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Introduction to SQL Ceiling

SQL Ceiling function is the mathematical function available in SQL that is used for the numeric type of values. These numeric values can be either integers or floating-point numbers. If the numeric value is formatted inside the string type of value as parameter then that value is also allowed for Ceiling function. In short, any value or expression that can be deduced to the numeric value can be used as a parameter to the Ceiling() mathematical function in SQL. This function helps us retrieve the minimum integer value that is greater or equivalent to the passed value.

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In this article, we will learn about how Ceiling function can be used to retrieve the integral value not less than the passed numeric value or expression, its syntax, and some of the examples that can help to make the implementation of the Ceiling() function easy and understandable.

The below is the syntax for the mathematical Ceiling() function in SQL –

Ceiling(expressionOrNumber);

expressionOrNumber: expressionOrNumber can be any integer or floating-point value or even a decimal value. In case if this numeric value is wrapped into strings then these string values are also acceptable. Other than the direct specification of numeric value any expression that will ultimately deduce to a numeric value is also allowed as a parameter to the Ceiling() function.

Return value: The return value of the Ceiling() function is the smallest integer value that is greater than or equal to the value that is passed as the parameter to the function. The type of the return value is dependent on the data type of the value that is passed as the parameter to the Ceiling() function. In case if the parameter is or integer data type then the return value is also of integer type. While in other cases if the deduced value of the parameter of the direct specification of the value of the parameter is of floating-point type then the datatype of the return value is of the floating-point data type itself.

Examples of SQL Ceiling

Following are the examples are given below:

1. Using Ceiling() function with Positive Values

We will consider the positive numeric value say 3.59 and then use the Ceiling function to retrieve the smallest integer value that is greater than or equivalent to the 3.59 value. Let us execute the following SQL query statement and observe the output –

SELECT Ceiling(3.59);

Output:

Let us consider one more example of positive value. But in this example, we will use an expression that will evaluate to the value that is of numeric type. Simply consider the expression 5 * 1.65 whose actual value is 8.25 and use this expression in Ceiling() function to retrieve minimum integral value greater than passed value using following query statement –

SELECT Ceiling(5 * 1.65);

Output:

Now, we will consider a positive number wrapped as a string and use it as a parameter to Ceiling() function. For example, consider “56.569” value that is used in the following manner –

SELECT Ceiling(56.569);

Output:

2. Using Ceiling() Function with Negative Values

We will consider the negative numeric value say -65.55 and then use the Ceiling function to retrieve the smallest integer value that is greater than or equivalent to the -65.55 value. Let us execute the following SQL query statement and observe the output –

SELECT Ceiling(-65.55);

Output:

Let us consider one more example of a negative value. But in this example, we will use an expression that will evaluate to the value that is of numeric type. Simply consider the expression 8 * -91.65 whose actual value is −733.2 and use this expression in Ceiling() function to retrieve minimum integral value greater than passed value using following query statement –

SELECT Ceiling(8 * -91.65);

Output:

Now, we will consider a negative number wrapped as a string and use it as a parameter to Ceiling() function. For example, consider “-98.154″value that is used in the following manner –

SELECT Ceiling(-98.154);

Output:

3. Using Ceiling() Function with Values in The Table

Let us now see how we can use the Ceiling() function in the query statements on the values of the columns of the table. We will create one table named workers using following query statement –

CREATE TABLE `workers` ( `developer_id` int(11) NOT NULL AUTO_INCREMENT, `team_id` int(11) NOT NULL, `name` varchar(100) DEFAULT NULL, `position` varchar(100) DEFAULT NULL, `technology` varchar(100) DEFAULT NULL, `salary` int(11) DEFAULT NULL, PRIMARY KEY (`developer_id`), UNIQUE KEY `name` (`name`) ) ENGINE=InnoDB AUTO_INCREMENT=28 DEFAULT CHARSET=latin1;

Output:

INSERT INTO `workers` VALUES (1,1,'Payal','Developer','Angular',30000), (2,1,'Heena','Developer','Angular',10000), (3,3,'Vishnu','Manager','Maven',25000), (4,3,'Rahul','Support','Digital Marketing',15000), (5,3,'Siddhesh','Tester','Maven',20000), (6,7,'Siddharth','Manager','Java',25000), (7,4,'Brahma','Developer','Digital Marketing',30000), (8,1,'Arjun','Tester','Angular',19000), (9,2,'Nitin','Developer','SQL',20000), (10,2,'Ramesh','Administrator','SQL',30000), (11,2,'Rohan','Admin',NULL,20000), (12,2,'Raj','Designer',NULL,30000);

