Friday, 29 March 2019

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Mastering Spring 4 and Hibernate 4 Integration

Integrating powerful frameworks like Spring and Hibernate is a core skill for any Java developer. In this guide, we walk through a complete example of how to connect these frameworks using MySQL 8 and Maven with a classic XML-based configuration.

1. Why XML Configuration?

While annotations are popular, understanding XML configuration is essential for maintaining legacy systems and understanding how the "magic" happens behind the scenes. It provides a clear, centralized place to manage your beans and database settings.

2. The Role of Maven

Maven acts as your project manager. Instead of manually searching for JAR files, we define our dependencies in the pom.xml. This ensures that Spring, Hibernate, and the MySQL connector all work together seamlessly.

3. Setting Up MySQL 8

MySQL 8 introduced new security and performance features. We'll show you the exact properties you need in your configuration to ensure a stable connection between your Java application and the database.

Key Takeaways for Beginners:

How to structure a Maven project.
Defining DataSources and SessionFactories in XML.
Performing basic CRUD operations.

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Spring 4 + Hibernate 4 + MySQL 8 + Maven Integration example using Annotations Configuration

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Spring 4 and Hibernate 4 Integration Guide

Welcome! In this tutorial, we explore how to integrate Spring 4 with Hibernate 4 using MySQL 8 and Maven. This guide is perfect for beginners who want to understand how these technologies work together using modern annotation-based configurations.

1. Setting Up Your Database

First, we start with a simple Employee table. This table includes essential columns such as:

ID: Unique identifier
Name: Employee name
Joining Date: When the employee started
Salary: Compensation details
SSN: Social Security Number for identification

2. Project Structure & Dependencies

Using Maven, we manage all necessary dependencies in the pom.xml file. A critical tip: Always ensure your MySQL Connector version is compatible with the MySQL server installed on your machine to avoid connection issues.

3. Configuration Classes

We move away from bulky XML files and use Java Annotations. We create a HibernateConfiguration class where we define:

DataSource: Contains the URL, username, and password for your database.
SessionFactory: Manages Hibernate sessions.
TransactionManager: Handles database transactions smoothly.

4. Performing CRUD Operations

In the tutorial, we demonstrate how to perform the core database actions (CRUD):

Create: Saving a new employee record.
Read: Fetching all employees or searching by SSN.
Update: Modifying existing data (like changing a salary).
Delete: Removing records from the table.

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Wednesday, 27 March 2019

What is HibernateTemplate [hibernate] in Spring?

https://www.youtube.com/watch?v=Jq1xJA26PWQ

What is AnnotationSessionFactoryBean [hibernate] in Spring?

https://www.youtube.com/watch?v=Rm7Owfjd9dE

Sunday, 24 March 2019

What is HibernateTransactionManager in Spring ?

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Spring hibernate integration - Playlist

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Spring 3 + hibernate 3 + Maven integration example

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Mastering Spring 3 and Hibernate 3 Integration

Are you looking to build robust Java applications? Integrating Spring 3 with Hibernate 3 is a classic yet powerful approach. In this comprehensive guide, we walk through a complete integration example using Maven to manage your dependencies.

Why Use Spring with Hibernate?

Spring provides excellent support for Hibernate by handling the boilerplate code. It manages the session factory, transaction management, and simplifies data access through the DAO pattern.

Key Components of the Project

In the video, we cover several critical areas for a successful setup:

Maven Project Structure: How to organize your folders and source files.
The pom.xml File: Adding dependencies for Spring Core, Spring ORM, Hibernate, and the MySQL Connector.
Application Context: Configuring the DataSource, SessionFactory, and Transaction Manager in XML.
Entity Mapping: Mapping your Java classes to database tables using Hibernate XML mappings.

Step-by-Step Implementation

We start by creating a simple Employee model. From there, we build the DAO (Data Access Object) layer to handle database interaction. You will see how the HibernateTemplate or SessionFactory makes database queries clean and efficient.

