Partner – Orkes – NPI EA (cat=Spring)
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Partner – Orkes – NPI EA (tag=Microservices)
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Modern software architecture is often broken. Slow delivery leads to missed opportunities, innovation is stalled due to architectural complexities, and engineering resources are exceedingly expensive.

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eBook – Guide Spring Cloud – NPI EA (cat=Spring Cloud)
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eBook – Mockito – NPI EA (tag = Mockito)
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Mocking is an essential part of unit testing, and the Mockito library makes it easy to write clean and intuitive unit tests for your Java code.

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eBook – Java Concurrency – NPI EA (cat=Java Concurrency)
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eBook – Reactive – NPI EA (cat=Reactive)
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Spring 5 added support for reactive programming with the Spring WebFlux module, which has been improved upon ever since. Get started with the Reactor project basics and reactive programming in Spring Boot:

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eBook – Java Streams – NPI EA (cat=Java Streams)
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Since its introduction in Java 8, the Stream API has become a staple of Java development. The basic operations like iterating, filtering, mapping sequences of elements are deceptively simple to use.

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To get a better understanding on how Streams work and how to combine them with other language features, check out our guide to Java Streams:

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Browser testing is essential if you have a website or web applications that users interact with. Manual testing can be very helpful to an extent, but given the multiple browsers available, not to mention versions and operating system, testing everything manually becomes time-consuming and repetitive.

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Read more through our step-by-step tutorial on how to set up Selenium tests with Java and run them on LambdaTest:

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Partner – Orkes – NPI EA (cat=Java)
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Partner – Moderne – NPI EA (cat=Spring Boot)
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Refactor Java code safely — and automatically — with OpenRewrite.

Refactoring big codebases by hand is slow, risky, and easy to put off. That’s where OpenRewrite comes in. The open-source framework for large-scale, automated code transformations helps teams modernize safely and consistently.

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Join the next session, bring your questions, and learn how to automate the kind of work that usually eats your sprint time.

1. Overview

In this introductory tutorial, we’ll learn about the HikariCP JDBC connection pool project. This is a very lightweight (at roughly 130Kb) and lightning-fast JDBC connection pooling framework developed by Brett Wooldridge around 2012.

Further reading:

A Simple Guide to Connection Pooling in Java

A quick overview of several popular connection pooling solutions, plus a quick dive into a custom connection pool implementation

Configuring a Hikari Connection Pool with Spring Boot

Learn how you can configure Hikari CP in your Spring Boot (1 and 2) applications

Using c3p0 with Hibernate

Learn how to add c3p0 to a Hibernate application and configure some common properties

2. Introduction

There are several benchmark results available to compare the performance of HikariCP with other connection pooling frameworks, such as c3p0, dbcp2, tomcat, and vibur. For example, the HikariCP team published the below benchmarks (original results available here):

HikariCP-bench-2.6.0

The framework is so fast because the following techniques have been applied:

  • Bytecode-level engineering – some extreme bytecode level engineering (including assembly level native coding) has been done
  • Micro-optimizations – although barely measurable, these optimizations combined boost the overall performance
  • Intelligent use of the Collections framework – the ArrayList<Statement> was replaced with a custom class, FastList, that eliminates range checking and performs removal scans from head to tail

3. Maven Dependency

First, let’s build a sample application to highlight its usage. HikariCP comes with support for all the main versions of JVM. Each version requires its dependency. For Java 8 through 11, we have:

<dependency>
    <groupId>com.zaxxer</groupId>
    <artifactId>HikariCP</artifactId>
    <version>5.1.0</version>
</dependency>

HikariCP also supports older JDK versions, like 6 and 7. The appropriate versions can be found here and here, respectively. We can also check the latest versions in the Central Maven Repository.

4. Usage

Now we can create a demo application. Please note that we need to include a suitable JDBC driver class dependency in the pom.xml. If no dependencies are provided, the application will throw a ClassNotFoundException.