Output:

Now we will calculate the average salary using the following query statement –

SELECT avg(salary) from workers;

Output:

If we want to retrieve the average salary in integer format with the greatest value that is greater than or equivalent to the average value using Ceiling() function using the following query statement –

SELECT Ceiling (avg(salary)) from workers;

Output:

Conclusion

Mathematical function Ceiling() is used rounding numeric values in SQL. We can retrieve the minimum value in integer format that is greater or equivalent to the passed numeric number or expression whose results can be either floating value of an integer or decimal value. The working of Ceiling() function is exactly different than Floor() function. Though both of them are used for rounding. Ceiling() funtion rounds up while Floor() function rounds down the numeric value.

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Basic Syntax Of Mariadb Logs With Examples

MariaDB server uses a different log file such as error log file, binary log file, general query log, and slow query log files. As per our requirement, we can change the status of log files that enable and disable log files. The main purpose of a log file is that to store different data during the different operation, for example, if we consider error log file, the error log file is used to store the critical error occurred during the MariaDB server operation, table corruption and start and stop information. If we consider SQL errors it can also be used in different log files by using the SQL_ERROR plugin.

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Syntax:

set global log type = value;

Explanation:

show global variables like 'log file name';

Explanation:

In the above example, we use show global variable command to see the log file, here we use log file name means you can use any log file name to see the details of a specified log file.

Now let’s see how logs work in MariaDB as follows. Basically, MariaDB uses different log files let’s see one by one.

1. Error Log

In this log file, it contains all records of critical errors that occurred during the different operations of the server like a corrupted table, which service start and stop information. SQL error is also used in a separate log file using the SQL_ERROR_LOG plugin.

Now let’s see how we can write error logs to a file.

When we need to configure an error log to write a log file at that time we must need to set the log_error system variable. By using a system variable we can configure a specific file name, if we don’t use specified file name to the configuration at that time log will be written to chúng tôi file in the directory and this is by default directory.

We can set the log_error system variable by using the server option group. For example to write error log in by default log file that is \${hostname}.err. We need to configure the following line as follows.

If we need to configure a specific file name as a log_error system variable and this file doesn’t have an absolute path then it uses a relative path to the datadir directory. Now see the following example of a configured error log that would be written to the chúng tôi file from datadir directory.

See in above example path is a relative path but some it also uses absolute path. For example:

We can also use another path to configure the error log file that is to set log – basename option which is configured by MariaDB.

2. General Query Log

The general query log file is used to store all details about every SQL query received from the client-side as well as all connected and disconnected client information.

Now see how we can enable the general query log as follows.

The general query log is to be disabled by default. To enable the general log file then we need to set the general_log system variable to 1 and it also changes dynamically.

For Example:

set global general_log = 1;

We can also set general_log file by using the server option group. For example:

Now see how we can configure the general query log file name as follows.

We can also set the general_log_file by using the server option group from the file option. for example:

In the above example, we use a relative path but it also uses an absolute path.

Let’s see how we select the destination file for the general query log as follows.

It can be written to a file on disk or it can be written on the general_log table in the MySQL database. For selecting the destination file for output we use log_output system variable.

set global log_output = 'specified file name'; 3. Slow Query Log

In this type of log file, the slow query log file is used to store records of SQL queries that take a long time to execute. In this type of query, the password then slow query log also contains the password.

Now let’s see how we can enable the slow query log as follows.

To enable the slow query log file we use the slow_query_log system variable that means we set the global variable is 1 as follows.

set global slow_query_log = 1

We can also set it by using the server option group from the file option.

Configuration of the slow query log by using the file name as follows.

We can configure the slow query log by using a filename that means we need to set a slow_query_log_file system variable by using the relative path as well as an absolute path, same like the above-mentioned types.

4. Binary Log Examples

Let’s see the different examples of MariaDB log as follows.

Suppose we need to show log error at that time we use the following statement.

show global variables like 'log_error';

Explanation:

In the above example, we use the show variable command to show log error. The final output of the show databases queries we illustrate by using the following snapshot.

