Azure Spring Apps is a fully managed service from Microsoft
(built in collaboration with VMware), focused on building and
deploying Spring Boot applications on Azure Cloud without
worrying about Kubernetes.
The Enterprise plan comes with some interesting features, such
as commercial Spring runtime support, a 99.95% SLA and some deep
discounts (up to 47%) when you are ready for production.
And, you can participate in a very quick (1 minute) paid user
research from the Java on Azure product team.
Partner – Aegik AB – NPI EA (cat=JPA)
Slow MySQL query performance is all too common. Of course
it is. A good way to go is, naturally, a dedicated profiler that
actually understands the ins and outs of MySQL.
The Jet Profiler was built for MySQL only, so it can do
things like real-time query performance, focus on most used tables
or most frequent queries, quickly identify performance issues and
basically help you optimize your queries.
Critically, it has very minimal impact on your server's
performance, with most of the profiling work done separately - so
it needs no server changes, agents or separate services.
Basically, you install the desktop application, connect to your MySQL
server, hit the record button, and you'll have results
within minutes:
Accelerate Your Jakarta EE Development with Payara Server!
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Beyond that, it provides intelligent insights and actions to
optimize Jakarta EE applications.
The goal is to apply an opinionated approach to get to
what's essential for mission-critical applications - really solid
scalability, availability, security, and long-term support:
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Looking for the ideal Linux distro for running modern Spring
apps in the cloud?
Meet Alpaquita Linux: lightweight, secure, and powerful
enough to handle heavy workloads.
This distro is specifically designed for running Java
apps. It builds upon Alpine and features significant
enhancements to excel in high-density container environments while
meeting enterprise-grade security standards.
Specifically, the container image size is ~30% smaller than
standard options, and it consumes up to 30% less RAM:
Yes, Spring Security can be complex, from the more advanced
functionality within the Core to the deep OAuth support in the
framework.
I built the security material as two full courses - Core and
OAuth, to get practical with these more complex scenarios. We
explore when and how to use each feature and code through it on
the backing project.
DbSchema is a super-flexible database designer, which can
take you from designing the DB with your team all the way to
safely deploying the schema.
The way it does all of that is by using a design model, a
database-independent image of the schema, which can be shared in a
team using GIT and compared or deployed on to any database.
And, of course, it can be heavily visual, allowing you to
interact with the database using diagrams, visually compose
queries, explore the data, generate random data, import data or
build HTML5 database reports.
Slow MySQL query performance is all too common. Of course
it is. A good way to go is, naturally, a dedicated profiler that
actually understands the ins and outs of MySQL.
The Jet Profiler was built for MySQL only, so it can do
things like real-time query performance, focus on most used tables
or most frequent queries, quickly identify performance issues and
basically help you optimize your queries.
Critically, it has very minimal impact on your server's
performance, with most of the profiling work done separately - so
it needs no server changes, agents or separate services.
Basically, you install the desktop application, connect to your MySQL
server, hit the record button, and you'll have results
within minutes:
Creating PDFs is actually surprisingly hard. When we
first tried, none of the existing PDF libraries met our needs. So
we made DocRaptor for ourselves and later launched it as one
of the first HTML-to-PDF APIs.
We think DocRaptor is the fastest and most scalable way to
make PDFs, especially high-quality or complex PDFs. And as
developers ourselves, we love good documentation, no-account trial
keys, and an easy setup process.
Jackson-jr is a lightweight JSON processing library for Java, designed to provide a simpler and smaller alternative to the original Jackson library. With its small footprint and easy-to-use API, Jackson-jr is an excellent choice for casual JSON reading and writing scenarios.
In this guide, we will explore the key features and usage of Jackson-jr, along with examples and best practices.
2. Getting Started With Jackson-jr
Jackson-jr offers a lightweight and efficient way to handle JSON data in Java applications. It provides a simple API for working with JSON objects and arrays, making it easier to parse, generate, and manipulate JSON data.
First, we must include the Jackson-jr library in our project. We can do this by adding the desired version of the Jackson-jr dependency to our project’s build configuration file.
For Maven, we can add the dependency to our pom.xml file:
The base object for working with Jackson-jr is the JSON object. A very important and not to forget fact about the JSON object: every JSON instance is fully immutable and thread-safe. We can use them however we want, a Singleton instance, a Spring Bean, or even construct individual objects. We can pass the same instance between different threads, as it is fully immutable.
3.1. Creating JSON Objects and Arrays
Creating JSON objects and arrays: Jackson-jr provides a convenient API for creating JSON objects and arrays. We can use classes like LinkedHashMap to represent JSON objects and ArrayList to represent JSON arrays.
The JSON object is a LinkedHashMap. We can easily add properties to it using the LinkedHashMap.put() method and get properties with the LinkedHashMap.get() method.
