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Moody DS 48: First pictures from the exclusive YACHT test | YACHT

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credit Performance Monitor, or , measures performance statistics on a regular interval, and saves those stats in a file. Perfmon To set it up for Server, do the below steps: SQL Open perfmon from the run Expand Data Collector Sets Right click User Defined Click -> New Data Collector Set Give it a name Click Create manually Click Next -> Create data logs -> Performance counter -> Next Click Add in the next screen Add Available Bytes, Available MBytes, Page faults per second, Pages per second under Memory Add % disk time, Average disk second per read, Average disk second per write, Current disk queue length, disk bytes per second, disk transfer per second under Physical Disk % privileged Time, % processor time under Processor Add Freespace scans per second, Fullscan/sec under SQL Server access methods Add buffer cache hit ratio, checkpoint pages/sec, free pages, lazy writes/sec, page life expectancy under SQL Server buffer manager Add user conections under SQL Server general statistics Add Total latch wait time under SQL Server latches Add Lock timeouts/sec, Lock wait time, number of deadlocks/sec under SQL Server locks Under SQL Server memory manager, add memory grants pending, targe server memory and total server memory Under SQL Server SQL statistics, add batch requests/sec, SQL compilations/sec, SQL re-compilations/sec Under System, add context switches/sec, processor queue length Click OK -> Next -> Next -> Finish Right click this new collector set under User defined and choose start When one needs to see the report, stop this collector and open the collector file and view as report. Source Photos Originally published at xameeramir.github.io .

tSetting Up Perfmon for SQL Server Tuning

The Golden Locket

In this post, we will see how an action can be dispatched using Redux on login, and set the app state accordingly. Assuming familiarity with React Native and Redux concepts We have the following Login component to begin with : React, { useState } ; { View, Button, Text } ; CustomButton ; InputField ; { styles } ; Login = { [username, setUsername] = useState( ); [password, setPassword] = useState( ); ( <InputField
        placeholder='Enter username'
        value={username}
        onChangeText={(text) => setUsername(text)}
      />
      <InputField
        placeholder='Enter password'
        secureTextEntry={true}
        value={password}
        onChangeText={(text) => setPassword(text)}
      />
      <CustomButton 
        title='Sign In' 
        onPress={() => }  
      />
  );
};

export default Login; import from 'react' import from 'react-native' import from '../../components/CustomButton' import from '../../components/InputField' import from './style' const ( ) => props // remove these initial assignments after testing const '' const '' return < > View Right now it doesn’t do anything, it’s just barebones UI. To make it “react” to user action we should update the paramter in the button. onPress SignIn <CustomButton title= onPress={() => } /> 'Sign In' We use here, so pressing the button should dispatch and action to the reducer which should in turn update the overall app's state. redux For sake of simplicity, all redux code is placed in a ‘ ’ folder, while the components are in ‘ ’. redux src/components/<ComponentName>/index.js This is how our folder looks like. redux ├── actions.js ├── actionTypes.js ├── initialState.js ├── reducer.js └── store.js redux Let’s set as follows. These are all the fields that our login API will return (yours may differ). initialState and in are flags that we will set on our own (these are not part of API response) userId isLogged initialState = { : , : , : , : , : , : ,
}; export const isLoggedIn false userId '' token '' refreshToken '' expiresOn '' data '' Define action type in actionTypes.js SET_LOGIN_STATE = export const "SET_LOGIN_STATE" Let’s now create our in loginReducer reducer.js { initialState } ; * t ; loginReducer = { (action.type) { t.SET_LOGIN_STATE: {
        ...state,
        ...action.payload, isLoggedIn: , }; : state;
  }
}; import from './initialState' import as from './actionTypes' export const ( ) => state = initialState, action switch case return // this is what we expect to get back from API call and login page input true // we set this as true on login default return We can now generate our redux store using all the available information and thunk as middle-ware to handle API calls. thunkMiddleware ; { createStore, combineReducers, applyMiddleware } ; { composeWithDevTools } ; { loginReducer } ; rootReducer = combineReducers({ : loginReducer,
}); store = createStore(
  rootReducer,
  composeWithDevTools(applyMiddleware(thunkMiddleware))
); import from 'redux-thunk' import from 'redux' import from 'redux-devtools-extension/developmentOnly' // this is for debugging with React-Native-Debugger, you may leave it out import from './reducer' const loginReducer export const We have these things in place but we still have not figured how to set the state from the Login component. For this we need to define some actions in actions.js What we are looking at is a function that can call the login API and return the result back to us. Something like : fetch(LoginUrl, { : , : { : , : ,
      }, : .stringify(loginInput),
    })
    .then()
................... return method 'POST' headers Accept 'application/json' 'Content-Type' 'application/json' body JSON But we also need to ensure that the action is “connected” to the “reducer” in order to update the state or store. redux Since API call is considered unpredictable, it should not dispatch the action object directly to reducer, but through a helper. Dispatching action can return only an Object. If it returns a promise the app will break. We need to make sure of this. In : actions.js * t ; { LoginUrl } ; setLoginState = { { : t.SET_LOGIN_STATE, : loginData,
  };
}; import as from './actionTypes' import from '../constants/Api' // this is what our action should look like which dispatches the "payload" to reducer const ( ) => loginData return type payload To fetch this in the action above, we create another function using the fetch operation discussed above: loginData { Alert } ; login = { { username, password } = loginInput; { fetch(LoginUrl, { : , : { Accept: , : ,
      }, : .stringify(loginInput),
    })
      .then( response.json())
      .then( { (json.msg === ) { dispatch(setLoginState({ ...json, : username })); } {
          Alert.alert( , );
        }
      })
      .catch( {
        Alert.alert( , ); .log(err);
      });
  };
}; import from 'react-native' // to show alerts in app export const ( ) => loginInput const return ( ) => dispatch // don't forget to use dispatch here! return method 'POST' headers // these could be different for your API call 'application/json' 'Content-Type' 'application/json' body JSON ( ) => response ( ) => json if 'success' // response success checking logic could differ userId // our action is called here else 'Login Failed' 'Username or Password is incorrect' ( ) => err 'Login Failed' 'Some error occured, please retry' console You can see how our action is dispatched from this function, which in turn will return a payload object to the reducer in order to perform state update. Only thing remaining now is connecting this function to the UI. Let’s go back to our component in the Submit button section and specify Login onPress { useDispatch } ; { login } ;

...............

