Discussion on NoSql Databases that can be used in android development. The talk discusses both firebase and realm databases and how one might wanna use them .
This document provides an overview of Elasticsearch and how to use it with .NET. It discusses what Elasticsearch is, how to install it, how Elasticsearch provides scalability through its architecture of clusters, nodes, shards and replicas. It also covers topics like indexing and querying data through the REST API or NEST client for .NET, performing searches, aggregations, highlighting hits, handling human language through analyzers, and using suggesters.
GreenDao is an ORM library that provides a lightweight way to work with SQLite databases on Android. It allows developers to define entities using annotations and perform CRUD operations and queries on those entities through generated DAO classes. Some key features include high performance, small code size, easy to use API, and support for database encryption, RxJava, and SQLCipher. Configuration involves setting up Gradle dependencies, defining entities, and generating DAO classes to work with the database. Relationships between entities can be defined using @ToOne and @ToMany annotations.
Getting started with Elasticsearch and .NETTomas Jansson
This document provides an introduction to using Elasticsearch with .NET and the NEST client library. It demonstrates how to install and configure Elasticsearch on Windows, define mappings and index documents using NEST, perform various queries including fuzzy, highlighted, faceted queries, and add filters. NEST provides a strongly typed, fluent abstraction over Elasticsearch that allows querying and filtering Elasticsearch in a similar manner to Elasticsearch JSON queries. The document encourages attendees to view the demo code on GitHub for examples of indexing, querying, highlighting, faceting, and filtering documents using NEST.
ElasticSearch is a free and open source distributed inverted index search engine created by shay banon. Build on top of Apache Lucene. Lucene is a most popular java-based full text search index implementation. First public release version v0.4 in February 2010. Developed in Java, so inherently cross-plateform.
In these slide following projects are presented:
* redis_wrap: A Pythonic wrapper that makes it nicer to work with builtin Redis datatypes
* redis_graph: A sample graph database
* redis_simple_queue: A simple queue implemented on Redis list structure
* bitmapist: a powerful analytics library using Redis bitmaps, great for retention and cohort tracking
* fixedlist: a fixed list structure that can optimize timelines (and other things)
* how to use Lua scripting for more advanced data structures and better performance
These are Python projects, but some of them (like bitmapist) have been ported to other languages.
This talk was given to PyCon Belarus on 31 Jan. 2015
Getting the most out of Java [Nordic Coding-2010]Sven Efftinge
In this talk we explain how we use the more recent concepts of the Java programming language in order to improve readability and maintainability of our code.
Going beyond Django ORM limitations with PostgresCraig Kerstiens
Postgres provides many advanced features for developers including a wide range of datatypes, indexing options like B-Tree and GIN, array datatypes, extensions for additional functionality like hstore for key-value stores and full text search, and the ability to use Postgres as a queue through extensions. Django and other ORMs provide options for integrating Postgres features into applications. Overall, Postgres is a full featured database with many capabilities beyond basic relational features.
How does a full-text search engine works? How is the index built and searched? Can I use PostgreSQL as a full-text search engine or should I go for a more specialised solution? How does one configure and use PostgreSQL search?
This presentation covers all those aspects, based on the work we did to index teowaki.com. It was presented at PgConf EU 2014 in Madrid
This document provides an overview of Elasticsearch and how to use it with .NET. It discusses what Elasticsearch is, how to install it, how Elasticsearch provides scalability through its architecture of clusters, nodes, shards and replicas. It also covers topics like indexing and querying data through the REST API or NEST client for .NET, performing searches, aggregations, highlighting hits, handling human language through analyzers, and using suggesters.
GreenDao is an ORM library that provides a lightweight way to work with SQLite databases on Android. It allows developers to define entities using annotations and perform CRUD operations and queries on those entities through generated DAO classes. Some key features include high performance, small code size, easy to use API, and support for database encryption, RxJava, and SQLCipher. Configuration involves setting up Gradle dependencies, defining entities, and generating DAO classes to work with the database. Relationships between entities can be defined using @ToOne and @ToMany annotations.
Getting started with Elasticsearch and .NETTomas Jansson
This document provides an introduction to using Elasticsearch with .NET and the NEST client library. It demonstrates how to install and configure Elasticsearch on Windows, define mappings and index documents using NEST, perform various queries including fuzzy, highlighted, faceted queries, and add filters. NEST provides a strongly typed, fluent abstraction over Elasticsearch that allows querying and filtering Elasticsearch in a similar manner to Elasticsearch JSON queries. The document encourages attendees to view the demo code on GitHub for examples of indexing, querying, highlighting, faceting, and filtering documents using NEST.
ElasticSearch is a free and open source distributed inverted index search engine created by shay banon. Build on top of Apache Lucene. Lucene is a most popular java-based full text search index implementation. First public release version v0.4 in February 2010. Developed in Java, so inherently cross-plateform.
In these slide following projects are presented:
* redis_wrap: A Pythonic wrapper that makes it nicer to work with builtin Redis datatypes
* redis_graph: A sample graph database
* redis_simple_queue: A simple queue implemented on Redis list structure
* bitmapist: a powerful analytics library using Redis bitmaps, great for retention and cohort tracking
* fixedlist: a fixed list structure that can optimize timelines (and other things)
* how to use Lua scripting for more advanced data structures and better performance
These are Python projects, but some of them (like bitmapist) have been ported to other languages.
This talk was given to PyCon Belarus on 31 Jan. 2015
Getting the most out of Java [Nordic Coding-2010]Sven Efftinge
In this talk we explain how we use the more recent concepts of the Java programming language in order to improve readability and maintainability of our code.