4.1. Creating a DataSource

We’ll use HikariCP’s DataSource to create a single instance of a data source for our application:

public class DataSource {

    private static HikariConfig config = new HikariConfig();
    private static HikariDataSource ds;

    static {
        config.setJdbcUrl( "jdbc_url" );
        config.setUsername( "database_username" );
        config.setPassword( "database_password" );
        config.addDataSourceProperty( "cachePrepStmts" , "true" );
        config.addDataSourceProperty( "prepStmtCacheSize" , "250" );
        config.addDataSourceProperty( "prepStmtCacheSqlLimit" , "2048" );
        ds = new HikariDataSource( config );
    }

    private DataSource() {}

    public static Connection getConnection() throws SQLException {
        return ds.getConnection();
    }
}

One point to note here is the initialization in the static block.

HikariConfig is the configuration class used to initialize a data source. It comes with four well-known, must-use parameters: username, password, jdbcUrl, and dataSourceClassName.

Out of jdbcUrl and dataSourceClassName, we generally use one at a time. However, when using this property with older drivers, we may need to set both properties.

In addition to these properties, there are several other properties available that we may not find offered by other pooling frameworks:

  • autoCommit
  • connectionTimeout
  • idleTimeout
  • maxLifetime
  • connectionTestQuery
  • connectionInitSql
  • validationTimeout
  • maximumPoolSize
  • poolName
  • allowPoolSuspension
  • readOnly
  • transactionIsolation
  • leakDetectionThreshold

HikariCP stands out because of these database properties. It’s even advanced enough to detect connection leaks by itself.

A detailed description of the above properties can be found here.

We can also initialize HikariConfig with a properties file placed in the resources directory:

private static HikariConfig config = new HikariConfig(
    "datasource.properties" );

The properties file should look something like this:

dataSourceClassName= //TBD
dataSource.user= //TBD
//other properties name should start with dataSource as shown above

In addition, we can use java.util.Properties-based configuration:

Properties props = new Properties();
props.setProperty( "dataSourceClassName" , //TBD );
props.setProperty( "dataSource.user" , //TBD );
//setter for other required properties
private static HikariConfig config = new HikariConfig( props );

Alternatively, we can initialize a data source directly:

ds.setJdbcUrl( //TBD  );
ds.setUsername( //TBD );
ds.setPassword( //TBD );

4.2. Using a Data Source

Now that we have defined the data source, we can use it to obtain a connection from the configured connection pool, and perform JDBC related actions.

Suppose we have two tables, named dept and emp, to simulate an employee-department use case. We’ll write a class to fetch those details from the database using HikariCP.

Below we’ll list the SQL statements necessary to create the sample data:

create table dept(
  deptno numeric,
  dname  varchar(14),
  loc    varchar(13),
  constraint pk_dept primary key ( deptno )
);
 
create table emp(
  empno    numeric,
  ename    varchar(10),
  job      varchar(9),
  mgr      numeric,
  hiredate date,
  sal      numeric,
  comm     numeric,
  deptno   numeric,
  constraint pk_emp primary key ( empno ),
  constraint fk_deptno foreign key ( deptno ) references dept ( deptno )
);

insert into dept values( 10, 'ACCOUNTING', 'NEW YORK' );
insert into dept values( 20, 'RESEARCH', 'DALLAS' );
insert into dept values( 30, 'SALES', 'CHICAGO' );
insert into dept values( 40, 'OPERATIONS', 'BOSTON' );
 
insert into emp values(
 7839, 'KING', 'PRESIDENT', null,
 to_date( '17-11-1981' , 'dd-mm-yyyy' ),
 7698, null, 10
);
insert into emp values(
 7698, 'BLAKE', 'MANAGER', 7839,
 to_date( '1-5-1981' , 'dd-mm-yyyy' ),
 7782, null, 20
);
insert into emp values(
 7782, 'CLARK', 'MANAGER', 7839,
 to_date( '9-6-1981' , 'dd-mm-yyyy' ),
 7566, null, 30
);
insert into emp values(
 7566, 'JONES', 'MANAGER', 7839,
 to_date( '2-4-1981' , 'dd-mm-yyyy' ),
 7839, null, 40
);

Please note, if we use an in-memory database such as H2, we need to automatically load the database script before running the actual code to fetch the data. Thankfully, H2 comes with an INIT parameter that can load the database script from the classpath at runtime. The JDBC URL should look like:

jdbc:h2:mem:test;DB_CLOSE_DELAY=-1;INIT=runscript from 'classpath:/db.sql'