<CustomButton 
        title= onPress={() => useDispatch(login({ : username, : password }))}  
      />
............... import from 'react-redux' import from '../../redux/actions' 'Sign In' 'username' 'password' Since we are using here, all our functions should ideally be in form of some action, which will be caught in the middleware first and then passed on appropriately to reducer. redux redux-thunk On successful login, the values will all be populated. On failure, an alert will show up stating error. initialState I hope this was helpful & informative :) Also published at https://dev.to/skd1993/creating-a-simple-login-function-with-redux-and-thunk-in-react-native-33ib

Smart Strategy To Create Login Function in React Native Using Powerful Tools

Since being back in 2009, has become one of the most popular databases of choice for developers over the past decade. While many technologists have likely gravitated to it as a solution due to its open source roots and that it's rooted in the relational database world, that really only begins to scratch the surface of what MariaDB has to offer. forked from MySQL MariaDB Over the years MariaDB has diverged from MySQL by adding many features and functionality, much of which we won't be able to dive into within the context of this article. However, one thing, above all else, has remained the same; providing a modern, open-source, high quality database solution that developers can use to power their innovation. But before you can dive into MariaDB and check out all it has to offer you'll need to answer the most fundamental of questions; how do you get started using MariaDB? MariaDB and Java Database Connectivity ( ) JDBC It likely comes as no surprise that , and ultimately the environment as a whole, has been an extremely popular option used by developers to create applications. Java Java Virtual Machine (JVM) With that in mind, I've written this short walkthrough to take you through the steps for getting started with using a image, ava and the . MariaDB (Community Server) Docker J MariaDB JDBC client In this walkthrough you'll be utilizing MariaDB and JDBC to create a simple ( based) "To do" application that, using , will expose a variety of endpoints to use to perform basic CRUD (create-read-update-delete) operations on a MariaDB database instance. Maven Java Spring Let's get started! Requirements Before jumping into code, you're going to need to make sure you have a few things on your machine: MariaDB client Docker Java (v. 8+) (for testing the API endpoints) Curl Creating a new MariaDB instance using Docker One of the simplest ways to get started with MariaDB, regardless of which operating system you're using, is to pull the Docker , from Docker Hub, and use it create a new container. MariaDB Server image To do this simply open a terminal window and run the following: $ docker run -p 3306:3306 -d --name mariadb -eMARIADB_ROOT_PASSWORD=Password123! mariadb/server:10.4 That's it. You should now have a running instance of MariaDB. Pretty painless, right? You can confirm the instance within a Docker container by running the following: $ docker ps And you should see your container within the output. Connecting to MariaDB Now that you've got a running MariaDB Server instance within a new Docker container the next step will be to connect to and communicate with the database instance using the . MariaDB client There are many SQL clients available out in the wild. For simplicity's sake, I've chosen to demonstrate how to use the official MariaDB Client, but certainly feel free to use whatever client you prefer. Connect to your MariaDB instance by executing the following: $ mariadb --host 127.0.0.1 -P 3306 --user root -pPassword123! You should see something like the following, which means you've successfully connected to the MariaDB instance! Once you're connected you can create a new database. todo; CREATE DATABASE Then create a new table. todo.tasks ( ( ) AUTO_INCREMENT,
  description ( ) ,
  completed ,
  PRIMARY ( )
); CREATE TABLE id INT 11 unsigned NOT NULL VARCHAR 500 NOT NULL BOOLEAN NOT NULL DEFAULT 0 KEY id Getting Started with Java Spring, JDBC and MariaDB With a database instance spun up and schema created you're ready to create a new application. Java Create a Maven project Start by navigating to , which will enable you to create a new -based project. For this project you can enter the following criteria. https://start.spring.io Spring Maven Next, add the following dependencies: : A library that will eliminate having to create boiler plate code (e.g. getters, setters) within the domain objects. Lombok : A library to create and expose RESTful API endpoints. Spring Web : A library that provides abstractions to help eliminate boiler plate code for connecting to and communicating with databases. Spring Data JPA Finally, click the "GENERATE" button to create and download the project (contained within a .zip file) to a desired location on your machine. Add the MariaDB R2DBC connector Navigate to the location where you downloaded the new Maven project (.zip file) to, and unzip.  Then use a code editor to open the project, and open pom.xml. Add a new dependency for MariaDB's JDBC connector to the collection of dependencies. <dependency> <artifactId>mariadb-java-client< version> org.mariadb.jdbc < > groupId </ > groupId /artifactId>
   <version>2.6.0</ </ > dependency Preparing the data integration Now that you've created a project that contains all of the dependencies you'll need, it's to jump into the Java code. Typically, I like to start by creating the entity classes. Navigate to , create a new folder called "domain", and create a new file within it named "Task.java". /src/main/java/com/mariadb/todo Open "Task.java" and add the following code. com.mariadb.todo.domain; javax.persistence.*; lombok.Data; (name = ) { (strategy = GenerationType.IDENTITY) Integer id; String description; Boolean completed = ;