Going beyond Django ORM limitations with PostgresCraig Kerstiens
Postgres provides many advanced features for developers including a wide range of datatypes, indexing options like B-Tree and GIN, array datatypes, extensions for additional functionality like hstore for key-value stores and full text search, and the ability to use Postgres as a queue through extensions. Django and other ORMs provide options for integrating Postgres features into applications. Overall, Postgres is a full featured database with many capabilities beyond basic relational features.
How does a full-text search engine works? How is the index built and searched? Can I use PostgreSQL as a full-text search engine or should I go for a more specialised solution? How does one configure and use PostgreSQL search?
This presentation covers all those aspects, based on the work we did to index teowaki.com. It was presented at PgConf EU 2014 in Madrid
A comparison of different solutions for full-text search in web applications using PostgreSQL and other technology. Presented at the PostgreSQL Conference West, in Seattle, October 2009.
The document describes a lawyer's journey learning web development and building their first two web applications in Go. It outlines how they learned HTML, CSS, and JavaScript from May to July 2014 before learning Go in mid-July 2014. By mid-August 2014, they had deployed their first application - a CRUD app using MySQL for persistence. By the end of August 2014, they deployed their second application - an API client that retrieved photos from Flickr and weather data for a random city. The document provides details on the structure, libraries, data structures, database functions, handler functions, and main function used in developing the applications.
Asp.net create delete directory folder in c# vb.netrelekarsushant
The document describes how to create and delete directories (folders) in ASP.NET using C# and VB.NET. It includes code samples for creating a directory when a user enters a name and clicks a button, deleting a directory when a user enters a name and clicks another button, and removing all directories and subdirectories recursively. The code utilizes the System.IO namespace and methods like Directory.CreateDirectory(), Directory.Exists(), Directory.Delete(), and GetFiles() to manage directories and files.
We describe the features of Oak Lucene indexes and how they can be used to get your queries perform better. In the second part we will talk about how asynchronous indexing works in general and how it can be monitored.
This was presented as part of AEM Gem Series -http://dev.day.com/content/ddc/en/gems/oak-lucene-indexes.html
1. The document discusses tips for using MongoDB, including avoiding regular expressions in queries, tokenizing field names to reduce index size, and using compound indexes instead of multiple single-field indexes.
2. It recommends tokenizing field names to reduce the size of indexes since MongoDB stores the full field name in indexes and regular expressions prevent indexes from being used in queries.
3. The document also suggests creating a single compound index on multiple fields instead of separate indexes on each field individually to allow a single index to be used across related queries.
Scala is a general-purpose programming language that is object-oriented, functional, and type-safe. It runs on the Java Virtual Machine and Common Language Runtime. Scala combines object-oriented and functional programming in a statically typed programming language. It is designed to express common programming patterns in a concise, elegant, and type-safe way.
In this session you'll learn about the decisions that went into designing and building DynamoDB, and how it allows you to stay focused on your application while enjoying single digit latencies at any scale. We'll dive deep on how to model data, maintain maximum throughput, and drive analytics against your data, while profiling real world use cases, tips and tricks from customers running on DynamoDB today.
MongoDB supports a wide range of indexing options to enable fast querying of your data. In this talk we’ll cover how indexing works, the various indexing options, and cover use cases where each might be useful.
The document describes a generic arithmetic system that allows uniform access to number packages with different data representations. It defines generic arithmetic procedures like add, sub, mul, and div that apply the corresponding operation for the specific number package. A scheme-number package for integer arithmetic is also installed. Generic tags are attached to values to identify their representation, and a mapping table is used to dispatch operations to appropriate handler procedures based on tags.
This document provides an introduction to NoSQL and MongoDB. It discusses key concepts like horizontal scalability, the CAP theorem, BASE consistency, and MongoDB's document-oriented data model using JSON-like documents and collections. It also covers common MongoDB operations like inserting, querying, updating, and deleting documents.
Apache Spark - Key-Value RDD | Big Data Hadoop Spark Tutorial | CloudxLabCloudxLab
Big Data with Hadoop & Spark Training: http://bit.ly/2sewz2m
This CloudxLab Key-Value RDD tutorial helps you to understand Key-Value RDD in detail. Below are the topics covered in this tutorial:
1) Spark Key-Value RDD
2) Creating Key-Value Pair RDDs
3) Transformations on Pair RDDs - reduceByKey(func)
4) Count Word Frequency in a File using Spark
Sequelize is a promise-based ORM for Node.js that allows for modeling of database tables, querying, and synchronization between models and tables. It supports PostgreSQL, MySQL, MariaDB, SQLite, and MSSQL. Sequelize provides advantages like saving time and effort for developers by handling basic tasks and allowing a focus on business logic. Models can be defined and queried, validated, associated with other models, and synchronized with database tables. Raw SQL queries can also be executed through Sequelize.
Fun with Functional Programming in ClojureCodemotion
"Fun with Functional Programming in Clojure" by John Stevenson.
Clojure is a simple, powerful and fun language. With a small syntax its quick to learn, meaning you can focus on functional design concepts and quickly build up confidence. There are also a wide range of Clojure libraries to build any kind of apps or services quickly. With a focus on Immutability, Persistent data structures & lazy evaluation, you will quickly feel confident about the Functional Programming (FP) approach to coding. Discover Clojure in action as we write & evaluate Clojure using the REPL (interactive run-time environment), giving instant feedback on what the code is doing.
Slick is a modern database query and access library for Scala that allows working with stored data like Scala collections while controlling database access. It provides easy, concise, scalable, and safe database access. Slick supports many databases and can be set up by adding dependencies to a build file. Queries are processed by compiling them to SQL and lifting query types for translation. Queries support filtering, dropping rows, deletion, and creation.