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Sunday, 17 March 2019

How to remove the Observer from the Observable in Java? | Observer and O...

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Managing Observers in Java's Observable Class

In event-driven architectures and the Observer Design Pattern, registering observers is only half the picture. To avoid memory leaks, unwanted event handling, and redundant notifications, applications must have clean mechanisms to unregister or unsubscribe observers when they are no longer needed.

Java's built-in java.util.Observable provides two primary methods to detach listeners:

deleteObserver(Observer o): Removes a specific observer from the internal observer list.
deleteObservers(): Clears and unregisters all active observers in a single operation.

How deleteObserver and deleteObservers Work

Consider an e-commerce price alert model where customer observers (such as PeterObserver and JohnObserver) listen for price changes on a product like NokiaMobilePriceObservable:

Initial State: Both observers are registered using addObserver(). Calling countObservers() returns 2. When the price changes, both receive notifications.
Removing a Single Observer: Calling deleteObserver(peterObserver) unregisters Peter. The count drops to 1, and subsequent price modifications will notify only John.
Removing All Observers: Calling deleteObservers() cleans up all remaining registrations, dropping the active count to 0. No further notifications are dispatched.

Why Observer Deregistration Matters

Prevents Memory Leaks: Known as the "lapsed listener" problem, keeping lingering references inside subjects prevents garbage collection of unused observer objects.
Optimizes Performance: Eliminates processing overhead by ensuring notifications are dispatched only to components actively listening.
Dynamic Lifecycle Control: Gives clients complete runtime authority over when to subscribe or unsubscribe from subject notifications.

Real-Time Example: Mobile Price Tracking Alert System

The Observer Design Pattern is widely applied in real-time notification systems, such as e-commerce price alerts, stock market updates, and live score trackers. In Java, this pattern can be implemented directly using the built-in java.util.Observer interface and java.util.Observable class.

In this scenario, a mobile phone's price changes dynamically, and multiple registered customers (observers) need to be instantly informed whenever an update occurs.

Core Participants in the Application

NokiaMobilePriceObservable (Subject/Observable): Extends Observable. It maintains the product price attribute and dispatches updates using setChanged() and notifyObservers().
JohnObserver & PeterObserver (Concrete Observers): Implement the Observer interface and override the update(Observable o, Object arg) method to react to price revisions.
ObservableDemo (Driver Class): Registers the observers with the observable and simulates changing the product price to trigger notifications.

Step-by-Step Implementation Flow

Define Observers: Create classes like JohnObserver and PeterObserver implementing java.util.Observer to receive and print notifications when update() is invoked.
Create the Observable: Subclass java.util.Observable to create NokiaMobilePriceObservable. When setPrice() is called, flag the change with setChanged() and notify listeners via notifyObservers().
Subscribe & Trigger: In the client code, instantiate the mobile observable with an initial price, attach both observers using addObserver(), and update the price to observe automatic event delivery.

Why Use Observer and Observable?

Loose Coupling: The observable subject does not need to know the internal implementation details of John or Peter; it only interacts via the standard Observer interface.
Broadcasting Capabilities: Supports one-to-many communication, allowing any number of interested observers to subscribe or unsubscribe at runtime.
Clean Event Architecture: Eliminates continuous polling by letting the subject automatically push data updates as soon as state changes happen.

What Are Observer and Observable in Java?

In software design, keeping dependent objects synchronized when a core data model changes is a common requirement. In Java, this is directly supported via the built-in classes in the java.util package:

java.util.Observable (Class): Represents the subject or model being observed. It maintains an internal list of observers and notifies them whenever its state changes.
java.util.Observer (Interface): Implemented by any class that wants to be informed of state changes occurring in an Observable object.

This mechanism forms the backbone of the classic Model-View paradigm and the Observer Design Pattern, decoupling state management from event listeners.