} package import import @Data @Entity @Table "tasks" public class Task @Id @GeneratedValue private private private false Next, create a new folder called "repositories" in , and create a new filed within it named "TaskRepository.java". /src/main/java/com/mariadb/todo Open "TaskRepository.java" and add the following code. com.mariadb.todo.repositories; com.mariadb.todo.domain.Task; org.springframework.data.repository.CrudRepository; {
} package import import public < , > interface TaskRepository extends CrudRepository Task Integer Like the name suggests the interface provides basic CRUD operations on a repository for a generic type (your Task class in this case) and the primary key type for that generic type. CrudRepository Create a data service Services can be used to manage the business logic of your application. The only service, TaskService, in this application is used for validating a Task object and integrating with the TaskRepository. Create a new folder called "services" in , and create a new filed within it named "TaskService.java". /src/main/java/com/mariadb/todo Open "TaskService.java" and add the following code. com.mariadb.todo.services; java.util.Optional; com.mariadb.todo.domain.Task; com.mariadb.todo.repositories.TaskRepository; org.springframework.beans.factory.annotation.Autowired; org.springframework.stereotype.Service; org.springframework.transaction.annotation.Transactional; { TaskRepository repository; { (task != && !task.getDescription().isEmpty()) { ;
        } ;
    } { .repository.findAll();
    } { .repository.save(task);
    } {
        Optional<Task> ot = .repository.findById(task.getId());
        Task t = ot.get();
        t.setDescription(task.getDescription());
        t.setCompleted(task.getCompleted()); .repository.save(t);
    } {
        Optional<Task> ot = .repository.findById(id);
        Task t = ot.get(); .repository.delete(t);
    }
} package import import import import import import // Registered as a Spring Service (Component) @Service public class TaskService // Automatically instantiate (via Spring IoC) @Autowired private // Boolean public isValid ( Task task) final if null return true return false // Get all records from the tasks table Iterable<Task> public getAllTasks () return this // Save a new task record Task public createTask ( Task task) final return this // Update an existing task record @Transactional Task public updateTask ( Task task) final this return this // Delete the task record by specified id @Transactional public void deleteTask ( id) final int this this Expose API endpoints Finally, you'll need to create a to expose four endpoints that can be used to perform the basic CRUD operations on your Tasks. controller Create a new folder called "controllers" in , and create a new filed within it named "TaskController.java". /src/main/java/com/mariadb/todo Open "TaskController.java" and add the following code. com.mariadb.todo.controllers; com.mariadb.todo.domain.Task; com.mariadb.todo.services.TaskService; org.springframework.beans.factory.annotation.Autowired; org.springframework.http.HttpStatus; org.springframework.http.ResponseEntity; org.springframework.web.bind.annotation.DeleteMapping; org.springframework.web.bind.annotation.GetMapping; org.springframework.web.bind.annotation.PostMapping; org.springframework.web.bind.annotation.PutMapping; org.springframework.web.bind.annotation.RequestBody; org.springframework.web.bind.annotation.RequestMapping; org.springframework.web.bind.annotation.RequestParam; org.springframework.web.bind.annotation.RestController; ( ) { TaskService service; () ResponseEntity<Iterable<Task>> get() { ResponseEntity.ok( .service.getAllTasks());
    } () { (service.isValid(task)) { ResponseEntity.ok( .service.createTask(task));
        } ResponseEntity.status(HttpStatus.I_AM_A_TEAPOT).build();
    } () { (service.isValid(task)) { ResponseEntity.ok( .service.updateTask(task));
        } ResponseEntity.status(HttpStatus.I_AM_A_TEAPOT).build();
    } () { (id > ) { .service.deleteTask(id); ResponseEntity.ok().build();
        } ResponseEntity.status(HttpStatus.I_AM_A_TEAPOT).build();
    }
} package import import import import import import import import import import import import import @RestController @RequestMapping "/api/tasks" public class TaskController @Autowired private // Get all tasks @GetMapping public return this // Create a new task @PostMapping ResponseEntity<Task> public post (@RequestBody Task task) if return this return // Update a task @PutMapping ResponseEntity<Task> public put (@RequestBody Task task) if return this return // Delete a task @DeleteMapping ResponseEntity<Void> public delete (@RequestParam id) int if 0 this return return Testing it out Now that everything has been constructed, it's time to test it out! First, build the application. $ mvn package And then run it. $ mvn spring-boot:run First, start by adding a new task to your to do list. $ curl --header \
  --request POST \
  --data \
  http: "Content-Type: application/json" '{"description":"A New Task"}' //localhost:8080/api/tasks While you can certainly query the database directly to confirm that a new task record has been added, where's the fun in that? Back to the API! $ curl https: //localhost:8080/api/tasks If all goes well you should receive the following JSON response: { : , : , : } "id" 1 "description" "A New Task" "completed" false Voilà, a fully reactive Java Spring application using JDBC and MariaDB! To view this code in its entirety check out the source . And if you're wondering "it'd sure be nice to see an implementation with a user interface", you're in luck! You can find a fully fleshed out implementation of a TODO application using and your choice of multiple API projects (R2DBC, JDBC, Node.js and Python) that integrate directly with MariaDB ! here React.js here Just getting started Now that you've successfully created a new Maven project using Spring Data JPA, JDBC and MariaDB, you have all the tools you need to get started creating fully reactive applications, utilizing the power of MariaDB, of your own!If you have any questions, suggestions or concerns with this blog post please let me know here or reach out to me directly on Twitter at !Thanks for taking the time to read this and happy coding! @probablyrealrob