The document discusses using JSON in MySQL. It begins by introducing the speaker and outlining topics to be covered, including why JSON is useful, loading JSON data into MySQL, performance considerations when querying JSON data, using generated columns with JSON, and searching multi-valued attributes in JSON. The document then dives into examples demonstrating loading sample data from XML to JSON in MySQL, issues that can arise, and techniques for optimizing JSON queries using generated columns and indexes.
The document discusses XML support in DB2 and Oracle databases, including native XML storage and indexing in DB2, SQL/XML functionality, XQuery support and examples, and how XML is stored relationally in Oracle requiring DOM operations rather than being stored natively. It also provides examples of how XQuery and indexing can be used more simply in DB2 compared to Oracle which lacks full native XML capabilities.
- MongoDB is a non-relational, document-oriented database that scales horizontally and uses JSON-like documents with dynamic schemas.
- It supports complex queries, embedded documents and arrays, and aggregation and MapReduce for querying and transforming data.
- MongoDB is used by many large companies for operational databases and analytics due to its scalability, flexibility, and performance.
The NoSQL DB is a database that provides a mechanism for storage and retrieval of data which is modeled in means other than the tabular relations used in relational databases. These databases have speed and high scalability. This kind of database has becoming more popular in several applications, that include financial one. As result of increase the number of user the number of vendors are increasing too, so the current problem how can we avoid lock in? The standard is the answer to solve this problem. Know more about the Diana proposal and the next step to became a NoSQL JSR.
This document discusses integration patterns in Adobe Experience Manager (AEM), including using Sling Models for dependency injection and accessing resources from different locations through a single ResourceResolver. It provides examples of integrating with backend APIs, databases, file systems and forms using techniques like ResourceProviders, Sling Filters and custom SlingServlets. It also covers accessing files from bundles and the filesystem using BundleResourceProvider and FsResourceProvider respectively.
MongoDB .local Houston 2019: REST-less Mobile Apps: Why Offline-first and Syn...MongoDB
The document discusses how mobile app users now expect always-on, responsive experiences from apps regardless of connectivity. Developing apps to meet these expectations is challenging due to variable network conditions. The Realm database is presented as a solution for building "REST-less" offline-first mobile apps that can work seamlessly and reliably even without connectivity through its live data model, implicit syncing, and change notifications. The document provides examples of how Realm can replace custom networking code and enable new use cases for digital transformation at various companies.
A comparison of different solutions for full-text search in web applications using PostgreSQL and other technology. Presented at the PostgreSQL Conference West, in Seattle, October 2009.
The document describes a lawyer's journey learning web development and building their first two web applications in Go. It outlines how they learned HTML, CSS, and JavaScript from May to July 2014 before learning Go in mid-July 2014. By mid-August 2014, they had deployed their first application - a CRUD app using MySQL for persistence. By the end of August 2014, they deployed their second application - an API client that retrieved photos from Flickr and weather data for a random city. The document provides details on the structure, libraries, data structures, database functions, handler functions, and main function used in developing the applications.
Asp.net create delete directory folder in c# vb.netrelekarsushant
The document describes how to create and delete directories (folders) in ASP.NET using C# and VB.NET. It includes code samples for creating a directory when a user enters a name and clicks a button, deleting a directory when a user enters a name and clicks another button, and removing all directories and subdirectories recursively. The code utilizes the System.IO namespace and methods like Directory.CreateDirectory(), Directory.Exists(), Directory.Delete(), and GetFiles() to manage directories and files.
We describe the features of Oak Lucene indexes and how they can be used to get your queries perform better. In the second part we will talk about how asynchronous indexing works in general and how it can be monitored.
This was presented as part of AEM Gem Series -http://dev.day.com/content/ddc/en/gems/oak-lucene-indexes.html
1. The document discusses tips for using MongoDB, including avoiding regular expressions in queries, tokenizing field names to reduce index size, and using compound indexes instead of multiple single-field indexes.
2. It recommends tokenizing field names to reduce the size of indexes since MongoDB stores the full field name in indexes and regular expressions prevent indexes from being used in queries.
3. The document also suggests creating a single compound index on multiple fields instead of separate indexes on each field individually to allow a single index to be used across related queries.
Scala is a general-purpose programming language that is object-oriented, functional, and type-safe. It runs on the Java Virtual Machine and Common Language Runtime. Scala combines object-oriented and functional programming in a statically typed programming language. It is designed to express common programming patterns in a concise, elegant, and type-safe way.
In this session you'll learn about the decisions that went into designing and building DynamoDB, and how it allows you to stay focused on your application while enjoying single digit latencies at any scale. We'll dive deep on how to model data, maintain maximum throughput, and drive analytics against your data, while profiling real world use cases, tips and tricks from customers running on DynamoDB today.
MongoDB supports a wide range of indexing options to enable fast querying of your data. In this talk we’ll cover how indexing works, the various indexing options, and cover use cases where each might be useful.
The document describes a generic arithmetic system that allows uniform access to number packages with different data representations. It defines generic arithmetic procedures like add, sub, mul, and div that apply the corresponding operation for the specific number package. A scheme-number package for integer arithmetic is also installed. Generic tags are attached to values to identify their representation, and a mapping table is used to dispatch operations to appropriate handler procedures based on tags.
This document provides an introduction to NoSQL and MongoDB. It discusses key concepts like horizontal scalability, the CAP theorem, BASE consistency, and MongoDB's document-oriented data model using JSON-like documents and collections. It also covers common MongoDB operations like inserting, querying, updating, and deleting documents.