How the Notification Workflow Works

Observer Registration: Observers implement the Observer interface and its update(Observable o, Object arg) method. They register with the observable instance using addObserver(Observer o).
State Modification: When internal state changes (e.g., product price updates), the observable invokes setChanged() to flag that a state modification occurred.
Automatic Broadcasting: The observable calls notifyObservers(), which loops through all registered observers and triggers each observer's update() method automatically.

Key Architectural Benefits

Loose Coupling: The subject only interacts with listeners through the generic Observer interface without caring about their concrete classes.
One-to-Many Communication: Easily supports multiple independent listeners receiving simultaneous updates.
Event-Driven Design: Replaces continuous polling with immediate, event-triggered updates.

Sunday, 10 March 2019

Spring - How to get all records by calling the stored procedure using SimpleJdbcCall

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Retrieve All Records from Stored Procedures Using SimpleJdbcCall

Stored procedures in relational databases are often used not just to perform updates or compute single output values, but to return entire result sets. In Spring JDBC, SimpleJdbcCall provides an elegant, multi-threaded mechanism to call stored procedures and map returned rows directly into domain objects or lists using RowMapper.

1. Returning ResultSets from Stored Procedures

When a database stored procedure executes a SELECT query, it opens a cursor or returns a ResultSet:

Database Encapsulation: Complex join queries or business filtering logic remain encapsulated inside the database procedure.
Automatic ResultSet Binding: Spring's SimpleJdbcCall intercepts the returned cursor and binds it directly to Java objects without manual iteration over JDBC result sets.
Thread Safety: Like other Spring JDBC template classes, a configured SimpleJdbcCall is thread-safe and can be reused concurrently across multiple requests.

2. Configuring returningResultSet with RowMapper

To map multiple returned rows to Java objects, configure returningResultSet on your SimpleJdbcCall instance:

Specify Procedure Name: Call withProcedureName("procedure_name") to identify the target stored procedure.
Bind ResultSet to RowMapper: Use returningResultSet("resultSetKey", new BeanPropertyRowMapper<>(TargetClass.class)) or supply a custom RowMapper implementation.
Zero Boilerplate: Spring automatically handles column-to-property conversion, connection management, and resource cleanup.

3. Executing the Call and Extracting the Record List

Executing the procedure and accessing your records takes only a couple of lines:

Execute the Call: Call simpleJdbcCall.execute() (or pass a MapSqlParameterSource if the procedure accepts filter parameters).
Extract the List: Access the returned Map<String, Object> using the key specified in returningResultSet.
Typed List Result: Cast the map entry directly to List<TargetClass> to obtain the complete record collection ready for use in your application.

4. Practical Summary & Best Practices

Key tips for production environments:

Always configure the SimpleJdbcCall instance during DAO initialization or bean definition rather than inside method calls.
Use BeanPropertyRowMapper for quick POJO mapping when column names match Java property names (camelCase to snake_case).

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Calling Stored Functions with SimpleJdbcCall in Spring JDBC

In addition to calling stored procedures, Spring JDBC's SimpleJdbcCall provides seamless support for executing database stored functions. Unlike stored procedures which return values through output parameters or result sets, stored functions compute and return a single scalar value directly. With SimpleJdbcCall, invoking stored functions requires minimal setup and zero SQL boilerplate.

1. Procedures vs. Functions in SimpleJdbcCall

While both are database routines, stored functions have specific differences:

Direct Return Value: Stored functions return an explicit scalar value via a RETURN statement rather than through output parameters.
Configuration Method: Instead of withProcedureName(...), you configure withFunctionName(...) on your SimpleJdbcCall instance.
Single-Value Execution: Using executeFunction(...) allows you to directly retrieve the typed return value without extracting it from a map.

2. Configuring SimpleJdbcCall for Stored Functions

Setting up SimpleJdbcCall to target a database function is clean and intuitive:

Initialize with DataSource: Instantiate SimpleJdbcCall by injecting your configured DataSource or JdbcTemplate bean.
Specify the Function Name: Call withFunctionName("function_name") to indicate the target function routine.
Compile Once: Configure the call instance once inside your DAO bean or repository constructor to ensure thread-safe reuse.

