This slide-set gives a brief overview of the Enonic Content Repository, part of Enonic eXperience Platform. This was a lightning talk at Elastic{ON} 2015 by Runar Myklebust.
The project is open source and can be found on http://github.com/enonic/xp
MongoDB is a scalable, high-performance, open-source NoSQL database that stores data in flexible, JSON-like documents. It is used by organizations of all sizes for applications where low latency and high availability are important. MongoDB is document-based, schemaless, and supports high performance, horizontal scalability through sharding and replication.
MySQL Without The SQL -- Oh My! PHP Detroit July 2018Dave Stokes
MySQL 8 can be used as a NoSQL JSON document store and with the new X DEVapi you can stop embedding SQL strings in your PHP code. Plus you can also access and JOIN SQL tables
A presentation by Aicha Khabil (Responsable IT à l'université Alger 3) done during the 11th edition of Algiers Tech Meetup on October 8th 2016, at Djezzy Training Center (Algiers)
This document provides an introduction to MongoDB, including:
1) MongoDB is a schemaless database that supports features like replication, sharding, indexing, file storage, and aggregation.
2) The main concepts include databases containing collections of documents like tables containing rows in SQL databases, but documents can have different structures.
3) Examples demonstrate inserting, querying, updating, and embedding documents in MongoDB collections.
Code Camp - Building a Glass app with Wakandatroxell
A description of using the Mirror API (Google) and WakandaDB.
Source code here: https://github.com/lyle/GlassWakanda
Original Reveil Slides: http://talks-2013.lyle.troxell.com/
Scala.js compiles to JavaScript with two major goals in mind: interoperability with JavaScript libraries, and portability with respect to Scala/JVM.
With the rise of WebAssembly as an alternative to JavaScript in the browser, one cannot help but wonder whether we could compile Scala.js to WebAssembly, with the promise of better performance. Unfortunately, WebAssembly quickly appears as a siren, and the path to it navigates between Charybdis and Scylla, the threats to interoperability and portability.
Watch in this, you will explore a whole lot of features of Scala to build a simple front-end application using Scala.js. And if you are developing any web application in Scala, you don’t need to sacrifice javascript interoperability.
This talk is quick reference of all the different queerability options that MongoDB offers to developers that want to build mobile and geospatial referenced applications. We reviewed the basic functionality but also recent improvements in the query and indexation engine of MongoDB geospatial features
MongoDB is a scalable, high-performance, open-source NoSQL database that stores data in flexible, JSON-like documents. It is used by organizations of all sizes for applications where low latency and high availability are important. MongoDB is document-based, schemaless, and supports high performance, horizontal scalability through sharding and replication.
MySQL Without The SQL -- Oh My! PHP Detroit July 2018Dave Stokes
MySQL 8 can be used as a NoSQL JSON document store and with the new X DEVapi you can stop embedding SQL strings in your PHP code. Plus you can also access and JOIN SQL tables
A presentation by Aicha Khabil (Responsable IT à l'université Alger 3) done during the 11th edition of Algiers Tech Meetup on October 8th 2016, at Djezzy Training Center (Algiers)
This document provides an introduction to MongoDB, including:
1) MongoDB is a schemaless database that supports features like replication, sharding, indexing, file storage, and aggregation.
2) The main concepts include databases containing collections of documents like tables containing rows in SQL databases, but documents can have different structures.
3) Examples demonstrate inserting, querying, updating, and embedding documents in MongoDB collections.
Code Camp - Building a Glass app with Wakandatroxell
A description of using the Mirror API (Google) and WakandaDB.
Source code here: https://github.com/lyle/GlassWakanda
Original Reveil Slides: http://talks-2013.lyle.troxell.com/
Scala.js compiles to JavaScript with two major goals in mind: interoperability with JavaScript libraries, and portability with respect to Scala/JVM.
With the rise of WebAssembly as an alternative to JavaScript in the browser, one cannot help but wonder whether we could compile Scala.js to WebAssembly, with the promise of better performance. Unfortunately, WebAssembly quickly appears as a siren, and the path to it navigates between Charybdis and Scylla, the threats to interoperability and portability.