Apache Spark - Key-Value RDD | Big Data Hadoop Spark Tutorial | CloudxLabCloudxLab
Big Data with Hadoop & Spark Training: http://bit.ly/2sewz2m
This CloudxLab Key-Value RDD tutorial helps you to understand Key-Value RDD in detail. Below are the topics covered in this tutorial:
1) Spark Key-Value RDD
2) Creating Key-Value Pair RDDs
3) Transformations on Pair RDDs - reduceByKey(func)
4) Count Word Frequency in a File using Spark
Sequelize is a promise-based ORM for Node.js that allows for modeling of database tables, querying, and synchronization between models and tables. It supports PostgreSQL, MySQL, MariaDB, SQLite, and MSSQL. Sequelize provides advantages like saving time and effort for developers by handling basic tasks and allowing a focus on business logic. Models can be defined and queried, validated, associated with other models, and synchronized with database tables. Raw SQL queries can also be executed through Sequelize.
Fun with Functional Programming in ClojureCodemotion
"Fun with Functional Programming in Clojure" by John Stevenson.
Clojure is a simple, powerful and fun language. With a small syntax its quick to learn, meaning you can focus on functional design concepts and quickly build up confidence. There are also a wide range of Clojure libraries to build any kind of apps or services quickly. With a focus on Immutability, Persistent data structures & lazy evaluation, you will quickly feel confident about the Functional Programming (FP) approach to coding. Discover Clojure in action as we write & evaluate Clojure using the REPL (interactive run-time environment), giving instant feedback on what the code is doing.
Slick is a modern database query and access library for Scala that allows working with stored data like Scala collections while controlling database access. It provides easy, concise, scalable, and safe database access. Slick supports many databases and can be set up by adding dependencies to a build file. Queries are processed by compiling them to SQL and lifting query types for translation. Queries support filtering, dropping rows, deletion, and creation.
The document discusses using JSON in MySQL. It begins by introducing the speaker and outlining topics to be covered, including why JSON is useful, loading JSON data into MySQL, performance considerations when querying JSON data, using generated columns with JSON, and searching multi-valued attributes in JSON. The document then dives into examples demonstrating loading sample data from XML to JSON in MySQL, issues that can arise, and techniques for optimizing JSON queries using generated columns and indexes.
The document discusses XML support in DB2 and Oracle databases, including native XML storage and indexing in DB2, SQL/XML functionality, XQuery support and examples, and how XML is stored relationally in Oracle requiring DOM operations rather than being stored natively. It also provides examples of how XQuery and indexing can be used more simply in DB2 compared to Oracle which lacks full native XML capabilities.
- MongoDB is a non-relational, document-oriented database that scales horizontally and uses JSON-like documents with dynamic schemas.
- It supports complex queries, embedded documents and arrays, and aggregation and MapReduce for querying and transforming data.
- MongoDB is used by many large companies for operational databases and analytics due to its scalability, flexibility, and performance.
The NoSQL DB is a database that provides a mechanism for storage and retrieval of data which is modeled in means other than the tabular relations used in relational databases. These databases have speed and high scalability. This kind of database has becoming more popular in several applications, that include financial one. As result of increase the number of user the number of vendors are increasing too, so the current problem how can we avoid lock in? The standard is the answer to solve this problem. Know more about the Diana proposal and the next step to became a NoSQL JSR.
This document discusses integration patterns in Adobe Experience Manager (AEM), including using Sling Models for dependency injection and accessing resources from different locations through a single ResourceResolver. It provides examples of integrating with backend APIs, databases, file systems and forms using techniques like ResourceProviders, Sling Filters and custom SlingServlets. It also covers accessing files from bundles and the filesystem using BundleResourceProvider and FsResourceProvider respectively.
MongoDB .local Houston 2019: REST-less Mobile Apps: Why Offline-first and Syn...MongoDB
The document discusses how mobile app users now expect always-on, responsive experiences from apps regardless of connectivity. Developing apps to meet these expectations is challenging due to variable network conditions. The Realm database is presented as a solution for building "REST-less" offline-first mobile apps that can work seamlessly and reliably even without connectivity through its live data model, implicit syncing, and change notifications. The document provides examples of how Realm can replace custom networking code and enable new use cases for digital transformation at various companies.
MongoDB World 2019: Realm: The Secret Sauce for Better Mobile AppsMongoDB
Realm Database is the fast, easy to use, and open source alternative to SQLite and Core Data that is popular with 100’s of thousands of developers. Learn from Alexander Stigsen, Realm’s creator, what makes it special and how it can be used to build better apps, faster.
Terrastore - A document database for developersSergio Bossa
Sergio Bossa is a software architect and engineer who has worked on online gambling and casino software. He is an open source enthusiast who has contributed to projects like Spring, Terracotta, and Terrastore. Terrastore is a document database for developers that is document-based, consistent, distributed, scalable, and written in Java using Terracotta. It allows for easy installation, no complex configuration, and simple basic operations like putting and getting documents from buckets. It also supports features like range queries, predicate queries, server-side updates, and easy scalability. Terrastore is best suited for data hot spots, computational data, complex or variable data, and throw-away data.
Talk was presented at PGConfUS on April 20th, 2016.
___________
With features like foreign data wrappers, Postgres makes it easy for you to integrate rich data stores into your application architectures. Yet sometimes you only have a few rich data structures to deal with, or can’t afford the time and resource cost of running a NoSQL cluster alongside Postgres. Happily Postgres natively supports several document data formats, giving you the best of both worlds in one database. You can keep document oriented data solely within Postgres, or write a foreign table schema that’s naturally compatible with your document database.
At this talk you’ll learn how to access document data stored in Postgres, and write Ruby code to make use of the data with your favorite ORM. We’ll survey the various document stores which are natively supported in Postgres. You’ll learn what are the pros and cons of each data type, and come away understanding which use cases are best suited to each document store.
This document summarizes a presentation on Spring Data by Eric Bottard and Florent Biville. Spring Data aims to provide a consistent programming model for new data stores while retaining store-specific features. It uses conventions over configuration for mapping objects to data stores. Repositories provide basic CRUD functionality without implementations. Magic finders allow querying by properties. Pagination and sorting are also supported.