3. Executing the Function and Retrieving Results

Invoking the database function takes only a couple of lines:

Supply Input Parameters: Use MapSqlParameterSource to pass arguments corresponding to the function's parameter signature.
Execute with Return Type: Call simpleJdbcCall.executeFunction(ReturnType.class, paramSource), specifying the expected return type (such as String.class, Integer.class, or Double.class).
Direct Value Access: The method returns the typed result directly, eliminating manual casting.

4. Key Advantages

Utilizing SimpleJdbcCall for database functions provides significant benefits:

Type Safety: Direct mapping into target Java wrapper classes eliminates casting bugs.
Zero Boilerplate: No need for manual CallableStatement setups or raw SQL syntax like {? = call function_name(?)}.
Metadata Awareness: Automatically resolves parameter bindings and types directly from the database schema.

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Spring - Calling a stored procedure with SimpleJdbcCall (Explicitly declaring parameters)

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Calling Stored Procedures with Explicit Parameters Using SimpleJdbcCall

While Spring JDBC’s SimpleJdbcCall is capable of discovering stored procedure parameters automatically via database metadata, certain databases or driver configurations restrict metadata access. In enterprise production environments, explicitly declaring parameters using declareParameters(...) provides fine-grained control, optimal performance, and deterministic parameter mapping.

1. Why Declare Parameters Explicitly?

Defining parameters explicitly offers key structural and architectural benefits:

Avoid Database Metadata Lookups: Bypasses catalog queries at startup, which speeds up initialization and works even when database user permissions restrict metadata visibility.
Precise SQL Type Mapping: Explicitly defines SQL types (such as Types.VARCHAR or Types.INTEGER) for both input and output parameters.
Consistent Cross-Platform Execution: Ensures predictable behavior across different database engines like MySQL, Oracle, PostgreSQL, and SQL Server.

2. Using declareParameters with SqlParameter & SqlOutParameter

Spring provides specialized parameter classes to declare procedure signatures clearly:

SqlParameter: Used to define an IN parameter, specifying its name and standard JDBC type from java.sql.Types.
SqlOutParameter: Used to declare an OUT parameter that captures return values from the procedure.
SqlInOutParameter: Used when a parameter supplies an initial value and receives a modified output upon execution.

3. Executing the Procedure and Handling Output

Once configured, executing the stored procedure and parsing output takes minimal effort:

Bind Values: Use MapSqlParameterSource to provide values corresponding to each declared SqlParameter.
Run Execute: Call simpleJdbcCall.execute(parameters) to invoke the database routine.
Extract Results: The returned Map<String, Object> contains values mapped by the exact names specified in your SqlOutParameter declarations.

4. Practical Summary & Best Practices

For critical enterprise applications:

Combine withoutProcedureColumnMetaDataAccess() with declareParameters(...) when connecting to locked-down production databases.
Initialize and configure the SimpleJdbcCall instance once inside your DAO bean for thread-safe concurrent execution.

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Calling Stored Procedures with SimpleJdbcCall in Spring JDBC

Executing database stored procedures in standard JDBC traditionally involves configuring verbose CallableStatement instances, registering OUT parameters manually, and handling raw SQL strings. Spring JDBC provides SimpleJdbcCall, a multi-threaded, metadata-aware class designed to simplify calling stored procedures and database functions with minimal configuration.

1. What is SimpleJdbcCall?

SimpleJdbcCall is part of the org.springframework.jdbc.core.simple package. It automatically reads database metadata to inspect parameter names, types, and directions (IN, OUT, and INOUT):

Automatic Parameter Detection: Discovers procedure signature parameters from the database catalog, reducing manual registration.
Zero Boilerplate: Eliminates explicit SQL execution queries like {call procedure_name(?, ?)}.
Result Mapping: Easily captures returned scalar values, output parameter maps, or multiple ResultSet rows using RowMappers.