Now how we can set the global general log by using the following statement.

set global general_log = 1;

Explanation:

The final output of the show databases queries we illustrate by using the following snapshot.

In this way, we can set all log types as per requirement.

Conclusion

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What Does Sql Stand For: Commands, Definitions, & Examples

SQL is one of the most widely used languages across various industries, from database development to data science and machine learning. Database administrators use it for creating and maintaining databases, whereas data scientists and analysts use it almost daily to extract, transform, and load data.

SQL stands for Structured Query Language and is a domain-specific programming language designed for managing and manipulating data in relational database management systems (RDBMS).

As you delve into the world of databases and start learning SQL, you’ll frequently come across experts calling SQL a universal language, meaning that it’s widely used in relational database systems such as MySQL, SQL Server, and Oracle.

In simpler words, if you learn SQL once, you can create, manage, and query data in all the relational databases out there (and have a lot of fun in the process).

At this point, you probably are wondering what a relational database is. Before you start working with SQL and SQL databases, you should have a solid understanding of the basic concepts of relational databases.

So, let’s take a brief look at relational databases!

A relational database is a type of database that organizes data into tables. Each table consists of rows and columns for you to work with. These tables are also called relations, hence the name “relational database.”

As you work with relational databases, you use SQL to create, modify, and query the data.

Like every programming language, to get started in SQL and SQL databases, you need to understand the syntax of SQL language. Luckily, the syntax of SQL is very different from all the other programming languages and it’s easy to get your head around the basics.

Let’s look at the syntax of SQL language!

SQL has many use cases, and each use case has its own set of syntax. We can divide the use cases into the following four branches:

Data Definition Language (DDL)

Data Manipulation Language (DML)

Data Control Language (DCL)

Data Query Language (DQL)

It is highly likely that you’ll not be required to know the syntax for all the above use cases. For instance, if you are a data analyst, you’ll mostly be working with the query syntax. However, familiarity with all the use cases will help you write more efficient SQL code.

In the sections below, we will look at the meaning of each of the above branches followed by examples to help you better understand the syntax of SQL.

DDL is a subset of SQL commands that deals with the structure of your database, tables, and other objects. Some common DDL commands are:

CREATE TABLE

ALTER TABLE

CREATE TABLE in SQL allows you to create a new table with specified columns and data types. Below you will find an example of a CREATE TABLE command:

CREATE TABLE employees ( id INT PRIMARY KEY, first_name VARCHAR(50), last_name VARCHAR(50), birth_date DATE );

These SQL statements code will create a new table named employees with the specified column properties.

With ALTER TABLE, you can modify an existing table, such as adding or dropping columns. Below, you will find an example of adding a new column to an existing table using ALTER TABLE.

ALTER TABLE employees ADD COLUMN email VARCHAR(100);

These SQL statements will add a new column called ’email’ with a VARCHAR data type and a maximum length of 100 characters to the existing ’employees’ table.

You can also use ALTER TABLE to remove columns from an existing table in your database. In the example below, we will remove a column from a table using ALTER TABLE:

ALTER TABLE employees DROP COLUMN email;

This command removes the ’email’ column from the ’employees’ table.

To delete an entire table from a database, you can use the DROP TABLE statement. Take a look at the following example where we delete the entire table using the DROP TABLE statement:

DROP TABLE employees;

This command will delete the entire ’employees’ table, including all of its data and constraints.

DML focuses on the manipulation and modification of data stored within your database. Some key DML commands include:

INSERT INTO

SELECT

UPDATE

DELETE

Once you create a table, you’d want to add data to it. To do that, you can use the INSERT INTO statement.

The example below demonstrates adding data to the employees table we created above.

INSERT INTO employees (id, first_name, last_name, birth_date) VALUES (1, 'John', 'Doe', '1985-03-20'); INSERT INTO employees (id, first_name, last_name, birth_date) VALUES (2, 'Jane', 'Smith', '1990-06-15'); INSERT INTO employees (id, first_name, last_name, birth_date) VALUES (3, 'Alice', 'Johnson', '1987-09-12'); INSERT INTO employees (id, first_name, last_name, birth_date) VALUES (4, 'Bob', 'Williams', '1992-01-23'); INSERT INTO employees (id, first_name, last_name, birth_date) VALUES (5, 'Charlie', 'Brown', '1988-11-07');

The above SQL statements will add 5 new entries to the employees table.