Watch in this, you will explore a whole lot of features of Scala to build a simple front-end application using Scala.js. And if you are developing any web application in Scala, you don’t need to sacrifice javascript interoperability.
This talk is quick reference of all the different queerability options that MongoDB offers to developers that want to build mobile and geospatial referenced applications. We reviewed the basic functionality but also recent improvements in the query and indexation engine of MongoDB geospatial features
This document summarizes MongoDB's geospatial features including 2d and 2dsphere indexing, GeoJSON support for lines and polygons, and geospatial aggregation. It provides examples of querying points and geometries within regions, near points, and intersecting geometries. Future plans include additional geospatial predicates and indexing composite shapes.
ENIB 2015 2016 - CAI Web S02E03 - Forge JS 2/4 - MongoDB and NoSQLHoracio Gonzalez
This document provides an introduction and overview of MongoDB and how to use it. Some key points:
- MongoDB is an open-source document database that provides high performance, high availability, and automatic scaling. It uses documents (similar to JSON objects) rather than tables and rows.
- Documents are stored in collections without a predefined schema. Fields can be added, modified or deleted at any time.
- Common operations include inserting, querying, updating, and removing documents from collections. Queries can use filters, projections, sorting, skips, limits, and regular expressions.
- MongoDB is flexible compared to relational databases as schemas are not rigidly defined. It is suitable for high performance applications that need
ENIB 2015-2016 - CAI Web - S01E01- MongoDB and NoSQLHoracio Gonzalez
This document provides an introduction and overview of MongoDB and NoSQL databases. It discusses key MongoDB concepts like document databases, collections and documents. It also covers how to install and run MongoDB, insert and query data, and use common operations. Some examples show how to create indexes, use JavaScript and regex queries. Exercises at the end propose practicing installing MongoDB, creating a collection and querying data.
Basic class definitions begin with the keyword class, followed by a class name, followed by a pair of curly braces which enclose the definitions of the properties and methods belonging to the class.
The class name can be any valid label which is not a PHP reserved word. A valid class name starts with a letter or underscore, followed by any number of letters, numbers, or underscores. As a regular expression, it would be expressed thus: [a-zA-Z_\x7f-\xff][a-zA-Z0-9_\x7f-\xff]*.
http://vibranttechnologies.co.in/
MongoDB is an open source NoSQL database that uses JSON-like documents with dynamic schemas (BSON format) instead of using tables as in SQL. It allows for embedding related data and flexible querying of this embedded data. Some key features include using JavaScript-style documents, scaling horizontally on commodity hardware, and supporting various languages through its driver interface.
Сергей Матвеенко: MongoEngine: NoORM for NoSQLit-people
This document summarizes MongoEngine, an ORM (object-relational mapper) for working with MongoDB in Python. It introduces MongoDB as a scalable, high-performance, document-oriented NoSQL database. It compares MongoDB to RDBMS and shows how MongoEngine allows defining schemas and querying/updating data similarly to an ORM for SQL, while still maintaining flexibility of MongoDB. It provides examples of defining schemas using MongoEngine classes, querying data, updating documents, and how MongoEngine interacts with PyMongo and MongoDB under the hood. It also briefly discusses performance and integration with Django.
This document describes how to use jQuery DataTables to dynamically display data from a MongoDB database. It includes code snippets for setting up the HTML table structure, initializing DataTables with JavaScript, and creating a Java servlet to retrieve data from MongoDB and return it in JSON format for population into the table. The servlet queries the MongoDB collection, converts the results to a JSON string, and returns it to the calling page to populate the DataTables initialization. This allows dynamic loading and display of tabular data from a MongoDB database into an HTML table using jQuery DataTables.
This document discusses ING's use of Elasticsearch for distributed tracing across its systems. It provides context on ING as a company with many DevOps teams and systems. It then summarizes how Elasticsearch is used to collect and correlate logs and events from different systems using a unique request ID. Statistics are given on the volume of events ingested and queries. Future plans are outlined to expand the data sources and integrate with other tools to provide more insights.