2. How to Configure SimpleJdbcCall

To set up SimpleJdbcCall inside your DAO or repository layer:

Instantiate with DataSource or JdbcTemplate: Initialize the instance by passing your configured DataSource or JdbcTemplate bean.
Declare the Procedure Name: Call withProcedureName("procedure_name") to specify the target procedure.
Register Out Parameters (Optional): If the database metadata does not supply return definitions, declare parameters explicitly with declareParameters(...).
Compile the Call: The configuration compiles automatically on the first call, making subsequent invocations fast and thread-safe.

3. Passing IN Parameters and Retrieving OUT Results

Invoking the procedure and obtaining results is straightforward:

Supplying Parameters: Use MapSqlParameterSource to add IN parameters by chaining .addValue("paramName", value).
Executing the Call: Call simpleJdbcCall.execute(paramSource), which returns a Map<String, Object> containing all OUT parameter values indexed by parameter name.
Accessing Outputs: Retrieve values cleanly from the map using the corresponding output parameter name key.

4. Key Advantages

Using SimpleJdbcCall provides significant improvements over low-level JDBC approaches:

Cleaner DAO Layer: Cuts out dozens of lines of repetitive setup code.
Thread Safety: Configure once during bean initialization and safely reuse across multiple concurrent requests.
Fewer Runtime Bugs: Eliminates mismatched index positions and incorrect SQL type registrations.

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Efficient Data Insertion: SimpleJdbcInsert with MapSqlParameterSource

In Spring JDBC, SimpleJdbcInsert streamlines database write operations by reading table metadata directly and eliminating the need for boilerplate INSERT INTO SQL statements. When coupled with MapSqlParameterSource, mapping input parameters becomes structured, highly readable, and type-safe.

1. Why Use MapSqlParameterSource?

While SimpleJdbcInsert can accept standard Java Map objects, MapSqlParameterSource provides key benefits tailored for JDBC operations:

Fluent Method Chaining: Add multiple parameters cleanly using chained .addValue("columnName", value) calls.
Explicit SQL Type Specification: Supports explicit SQL types (e.g., Types.VARCHAR, Types.INTEGER) when inserting null or custom values.
Spring-Native Integration: Implements the SqlParameterSource interface natively, allowing seamless interoperability across Spring JDBC components.

2. Setting Up SimpleJdbcInsert

Configuring SimpleJdbcInsert in your data access layer is quick and clean:

Instantiate with DataSource: Initialize the instance by passing your configured DataSource bean.
Set Table Name: Use withTableName("table_name") to specify the target database table.
Restrict Columns (Optional): Optionally define specific columns using usingColumns(...) to let database defaults handle the rest.
Generated Keys: Use usingGeneratedKeyColumns(...) if your table features auto-increment primary keys.

3. Executing Inserts with MapSqlParameterSource

Executing the insert takes just two concise steps:

Build the Parameters: Instantiate new MapSqlParameterSource() and chain .addValue("column", value) for each database field.
Execute the Statement: Call simpleJdbcInsert.execute(paramSource) or executeAndReturnKey(paramSource) to run the insert and retrieve generated identifiers.

4. Key Takeaways

Using MapSqlParameterSource with SimpleJdbcInsert prevents common syntax mistakes, eliminates positional parameter bugs, and keeps your DAO implementation concise and easy to maintain.

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Inserting Data with SimpleJdbcInsert and SqlParameterSource

When working with database persistence in Spring applications, SimpleJdbcInsert provides a clean way to insert records without writing repetitive SQL queries. Pairing it with the SqlParameterSource interface makes parameter binding structured, type-safe, and effortless.