How To Connect MariaDB Docker Containers with Java Spring And JDBC

Whether or not you've been actively developing within one of the or not, you've likely at least heard of the concept of by now. If not, I certainly encourage you to do a little research into the whole idea of using . JVM languages reactive programming declarative programming data streams In this article we'll take a look at the (very) brief background of not only what Reactive Relational Database Connectivity (R2DBC) is but it exists, and then dive into the code to see how the new can be used to create fully reactive, applications! why MariaDB R2DBC connector Java Spring We're going to walking through the process of creating a simple todo application, but if you'd prefer to jump directly into the code you can find it . here It all starts with Reactive Streams While I'm not going to give you the backstory and technical details behind reactive programming, it's important that we go over a few of the high level points before diving to all the hoopla. entire R2DBC For starters, it's important to know (or recall, depending on your current circumstance) that reactive programming boils down to the idea of using asynchronous data streams. A data stream is basically what it sounds like, a stream of data. But what does that really mean exactly? A stream is a sequence of ongoing events ordered in time. There are three types of events; value, error, completed signal. While we could certainly dive even deeper into the plethora of use cases for data streams, that's a little out of scope for this walk-through (I promise all of this is culminating to a walk-through). Instead we're going to focus on that the structure of a data stream is what brings the concept of to life. reactive streams Ok, ok, I know what you're thinking; "Damn, this dude is throwing around the word reactive more than a Midwesterner roaming through a crowd using the word ' '". Bear with me, there's a point to all this madness. I promise! ope Reactive Streams is simply a standard for asynchronous stream processing using the idea of non-blocking back pressure. "Seriously, Rob! Back pressure?! Are you just making things up now? I think I'm getting back pressure just reading this nonsense." No, I'm not just messing with you. You can think of back pressure as a way of the receiving side (of a data stream) telling the sending side when they are ready for more information and how much to send. Back pressure is an important concept because it's the foundation of which the reactive streams initiative is built on. Keeping out of the gritty details, the key takeaway here is that Reactive Streams is a set of specifications, or rules, used to define the way asynchronous streams are managed. - reactive streams creates a standard approach. TL;DR The following (very high level) diagram shows the interactions (to manage, yep, you guessed it, data streams!) between publishers and subscribers. For more information on reactive streams, specification came about, the interfaces involved and analysis on use cases, I encourage you to take a look at the . why this write-up by John Thompson For our purposes, we're interested in the specification itself, specifically how it's utilized with Reactive Relational Database Connectivity (R2DBC). R2DBC to the rescue R2DBC started as an experiment and proof of concept to enable integration of SQL databases into systems that use reactive programming models. It's necessary because of limitations of the API. Java Database Connectivity (JDBC) According to the : http://r2dbc.io "R2DBC specifies a that is intended to be implemented by driver vendors and used by client libraries. By using the R2DBC SPI, applications written in a JVM programming language can run SQL statements and retrieve results by using an underlying data source." service-provider interface (SPI) And if you haven't guess by now, the R2DBC SPI is based on and uses the concepts of publishers and subscribers to allow non-blocking back-pressure-aware data access. Ah, yes, we've come full circle! Reactive Streams - R2DBC is a new connectivity specification that supports reactive interactions all the way to the database level. TL;DR recently released their R2DBC connector implementation. It's completely and follows the MariaDB Corporation open-source R2DBC 0.8.1 specifications. This is where you ceremoniously crack your knuckles. It's time to code! Requirements Before jumping into code, you're going to need to make sure you have a few things on your machine: MariaDB Client Docker Java (v. 8+) (for testing the API endpoints) Curl Getting Started with MariaDB Let's assume you've either never used MariaDB or don't currently have an instance running on your machine. No problem! It only takes a couple of minutes, using a Docker container, to get MariaDB up and running. If you've already got an instance running feel free to skip down to the part where we create a new schema. To pull the and spin up a container simply open a terminal window and run the following: MariaDB Server image $ docker run -p 3306:3306 -d --name mariadb -eMARIADB_ROOT_PASSWORD=Password123! mariadb/server:10.4 The previous command will spin up a MariaDB Server container that you can connect to and communicate with using the . MariaDB client There are many SQL clients available out in the wild. For simplicity's sake, I've chosen to demonstrate how to use the official MariaDB Client, but certainly feel free to use whatever client you prefer. Connect to your MariaDB instance by executing the following command in a terminal window. You should see something like the following, which means you've successfully connected to the MariaDB instance! Next, create a new database for our TODO application. todo; CREATE DATABASE Then create a new table to store our tasks. todo.tasks ( , description ( ), completed ); CREATE TABLE id int varchar 200 boolean Getting reactive with R2DBC With a database instance spun up and schema created you're ready to create a fully-reactive application. Java Create a Maven project Start by navigating to , which will enable you to create a new -based project. https://start.spring.io Spring Maven For this project you can enter the following criteria. Next, add the following dependencies: Finally, click the "GENERATE" button to create and download the project (contained within a .zip file) to a desired location on your machine. Add the MariaDB R2DBC connector Navigate to the location where you downloaded the new Maven project (.zip file) to, and unzip.  Then use a code editor to open the project, and open pom.xml. Add a new dependency for MariaDB's R2DBC connector to the collection of dependencies. org.mariadb r2dbc-mariadb 0.8.2-alpha2 < > dependency < > groupId </ > groupId < > artifactId </ > artifactId < > version </ > version </ > dependency The MariaDB R2DBC connector is not available in the Spring dependencies listing because it's currently still in the alpha phase of development. Preparing the data integration Now that you've created a project that contains all of the dependencies you'll need, it's time to start really coding. Typically, I like to start by creating the entity (or model) classes. Navigate to /src/main/java/com/example/todo , create a new folder called "models", and create a new file within it named "Task.java". Open "Task.java" and add the following code. com.mariadb.todo.models; org.springframework.data.relational.core.mapping.Table; lombok.Data; ( ) { Integer id; String description; Boolean completed;
} package import import // Lombok annotation that eliminates getter/setter boilerplate code @Data // Annotation that will point to table "tasks" (pluralized in the database) @Table "tasks" public class Task @Id private private private Next, create a new folder called "repositories" in , and create a new filed within it named "TasksRepository.java" /src/main/java/com/mariadb/todo Open "TasksRepository.java" and add the following code. com.mariadb.todo.repositories; com.mariadb.todo.models.Task; org.springframework.data.repository.reactive.ReactiveCrudRepository; {