Changing Your Mindset: Getting Started With Test-Driven DevelopmentViget Labs
This document provides an overview of test-driven development (TDD) and how to get started with it. It discusses the TDD process of writing a failing test first, then code to pass that test, and refactoring. Examples show how to write tests using Test::Unit, use stubs and mocks with Mocha, and address common pitfalls like over-mocking or non-descriptive test names. The document also covers integrating tests with Rake, using expectations as tests, and analyzing test coverage with tools like RCov.
Getting Started with MongoDB and Node.jsGrant Goodale
Node.js is an application engine for scalable network applications. It uses an event-driven, non-blocking I/O model that makes it lightweight and efficient, especially for real-time applications that require high-concurrency. MongoDB is a popular document database that uses JSON-like documents with dynamic schemas. Node.js and MongoDB are a good fit together because they are both fast, use JavaScript, and understand JSON documents. The document provides an introduction to getting started with Node.js and MongoDB by explaining what they are, how they work together well, and how to set them up on your system.
So you are considering going agile, huh? Your biggest question is probably "where do I start"? This session will help you answer that question and get you started down the road to agility . Mike will explore how to choose your first project and ensure that the pilot team is setup for success. He will talk through common organizational challenges and show you how to overcome them. You'll leave this talk with the knowledge necessary to get your first team going while laying the foundation to build on that success.
This document provides an overview of version control using Subversion (SVN). It discusses key SVN concepts like the trunk, branches, and tags. It explains how SVN allows for collaboration between developers and management of code revisions. The document also summarizes SVN features like authentication, revision management, tagging for releases, and advanced topics like hooks and externals.
This document summarizes techniques for optimizing Logstash and Rsyslog for high volume log ingestion into Elasticsearch. It discusses using Logstash and Rsyslog to ingest logs via TCP and JSON parsing, applying filters like grok and mutate, and outputting to Elasticsearch. It also covers Elasticsearch tuning including refresh rate, doc values, indexing performance, and using time-based indices on hot and cold nodes. Benchmark results show Logstash and Rsyslog can handle thousands of events per second with appropriate configuration.
I made a simple SVN (Subversion) tutorial for my co-workers and just wanted to share it with you. It is based on other lectures and practical experience I had in the past.
Some ideas also come from the GIT world, which is still too far and new for everyone, but which I already love and embrace fully :)
ElasticSearch introduction talk. Overview of the API, functionality, use cases. What can be achieved, how to scale? What is Kibana, how it can benefit your business.
This document discusses Elasticsearch, including understanding how it works and optimizing performance. It covers Elasticsearch concepts like clusters, indexes, shards and nodes. It also discusses installing and configuring Elasticsearch, modeling data, indexing and querying optimizations. Lastly it discusses integrating Elasticsearch with Hadoop and using SQL on Elasticsearch.
Building a Dataset Search Engine with Spark and Elasticsearch: Spark Summit E...Spark Summit
Elasticsearch provides native integration with Apache Spark through ES-Hadoop. However, especially during development, it is at best cumbersome to have Elasticsearch running in a separate machine/instance. Leveraging Spark Cluster with Elasticsearch Inside it is possible to run an embedded instance of Elasticsearch in the driver node of a Spark Cluster. This opens up new opportunities to develop cutting-edge applications. One such application is Dataset Search.
Oscar will give a demo of a Dataset Search Engine built on Spark Cluster with Elasticsearch Inside. Motivation is that once Elasticsearch is running on Spark it becomes possible and interesting to have the Elasticsearch in-memory instance join an (existing) Elasticsearch cluster. And this in turn enables indexing of Datasets that are processed as part of Data Pipelines running on Spark. Dataset Search and Data Management are R&D topics that should be of interest to Spark Summit East attendees who are looking for a way to organize their Data Lake and make it searchable.
Real-Time Data Exploration and Analytics with Amazon Elasticsearch ServiceAmazon Web Services
Elasticsearch is a fully featured search engine used for real-time analytics, and Amazon Elasticsearch Service makes it easy to deploy Elasticsearch clusters on AWS. With Amazon ES, you can ingest and process billions of events per day, and explore the data using Kibana to discover patterns. In this session, we use Apache web logs as example and show you how to build an end-to-end analytics solution.