1. What is SqlParameterSource?

In Spring JDBC, SqlParameterSource is an interface designed to provide named parameter values for SQL operations. Instead of manually putting entries into a standard Java Map, it provides structured mechanisms to supply parameter values:

MapSqlParameterSource: A flexible implementation that allows chaining parameter name-value pairs fluently via .addValue().
BeanPropertySqlParameterSource: Directly binds properties from a Java Bean or POJO to database column names using reflection.
Type Safety: Provides better support for explicit SQL type mapping when inserting custom or nullable types.

2. Using MapSqlParameterSource with SimpleJdbcInsert

MapSqlParameterSource is ideal when inserting dynamic data or when your data fields do not directly map to a single entity object:

Fluently Add Values: Use new MapSqlParameterSource().addValue("columnName", value) to map database fields.
Direct Execution: Pass the parameter source instance directly into simpleJdbcInsert.execute(parameters).
Cleaner Syntax: Avoids manual hash map instantiations and repetitive put() calls.

3. Simplifying POJO Inserts with BeanPropertySqlParameterSource

If you already have a domain object (such as an Employee or User bean):

Wrap the bean with new BeanPropertySqlParameterSource(myBean).
Spring automatically extracts getter properties and aligns them with matching table column names.
Minimizes boilerplate code and makes domain-driven persistence seamless.

4. Key Advantages

Combining SimpleJdbcInsert with SqlParameterSource gives you:

Zero Boilerplate SQL: No need to craft explicit INSERT INTO statements.
Less Human Error: Reduces typo risks associated with positional parameter placeholders (?).
Enhanced Maintainability: Code is cleaner, concise, and easier to test across enterprise data layers.

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Wednesday, 6 March 2019

Spring - Specifying columns for SimpleJdbcInsert | Spring JDBC tutorial | Spring JDBC

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Specifying Columns with SimpleJdbcInsert in Spring JDBC

While Spring JDBC’s SimpleJdbcInsert can automatically read all table columns through database metadata, real-world database design often requires inserting data only into selected columns. By explicitly configuring target columns with usingColumns(...), you gain precise control over your SQL insert statements while skipping default or auto-managed columns.

1. Why Restrict Columns with usingColumns()?

Explicitly declaring the columns for an insert operation provides key technical advantages:

Database Defaults: Allows the database to assign predefined default values (such as timestamps or UUIDs) to columns you choose to omit.
Improved Performance: Restricts metadata retrieval and query preparation strictly to the specified fields.
Prevent Unwanted Overwrites: Guarantees that unassigned entity properties do not accidentally push NULL into columns meant to retain system defaults.

2. Configuring usingColumns in SimpleJdbcInsert

Setting up usingColumns is straightforward and chains fluently with other configuration methods during initialization:

Define the Table Name: Use withTableName("table_name") to specify the target database table.
Chain usingColumns: Call usingColumns("col1", "col2", "col3") with the specific column names to be included in the generated INSERT query.
Thread Safety: Configure the SimpleJdbcInsert instance once during DAO initialization or bean creation so it remains thread-safe for all incoming requests.

3. Passing Parameters to the Operation

Once configured, you can execute the insert using Spring’s standard parameter mapping utilities:

MapSqlParameterSource: Provide named parameters via key-value chaining matching the specified column names.
BeanPropertySqlParameterSource: Pass a domain POJO; Spring matches getter method names directly to your declared columns.
Map<String, Object>: Use a standard Java map to dynamically supply values at runtime.

4. Practical Summary & Best Practices

Whenever a database table contains auto-generated IDs, audit timestamps, or default trigger columns, explicitly specifying columns with usingColumns(...) ensures clean, error-free inserts without generating manual SQL statements.

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Inserting Data Using SimpleJdbcInsert in Spring JDBC

In standard JDBC and basic JdbcTemplate setups, executing insert statements often requires writing boilerplate SQL strings and mapping parameters manually. SimpleJdbcInsert is a powerful multi-threaded class provided by Spring JDBC that dramatically simplifies insert operations by utilizing database metadata to configure the insert statement automatically.