This document discusses different ways to store data in Android applications, including shared preferences, files, SQLite databases, and content providers. It provides examples of how to use shared preferences to store private data for a single activity or across all app components. It also discusses how to use files, SQLite databases to store data, including creating databases, inserting, updating and querying data. Finally, it covers how to create and use custom content providers to expose app data through a content URI.
This document introduces Android Architecture Components and provides an overview of some key components:
- Room is a persistence library that provides an abstraction layer over SQLite to allow for more robust database access while reducing boilerplate code.
- Lifecycle-aware components allow classes to observe Activity and Fragment lifecycles so their behavior is linked to the lifecycle status of other components.
- Additional components like ViewModel, LiveData, and Paging Library are mentioned but not described in detail.
The document focuses on Room by explaining entity, DAO and database classes as well as more advanced Room features like relationships, custom types, migrations and testing. Lifecycle components are introduced to link observer behavior to owner lifec
- Discuss the Android Jetpack: New Android libraries officially developed by Google.
- Discuss the Room persistence library in Jetpack. How does Room library help developer life easier when working with databases.
09.Local Database Files and Storage on WPNguyen Tuan
This document provides an overview of local data storage options for Windows apps, including isolated storage, file I/O, settings storage, SQLite database, and external storage. It discusses using the local, installation, and shared application folders to store files. It also covers serialization, file associations, and APIs for reading and writing files like IsolatedStorageFile and StorageFile. The document demonstrates saving data to isolated storage, settings, and a SQLite database and loading data from these sources. It recommends SQLite as a local database option and provides instructions for adding SQLite support to a project.
Using Combine, SwiftUI and callAsFunction to build an experimental localizati...Donny Wals
Learn how to use Combine, SwiftUI and Swift 5.2's callAsFunction to build an experimental localization system and familiarize yourself with these new APIs in iOS 13.
Describes the Darwino framework for writing portable REST services, that can execute on Java web server but also on mobile devices, for the best hybrid experience even when running offline.
Java Web Programming on Google Cloud Platform [2/3] : DatastoreIMC Institute
This document provides an introduction to Google App Engine Datastore and using JPA with Datastore. It describes Datastore as a schema-less database that stores entities composed of properties. It discusses Datastore operations, the storage model, and compares Datastore to relational databases. It also covers setting up JPA, example entity and query code, and transaction management. Unsupported JPA features on Datastore are also listed.
In a world where users have ever higher expectations from the apps they use, having data always available, even when the device is offline has become increasingly important.
In this talk we will go through different ways of saving data on the phone and introduce Realm as a replacement for SQLite and ORM's.
Through an example app it will be demonstrated that thinking "Offline first" not only affects your apps architecture for the better, but also results in happier users.
MongoDB .local Chicago 2019: REST-less Mobile Apps: Why Offline-first & Sync ...MongoDB
Learn how Seamless Sync helps businesses empower their workforce with mobile apps that work seamlessly anywhere. Get to know what offline-first apps are, use-cases that drive this need, why sync matters and why “REST is not best” for client/server communication.
Webinar: Simplifying Persistence for Java and MongoDBMongoDB
Jeff Yemin will host a webinar covering the design and major features of Morphia, an Object Document Mapper (ODM) for Java and MongoDB. This webinar will start with a short introduction to MongoDB and the various options for building MongoDB applications on the JVM before taking a deep dive into Morphia. Morphia will be presented as an extended example format that demonstrates, for each feature, the domain model, a test driver, and the results as they appear in MongoDB.
Infinispan is a distributed, scalable, and transactional data grid that can be used as a NoSQL key-value store. It supports indexing and querying of data through integration with Apache Lucene. Queries can be executed on the data grid to search for objects by fields or perform more complex searches. Infinispan also supports MapReduce-style processing on the data grid. Hibernate Search leverages Infinispan to provide full-text search capabilities for Hibernate entities in a clustered environment.
Object Graph Mapping with Spring Data Neo4j 3 - Nicki Watt & Michael Hunger @...Neo4j
Nicki and Michael have recently been working together on the project to develop/upgrade the Spring Data Neo4j 3 (SDN) library to take advantage of some of the latest Neo4j 2.0 features. This talk takes a look at what can be expected of the new framework, and how it can be used to help model various different use cases with a simple Java domain model backed by a Neo4j database.
S313265 - Advanced Java API for RESTful Web Services at JavaOne Brazil 2010Arun Gupta
1. The document examines advanced features of JAX-RS, the Java API for RESTful web services.
2. It discusses runtime resource resolution, integration with EJB and CDI, runtime content negotiation, conditional HTTP requests, dealing with type erasure, and pluggable exception handling in JAX-RS.
3. The presentation encourages the use of "Software. Hardware. Complete." as the new corporate tagline to replace "Oracle Is the Information Company."
Similar to No sql databases blrdroid devfest 2016 (20)
This document summarizes a meetup on Firebase hosted by Amrit Sanjeev. It introduces Firebase and its features including realtime database, user authentication, hosting, and security. It provides code examples for adding Firebase dependencies, reading and writing data to the realtime database, and enabling offline support. The document also discusses Firebase's reliability, data retention policies, and security measures.
The document summarizes new features in Android M, including changes to app permissions where users can now revoke permissions after install instead of granting all upfront, a new fingerprint API, Doze and App Standby modes for improved battery life, Assistant support to provide context about app screens, and data binding, material design libraries, App Links, and Direct Share. The presentation was given by Amrit Sanjeev from the organization Blrdroid on introducing developers to the top 10 things in Android M.