} package import import // Registered as a Spring Repository (Component) // Repository = a mechanism for encapsulating storage, retrieval, and search behavior which emulates a collection of objects public < , > interface TasksRepository extends ReactiveCrudRepository Task Integer The interface provides CRUD operations on a repository for a specific type, and follows reactive paradigms and uses types which are built on top of Reactive Streams. ReactiveCrudRepository Project Reactor Setting up the connection configuration As previously mentioned, in order to create a connection to a database using R2DBC you must first create a . The MariaDB implementation of the ConnectionFactory interface is called and it requires a instance, which contains a variety of configuration details used to connect to a MariaDB database instance. ConnectionFactory MariadbConnectionFactory MariadbConnectionConfiguration Create a new folder called "config" in , and create a new filed within it named "R2DBCConfig.java" /src/main/java/com/mariadb/todo Open "R2DBCConfig.java" and add the following code. com.mariadb.todo.config; org.mariadb.r2dbc.MariadbConnectionConfiguration; org.mariadb.r2dbc.MariadbConnectionFactory; org.mariadb.r2dbc.SslMode; org.springframework.context.annotation.Bean; org.springframework.context.annotation.Configuration; org.springframework.data.r2dbc.config.AbstractR2dbcConfiguration; org.springframework.data.r2dbc.repository.config.EnableR2dbcRepositories; java.io.IOException; java.io.InputStream; java.util.Properties; 2dbcRepositories { {
		ClassLoader loader = Thread.currentThread().getContextClassLoader();
		Properties props = Properties(); (InputStream f = loader.getResourceAsStream( )) {
			props.load(f); MariadbConnectionFactory(MariadbConnectionConfiguration.builder()
				.host(props.getProperty( ))
				.port(Integer.parseInt(props.getProperty( )))
				.username(props.getProperty( ))
				.password(props.getProperty( ))
				.database(props.getProperty( ))
				.build());
		} (IOException e) {
			System.out.println(e.getMessage()); ;
		}
	}
} package import import import import import import import import import import @Configuration @EnableR public class R2DBCConfig extends AbstractR2dbcConfiguration @Override @Bean MariadbConnectionFactory public connectionFactory () new try "db.properties" return new "host" "port" "username" "password" "database" catch return null Notice that R2DBCConfig retrieves the database connection details from a file called "db.properties". To add the connection configuration navigate to , create a new file called "db.properties" and add the following code. /src/main/java/com/mariadb/resources host=127.0.0.1
port=3306
username=USERNAME_HERE
password=PASSWORD_HERE
database=todo Although not recommended you can add connection details directly to R2DBCConfig.java. Create a data service Services can be used to manage the business logic of your application. The only service, TasksService, in this application is used for validating a Task object and integrating with the TasksRepository. Create a new folder called "services" in , and create a new filed within it named "TasksService.java" /src/main/java/com/mariadb/todo Open "TasksService.java" and add the following code. com.mariadb.todo.services; com.mariadb.todo.models.Task; com.mariadb.todo.repositories.TasksRepository; org.springframework.beans.factory.annotation.Autowired; org.springframework.stereotype.Service; org.springframework.transaction.annotation.Transactional; reactor.core.publisher.Flux; reactor.core.publisher.Mono; { TasksRepository repository; { (task != && !task.getDescription().isEmpty()) { ;
        } ;
    } { .repository.findAll();
    } { .repository.save(task);
    } { .repository.findById(task.getId())
                .flatMap(t -> {
                    t.setDescription(task.getDescription());
                    t.setCompleted(task.getCompleted()); .repository.save(t);
                });
    } { .repository.findById(id)
                .flatMap( .repository::delete);
    }
} package import import import import import import import // Registered as a Spring Service (Component) @Service public class TaskService // Automatically instantiate (via Spring IoC) @Autowired private // Boolean public isValid ( Task task) final if null return true return false // Get all records from the tasks table Flux<Task> public getAllTasks () return this // Save a new task record Mono<Task> public createTask ( Task task) final return this // Update an existing task record @Transactional Mono<Task> public updateTask ( Task task) final return this return this // Delete the task record by specified id @Transactional Mono<Void> public deleteTask ( id) final int return this this Expose API endpoints Finally, you'll need to create a controller to expose four endpoints that can be used to perform the basic CRUD operations on your Tasks. Create a new folder called "controllers" in , and create a new filed within it named "TasksController.java" /src/main/java/com/mariadb/todo Open "TasksController.java" and add the following code. com.mariadb.todo.controllers; com.mariadb.todo.models.Task; com.mariadb.todo.services.TaskService; org.springframework.beans.factory.annotation.Autowired; org.springframework.http.HttpStatus; org.springframework.http.ResponseEntity; org.springframework.web.bind.annotation.DeleteMapping; org.springframework.web.bind.annotation.GetMapping; org.springframework.web.bind.annotation.PostMapping; org.springframework.web.bind.annotation.PutMapping; org.springframework.web.bind.annotation.RequestBody; org.springframework.web.bind.annotation.RequestMapping; org.springframework.web.bind.annotation.RequestParam; org.springframework.web.bind.annotation.RestController; reactor.core.publisher.Flux; reactor.core.publisher.Mono; ( ) { TaskService service; () ResponseEntity<Flux<Task>> get() { ResponseEntity.ok( .service.getAllTasks());
    } () ResponseEntity<Mono<Task>> post( Task task) { (service.isValid(task)) { ResponseEntity.ok( .service.createTask(task));
        } ResponseEntity.status(HttpStatus.I_AM_A_TEAPOT).build();
    } () ResponseEntity<Mono<Task>> put( Task task) { (service.isValid(task)) { ResponseEntity.ok( .service.updateTask(task));
        } ResponseEntity.status(HttpStatus.I_AM_A_TEAPOT).build();
    } () ResponseEntity<Mono<Void>> delete( id) { (id > ) { ResponseEntity.ok( .service.deleteTask(id));
        } ResponseEntity.status(HttpStatus.I_AM_A_TEAPOT).build();
    }
} package import import import import import import import import import import import import import import import @RestController @RequestMapping "/api/tasks" public class TasksController @Autowired private @GetMapping public return this @PostMapping public @RequestBody if return this return @PutMapping public @RequestBody if return this return @DeleteMapping public @RequestParam int if 0 return this return Testing it out Now that everything has been constructed, it's time to test it out! First, build the application. $ mvn package And then run it. $ mvn spring-boot:run First, start by adding a new task to your to do list. $ curl --header \
  --request POST \
  --data '{ : }' \
  http://localhost: /api/tasks "Content-Type: application/json" "description" "A New Task" 8080 While you can certainly query the database directly to confirm that a new task record has been added, where's the fun in that? Back to the API! $ curl https://localhost:8080/api/tasks If all goes well you should receive the following JSON response: { : , : , : } "id" 1 "description" "A New Task" "completed" false Voilà, a fully reactive Java Spring application using R2DBC and MariaDb! To view this code in its entirety check out the source . And if you're wondering "it'd sure be nice to see an implementation with a user interface", you're in luck! You can find a fully fleshed out implementation of a TODO application using React.js and your choice of multiple API projects (R2DBC, JDBC, Node.js and Python) that integrate directly with MariaDB ! here here Just getting started Now that you've successfully created a new Maven project using Spring Data, R2DBC and MariaDB, you have all the tools you need to get started creating fully reactive applications, utilizing the power of MariaDB, of your own! If you have any questions, suggestions or concerns with this blog post please let me know here or reach out to me directly on Twitter at ! @probablyrealrob Thanks for taking the time to read this and happy coding!