You can use the DELETE statement to delete records from your data tables.

Suppose you want to delete the employee with an id of 3 from the ’employees’ table. You can use the following DELETE statement:

DELETE FROM employees WHERE id = 3;

The SELECT statement is one of the statements that data analysts and scientists most frequently use. It allows you to retrieve data stored in a data table.

In the example below, we use the SELECT statement to retrieve data stored in the employees table.

SELECT * FROM employees;

The ‘*’ tells the compiler to retire all the data in the employees table.

If you’d like to make any changes to the data stored in your tables, you can use the UPDATE statement in SQL.

Suppose you want to update the last_name of the employee with an id of 1 in the ’employees’ table. You can use the following UPDATE statement:

UPDATE employees SET last_name = 'UpdatedLastName' WHERE id = 1;

These SQL statements will change the last_name in the employees table where the id is equal to 1.

DCL allows you to manage access and permissions within your database. With DCL commands, you can grant, revoke, or modify user privileges.

Some common DCL commands are:

GRANT

REVOKE

Suppose you want to grant the SELECT and INSERT privileges on the ’employees’ table to a user named ‘user1’. You can use the following GRANT statement:

GRANT SELECT, INSERT ON employees TO user1;

These SQL statements will allow ‘user1′ to SELECT and INSERT data into the ’employees’ table.

If you want to remove the INSERT privilege from ‘user1′ on the ’employees’ table, you can use the following REVOKE statement:

REVOKE INSERT ON employees FROM user1;

These SQL statements will remove the INSERT privilege from ‘user1′ on the ’employees’ table, while still allowing them to SELECT data from the table.

DQL deals exclusively with the retrieval of data from a database. In SQL, the main DQL command is SELECT. Using the SELECT command, you can define which columns to retrieve, apply filters, and join multiple tables.

In the following example, we use DQL statements to retrieve data and apply filters to it.

SELECT * FROM employees ORDER BY birth_date ASC;

In these SQL statements, the WHERE clause specifies that only rows with a birth_date greater than ‘1990-01-01’ should be returned. The ORDER BY statement sorts the result in ascending order.

One of the key aspects of SQL is that it can be easily integrated into the environment you are working in. For example, if you are making an application in Python, you can integrate SQL and Python together to run SQL queries within Python.

To know more about using SQL to query data, take a look at the following video:

In the next section, we will go over the popular integrations that SQL supports. Let’s get into it!

SQL easily integrates with languages like Python, C++, and Java. As you work with data analysis or data science projects, you will realize the effectiveness of SQL integrations with other programming languages. The seamless integration helps you handle large datasets efficiently.

Python: Python’s pandas library enables smooth SQL integration by allowing you to read and write data from SQL databases. Additionally, libraries like SQLAlchemy provide robust support for working with relational databases using SQL and Python together.

C++: Libraries like sqlpp11 and nanodbc allow you to connect and interact with relational databases using SQL within your C++ code. These libraries make it simple to execute SQL queries and manage database connections in a C++ environment.

Java: Java’s JDBC API allows seamless SQL database integration. With JDBC, you can connect, execute queries, and manipulate data from Java code.

Using SQL alongside these programming languages will improve your proficiency in data analysis. This will give you the ability to create more efficient and robust data-driven solutions.

Due to the widespread applications of SQL, several top companies have built their own relational database management systems which use SQL as their primary language. Knowledge of these databases will help you work across platforms.

We have listed some of the top relational database management systems in the next section.

As you explore SQL language, you’ll come across various relational database management systems that use SQL as their primary language for managing and interacting with stored data. Each SQL implementation has unique features and syntax variations.

Some popular RBDMS and their SQL implementations include: MySQL, SQL Server, Oracle, Oracle v2, and PostgreSQL.

MySQL is an open-source database management system developed by Oracle Corporation. It’s widely used in web applications and Oracle databases and is known for its speed, reliability, and ease of use.

MySQL supports standard SQL and provides a range of additional features, such as full-text search, transactions, and spatial data types.

MS SQL Server is Microsoft’s enterprise-level relational database management system (RDBMS). It offers a comprehensive range of tools and features required for enterprise-level data management, such as integration services, reporting, and Analysis Services.