The document provides an overview of new location APIs introduced in Android, including the Fused Location Provider, Geofencing, and Activity Recognition APIs. It discusses key changes like simplified and more accurate location access using a single API, support for up to 100 geofences per app, and activity detection using sensor data. The implementation relies on Google Play Services for distribution to older Android versions and leverages new technologies for improved indoor positioning and location accuracy.
Jelly Bean (Android 4.1) provides faster performance, improved notifications and features like Google Now and improved speech recognition. It focuses on smoother animations, reduced latency and touch response times. New capabilities include enhanced accessibility, international support, media codecs and connectivity options like Android Beam using Bluetooth. The developer tools and APIs are also expanded.
The document discusses key factors for designing good user experiences on mobile applications. It emphasizes making users feel comfortable, keeping interfaces simple, and being sensitive to the mobile context and environment. The first 30-60 seconds of using an app are critical to retaining users. Good design considers layout, colors, typography, graphics and how users will interact in different contexts while on the go.
The document discusses location-based services (LBS) and best practices for programming using location APIs. It introduces LBS and outlines some of the technical challenges, including maintaining battery performance, varying accuracy levels, and continuous changes in location technologies. The document then provides recommendations for deciding on location requirements upfront and using criteria to select the best location provider. It suggests practices like implementing a back off pattern to reduce accuracy needs over time and monitoring battery usage.
The document discusses Near Field Communication (NFC), a short-range wireless connectivity standard that allows data exchange between devices over short distances. It operates at 13.56 MHz and can transfer data at rates from 106-424 kbps. NFC offers automatic connection establishment, low energy usage, and compatibility with existing RFID infrastructure. However, it does not ensure secure communication or protect against attacks. The document outlines usage models, communication modes, implementation options, applications, Android support details, and key industry developments around NFC adoption.
The document discusses the new features and changes in Android Ice Cream Sandwich, the latest version of the Android mobile operating system. Some of the key improvements include a more unified user experience across devices, an updated notification system, improved camera and spell checking, and more controls over app usage and data. Developers will benefit from new APIs and more consistent user interfaces making app development easier. Technically, Ice Cream Sandwich features updates to multimedia, connectivity, security, and developer tools.
How information systems are built or acquired puts information, which is what they should be about, in a secondary place. Our language adapted accordingly, and we no longer talk about information systems but applications. Applications evolved in a way to break data into diverse fragments, tightly coupled with applications and expensive to integrate. The result is technical debt, which is re-paid by taking even bigger "loans", resulting in an ever-increasing technical debt. Software engineering and procurement practices work in sync with market forces to maintain this trend. This talk demonstrates how natural this situation is. The question is: can something be done to reverse the trend?
GlobalLogic Java Community Webinar #18 “How to Improve Web Application Perfor...GlobalLogic Ukraine
Під час доповіді відповімо на питання, навіщо потрібно підвищувати продуктивність аплікації і які є найефективніші способи для цього. А також поговоримо про те, що таке кеш, які його види бувають та, основне — як знайти performance bottleneck?
Відео та деталі заходу: https://bit.ly/45tILxj
Northern Engraving | Nameplate Manufacturing Process - 2024Northern Engraving
Manufacturing custom quality metal nameplates and badges involves several standard operations. Processes include sheet prep, lithography, screening, coating, punch press and inspection. All decoration is completed in the flat sheet with adhesive and tooling operations following. The possibilities for creating unique durable nameplates are endless. How will you create your brand identity? We can help!
AI in the Workplace Reskilling, Upskilling, and Future Work.pptxSunil Jagani
Discover how AI is transforming the workplace and learn strategies for reskilling and upskilling employees to stay ahead. This comprehensive guide covers the impact of AI on jobs, essential skills for the future, and successful case studies from industry leaders. Embrace AI-driven changes, foster continuous learning, and build a future-ready workforce.
Read More - https://bit.ly/3VKly70
Conversational agents, or chatbots, are increasingly used to access all sorts of services using natural language. While open-domain chatbots - like ChatGPT - can converse on any topic, task-oriented chatbots - the focus of this paper - are designed for specific tasks, like booking a flight, obtaining customer support, or setting an appointment. Like any other software, task-oriented chatbots need to be properly tested, usually by defining and executing test scenarios (i.e., sequences of user-chatbot interactions). However, there is currently a lack of methods to quantify the completeness and strength of such test scenarios, which can lead to low-quality tests, and hence to buggy chatbots.
To fill this gap, we propose adapting mutation testing (MuT) for task-oriented chatbots. To this end, we introduce a set of mutation operators that emulate faults in chatbot designs, an architecture that enables MuT on chatbots built using heterogeneous technologies, and a practical realisation as an Eclipse plugin. Moreover, we evaluate the applicability, effectiveness and efficiency of our approach on open-source chatbots, with promising results.
inQuba Webinar Mastering Customer Journey Management with Dr Graham HillLizaNolte
HERE IS YOUR WEBINAR CONTENT! 'Mastering Customer Journey Management with Dr. Graham Hill'. We hope you find the webinar recording both insightful and enjoyable.
In this webinar, we explored essential aspects of Customer Journey Management and personalization. Here’s a summary of the key insights and topics discussed:
Key Takeaways:
Understanding the Customer Journey: Dr. Hill emphasized the importance of mapping and understanding the complete customer journey to identify touchpoints and opportunities for improvement.
Personalization Strategies: We discussed how to leverage data and insights to create personalized experiences that resonate with customers.
Technology Integration: Insights were shared on how inQuba’s advanced technology can streamline customer interactions and drive operational efficiency.
"NATO Hackathon Winner: AI-Powered Drug Search", Taras KlobaFwdays
This is a session that details how PostgreSQL's features and Azure AI Services can be effectively used to significantly enhance the search functionality in any application.
In this session, we'll share insights on how we used PostgreSQL to facilitate precise searches across multiple fields in our mobile application. The techniques include using LIKE and ILIKE operators and integrating a trigram-based search to handle potential misspellings, thereby increasing the search accuracy.