Content marketing careers are constantly evolving, but one thing is certain: The power of LinkedIn for personal branding and career advancement is here to stay. Of course, because so many people rely on LinkedIn for professional networking these days, it’s essential to create a profile that will help you stand out and get noticed by the people who make hiring decisions in your industry. It’s not an easy task, but it can be
done – with the help of some pro-level tips for strengthening your LinkedIn presence and gaining an edge over the competition. If your “Who’s Viewed Your Profile” chart is flatlining week after week, the advice below will help breathe new life into your profile, improve your visibility in search results, generate more views, and impress your audience.
This document summarizes MongoDB's geospatial features including 2d and 2dsphere indexing, GeoJSON support for lines and polygons, and geospatial aggregation. It provides examples of querying points and geometries within regions, near points, and intersecting geometries. Future plans include additional geospatial predicates and indexing composite shapes.
ENIB 2015 2016 - CAI Web S02E03 - Forge JS 2/4 - MongoDB and NoSQLHoracio Gonzalez
This document provides an introduction and overview of MongoDB and how to use it. Some key points:
- MongoDB is an open-source document database that provides high performance, high availability, and automatic scaling. It uses documents (similar to JSON objects) rather than tables and rows.
- Documents are stored in collections without a predefined schema. Fields can be added, modified or deleted at any time.
- Common operations include inserting, querying, updating, and removing documents from collections. Queries can use filters, projections, sorting, skips, limits, and regular expressions.
- MongoDB is flexible compared to relational databases as schemas are not rigidly defined. It is suitable for high performance applications that need
ENIB 2015-2016 - CAI Web - S01E01- MongoDB and NoSQLHoracio Gonzalez
This document provides an introduction and overview of MongoDB and NoSQL databases. It discusses key MongoDB concepts like document databases, collections and documents. It also covers how to install and run MongoDB, insert and query data, and use common operations. Some examples show how to create indexes, use JavaScript and regex queries. Exercises at the end propose practicing installing MongoDB, creating a collection and querying data.
Basic class definitions begin with the keyword class, followed by a class name, followed by a pair of curly braces which enclose the definitions of the properties and methods belonging to the class.
The class name can be any valid label which is not a PHP reserved word. A valid class name starts with a letter or underscore, followed by any number of letters, numbers, or underscores. As a regular expression, it would be expressed thus: [a-zA-Z_\x7f-\xff][a-zA-Z0-9_\x7f-\xff]*.
http://vibranttechnologies.co.in/
MongoDB is an open source NoSQL database that uses JSON-like documents with dynamic schemas (BSON format) instead of using tables as in SQL. It allows for embedding related data and flexible querying of this embedded data. Some key features include using JavaScript-style documents, scaling horizontally on commodity hardware, and supporting various languages through its driver interface.
Сергей Матвеенко: MongoEngine: NoORM for NoSQLit-people
This document summarizes MongoEngine, an ORM (object-relational mapper) for working with MongoDB in Python. It introduces MongoDB as a scalable, high-performance, document-oriented NoSQL database. It compares MongoDB to RDBMS and shows how MongoEngine allows defining schemas and querying/updating data similarly to an ORM for SQL, while still maintaining flexibility of MongoDB. It provides examples of defining schemas using MongoEngine classes, querying data, updating documents, and how MongoEngine interacts with PyMongo and MongoDB under the hood. It also briefly discusses performance and integration with Django.
This document describes how to use jQuery DataTables to dynamically display data from a MongoDB database. It includes code snippets for setting up the HTML table structure, initializing DataTables with JavaScript, and creating a Java servlet to retrieve data from MongoDB and return it in JSON format for population into the table. The servlet queries the MongoDB collection, converts the results to a JSON string, and returns it to the calling page to populate the DataTables initialization. This allows dynamic loading and display of tabular data from a MongoDB database into an HTML table using jQuery DataTables.
This document discusses ING's use of Elasticsearch for distributed tracing across its systems. It provides context on ING as a company with many DevOps teams and systems. It then summarizes how Elasticsearch is used to collect and correlate logs and events from different systems using a unique request ID. Statistics are given on the volume of events ingested and queries. Future plans are outlined to expand the data sources and integrate with other tools to provide more insights.