MS SQL Server provides support for various programming languages, including T-SQL, which extends the standard SQL with additional constructs and features specific to SQL Server.

Oracle is the RDBMS developed by Oracle Corporation, servicing large corporations and enterprises requiring high-level data security, performance, and scalability.

Oracle v2 is just an older version of the Oracle RDBMS, and while it shares the core functionality, it may lack certain features introduced in later versions.

PostgreSQL is an open-source object-relational database management system (ORDBMS). It emphasizes extensibility and SQL compliance.

With all these options available in the market, you might be wondering what RDBMS and SQL implementation is better. The answer to this question drills down to your project requirements.

A good approach is to first understand your project requirements and then look for RDBMS that can address your requirements.

Data has become the fuel of our digital world because we see vast amounts of data being generated daily. To effectively utilize this data, you need a powerful tool like SQL.

As a professional in data science, data analysis, business analytics, or machine learning, mastering SQL is essential. In fact, proficiency in SQL can be a deciding factor in whether an employer hires or rejects you.

Beyond its value in the job market, SQL is invaluable for individuals working in the data field. Experts estimate that up to 80% of data work involves cleaning and managing data, which SQL can handle remarkably.

Moreover, SQL’s integration with various programming languages, such as Python, C++, and Java, broadens its applicability. This allows you to create robust data-driven solutions.

Learning SQL equips you with a competitive edge and a versatile tool to tackle data challenges in your professional journey.

So, as you navigate the expansive landscape of data management and analysis, remember SQL as your steadfast companion. With its powerful syntax and widespread use, mastering SQL can open up a multitude of opportunities in the tech world. Happy querying!

Comparison Of Different Sql Clauses

This article was published as a part of the Data Science Blogathon.

Introduction to SQL Clauses

SQL clauses like HAVING and WHERE both serve to filter data based on a set of conditions. The difference between the functionality of HAVING and WHERE  as SQL clauses are generally asked for in SQL interview questions. In this article, we will explain the functionalities and differences between the HAVING and WHERE clauses using an example.

HAVING Clause

SQL HAVING clause fetches the necessary records from the aggregated rows or groups on the basis of the given condition. It is generally used along with the GROUP BY clause and applies to the column operations. It operates on the aggregate functions such as ‘SUM’, ‘COUNT’, ‘MAX’, ‘MIN’, or ‘AVG’. We can use the HAVING clause only with SELECT statements. It cannot be used with UPDATE or DELETE statements. The syntax is as follows:

Syntax of the HAVING Clause with the SELECT statement:

FROM Table_Name

WHERE condition

GROUP BY column_1, column_N

HAVING condition

ORDER BY column_1, column_2, column_N;

WHERE Clause

SQL WHERE clause fetches the necessary records from a single table or multiple tables that meet the given condition. The WHERE clause can function without the GROUP BY clause and can perform row operations. It is used with single row functions like character functions, general functions, case conversion functions, date functions, or number functions. We can use the WHERE clause with any SELECT, UPDATE, and DELETE statement. The syntax is as follows:

a) Syntax of the WHERE Clause with the SELECT statement:

SELECT column_1, column_2, column_3, column_N

FROM Table_Name

WHERE condition;

b) Syntax of WHERE Clause with the UPDATE statement:

UPDATE Table_Name

SET column_1=value_1, column_2=value_2, column_3=value_3, column_N=value_N

WHERE condition;

c) Syntax of WHERE Clause with the DELETE statement:

DELETE FROM Table_Name WHERE condition;

Examples of HAVING and WHERE Clause Functionality

In the following example, we will demonstrate the functionality of the HAVING and WHERE clause:

Let’s start by creating a database called Student:

Use the Student database:

Let’s create the Student_Score table with Student_ID as the primary key:

Student_ID INT NOT NULL PRIMARY KEY,

Student_Name varchar(20),

Gender varchar(20),

Math_Score INT,

Bio_Score INT);

Insert the values into the Employee_detail table, then use the SELECT command to view the contents:

VALUES(1001, ‘Tom Ford’, ‘Male’, 68, 90),

(1002, ‘Ananya Verma’, ‘Female’, 97, 86),

(1003, ‘Eva Jackson’, ‘Female’, 86, 72),

(1004, ‘John Smith’, ‘Male’, 65, 91),

(1005, ‘Tanvi Sharma’, ‘Female’, 89, 63),

(1006, ‘Lilly Mathew’, ‘Female’, 74, 82);

HAVING clause with SELECT statement:

Our goal is to find out the average Math_Score of students who are gender grouped and have an average Math_Score greater than 60 and arranged in descending order.