1. What is SimpleJdbcInsert?

SimpleJdbcInsert is part of the org.springframework.jdbc.core.simple package. It inspects table metadata directly through the JDBC driver, allowing you to execute inserts without manually writing the standard INSERT INTO table_name (...) VALUES (...) SQL statement:

Metadata Discovery: Reads column definitions and primary key configurations automatically.
Reduced Boilerplate: Eliminates tedious SQL query strings and placeholder parameter matching.
Clean Mapping: Accepts key-value pairs using Java Map implementations or bean property holders.

2. How to Configure SimpleJdbcInsert

To set up SimpleJdbcInsert in your Spring DAO or repository layer:

Initialize with DataSource: Instantiate SimpleJdbcInsert by passing the configured DataSource bean.
Define Table Name: Use the withTableName("table_name") method to specify your target table.
Specify Columns (Optional): You can optionally restrict operations to specific columns using usingColumns(...).
Auto-Generated Keys: Use usingGeneratedKeyColumns("column_name") if your table features auto-increment primary keys.

3. Executing the Insert Operation

Spring provides flexible ways to supply the data being inserted into the database:

Map-Based Execution: Pass a Map<String, Object> containing column names as keys and field values as map values directly to execute(parameters).
MapSqlParameterSource: A Spring utility class that simplifies building parameter maps with fluent chaining methods.
BeanPropertySqlParameterSource: Automatically maps getter methods on a POJO/domain model directly to matching database table columns.

4. Key Advantages of Using SimpleJdbcInsert

Leveraging SimpleJdbcInsert provides several practical benefits:

Cleaner DAO Classes: Your data access layer remains readable and free of repetitive SQL strings.
Fewer Syntax Mistakes: By avoiding manual SQL statement construction, column mismatch and type conversion bugs are minimized.
Effortless Key Retrieval: Retrieving generated database primary key IDs is handled seamlessly in a single step using executeAndReturnKey(...).

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How to format the string using java.util.Formatter class - Playlist

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https://www.youtube.com/watch?v=qt89kDYMBGo&list=PLmCsXDGbJHdhKv54h0smpbiNuL9umvbUQ

See also:

All JavaEE Videos Playlist

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JDBC Tutorial

Java Collection Framework Tutorial

JAVA Tutorial

Kids Tutorial

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Tuesday, 5 March 2019

How to use format(Locale l, String format, Object... args) method of java.util.Formatter class

Click here to watch on Youtube:
https://www.youtube.com/watch?v=ec2-YfmtPSk&list=UUhwKlOVR041tngjerWxVccw

FormatterDemo.java

import java.util.Formatter;

import java.util.Locale;



/**
 * public Formatter format(Locale l, String format, Object... args)
 * 
 * Parameters:
 * 
 * l - The locale to apply during formatting.
 * 
 * format - A format string as described in Format string syntax.
 * 
 * args - Arguments referenced by the format specifiers in the format
 * string. If there are more arguments than format specifiers, the
 * extra arguments are ignored. The maximum number of arguments is
 * limited by the maximum dimension of a Java array as defined by The
 * Java™ Virtual Machine Specification.
 * 
 * Returns: This formatter
 *
 */

public class FormatterDemo

{



    public static void main(String[] args)

    {

        Formatter formatter = new Formatter();



        /*
         * In this example, the format specifiers, %s and %d are
         * replaced with the arguments that follow the format string.
         * %s is replaced by "Peter", %d is replaced by 10. %s
         * specifies a string, and %d specifies an integer value. All
         * other characters are simply used as-is.
         */

        formatter.format(Locale.US, "%s age is %d", "Peter", 10);

        System.out.println(formatter.out());

        formatter.close();

    }



}

Output:

Peter age is 10

Click the below link to download the code:
https://sites.google.com/site/javaspringram2019/java_spring_2019/FormatterDemo_format_locale.zip?attredirects=0&d=1