Changing Your Mindset: Getting Started With Test-Driven DevelopmentViget Labs
This document provides an overview of test-driven development (TDD) and how to get started with it. It discusses the TDD process of writing a failing test first, then code to pass that test, and refactoring. Examples show how to write tests using Test::Unit, use stubs and mocks with Mocha, and address common pitfalls like over-mocking or non-descriptive test names. The document also covers integrating tests with Rake, using expectations as tests, and analyzing test coverage with tools like RCov.
Getting Started with MongoDB and Node.jsGrant Goodale
Node.js is an application engine for scalable network applications. It uses an event-driven, non-blocking I/O model that makes it lightweight and efficient, especially for real-time applications that require high-concurrency. MongoDB is a popular document database that uses JSON-like documents with dynamic schemas. Node.js and MongoDB are a good fit together because they are both fast, use JavaScript, and understand JSON documents. The document provides an introduction to getting started with Node.js and MongoDB by explaining what they are, how they work together well, and how to set them up on your system.
So you are considering going agile, huh? Your biggest question is probably "where do I start"? This session will help you answer that question and get you started down the road to agility . Mike will explore how to choose your first project and ensure that the pilot team is setup for success. He will talk through common organizational challenges and show you how to overcome them. You'll leave this talk with the knowledge necessary to get your first team going while laying the foundation to build on that success.
This document provides an overview of version control using Subversion (SVN). It discusses key SVN concepts like the trunk, branches, and tags. It explains how SVN allows for collaboration between developers and management of code revisions. The document also summarizes SVN features like authentication, revision management, tagging for releases, and advanced topics like hooks and externals.
This document summarizes techniques for optimizing Logstash and Rsyslog for high volume log ingestion into Elasticsearch. It discusses using Logstash and Rsyslog to ingest logs via TCP and JSON parsing, applying filters like grok and mutate, and outputting to Elasticsearch. It also covers Elasticsearch tuning including refresh rate, doc values, indexing performance, and using time-based indices on hot and cold nodes. Benchmark results show Logstash and Rsyslog can handle thousands of events per second with appropriate configuration.
I made a simple SVN (Subversion) tutorial for my co-workers and just wanted to share it with you. It is based on other lectures and practical experience I had in the past.
Some ideas also come from the GIT world, which is still too far and new for everyone, but which I already love and embrace fully :)
ElasticSearch introduction talk. Overview of the API, functionality, use cases. What can be achieved, how to scale? What is Kibana, how it can benefit your business.
This document discusses Elasticsearch, including understanding how it works and optimizing performance. It covers Elasticsearch concepts like clusters, indexes, shards and nodes. It also discusses installing and configuring Elasticsearch, modeling data, indexing and querying optimizations. Lastly it discusses integrating Elasticsearch with Hadoop and using SQL on Elasticsearch.
Building a Dataset Search Engine with Spark and Elasticsearch: Spark Summit E...Spark Summit
Elasticsearch provides native integration with Apache Spark through ES-Hadoop. However, especially during development, it is at best cumbersome to have Elasticsearch running in a separate machine/instance. Leveraging Spark Cluster with Elasticsearch Inside it is possible to run an embedded instance of Elasticsearch in the driver node of a Spark Cluster. This opens up new opportunities to develop cutting-edge applications. One such application is Dataset Search.
Oscar will give a demo of a Dataset Search Engine built on Spark Cluster with Elasticsearch Inside. Motivation is that once Elasticsearch is running on Spark it becomes possible and interesting to have the Elasticsearch in-memory instance join an (existing) Elasticsearch cluster. And this in turn enables indexing of Datasets that are processed as part of Data Pipelines running on Spark. Dataset Search and Data Management are R&D topics that should be of interest to Spark Summit East attendees who are looking for a way to organize their Data Lake and make it searchable.
Real-Time Data Exploration and Analytics with Amazon Elasticsearch ServiceAmazon Web Services
Elasticsearch is a fully featured search engine used for real-time analytics, and Amazon Elasticsearch Service makes it easy to deploy Elasticsearch clusters on AWS. With Amazon ES, you can ingest and process billions of events per day, and explore the data using Kibana to discover patterns. In this session, we use Apache web logs as example and show you how to build an end-to-end analytics solution.