FROM Student_Score

GROUP BY  Gender

ORDER BY AVG(Math_Score) DESC;

WHERE clause with SELECT statement:

FROM Student_Score

WHERE clause with an UPDATE statement:

For the student with Student_ID 1004, we want to update the Math_Score column to 65 and the Bio_Score column to 95.

SET Math_Score=70, Bio_Score=95

WHERE Student_ID=1004;

We can use the SELECT statement to view the updated Student_Score table:

WHERE clause with DELETE statement:

WHERE Gender=’Male’;

We can use the SELECT statement to view the filtered record:

Difference Between HAVING and WHERE Clause

HAVING WHERE

1. to fetch necessary records from the aggregated rows or groups on the basis of the specified condition. WHERE  clause enables you to fetch necessary records from the table on the basis of the specified condition.

2. HAVING clause should be used along with the GROUP BY clause and is used after the GROUP BY clause. It is possible for the WHERE clause to function without the GROUP BY clause and with the GROUP BY Clause, it’s been used before the GROUP BY Clause.

3. HAVING Clause applies to the column operations. WHERE Clause applies to the row operations.

4. Aggregate functions can be used in the HAVING Clause Aggregate functions cannot be used in the WHERE Clause

5. HAVING Clause is also known as a post-filter since it selects rows after aggregate calculations have been carried out. conducted.

6. HAVING Clause can only be used with ‘SELECT’ statements, but not with ‘UPDATE’ or ‘DELETE’ statements. WHERE Clause can be used with the ‘SELECT’, ‘UPDATE’, and ‘DELETE’ statements.

7. HAVING clause can be used with multiple row functions, such as ‘SUM’, ‘COUNT’, ‘MAX’, ‘MIN’, or ‘AVG’.

WHERE Clause can be used with a single row function such as character, general, case conversion, date, or number functions such as UPPER, LOWER, REPLACE, etc.

Conclusion

Related

Working And Examples Of React Render

Introduction to React Render

The following articles provide an outline for React Render. In React, Rendering is one of the most important processes used for making the browser to understand the components used. It is used to transform the react components in the Document Object Model (DOM) nodes which help the browser to understand and display the components on the screen. Elements manipulation is quite faster than manipulating DOM. React creates a Virtual DOM which looks the same as a DOM. Now, it allows us to make changes in the running application. React batches all of the changes made in the virtual DOM and compares it to the original DOM, and then it updates whatever has been changed.

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Syntax of React Render

ReactDOM.render()

ReactDOM.render(element, document.getElementById(‘root’));

Working of React Render

React elements are rendered into a DOM node by using ReactDOM.render. When we call for the first time to reactDOM.render(element, domnode). The contents of the DOM Node are replaced by the Element’s content. Now, if we call the render statement again, it updates the content of the DOM node by the new content from the element.

Examples of React Render

Different examples are mentioned below:

Example #1 – Basic Render in Timer

In the example below, we have used Render using a simple statement ReactDOM.render. The example below focuses on showing the time according to IST (Indian Standard Time).

chúng tôi

import React from "react"; import ReactDOM from "react-dom"; function tick() { const element = ( ); ReactDOM.render(element, document.getElementById("root")); } setInterval(tick, 1000);

Output:

Example #2 – Render used in List Rendering

In the example below, we have used render before return to import data from the database link in the chúng tôi file. And in chúng tôi we have imported render from react-dom.

chúng tôi

import React , { Component } from "react"; import axios from "axios"; export default class App extends Component { constructor() { super(); console.log("Constructor"); this.state = { title: "Heyoo! Welcome to Our Database", users: [] }; } callBeforeRender() { console.log( "Called after render 🙁 "); } async loadData() { console.log("Load data"); let { data } = await axios.get( ); this.setState({ users: data }); this.callBeforeRender(); } componentDidMount() { console.log("Did mount"); this.loadData(); }, 2000); } componentWillUpdate() { console.log("Will update"); }); } render() { console.log("Render"); return ( })} ); } }

chúng tôi

import React from "react"; import { render } from "react-dom"; import Main from "./App"; );

Output:

Example #3 – Counter using Render

In the example below, a simple counter with an increment of 1 is implemented, and in our chúng tôi file, render is used through ReactDOM.render.

import React from "react"; import ReactDOM from "react-dom"; function Logger(props) { console.log(`\${props.label} rendered`); return null; } function Counter(props) { const [count, setCount] = React.useState(0); return ( {props.logger} ); } ReactDOM.render( document.getElementById("root") );

Output:

Example #4 – Auto Rendering in React

In the example below, render is imported through ‘react-dom’ and used to return the values. The timer automatically increases and tells the time spent by you on the page.

chúng tôi

import React , { Component } from 'react' import { render , createPortal } from 'react-dom' class Foo extends Component { componentDidMount () { this.props.shareState({ foo: 'You have spent time in seconds notified above' }) } render () { return ( Heyoo! {this.props.append} ({this.props.count}) ) } } const target = document.body.appendChild( document.createElement('div') ) const className = `.js-component-\${name}` const targets = document.querySelectorAll(className) return [ ...reduced, target )) ] }, []) class App extends Component { constructor (props) { super(props) this.state = { theme: 'cyan', count: 0 } } componentDidMount () { count: count + 1 })) }, 1000) } render () { return ( <Components theme={this.state.theme} count={this.state.count} shareState={this.setState.bind(this)} sharedState={this.state} components={{ foo: Foo }} ) } }

Output:

Example #5 – Implementing 2 Patterns using Renders in React

In the example below, we have 2 props patterns, i.e Counter and List, and are combined in an application using Render through ReactDOM.render in chúng tôi file.

Counter.js and chúng tôi are the files used to implement the counter, and chúng tôi and chúng tôi are the files used to implement the list. Finally, the styling is taken care of using the chúng tôi file.

import React from "react"; import CounterWrapper from "./CounterWrapper"; return ( {({ increment , decrement )} ); }; export { Counter as default };

chúng tôi

import React from "react"; class CounterWrapper extends React.Component { state = { count: 0 }; const { count } = this.state; return this.setState({ count: count + 1 }); }; const { count } = this.state; return this.setState({ count: count - 1 }); }; render() { const { count } = this.state; return ( {this.props.children({ increment: this.increment, decrement: this.decrement, count: count })} ); } } export { CounterWrapper as default };

chúng tôi

import React from "react"; import ListWrapper from "./ListWrapper"; return ( {({ list , isLoading {isLoading ? ( ) : ( ))} )} )} ); }; export { List as default };

chúng tôi

import React from "react"; import axios from "axios"; class ListWrapper extends React.Component { state = { isLoading: true, error: null, list: [] }; fetchData() { axios .get(this.props.link) this.setState({ list: response.data, isLoading: false }); }) .catch( { error , isLoading: false } ) ); } componentDidMount() { this.setState({ isLoading: true }, this.fetchData); } render() { const { children } = this.props; const ui = typeof children === "function" ? children(this.state) : children; } } export { ListWrapper as default };

chúng tôi

import React from "react"; import ReactDOM from "react-dom"; import "./styles.css"; import Counter from "./Counter"; import List from "./List"; class App extends React.Component { render() { return ( ); } } const rootElement = document.getElementById("root");

chúng tôi

.App { font-family: 'Times New Roman' , Times , serif; text-align: center; }

Output:

Conclusion

Based on the above article, we have explained about React Render and its working. We have demonstrated multiple examples to understand how rendering can be used to transform the components into DOM nodes in different situations and requirements of the application.

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This is a guide to React Render. Here we discuss the introduction, syntax, and working of React Render along with examples and code implementation. You may also have a look at the following articles to learn more –

Constructor, Methods And Examples Of Java Printwriter

Introduction to Java PrintWriter

The java PrintWriter class is used to print objects in the formatted representation to the text output stream. The PrintWriter class is a built-in class in java that defines the java.io.PrintWriter package. The Writer class is a superclass of the PrintWriter. The PrintWriter class enables to write the formatted object to the underlying Writer class, for example, to write int, double, long and other primitive object or data as in the text, not in the values of the bytes. The PrintWriter class implements all the print method as the PrintStream except the methods which write the raw bytes. As the PrintWriter class intended to write the text, it is useful to generate reports to mix the numbers and text.