We need to create a method to fetch this data from the database:

public static List<Employee> fetchData() throws SQLException {
    String SQL_QUERY = "select * from emp";
    List<Employee> employees = null;
    try (Connection con = DataSource.getConnection();
        PreparedStatement pst = con.prepareStatement( SQL_QUERY );
        ResultSet rs = pst.executeQuery();) {
            employees = new ArrayList<>();
            Employee employee;
            while ( rs.next() ) {
                employee = new Employee();
                employee.setEmpNo( rs.getInt( "empno" ) );
                employee.setEname( rs.getString( "ename" ) );
                employee.setJob( rs.getString( "job" ) );
                employee.setMgr( rs.getInt( "mgr" ) );
                employee.setHiredate( rs.getDate( "hiredate" ) );
                employee.setSal( rs.getInt( "sal" ) );
                employee.setComm( rs.getInt( "comm" ) );
                employee.setDeptno( rs.getInt( "deptno" ) );
                employees.add( employee );
            }
	} 
    return employees;
}

Then we need to create a JUnit method to test it. Since we know the number of rows in the table emp, we can expect that the size of the returned list should be equal to the number of rows:

@Test
public void givenConnection_thenFetchDbData() throws SQLException {
    HikariCPDemo.fetchData();
 
    assertEquals( 4, employees.size() );
}

5. Conclusion

In this brief article, we learned the benefits of using HikariCP, and its configuration.

The code backing this article is available on GitHub. Once you're logged in as a Baeldung Pro Member, start learning and coding on the project.
Baeldung Pro – NPI EA (cat = Baeldung)
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Partner – Orkes – NPI EA (cat = Spring)
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Modern software architecture is often broken. Slow delivery leads to missed opportunities, innovation is stalled due to architectural complexities, and engineering resources are exceedingly expensive.

Orkes is the leading workflow orchestration platform built to enable teams to transform the way they develop, connect, and deploy applications, microservices, AI agents, and more.

With Orkes Conductor managed through Orkes Cloud, developers can focus on building mission critical applications without worrying about infrastructure maintenance to meet goals and, simply put, taking new products live faster and reducing total cost of ownership.

Try a 14-Day Free Trial of Orkes Conductor today.

Partner – Orkes – NPI EA (tag = Microservices)
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Modern software architecture is often broken. Slow delivery leads to missed opportunities, innovation is stalled due to architectural complexities, and engineering resources are exceedingly expensive.

Orkes is the leading workflow orchestration platform built to enable teams to transform the way they develop, connect, and deploy applications, microservices, AI agents, and more.

With Orkes Conductor managed through Orkes Cloud, developers can focus on building mission critical applications without worrying about infrastructure maintenance to meet goals and, simply put, taking new products live faster and reducing total cost of ownership.

Try a 14-Day Free Trial of Orkes Conductor today.

eBook – HTTP Client – NPI EA (cat=HTTP Client-Side)
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The Apache HTTP Client is a very robust library, suitable for both simple and advanced use cases when testing HTTP endpoints. Check out our guide covering basic request and response handling, as well as security, cookies, timeouts, and more:

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eBook – Java Concurrency – NPI EA (cat=Java Concurrency)
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Handling concurrency in an application can be a tricky process with many potential pitfalls. A solid grasp of the fundamentals will go a long way to help minimize these issues.

Get started with understanding multi-threaded applications with our Java Concurrency guide:

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eBook – Java Streams – NPI EA (cat=Java Streams)
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Since its introduction in Java 8, the Stream API has become a staple of Java development. The basic operations like iterating, filtering, mapping sequences of elements are deceptively simple to use.

But these can also be overused and fall into some common pitfalls.

To get a better understanding on how Streams work and how to combine them with other language features, check out our guide to Java Streams:

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eBook – Persistence – NPI EA (cat=Persistence)
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Partner – Moderne – NPI EA (tag=Refactoring)
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Modern Java teams move fast — but codebases don’t always keep up. Frameworks change, dependencies drift, and tech debt builds until it starts to drag on delivery. OpenRewrite was built to fix that: an open-source refactoring engine that automates repetitive code changes while keeping developer intent intact.

The monthly training series, led by the creators and maintainers of OpenRewrite at Moderne, walks through real-world migrations and modernization patterns. Whether you’re new to recipes or ready to write your own, you’ll learn practical ways to refactor safely and at scale.

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