Reactive Programming with Java Spring, R2DBC and MariaDB

Your head hits the pillow after a long day and instead of effortlessly drifting off to sleep, you find yourself staring at the ceiling not able to fall asleep. Or worse, you close your eyes only to open them frequently to check the clock. Clinical studies show that 40% of the population has trouble sleeping. I know for myself, it typically takes about 30 minutes to fall asleep. Now and then it is restless sleep. When I was younger, from about my teens to thirties, it would take me more than two hours to fall asleep. As an adult, I discovered I had weight ­related sleep apnea and had reached an unhealthy level where good sleep became a problem for me. Additionally, my years of sleep issues (compounded with genetics) recently resulted in a near fatal heart attack. This led me to thoroughly research the topic and share the facts with you in this article. Strange as it may sound, sleep is a very active process and it is more than the absence of wakefulness. It involves a complex physiological, psychological and behavioral states coordinated by your nerve cells (neurons) and brain chemicals (neurotransmitters). This is regulated by your central nervous system. Every organ in the body is affected by the quality your sleep. 5 Stages of Sleep To break it down even more, human sleep is characterized by five stages: Very shallow, superficial sleep. Eyes move slowly and little muscle activity occurs. Stage 1 sleep is fragmented and waking up occurs easily. It is not restorative or refreshing. Stage 1: Usually the longest stage of sleep. Eye movements slow down but awakening can still occur easily. Older individuals and those with chronic illness may spend most of the night in stage 2 sleep. Stage 2: The beginning of slow wave sleep. Many of the body’s repair processes occur during this deeper stage of sleep. It is more difficult to wake up and awakening may result in a confused, disoriented feeling. Stage 3: The deepest stage of Non REM sleep. Neurotransmitters and growth hormones are synthesized. Slow wave sleep is most prominent and intense during childhood and declines sharply at puberty and then slowly across the second and third decades of life. Stage 4: (Rapid Eye Movement) ­Most dreaming occurs in this stage. Breathing becomes more shallow. Rapid and irregular blood pressure and pulse rise, oxygen consumption increases and blood flow to the brain increases. Eyes move in a jerking manner, but muscle paralysis occurs in the extremities (to prevent acting out of dreams or nightmare). Stage 5 or REM: I was most interested in the relationship between sleep and heart disease. I found good research from Norway that suggests a strong link between insomnia and an increased risk of heart failure. This got my attention. During heart failure, the heart stops pumping enough blood around the body at the correct pressure. This is usually due to a weakened heart muscle or stiffness of the arteries that impairs the ability of the heart to work effectively. The Norway research is an examining insomnia and cardiovascular risk factors in more than 54,000 men and women aged 20­-89, who were free of heart failure at the beginning of the study. The results showed that those who reported insomnia symptoms suffered a threefold increased risk for heart failure, compared with those individuals who had no insomnia symptoms. This was the case even after adjustments for factors such as age, sex, marital status, tobacco and alcohol use, depression and anxiety. 11 ­year study Researchers concluded that difficulty falling asleep or maintaining sleep increased the risk of developing and/or dying from cardiovascular disease. Unhealthy Habits Below are some typical habits that cause problems with sleep include: Stress and excessive worry Limited exercise or inactivity Erratic sleep schedule Overeating and indigestion Excessive Alcohol, Caffeine and/or Nicotine Late afternoon napping (after 3pm) Bedroom disruptors: bright light, noise, temperature, television Overuse of sleep medications and/or other prescription drugs Norwegian researcher Dr. Borge Sversten, a professor of clinical psychology at the University of Bergen, noted in his research that sleep problems have become an economic nightmare with 253 million sick days being taken per year in the United States alone due to the problem. There is a growing recognition that insomnia and sleep apnea cause both absenteeism and may lead to serious accidents. A Harvard Medical School sleep study conducted in 2011 by researcher Ronald C. Kessler, Ph.D., found that American workers lost about 11 days and roughly $2,280 per year in lost productivity. The study also found that the estimated annual cost of sleep deprivation is over $63 billion in the U.S. A new Australian study found that about 2% of Australia’s GDP is lost due to sick leave caused by various sleep disorders. Aurora Health Care in Wisconsin, for example, had over 2600 employees take part in a 6 week online course for insomnia sufferers in 2012. This was after the managers surmised that sleep deprivation was an issue with their workforce. The follow up surveys and observations by Aurora say that an average of $672 in productivity savings per participant, per year were realized. There are around 90 sleep disorders listed in the International Classification of Sleep Disorders (or ICSD), these break down into four categories: Dyssomnias- A broad category of sleep disorders characterized by either hypersomnia or insomnia. The three major subcategories include intrinsic (i.e., arising from within the body), extrinsic (secondary to environmental conditions or various pathologic conditions), and disturbances of circadian rhythm. As much as 60% of the population suffers from one of these types of dissorders. Parasomnias- A category of sleep disorders that involve abnormal and unnatural movements, behaviors, emotions, perceptions, and dreams in connection with sleep. Most of these are more pronounced in youths and teenagers, with up to 20% of the population suffering from them, but scaling down to about 4% in adults. Medical or psychiatric conditions that may produce sleep disorders such as Pyschosis and mood disorders like Depression and Anxiety. Getting numbers for this is problematic as depression and anxiety can be caused by lack of sleep as opposed to the other way around. Lack of sleep can lead to a lot of psychiatric conditions. Sleeping sickness- a parasitic disease which can be transmitted by the Tsetse fly. The percentage of people getting insufficient rest or sleep from the ages of 18–64 is fairly consistent at around 25% according to the CDC, but the 25–34 group are the worst at nearly 29%. Not surprisingly, according to the same CDC data, people with children or who are obese get less sleep than their counterparts, around 30%. Somewhat surprising is that married couples get better sleep than all other configurations of singles and couples. Sleeping medications (either prescription or over the counter), when taken for long periods of time, become less effective. Also, studies with older individuals indicate that prolonged sleep medication may falsely appear as symptoms of dementia, including slowed and/or slurred speech, impaired thinking and memory problems. Over 20% of non-­chronic insomnia sufferers report yearly bouts of severe sleeping problems when experiencing stressful events, marital difficulty, health problems and problems with children and relatives. Mobile App Remedies With all the health apps and other health-­related technology, I decided to see if could find something helpful on my Android phone. Everything I found was some variation of nature sounds, white noise or monitoring systems that recorded how often I slept or woke up. None of these really helped, but then I ran across a brand new app called . The reason this stood out is because it is designed by two clinical psychologists with behavioral medical specialties. They took a completely different approach. SleepSound This particular app works by pulsing sound and light in a pattern that essentially synchronizes with your brain waves, causing the brain to slow down to the point that you are gently put it into sleep state. When I first tried, it was a very odd sensation. To start I was thinking that pulsing sounds and flashing lights would not calm me down. In fact, it feels strange for the first minute or two and then suddenly my brain started to relax. All I know is that I was asleep in what seemed to be a much shorter period of time than usual. The app has a configurable start and end pulse rate, as well as a session duration in case you take longer or shorter to get to sleep. The adjustable start rate is important as you could be more or less alert when you start. I tried a higher rate and was getting agitated, so according to the instructions, I lowered the start rate. Another nice feature if you’re prone to waking up is that you can use the app again and adjust the time and pulse rate until you are able to get back to sleep. The app also allowed for background sounds like ocean and wind chimes or no sound at all. I was getting fairly desperate for a better way to fall asleep and I found it.