We'll also discuss how the azure_ai extension on PostgreSQL databases in Azure and Azure AI Services were utilized to create vectors from user input, a feature beneficial when users wish to find specific items based on text prompts. While our application's case study involves a drug search, the techniques and principles shared in this session can be adapted to improve search functionality in a wide range of applications. Join us to learn how PostgreSQL and Azure AI can be harnessed to enhance your application's search capability.
From Natural Language to Structured Solr Queries using LLMsSease
This talk draws on experimentation to enable AI applications with Solr. One important use case is to use AI for better accessibility and discoverability of the data: while User eXperience techniques, lexical search improvements, and data harmonization can take organizations to a good level of accessibility, a structural (or “cognitive” gap) remains between the data user needs and the data producer constraints.
That is where AI – and most importantly, Natural Language Processing and Large Language Model techniques – could make a difference. This natural language, conversational engine could facilitate access and usage of the data leveraging the semantics of any data source.
The objective of the presentation is to propose a technical approach and a way forward to achieve this goal.
The key concept is to enable users to express their search queries in natural language, which the LLM then enriches, interprets, and translates into structured queries based on the Solr index’s metadata.
This approach leverages the LLM’s ability to understand the nuances of natural language and the structure of documents within Apache Solr.
The LLM acts as an intermediary agent, offering a transparent experience to users automatically and potentially uncovering relevant documents that conventional search methods might overlook. The presentation will include the results of this experimental work, lessons learned, best practices, and the scope of future work that should improve the approach and make it production-ready.
"$10 thousand per minute of downtime: architecture, queues, streaming and fin...Fwdays
Direct losses from downtime in 1 minute = $5-$10 thousand dollars. Reputation is priceless.
As part of the talk, we will consider the architectural strategies necessary for the development of highly loaded fintech solutions. We will focus on using queues and streaming to efficiently work and manage large amounts of data in real-time and to minimize latency.
We will focus special attention on the architectural patterns used in the design of the fintech system, microservices and event-driven architecture, which ensure scalability, fault tolerance, and consistency of the entire system.
QA or the Highway - Component Testing: Bridging the gap between frontend appl...zjhamm304
These are the slides for the presentation, "Component Testing: Bridging the gap between frontend applications" that was presented at QA or the Highway 2024 in Columbus, OH by Zachary Hamm.
Session 1 - Intro to Robotic Process Automation.pdfUiPathCommunity
👉 Check out our full 'Africa Series - Automation Student Developers (EN)' page to register for the full program:
https://bit.ly/Automation_Student_Kickstart
In this session, we shall introduce you to the world of automation, the UiPath Platform, and guide you on how to install and setup UiPath Studio on your Windows PC.
📕 Detailed agenda:
What is RPA? Benefits of RPA?
RPA Applications
The UiPath End-to-End Automation Platform
UiPath Studio CE Installation and Setup
💻 Extra training through UiPath Academy:
Introduction to Automation
UiPath Business Automation Platform
Explore automation development with UiPath Studio
👉 Register here for our upcoming Session 2 on June 20: Introduction to UiPath Studio Fundamentals: https://community.uipath.com/events/details/uipath-lagos-presents-session-2-introduction-to-uipath-studio-fundamentals/
Getting the Most Out of ScyllaDB Monitoring: ShareChat's TipsScyllaDB
ScyllaDB monitoring provides a lot of useful information. But sometimes it’s not easy to find the root of the problem if something is wrong or even estimate the remaining capacity by the load on the cluster. This talk shares our team's practical tips on: 1) How to find the root of the problem by metrics if ScyllaDB is slow 2) How to interpret the load and plan capacity for the future 3) Compaction strategies and how to choose the right one 4) Important metrics which aren’t available in the default monitoring setup.
3. Agenda
● Type of databases available in Android
● When to use them
● How they help ?
● Some feature of popular db products
4. Data trends
- Amount of data stored is increasing
- Data is more unstructured
- Efficiency and performance are critical
- Relations are more complex
6. RDBMS vs NoSQL
- Structured data
- Transform data policy
- Atomic transactions
- Data model != Entity model
- Scale up
- Semi or unstructured data
- Update schema policy
- Eventual consistency
- Data model ~= Entity model
- Scale out
7.
8. Real time database
- NoSQL, JSON database
- Maps each piece of data to a URL
- Offline support
- Supports iOS , Android and Web
- Pushes updates in milliseconds when
things change
10. Listening to data changes
● Attach an asynchronous listener to a Firebase reference.
● The listener will be triggered
○ once for the initial state of the data
○ again anytime the data changes
Firebase ref = new Firebase("https://docs-examples.firebaseio.com/web/saving-data/fireblog/posts");
ref.addValueEventListener(new ValueEventListener() {
@Override
public void onDataChange(DataSnapshot snapshot) {
System.out.println(snapshot.getValue());
}
@Override
public void onCancelled(FirebaseError firebaseError) {
System.out.println("The read failed: " + firebaseError.getMessage());
}
});
11. Reading data once
● Callback will be called only once
● removed after the first trigger
Firebase ref = new Firebase("https://docs-examples.firebaseio.com/web/saving-data/fireblog/posts");
ref.addListenerForSingleValueEvent(new ValueEventListener() {
@Override
public void onDataChange(DataSnapshot snapshot) {
// do some stuff once
}
@Override
public void onCancelled(FirebaseError firebaseError) {
}
});
12. Querying data
● Selectively retrieve data based on various factors.
● Start by specifying how you want your data to be ordered
○ orderByChild()
○ orderByKey()
○ orderByValue()
○ orderByPriority()
● combine these other methods to conduct complex queries
○ limitToFirst()
○ limitToLast()
○ startAt()
○ endAt()
○ equalTo()
13.