Jackson-jr allows us to easily convert Java objects to JSON strings and vice versa. We can configure the writer with desired options, such as pretty-printing or custom date formats, and then use it to write objects as JSON strings.
Jackson-jr supports complex object structures, including nested objects and arrays. By properly defining the structure of our Java classes and their relationships, Jackson-jr can handle the serialization and deserialization of complex JSON data.
Jackson-jr supports various annotations, such as @JsonProperty, to customize the serialization and deserialization process. These annotations allow us to control the names of properties, specify date and time formats, and handle other customization scenarios. We can see a list of all the supported annotations in their official Github project for annotations.
Jackson-jr has a list of feature customization that we can use to customize the input and output of our serialization and deserialization, customization like pretty print, write null properties, etc. The easiest way to see all of them would be right in the base code.
Jackson-jr allows us to create custom serializers and deserializers to handle specific data types or complex serialization scenarios. By implementing the appropriate interfaces, ValueWriter, and extending the provided classes, ValueReader and ReadWriterProvider, we can define how our custom objects should be serialized and deserialized.
Jackson-jr does not support java.time.* package, but we can add this with custom serializers and deserializers:
public class CustomDateSerializer implements ValueWriter {
@Override
public void writeValue (JSONWriter jsonWriter, JsonGenerator jsonGenerator, Object o) throws IOException {
jsonGenerator.writeString(o.toString());
}
@Override
public Class<?> valueType () {
return LocalDate.class;
}
}
public class CustomDateDeserializer extends ValueReader {
private final static DateTimeFormatter dtf = DateTimeFormatter.ofPattern("yyyy-MMM-dd");
public CustomDateDeserializer () {
super(LocalDate.class);
}
@Override
public Object read (JSONReader jsonReader, JsonParser jsonParser) throws IOException {
return LocalDate.parse(jsonParser.getText(), dtf);
}
}
After we register them, we can start serializing and deserializing LocalDate objects:
public class MyHandlerProvider extends ReaderWriterProvider {
@Override
public ValueWriter findValueWriter (JSONWriter writeContext, Class<?> type) {
if (type == LocalDate.class) {
return new CustomDateSerializer();
}
return null;
}
@Override
public ValueReader findValueReader (JSONReader readContext, Class<?> type) {
if (type.equals(LocalDate.class)) {
return new CustomDateDeserializer();
}
return null;
}
}
Person person = new Person("John Doe", 30, LocalDate.now());
JSON jsonMapper = JSON.builder().register(new JacksonJrExtension() {
@Override
protected void register (ExtensionContext extensionContext) {
extensionContext.insertProvider(new MyHandlerProvider());
}
}).build().with(JSON.Feature.PRETTY_PRINT_OUTPUT);
String json = jsonMapper.asString(person);
Person deserializedPerson = jsonMapper.beanFrom(Person.class, json);
5. Jackson-jr vs. Jackson
Jackson-jr
Jackson
Smaller jar
Bigger jar
Fewer features
More complex features
Better for simpler serialization and deserialization
Better for more complex serialization and deserialization
Faster start-up time
Slower start-up time
Simpler API
More complex API
6. Conclusion
Jackson-jr offers a lightweight and user-friendly approach to JSON processing in Java applications. With its simplified API, customization options, and efficient performance, it is an excellent choice for developers who need a lightweight JSON processing library without compromising on functionality.
As always, the source code for the examples is available over on GitHub.
Partner – Bellsoft – NPI EA (cat = Spring)
Looking for the ideal Linux distro for running modern Spring
apps in the cloud?
Meet Alpaquita Linux: lightweight, secure, and powerful
enough to handle heavy workloads.
This distro is specifically designed for running Java
apps. It builds upon Alpine and features significant
enhancements to excel in high-density container environments while
meeting enterprise-grade security standards.
Specifically, the container image size is ~30% smaller than
standard options, and it consumes up to 30% less RAM:
Creating PDFs is actually surprisingly hard. When we
first tried, none of the existing PDF libraries met our needs. So
we made DocRaptor for ourselves and later launched it as one
of the first HTML-to-PDF APIs.
We think DocRaptor is the fastest and most scalable way to
make PDFs, especially high-quality or complex PDFs. And as
developers ourselves, we love good documentation, no-account trial
keys, and an easy setup process.
Slow MySQL query performance is all too common. Of course
it is.
The Jet Profiler was built entirely for MySQL, so it's
fine-tuned for it and does advanced everything with relaly minimal
impact and no server changes.
Basically, write code that works the way you meant it to.
Partner – Machinet – NPI EA (cat = Testing)
AI is all the rage these days, but for very good reason. The
highly practical coding companion, you'll get the power of
AI-assisted coding and automated unit test generation.
Machinet's Unit Test AI Agent utilizes your own project
context to create meaningful unit tests that intelligently aligns
with the behavior of the code.