Is Your Career Suffering Because of a Sleep Disorder?

Additional performance comparisons available in an updated post . Come see me speak about JSON and XML at SQL Saturday Columbus on July 22 ! Starting with the 2016 release, SQL Server offers native JSON support. Although the implementation is not perfect, . I am still a huge fan Even if a new feature like JSON support is awesome, I am only likely to use it if it is practical and performs better than the alternatives. Today I want to pit JSON against XML and see which is the better format to use in SQL Server. Enter XML, SQL’s Bad Hombre Full disclosure: I don’t love XML and I also don’t love SQL Server’s implementation of it. XML is too wordy (lots of characters wasted on closing tags), it has elements AND attributes (I don’t like having to program for two different scenarios), and depending on what language you are in, sometimes you need schema files and sometimes you don’t. programming SQL Server’s implementation of XML does have some nice features like a dedicated datatype that reduces storage space and validates syntax, but I find the querying of XML to be clumsy. All XML grievances aside, I am still willing to use XML if it outperforms JSON. So let’s run some test queries! Is JSON SQL Server’s New Sheriff in Town? Although performance is the final decider in these comparison tests, I think JSON has a head start over XML purely in terms of usability. SQL Server’s JSON function signatures are easier to remember and cleaner to write on screen. The test data I’m using is vehicle year/make/model data from . Here’s what it looks like once I loaded it into a table called : https://github.com/arthurkao/vehicle-make-model-data dbo.XmlVsJson CREATE TABLE dbo.XmlVsJson(Id INT IDENTITY PRIMARY KEY,XmlData XML,JsonData NVARCHAR(MAX)) ( if you want to play along at home) The full data query is available in this gist Data Size So XML should be larger right? It’s got all of those repetitive closing tags? SELECTDATALENGTH(XmlData)/1024.0/1024.0 AS XmlMB,DATALENGTH(JsonData)/1024.0/1024.0 AS JsonMBFROMdbo.XmlVsJson Turns out the XML is actually smaller! How can this be? This is the magic behind the . SQL doesn’t store XML as a giant string; it stores only the , leading to a reduction in space. SQL Server XML datatype XML InfoSet The JSON on the other hand is stored as regular old nvarchar(max) so its full string contents are written to disk. XML wins in this case. INSERT Performance So XML is physically storing less data when using the XML data type than JSON in the nvarchar(max) data type, does that mean it will insert faster as well? Here’s our query that tries to insert 100 duplicates of the row from our first query: SET STATISTICS TIME ON INSERT INTO dbo.XmlVsJson (XmlData)SELECT XmlData FROM dbo.XmlVsJsonCROSS APPLY(SELECT DISTINCT numberFROM master..spt_valuesWHERE number BETWEEN 1 AND 100)t WHERE Id = 1GO INSERT INTO dbo.XmlVsJson (JsonData)SELECT JsonData FROM dbo.XmlVsJsonCROSS APPLY(SELECT DISTINCT numberFROM master..spt_valuesWHERE number BETWEEN 1 AND 100)t WHERE Id = 1GO And the results? Inserting the 100 XML rows took 613ms on my machine, while inserting the 100 JSON rows took 1305ms… XML wins again! JSON ain’t looking too hot. Wait for it… I’m guessing since the XML data type physically stores less data, it makes sense that it would also write it out to the table faster as well. CRUD Operations — but how does it compare to XML on ? I’m incredibly impressed by SQL Server’s JSON performance when compared to .NET SQL Server Read Let’s select the fragment for our second car from our XML and JSON: SELECT t.XmlData.query('/cars/car[2]')FROM dbo.XmlVsJson tWHERE Id = 1 SELECT JSON_QUERY(t.JsonData, '$.cars[1]')FROM dbo.XmlVsJson tWHERE Id = 1 Result? (at 0ms vs 63ms for XML) when needing to pluck out a fragment from our larger object string. JSON wins What if we want to grab a specific value instead of a fragment? SELECT t.XmlData.value('(/cars/car[2]/model)[1]', 'varchar(100)') FROM dbo.XmlVsJson tWHERE Id = 1 SELECT JSON_VALUE(t.JsonData, '$.cars[1].model')FROM dbo.XmlVsJson tWHERE Id = 1 Once again with 0ms vs 11ms for XML. JSON wins If you look at the execution plans for these last two queries, it’s easy to see that XML has a lot more to do behind the scenes to retrieve the data: XML: JSON: Create We saw above that inserting rows of XML data is faster than inserting rows of JSON, but what if we want to insert new data into the object strings themselves? Here I want to insert the property “mileage” into the first car object: UPDATE t SET XmlData.modify('insert <mileage>100,000</mileage>into (/cars/car[1])[1]')FROM dbo.XmlVsJson tWHERE Id = 1 UPDATE t SET JsonData = JSON_MODIFY(JsonData,'$.cars[0].mileage','100,000')FROM dbo.XmlVsJson tWHERE Id = 1 In addition to the cleaner syntax ( is essentially the same as a ) the JSON insert runs in 22ms compared to the 206ms for XML. JSON_MODIFY() REPLACE() Another JSON win. Update Let’s update the mileage properties we just added to have values of 110,000: UPDATE t SET XmlData.modify('replace value of (/cars/car[1]/mileage/text())[1]with     "110,000"')FROM dbo.XmlVsJson tWHERE Id = 1 UPDATE t SET JsonData = JSON_MODIFY(JsonData, '$.cars[0].mileage','110,000')FROM dbo.XmlVsJson tWHERE Id = 1 Result? and was able to perform this update in 54ms vs XML’s 194ms. JSON has the quicker draw Delete Deleting large string data, a DBA’s dream *snicker*. Let’s delete the mileage property, undoing all of that hard work we just did: UPDATE t SET XmlData.modify('delete /cars/car[1]/mileage[1]')FROM dbo.XmlVsJson tWHERE Id = 1 UPDATE t SET JsonData = JSON_MODIFY(JsonData, '$.cars[0].mileage', null)FROM dbo.XmlVsJson tWHERE Id = 1 50ms to 159ms. JSON doesn’t take any time to reload and wins against XML again Read Part 2: Indexes So above we saw that JSON was faster than XML at reading fragments and properties from a single row of serialized data. But our SQL Server’s probably have LOTS of rows of data — how well does indexed data parsing do in our match up? First let’s expand our data — instead of storing all of our car objects in a single field, let’s build a new table that has each car on its own row: (once again, if you are playing along at home) full dataset at GitHub Now that we have our expanded data in our table, let’s add some indexes. The XML datatype in SQL Server has its own types of indexes, while . JSON simply needs a computed column with a regular index applied to it DROP INDEX IF EXISTS PXML_XmlData ON XmlVsJson2CREATE PRIMARY XML INDEX PXML_XmlDataON XmlVsJson2 (XmlData); ALTER TABLE dbo.XmlVsJson2ADD MakeComputed AS JSON_VALUE(JsonData, '$.make')CREATE NONCLUSTERED INDEX IX_JsonData ON dbo.XmlVsJson2 (MakeComputed) (Note: I also tried adding an XML secondary index for even better performance, but I couldn’t get the query engine to use that secondary index on such a basic dataset) If we try to find all rows that match a predicate: SELECT Id, XmlDataFROM dbo.XmlVsJson2 tWHERE t.XmlData.exist('/car/make[.="ACURA"]') = 1 SELECT Id, JsonDataFROM dbo.XmlVsJson2 tWHERE JSON_VALUE(t.JsonData, '$.make') = 'ACURA' XML is able to filter out 96 rows in 200ms and JSON accomplishes the same in 9ms. . A final win for JSON Conclusion If you need to store and manipulate serialized string data in SQL Server, there’s no question: JSON is the format of choice. Although JSON’s storage size is a little larger than its XML predecessor, SQL Server’s JSON functions outperform XML in speed in nearly all cases. Is there enough performance difference to rewrite all of your old XML code to JSON? Probably not, but every case is different. One thing is clear: new development should consider taking advantage of SQL Server’s new JSON functions. 💚 Enjoyed this post? Please recommend it by giving it a green heart below. Do you still plan on using XML instead of JSON for new development in SQL Server 2016+? I’d be curious to know why in the comments below.