Content marketing careers are constantly evolving, but one thing is certain: The power of LinkedIn for personal branding and career advancement is here to stay. Of course, because so many people rely on LinkedIn for professional networking these days, it’s essential to create a profile that will help you stand out and get noticed by the people who make hiring decisions in your industry. It’s not an easy task, but it can be
done – with the help of some pro-level tips for strengthening your LinkedIn presence and gaining an edge over the competition. If your “Who’s Viewed Your Profile” chart is flatlining week after week, the advice below will help breathe new life into your profile, improve your visibility in search results, generate more views, and impress your audience.
This document provides an overview of Docker and container orchestration on AWS using Amazon ECS. It discusses the benefits of containers, microservices architecture, and how ECS handles scheduling and placement of containers across a cluster. It also introduces Blox, an open source project that provides an alternative scheduler and cluster state service for ECS. Key points include:
- Containers provide portability, flexibility, and efficiency for applications compared to virtual machines.
- ECS handles scheduling and orchestrating containers across a cluster of EC2 instances, providing high availability and scalability.
- Blox is an open source project that provides an alternative to ECS for scheduling and managing cluster state, giving more control and flexibility
Amber Bauerly is a student at the University of South Dakota majoring in Elementary Education. She comes from a close family and has been involved in gymnastics and dance for many years. Her goals are to become a kindergarten teacher and eventually get married, have children, and own a home. She finds her sorority, Pi Beta Phi, to be a great support system and source of her closest friends.
Leah Stensland is a 22-year-old senior at USD studying Elementary Education with endorsements in Kindergarten Education and Early Childhood Education. She is from Garretson, South Dakota and enjoys spending time with her family, including her parents, sister Kayli, and dog Marley. Her professional goals are to graduate from USD and obtain a master's degree in education so that she can become a Kindergarten teacher in a small South Dakota school district.
Talk given for the #phpbenelux user group, March 27th in Gent (BE), with the goal of convincing developers that are used to build php/mysql apps to broaden their horizon when adding search to their site. Be sure to also have a look at the notes for the slides; they explain some of the screenshots, etc.
An accompanying blog post about this subject can be found at http://www.jurriaanpersyn.com/archives/2013/11/18/introduction-to-elasticsearch/
The X Dev API is a new protocol for non-blocking, asynchronous calls to MySQL. In this talk, Lior explores the benefits of working with this protocol and connectors, and the challenges we encountered during the process of adopting X Dev API in Wix Engineering.
Lior shares how we are incorporating the protocol in our massive multi dc architecture, and how it helps us, at Wix Engineering, rollout to production faster.
Working with NoSQL in a SQL Database (XDevApi)Lior Altarescu
The document discusses X DevAPI, which allows MySQL to be used as both a relational and non-relational (schema-less) database. It provides NoSQL and SQL functionality in a single database using CRUD operations. The presenter worked with X DevAPI at Wix, where they initially used ProxySQL for failover but it did not support X DevAPI. They were able to use InnoDB cluster instead to gain its automatic failover capabilities while taking advantage of X DevAPI.
One of the top new features in the AEM 6.2 release is in the introduction of a unified search experience for content authors called OmniSearch which provides a consistent and continuous search experience across the entire AEM user interface. This session will cover the significant points in OmniSearch. We will cover both backend extension to create new search sources and front end extension to define how search results are visualized. This will be an intermediate-level session and attendees will come out of it with a clear understand as to how to extend this new capability.
Omnisearch in AEM 6.2 - Search All the ThingsJustin Edelson
This document provides an overview of Omnisearch in AEM 6.2, including how to use it, add new locations, and implement a custom Omnisearch handler. Omnisearch provides a unified search experience across AEM authoring tools and content. Key points covered include how to build queries for search results, suggestions, and spell check, as well as configure the UI display of search locations and results. The presentation includes code examples for implementing a custom Omnisearch handler that searches content fragments. It concludes with a demonstration and overview of potential future enhancements.
Trivadis TechEvent 2016 Polybase challenges Hive relational access to non-rel...Trivadis
In this presentation, Olaf Nimz talks about a proposed marriage between SQL Server and Hadoop, about Building Bridges to HDFS, Distributed query processing and about Sensible Hybrid Scenarios.