Github Link:
https://github.com/ramram43210/Java_Spring_2019/tree/master/Java_2019/FormatterDemo_format_locale

Bitbucket Link:
https://bitbucket.org/ramram43210/java_spring_2019/src/ef6f73b2185c28cb9cd0149bcd1e9fa0a5b2bdf3/Java_2019/FormatterDemo_format_locale/?at=master

See also:

All JavaEE Videos Playlist

All Design Patterns Links

JDBC Tutorial

Java Collection Framework Tutorial

JAVA Tutorial

Kids Tutorial

Cooking Tutorial

Friday, 29 March 2019

🚀 Level Up Your Java Skills!

Mastering Spring 4 and Hibernate 4 Integration

1. Why XML Configuration?

2. The Role of Maven

3. Setting Up MySQL 8

Key Takeaways for Beginners:

Check Out More Tutorials:

🚀 Master Java Development with Us!

Spring 4 and Hibernate 4 Integration Guide

1. Setting Up Your Database

2. Project Structure & Dependencies

3. Configuration Classes

4. Performing CRUD Operations

Watch and Learn More

Wednesday, 27 March 2019

Sunday, 24 March 2019

🔥 Level Up Your Coding Skills!

Mastering Spring 3 and Hibernate 3 Integration

Why Use Spring with Hibernate?

Key Components of the Project

Step-by-Step Implementation

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Sunday, 17 March 2019

Managing Observers in Java's Observable Class

How deleteObserver and deleteObservers Work

Why Observer Deregistration Matters

Related Observer Pattern Tutorials to Watch Next

Real-Time Example: Mobile Price Tracking Alert System

Core Participants in the Application

Step-by-Step Implementation Flow

Why Use Observer and Observable?

Related Observer Pattern Tutorials to Watch Next

What Are Observer and Observable in Java?

How the Notification Workflow Works

Key Architectural Benefits

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Sunday, 10 March 2019

Retrieve All Records from Stored Procedures Using SimpleJdbcCall

1. Returning ResultSets from Stored Procedures

2. Configuring returningResultSet with RowMapper

3. Executing the Call and Extracting the Record List

4. Practical Summary & Best Practices

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Calling Stored Functions with SimpleJdbcCall in Spring JDBC

1. Procedures vs. Functions in SimpleJdbcCall

2. Configuring SimpleJdbcCall for Stored Functions

3. Executing the Function and Retrieving Results

4. Key Advantages

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Calling Stored Procedures with Explicit Parameters Using SimpleJdbcCall

1. Why Declare Parameters Explicitly?

2. Using declareParameters with SqlParameter & SqlOutParameter

3. Executing the Procedure and Handling Output

4. Practical Summary & Best Practices

📺 Explore More Spring JDBC Tutorials

Calling Stored Procedures with SimpleJdbcCall in Spring JDBC

1. What is SimpleJdbcCall?

2. How to Configure SimpleJdbcCall

3. Passing IN Parameters and Retrieving OUT Results

4. Key Advantages

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Efficient Data Insertion: SimpleJdbcInsert with MapSqlParameterSource

1. Why Use MapSqlParameterSource?

2. Setting Up SimpleJdbcInsert

3. Executing Inserts with MapSqlParameterSource

4. Key Takeaways

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Inserting Data with SimpleJdbcInsert and SqlParameterSource

1. What is SqlParameterSource?

2. Using MapSqlParameterSource with SimpleJdbcInsert

3. Simplifying POJO Inserts with BeanPropertySqlParameterSource

4. Key Advantages

📺 Explore More Spring JDBC Tutorials

Wednesday, 6 March 2019

Specifying Columns with SimpleJdbcInsert in Spring JDBC

1. Why Restrict Columns with usingColumns()?

2. Configuring usingColumns in SimpleJdbcInsert

3. Passing Parameters to the Operation

4. Practical Summary & Best Practices