Or put a static ref somewhere, eg Global.asax
37. Proxy
• Proxy has same interface as the Model
• Method calls are intercepted
• void methods interpreted as commands (and logged)
• other methods interpreted as queries
• Can be overriden with attributes
• Local or remote, cluster
38. Demo: Let’s build a key/value store
• New project
• Reference origodb.core
• Define KeyValueStoreModel
• void Put(key, value)
• object Get(key,value)
• bool Exists(key, value)
• bool Remove(key,value)
• Add some unit tests
41. EngineConfiguration.Location property
• File location for FileStorage
• Connection string when SqlStorage
• Defaults (when null)
• Will look in app.config for connection string
• Type name of model
• Current working directory
• App_Data in web context
• Magic
• mode=remote;host=10.0.0.20;port=3001
42. Persistence modes
• Journaling (default)
• SnapshotPerTransaction
• ManualSnapshots
var config = EngineConfiguration.Create();
config.PersistenceMode = PersistenceMode.SnapshotPerTransaction;
var db = Engine.For<MyModel>(config);
43. Kernels
• OptimisticKernel (default)
• RoyalFoodTaster
var config = EngineConfiguration.Create();
config.Kernel = Kernels.RoyalFoodTaster;
var db = Db.For<MyModel>(config);
46. ProtobufFormatter
• Protocol Buffers by Google
• IFormatter wrapper around protobuf-net by @marcgravell
• Contract based as opposed to embedded metadata
• Compact, fast, loose coupling, cross platform
• Configure with attributes or code
• Use it!
47. Protobuf: Attribute based configuration
[ProtoContract]
public class Company
{
[ProtoMember(1)]
public string Name { get; set; }
[ProtoMember(2)]
public List<Employee> Employees { get; set; }
}
58. OrigoDB Server
• Console Application or Windows Service
• Process hosting single Engine / Model
• Ad-hoc Linq / Razor queries
• Javascript API
• Primitive web based UI
• Commercial License
• Multiserver replication
60. Lab M6
• Follow the OrigoDB Server online tutorial
http://origodb.com/
61. Thank you for listening!
• http://origodb.com
• http://dev.origodb.com
• http://github.com/devrexlabs
• http://geekstream.devrexlabs.com
• @robertfriberg, @devrexlabs
Editor's Notes
What is it? How does it work? Who built it and why? When does it shine? When does it suck?
What if we just keep all the data in RAM?
Moving back and forth and mapping is silly.
Code and data in same process.
Productivity
Simplicity
Consistency
Testability
Strongly typed, compile time checked
Operations
Capturing the essence..
In-memory
In-memory object graph, user defined. Probably collections, entities and references.
Your choice.
Is it a database? Is it an object database? Linq queries.
Toolkit
Flexible, configurable, kernels, storage, data model, persistence modes, formatting
Bring your own model. – this is key.
Usually a product based on a specific data model. VoltDB, Raven
Naming. LiveDomain -> LiveDB -> OrigoDB
Code and data in same process
Don’t do CRUD. It’s silly. ORMS are based on crud.
One of the first thing you learn is don’t do SELECT *. EF
Command logging
The in-memory data is a projection of the commands,
compare ES with a single aggregate. Same benefits as ES.
Requires NET 4.0
What is OrigoDB?
OrigoDB is an in-memory database toolkit. The core component is the Engine. The engine is 100% ACID, runs in-process and hosts a user defined data model. The data model can be domain specific or generic and is defined using plain old NET types. Persistence is based on snapshots and write-ahead command logging to the underlying storage.
The Model
is an instance of the user defined data model
lives in RAM only
is the data
is a projection of the entire sequence of commands applied to the initial model, usually empty.
can only be accessed through the engine
The Client
has no direct reference to the model
interacts directly with the Engine either in-process or remote
or indirectly via a proxy with the same interface as the model
passes query and command objects to the engine
The Engine
The Engine encapsulates an instance of the model and is responsible for atomicity, consistency, isolation and durability. It performs the following tasks:
writes commands to the journal
executes commands and queries
reads and writes snapshots
restores the model on startup
We call it a toolkit because you have a lot of options
Modelling - define your own model or use an existing one. Generic or domain specific. It’s up to you.
Storage - Default is FileStore. SqlStore or write your own module.
Data format - Choose wire and storage format by plugging in different IFormatter implementations. Binary, JSON, ProtoBuf, etc
Read more in the docs on Extensibility
Design goals
Our initial design goals were focused on rapid development, testability, simplicity, correctness, modularity, flexibility and extensibility. Performance was never a goal but running in-memory with memory optimized data structures outperforms any disk oriented system. But of course a lot of optimization is possible.
Performance –> in-memory, specialization
Data volume -> sharding, partitioning
Availability -> redundancy
Mångfald, det händer saker.
Fi
B-TREE, 8kb block, buffer pool, animering av en transaktion. Column stores
Varje tabell är en B-TREE (om den inte är en HEAP), varje index är en b-tree
Effect logging – log the effect of the transaction = modified pages, new pages
Support rollback by including deleted pages and original version of modified page.
Simplicity and all that comes with it. 40% less code. Reason enough.
Low latency queries, heavy load querying
With event sourcing, polyglot persistence. Build a read model from an event stream
Complex domain models: Because a trivial model is trivial to ORM, RDBMS. Difficult to model relationally
An in-memory instance of the Model is the data.
Commands are like Stored Procedures
Queries are like Views
Ad-hoc LINQ
A quick example
Show the web site, search, show about, mention github, show some code
approx 500’ articles
Not necessarily data
Sole purpose is to update the state of the model, from one state to another.
Avoid embedding entities and graphs, regard commands as simple messages.
Lambdas won’t serialize – local process only
Results get cloned unless otherwise specified.
Show the model, the entities, the commands. Queries/lambdas in controllers. Show hosting in global.asax
Describe the In-memory store and config for isolated test
Depends on where the logic is, commands or model or both
Test with storage exercises serialization, use to ensure serialization and isolation
Full stack as smoke tests and to verify configuration or framework related behavior
Considerations when hosting the in-process engine and model.
Lifecycle
Snapshots, direct interaction, Dispose, plenty of overloads taking config, config-string, initial model
Abstraction for convenience
Thread safe execute overloads
Or – demonstrate geeksream
Considerations when hosting the in-process engine and model.
Lifecycle
Explain each briefly
Pretty messy, leaky abstractions, needs redesign. Any takers?
Authorizer uses IPrincical and Roles of current thread identity.
Synchronizer unimportant, ReaderWriterLockSlim default
SqlStorage, EventStoreStore, Azure TableStorage for snapshots
BinaryFormatter, JsonFormatter, ProtobufFormatter
Compare with BinaryFormatter, Reflection
Use it: In production, let the design stabilize first
Considerations when hosting the in-process engine and model.
Lifecycle
Write transactions are serialized without blocking readers. Reader gets the most recent state.
This is an animated slide
_tasks.ToArray() creates a new array, thus no way to modify the _tasks array.
AddTask() returns a new TodoModel instance, thus it is immutable
Strings are immutable. The strings are shared among consecutive instances of TodoModel
Could have had an IsCompleted() method and assert !IsCompleted() in the Complete method. But the point is that instances of Task are immutable.
Notice base class and out parameter on execute
Considerations when hosting the in-process engine and model.
Lifecycle