Elasticsearch and Symfony Integration - Debarko DeDebarko De
This document provides an overview of Elasticsearch and how to integrate it with Symfony. It discusses how Elasticsearch is a search engine that uses JSON documents and distributed indexing, while SQL is a relational database. It then covers how to install the Elasticsearch PHP client, connect to Elasticsearch from Symfony, perform queries, create and manage indexes, index and search documents, and delete documents.
This document discusses using Redis and Elasticsearch together for time series data. Redis Streams can be used to store time-stamped data in Redis, and then a Logstash pipeline can be used to extract the data from Redis and index it into Elasticsearch. The RediSearch module for Redis allows full-text search of Redis data. Dashboards in Kibana can then visualize and analyze the time series data stored in Elasticsearch.
MySQL Without the SQL - Oh My! -> MySQL Document Store -- Confoo.CA 2019Dave Stokes
MySQL an be used as a NoSQL JSON Document Store as well as its well known ability as a SQL Relational Data Base. This presentation covers why you would want to use NoSQL and JSON and how to combine it what the relational data you already have
MySQL flexible schema and JSON for Internet of ThingsAlexander Rubin
My presentation at Oracle Open World Conference 2017: Using MySQL Flexible Schema (Document Store/JSON) for IoT
Tuesday, Oct 03, 11:30 a.m. - 12:15 p.m. | Marriott Marquis (Yerba Buena Level) - Salon 14
Storing data from sensors (Internet of Things) may be challenging in many respects, specifically due to the changing nature of the data. For example, if you have a fixed table structure and a sensor will need to store new property, it will be hard to make this change. This session discusses different options for implementing flexible schemas with MySQL 5.7 and MySQL 8.0, using JSON and calculated fields as well as the MySQL Document Store feature. It includes a demo with IoT devices where data is stored in MySQL 8.0.
DataFrame: Spark's new abstraction for data science by Reynold Xin of DatabricksData Con LA
Spark DataFrames provide a unified data structure and API for distributed data processing across Python, R and Scala. DataFrames allow users to manipulate distributed datasets using familiar data frame concepts from single machine tools like Pandas and dplyr. The DataFrame API is built on a logical query plan called Catalyst that is optimized for efficient execution across different languages and Spark execution engines like Tungsten.
This document provides an overview of different data access technologies including ADO.NET, LINQ, XML, and LINQ to XML. It discusses the basic objects and functions of ADO.NET for querying and updating data from databases. It also introduces LINQ as a way to query data in memory or across application layers. Finally, it covers working with XML documents and LINQ to XML for querying XML data.
The document discusses a webinar presented by LOD2 on creating knowledge from interlinked data. It describes LOD2 as an EU-funded project involving leading linked open data organizations. The webinar agenda includes discussing SIREn, a plugin for Elasticsearch that allows indexing and searching of JSON documents. It provides an overview of Elasticsearch and describes how to install SIREn, create an index, index documents, and perform searches on nested JSON data.
JSON, A Splash of SODA, and a SQL Chaser: Real-World Use Cases for Autonomous...Jim Czuprynski
JSON is the new XML! It’s everywhere, from NoSQL databases to REST APIs. Let me share with you how Oracle’s Autonomous JSON Database (AJD) makes short work of handling JSON-resident information, especially when paired with robust functions and features of Oracle 19c and 21c.
The Flex Framework provides a lot of benefit, and we implement design patterns to keep things "clean". Those things often make creating expressive interactions difficult, and frustrating. These are tips learned of the past year for common areas to overcome those things by gaining a proper understanding of how to leverage what the framework provides.
(BDT401) Big Data Orchestra - Harmony within Data Analysis Tools | AWS re:Inv...Amazon Web Services
This document discusses using various AWS services like Kinesis, CloudSearch, DynamoDB, Redshift and EMR for processing streaming data and performing analytics. It provides code snippets for initializing the services, ingesting and analyzing data using Spark on EMR, and scaling the infrastructure as needed. It also discusses updating event data in DynamoDB based on geospatial proximity and lists SDKs for interacting with AWS services from different programming languages.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfMalak Abu Hammad
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
Building Production Ready Search Pipelines with Spark and MilvusZilliz
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.