XML vs JSON Shootout: Which Should I Use in SQL Server?

In these intensely competitive times, every application needs to be aesthetically appealing in addition to providing seamless functionality to satisfy the users. If an app does not function properly because of a visual interface error or if the site is unreadable, users may uninstall or leave the app. This can ultimately lead to a loss of customers and a drop in revenues. To avoid this and ensure the best possible user experience, companies are prioritizing visual regression testing. Let us study a couple of examples of visual regression testing to understand its importance: When you click on a drop-down image the menu does not slide down after adding more options.
You have reworked the complete layout of the page, and the submit button on the page is broken. These UI errors need to be fixed since changes in the elements can lead to the breakdown of the visual aesthetics. These illustrations clearly highlight the importance of conducting thorough visual regression testing before software releases. Visual regression testing checks the UI of an application after code changes and ensures that these different visual elements, like buttons, images, and text, all render correctly. Through this blog, we will examine visual regression, the different techniques used, the challenges testers face when performing the tests, and the best practices to overcome them. Common Visual Regression Techniques Visual testing ensures that visual glitches are identified early and do not spill over to the production stage. Let us now briefly examine the commonly used methods for regression testing: Manual visual testing: In this method, testers manually compare UI screenshots before and after making changes in the code.
Comparing layouts: It requires comparing the UI layout before and after changes are made and accounts for changes in the UI’s font, color, and other visual elements.
Comparing pixel-by-pixel: Used to test small, complex UI elements, this method involves comparing the UI’s pixels before and after changes.
Structural comparison: It compares the UI’s Document Object Model (DOM) before and after making changes.
Inserting visual checkpoints: In this technique, checkpoints are inserted into the UI to check the UI’s visual state at specific points in time. Manual Regression Testing Manual regression testing is recommended in the early testing stages when the UI is unstable. It is suitable for ad hoc testing and conducting quick on-the-spot checks. In this method, the testers manually check the layout and appearance of the visual elements. It involves taking the latest screenshots and comparing them with baseline screenshots to unearth any gaps. Benefits of Automated Visual Regression Testing Over Manual Methods The manual technique can be time-consuming and lead to a waste of resources because of its repetitive nature. The scale of manual testing grows with every new feature addition, thereby increasing the time spent by a human tester pouring over screenshots to identify bugs. It is impractical to manually conduct visual regression testing when there are tight deadlines to meet. In contrast, automated visual regression testing helps you automate repetitive tasks like checking the page following every code change. Even with the heavy initial investment, automated testing, especially with AI-powered features, helps you save time and money in the long run. Though automated visual regression testing reaps many benefits for testers and developers, it has to be properly implemented if they are to receive its benefits. Let us examine the best practices that go into a proper visual regression testing process. What To Remember While Conducting Visual Regression Testing Following these best practices will help optimize your automated visual regression testing process and help you gain its maximum benefits: Develop Appropriate Test Scenarios Clearly define what to record in the snapshots and the time to take them while testing. Remember to include user interactions in such scenarios since the applications will need to deal with them in the real world. Validate the Entire UI Page Instead of only validating individual components, ensure to validate the entire UI page. This practice will increase the test coverage and improve it. Pick the Right Automated Tool The visual regression testing tool you choose should be capable of ignoring false positives. It should be able to take care of pixel offsets, anti-aliasing, and other issues while ensuring the tests don’t fail. The automated algorithm must be able to analyze the page’s structure and perform layout comparisons. It should also be able to take care of content that is dynamic and moving. Compare Screenshots Testers should compare screenshots with recent ones to identify the disparities. This will help ensure that the UI remains the same, improving the user experience and product quality. Identify and Resolve Bugs Ensure to resolve bugs that the testing tool identifies or send them to the respective developers for fixing them. Remember to update screenshots to be used as a baseline for future regression tests after it is done. Choose the Right Situation To Perform Automated Testing Automated visual regression testing may not be appropriate for all scenarios. In some situations, using a combination of manual and automated methods is advisable. For example, when new features are added, they can be validated using an automation technique and then checked manually. Conduct a Detailed Review A team of reviewers or a single reviewer can examine how adjustments are made without causing interruptions in the desired outcome and make a report accordingly. Learn From Your Mistakes Learning from your successes and failures is crucial in visual regression testing. You need to identify the root causes and impacts of the visual changes detected by your tool. Testers must also identify false negatives and positives and adjust the tool settings and test cases accordingly. Conclusion In conclusion, successful implementation of visual regression testing in Agile teams requires a holistic approach that encompasses automation, collaboration, scalability, and comprehensive analysis. Visual regression testing can be a game-changer if you choose an appropriate automated testing tool with the right features and advantages. By adhering to these best practices, Agile teams can effectively leverage visual regression testing to deliver high-quality user interfaces in an iterative and efficient manner. In these intensely competitive times, every application needs to be aesthetically appealing in addition to providing seamless functionality to satisfy the users. If an app does not function properly because of a visual interface error or if the site is unreadable, users may uninstall or leave the app. This can ultimately lead to a loss of customers and a drop in revenues. To avoid this and ensure the best possible user experience, companies are prioritizing visual regression testing . visual regression testing Let us study a couple of examples of visual regression testing to understand its importance: Let us study a couple of examples of visual regression testing to understand its importance: When you click on a drop-down image the menu does not slide down after adding more options. You have reworked the complete layout of the page, and the submit button on the page is broken. When you click on a drop-down image the menu does not slide down after adding more options. You have reworked the complete layout of the page, and the submit button on the page is broken. These UI errors need to be fixed since changes in the elements can lead to the breakdown of the visual aesthetics. These illustrations clearly highlight the importance of conducting thorough visual regression testing before software releases. Visual regression testing checks the UI of an application after code changes and ensures that these different visual elements, like buttons, images, and text, all render correctly. Through this blog, we will examine visual regression, the different techniques used, the challenges testers face when performing the tests, and the best practices to overcome them. Common Visual Regression Techniques Visual testing ensures that visual glitches are identified early and do not spill over to the production stage. Let us now briefly examine the commonly used methods for regression testing: Manual visual testing: In this method, testers manually compare UI screenshots before and after making changes in the code. Comparing layouts: It requires comparing the UI layout before and after changes are made and accounts for changes in the UI’s font, color, and other visual elements. Comparing pixel-by-pixel: Used to test small, complex UI elements, this method involves comparing the UI’s pixels before and after changes. Structural comparison: It compares the UI’s Document Object Model (DOM) before and after making changes. Inserting visual checkpoints: In this technique, checkpoints are inserted into the UI to check the UI’s visual state at specific points in time. Manual visual testing: In this method, testers manually compare UI screenshots before and after making changes in the code. Manual visual testing: Comparing layouts: It requires comparing the UI layout before and after changes are made and accounts for changes in the UI’s font, color, and other visual elements. Comparing layouts: Comparing pixel-by-pixel: Used to test small, complex UI elements, this method involves comparing the UI’s pixels before and after changes. Comparing pixel-by-pixel: Structural comparison: It compares the UI’s Document Object Model (DOM) before and after making changes. Structural comparison: Inserting visual checkpoints: In this technique, checkpoints are inserted into the UI to check the UI’s visual state at specific points in time. Inserting visual checkpoints: Manual Regression Testing Manual regression testing is recommended in the early testing stages when the UI is unstable. It is suitable for ad hoc testing and conducting quick on-the-spot checks. In this method, the testers manually check the layout and appearance of the visual elements. It involves taking the latest screenshots and comparing them with baseline screenshots to unearth any gaps. Benefits of Automated Visual Regression Testing Over Manual Methods The manual technique can be time-consuming and lead to a waste of resources because of its repetitive nature. The scale of manual testing grows with every new feature addition, thereby increasing the time spent by a human tester pouring over screenshots to identify bugs. It is impractical to manually conduct visual regression testing when there are tight deadlines to meet. In contrast, automated visual regression testing helps you automate repetitive tasks like checking the page following every code change. Even with the heavy initial investment, automated testing, especially with AI-powered features, helps you save time and money in the long run. Though automated visual regression testing reaps many benefits for testers and developers, it has to be properly implemented if they are to receive its benefits. Let us examine the best practices that go into a proper visual regression testing process. What To Remember While Conducting Visual Regression Testing Following these best practices will help optimize your automated visual regression testing process and help you gain its maximum benefits: Develop Appropriate Test Scenarios Clearly define what to record in the snapshots and the time to take them while testing. Remember to include user interactions in such scenarios since the applications will need to deal with them in the real world. Validate the Entire UI Page Instead of only validating individual components, ensure to validate the entire UI page. This practice will increase the test coverage and improve it. Pick the Right Automated Tool The visual regression testing tool you choose should be capable of ignoring false positives. It should be able to take care of pixel offsets, anti-aliasing, and other issues while ensuring the tests don’t fail. The automated algorithm must be able to analyze the page’s structure and perform layout comparisons. It should also be able to take care of content that is dynamic and moving. Compare Screenshots Testers should compare screenshots with recent ones to identify the disparities. This will help ensure that the UI remains the same, improving the user experience and product quality. Identify and Resolve Bugs Ensure to resolve bugs that the testing tool identifies or send them to the respective developers for fixing them. Remember to update screenshots to be used as a baseline for future regression tests after it is done. Choose the Right Situation To Perform Automated Testing Automated visual regression testing may not be appropriate for all scenarios. In some situations, using a combination of manual and automated methods is advisable. For example, when new features are added, they can be validated using an automation technique and then checked manually. Conduct a Detailed Review A team of reviewers or a single reviewer can examine how adjustments are made without causing interruptions in the desired outcome and make a report accordingly. Learn From Your Mistakes Learning from your successes and failures is crucial in visual regression testing. You need to identify the root causes and impacts of the visual changes detected by your tool. Testers must also identify false negatives and positives and adjust the tool settings and test cases accordingly. Conclusion In conclusion, successful implementation of visual regression testing in Agile teams requires a holistic approach that encompasses automation, collaboration, scalability, and comprehensive analysis. Visual regression testing can be a game-changer if you choose an appropriate automated testing tool with the right features and advantages. By adhering to these best practices, Agile teams can effectively leverage visual regression testing to deliver high-quality user interfaces in an iterative and efficient manner.

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