14. What is Realm ?
- Zero copy object store database
- Easy setup
- Optimized for read , not writes
- Cross platform
- Simple Querying interface
15. Defining objects in realm
public class Person extends RealmObject {
@PrimaryKey
private long id;
private String name;
private RealmList<Dog> dogs;
// Declare one-to-many relationships
// ... Generated getters and setters ...
}
@RealmClass
public class Person implements RealmModel {
@PrimaryKey
private long id;
private String name;
private RealmList<Dog> dogs;
// Declare one-to-many relationships
// ... Generated getters and setters ...
}
16. Relationships
public class Person extends RealmObject {
private String firstName;
private String lastName;
private Dog dog;
// ... Generated getters and setters ...
}
public class Person extends RealmObject {
private String firstName;
private String lastName;
private RealmList<Dog> dogs;
// ... Generated getters and setters ...
}
public class Person extends RealmObject {
private String firstName;
private String lastName;
private RealmList<Person> friends;
// .. getters/setters
}
17. Saving objects in realm
// Use them like regular java objects
Dog dog = new Dog();
dog.setName("Rex");
dog.setAge("1");
// Get a Realm instance
Realm realm = Realm.getDefaultInstance();
// Persist your data easily
realm.beginTransaction();
realm.copyToRealm(dog);
realm.commitTransaction();
// Get a Realm instance
Realm realm = Realm.getDefaultInstance();
// Create and persist your data easily
realm.beginTransaction();
Dog dog = realm.createObject(Dog.class);
dog.setName("Rex");
dog.setAge("1");
realm.commitTransaction();
18. Transactions
try {
realm.beginTransaction();
Dog dog = realm.where(Dog.class).
equalTo("name", "Fido").findFirst();
dog.setAge(15);
realm.commitTransaction();
}
catch (Exception ex) {
// rollback
realm.cancelTransaction();
}
realm.executeTransaction(
new Realm.Transaction() {
@Override
public void execute(Realm realm) {
Dog dog= realm.where(Dog.class).
equalTo("name", "Fido").findFirst();
dog.setAge(15);
}
})
19. Async Transactions
// Use them like regular java objects
realm.executeTransactionAsync(new Realm.Transaction() {
@Override
public void execute(Realm bgRealm) {
User user = bgRealm.createObject(User.class);
user.setName("John");
}
}, new Realm.Transaction.OnSuccess() {
@Override
public void onSuccess() {
// Transaction was a success.
}
}, new Realm.Transaction.OnError() {
@Override
public void onError(Throwable error) {
// Transaction failed and was automatically canceled.
}
});
RealmAsyncTask transaction = realm.executeTransactionAsync(
new Realm.Transaction() {
@Override
public void execute(Realm bgRealm) {
User user = bgRealm.createObject(User.class);
user.setName("John");
user.setEmail("john@corporation.com");
}
}, null);
20. Querying data
// Build the query looking at all users:
RealmQuery<User> query = realm.where(User.class);
// Add query conditions:
query.equalTo("name", "John");
query.or().equalTo("name", "Peter");
// Execute the query:
RealmResults<User> result1 = query.findAll();
// Or alternatively do the same all at once (the "Fluent interface"):
RealmResults<User> result2 = realm.where(User.class)
.equalTo("name", "John")
.or()
.equalTo("name", "Peter")
.findAll();
21. Query data supports
- Conditions like lessThan, greaterThan, contains, beginsWith etc
- Modifiers for ignoring Cases
- Logical Operations OR AND
- Sorting Ascending, Descending
- Chaining Queries
- Aggregations like SUM, MIN, MAX, AVG
- Synchronous, Asynchronous operations
22. Linked queries
public class Person extends RealmObject {
private String id;
private String name;
private RealmList<Dog> dogs;
// getters and setters
}
public class Dog extends RealmObject {
private String id;
private String name;
private String color;
// getters and setters
}
24. Auto updating objects
Dog d1 = realm.where(Dog.class).equals("id", 123).findFirst();
// register a listener to get notified when the object is updated.
d1.registerChangeListener(new RealmChangeListener() {
@Override
public void onChange() {
// called once the query complete and on every update
// do something now that the obj is updated
}
});
// assume code below is in some other thread
// Retrieve the same dog as above
Dog d2 = realm.where(Dog.class).equals("id", 123).first();
realm.beginTransaction();
d2.setAge(12);
realm.commitTransaction();
// d1's change listener gets called after the commit.*
25. Migration
// Example migration adding a new class
RealmMigration MyMigration = new RealmMigration() {
@Override
public void migrate(DynamicRealm realm, long oldVersion, long newVersion) {
// DynamicRealm exposes an editable schema
RealmSchema schema = realm.getSchema();
if (oldVersion == 0) {
schema.create("Person")
.addField("id", long.class, FieldAttribute.PRIMARY_KEY)
.addField("name", String.class)
.addField("age", int.class);
oldVersion++;
}
}
}
// in your init
RealmConfiguration config = new RealmConfiguration.Builder(context).schemaVersion(1)
.migration(new MyMigration()) ;
26. More features
● Direct support for Json to Object store
● Notification for database change like CP
● Encryption support in built
● Adapters for binding data with views (Android)
● Cross Platform, same data can work across ios and android
● Robust 3rd parties addons
27. Limitations
● Managing memory is tricky
● Not Entirely NOSQL, need migration on schema Changes
● No support for auto incrementing primary keys
● Mutable, thread-confined objects.
● Slower write
● Increase method count and size of apk
28. Latest update
● Server side tech
○ Real time sync
○ Conflict resolution
○ Reactive event handling
○ Authentication
○ Access control
● Good to building offline experiences
● Not a managed service yet