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Syntax:

The following is the declaration for chúng tôi PrintWriter class:

public class PrintWriter extends Writer { }

The above is the syntax of the PrintWriter, where it is extended to the Writer class.

Constructors of Java PrintWriter Class

Given below are the constructors mentioned:

PrintWriter(File file): These constructs create the new instance of PrintWriter, with the specified file and which is not automat line flushing.

PrintWriter(File file, String ch): These constructs create the new instance of PrintWriter, with the specified file, charset, and not automatic line flush.

PrintWriter(OutputStream out): These constructs create the new instance of PrintWriter from an existing OutputStream and which is not automat line flush.

PrintWriter(OutputStream out, booleanautoFlush): These constructs create the new instance of PrintWriter from an existing OutputStream.

PrintWriter(String fName): These constructs create the new instance of PrintWriter with the specified file name and which is not automat line flush.

PrintWriter(String fileName, String csn): These constructs create the new instance of PrintWriter with the specified file name and charset, and it is not automat line flush.

PrintWriter(Writer out): These constructs create the new instance of PrintWriter, which is not an automat line flush.

PrintWriter(Writer out, booleanautoFlush): These constructs create the new instance of PrintWriter.

Methods of Java PrintWriter Class

Given below are the methods:

public void print( Object obj): This method prints an object.

public void println(boolean x): This method prints the boolean value.

public void println(char[] x): This method prints an array of characters.

public void println(int x): This method prints an integer. Similar methods to prints for all different primitive objects.

public PrintWriterappend(char ch): This method appends the pass character to the writer.

public PrintWriterappend(CharSequencechseq): This method appends the specified character sequence to the writer.

public PrintWriterappend(CharSequencech, int start, int end): This method appends a subsequence of pass character to the writer.

public booleancheckError(): This method checks its error state and flushes the stream.

public protected void clearError(): This method clears an internal error state of the stream.

public protected void setError(): This method indicates that an error occurs.

public PrintWriterformat(String format, Object..args): This method writes the formatted string to this writer with the passed format string and arguments.

public void flush(): This method flushes the stream.

public void close(): This method closes the stream.

Examples of Java PrintWriter

Given below are the examples mentioned:

Example #1

Here we create a PrintWriter object by using the PrintWriter class constructor and pass the file name to write in it.

package p1; import java.io.File; import java.io.PrintWriter; public class Demo { public static void main( String[] arg) { try { PrintWriter pw =null; pw = new PrintWriter(new File("D:\data.txt")); pw.write("This ia an example text for PrintWriter."+"n"); pw.write("This ia an example number for PrintWriter :" +(int)563+ "."); pw.flush(); pw.close(); System.out.println("Print writer done. you can open the file."); }catch(Exception e) { System.out.println(e); } } }

Output:

When we open the file, we can see the content of the file as below:

As in the above code, the file “data.txt” is opened to write some data with the help of PrintWriter class and its constructor.

Example #2

Code:

package p1; import java.io.File; import java.io.PrintWriter; import java.util.Locale; public class Demo { public static void main( String[] arg) { String str="Hello"; String str2=" World"; char ch='H'; try { PrintWriter pw =null; pw = new PrintWriter(System.out); pw.print("print(inti) : "+ 123); pw.println(); pw.print("print(float f) : " +34.65f); pw.println(); pw.print("print(boolean b) : " +true); pw.println(); pw.print("print(char ch) : "+ch); pw.println(); pw.print("print(String s) : "+str); pw.println(); pw.print("print(Object Obj) : " +pw); pw.println(); pw.print("append(CharSequencecsq) : "); pw.append(str); pw.append(str2); pw.println(); pw.println("checkError() : " +pw.checkError()); pw.print("format() : "); pw.format(Locale.CHINA, " This is an china formatted example for %s text.",str); pw.flush(); pw.close(); }catch(Exception e) { System.out.println(e); } } }

Output:

As in the above code, writing some of the data we can see in the output to the out console (System.out) with PrintWriter class constructor and methods.

Conclusion

The PrintWriter class is a built-in class in java that is defined in the java.io.PrintWriter package, and it is used to print an object in the formatted representation to the text output stream. The PrintWriter class is the subclass of the Writer class.

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This is a guide to Java PrintWriter. Here we discuss the introduction to java PrintWriter, constructors, methods and examples for better understanding. You may also have a look at the following articles to learn more –

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