JSON and API Integration

Why JSON Processing Matters

JSON (JavaScript Object Notation) is the universal data interchange format for modern applications. REST APIs, configuration files, message queues, and data storage all rely on JSON for communication between services.

Core Benefits:

REST API communication: Send and receive data from web services
Configuration management: Store application settings in readable format
Data persistence: Save application state to files or databases
Message queues: Exchange data between distributed systems
External integrations: Communicate with third-party services

Problem: Java lacks built-in JSON support. Manual string manipulation is error-prone and tedious. Parsing JSON requires extensive boilerplate code vulnerable to typos and runtime errors.

Solution: Progress from manual approaches to understand fundamentals, then leverage libraries for production use.

Approach Comparison

Java offers multiple approaches for JSON processing, ranging from manual string manipulation to sophisticated libraries.

Approach	Abstraction Level	Type Safety	Performance	Production Ready	Use When
Manual StringBuilder	Low	None	Fast	No	Learning, trivial cases
javax.json (JSON-P)	Medium	Moderate	Good	Yes	Standards compliance needed
Jackson	High	Strong	Excellent	Yes	Production applications
Gson	High	Strong	Good	Yes	Simpler API preference

Recommended progression: Start with manual approach to understand JSON structure → Explore javax.json for specification-based approach → Use Jackson for production systems.

Manual JSON Serialization (Standard Library)

Manual JSON construction teaches JSON structure fundamentals and reveals why libraries exist. Use StringBuilder for simple serialization and parsing.

Basic Object to JSON String

Convert a simple Java object to JSON manually.

Pattern:

public class Person {
    private String name;  // => Field: person's name
    private int age;  // => Field: person's age

    public Person(String name, int age) {  // => Constructor
        this.name = name;  // => Sets name field
        this.age = age;  // => Sets age field
    }

    public String toJson() {
        return "{\"name\":\"" + name + "\",\"age\":" + age + "}";  // => Manually constructs JSON string
                                                                    // => Escapes quotes with backslash: \" → "
                                                                    // => age is number (unquoted), name is string (quoted)
                                                                    // => Result: {"name":"Alice","age":30}
    }

    public static void main(String[] args) {
        Person person = new Person("Alice", 30);  // => Creates Person: name="Alice", age=30
        String json = person.toJson();  // => Converts to JSON: "{\"name\":\"Alice\",\"age\":30}"
        System.out.println(json);  // => Prints: {"name":"Alice","age":30}
        // Output: {"name":"Alice","age":30}
    }
}

Before: No JSON representation After: JSON string ready for transmission

Escaping Special Characters

JSON requires escaping quotes, newlines, and control characters.

Pattern:

public class JsonEscaper {
    public static String escape(String value) {
        if (value == null) {
            return "null";
        }

        StringBuilder escaped = new StringBuilder();
        for (char c : value.toCharArray()) {
            switch (c) {
                case '"'  -> escaped.append("\\\"");
                case '\\' -> escaped.append("\\\\");
                case '\b' -> escaped.append("\\b");
                case '\f' -> escaped.append("\\f");
                case '\n' -> escaped.append("\\n");
                case '\r' -> escaped.append("\\r");
                case '\t' -> escaped.append("\\t");
                default -> {
                    if (c < 32 || c > 126) {
                        escaped.append(String.format("\\u%04x", (int) c));
                    } else {
                        escaped.append(c);
                    }
                }
            }
        }
        return escaped.toString();
    }

    public static void main(String[] args) {
        String text = "Hello\n\"World\"";
        String escaped = escape(text);
        System.out.println("\"" + escaped + "\"");
        // Output: "Hello\n\"World\""
    }
}

Problem: Raw strings contain characters that break JSON syntax.

Solution: Escape quotes, backslashes, and control characters following JSON specification.

JSON Arrays and Collections

Serialize lists to JSON arrays manually.

Pattern:

import java.util.*;

public class JsonArraySerializer {
    public static String toJsonArray(List<String> items) {
        StringBuilder json = new StringBuilder("[");

        for (int i = 0; i < items.size(); i++) {
            json.append("\"").append(JsonEscaper.escape(items.get(i))).append("\"");
            if (i < items.size() - 1) {
                json.append(",");
            }
        }

        json.append("]");
        return json.toString();
    }

    public static void main(String[] args) {
        List<String> names = Arrays.asList("Alice", "Bob", "Charlie");
        String json = toJsonArray(names);
        System.out.println(json);
        // Output: ["Alice","Bob","Charlie"]
    }
}

Before: List of strings in memory After: JSON array string with proper comma separation

Nested Objects

Handle nested object structures manually.

Pattern:

public class Address {
    private String street;
    private String city;

    public Address(String street, String city) {
        this.street = street;
        this.city = city;
    }

    public String toJson() {
        return "{\"street\":\"" + JsonEscaper.escape(street) +
               "\",\"city\":\"" + JsonEscaper.escape(city) + "\"}";
    }
}

public class PersonWithAddress {
    private String name;
    private Address address;

    public PersonWithAddress(String name, Address address) {
        this.name = name;
        this.address = address;
    }

    public String toJson() {
        return "{\"name\":\"" + JsonEscaper.escape(name) +
               "\",\"address\":" + address.toJson() + "}";
    }

    public static void main(String[] args) {
        Address addr = new Address("123 Main St", "New York");
        PersonWithAddress person = new PersonWithAddress("Alice", addr);
        String json = person.toJson();
        System.out.println(json);
        // Output: {"name":"Alice","address":{"street":"123 Main St","city":"New York"}}
    }
}

Problem: Objects contain other objects requiring nested JSON.

Solution: Each object provides toJson() method, parent objects embed child JSON.

Parsing JSON String to Object

Parse JSON manually using string operations.

Pattern:

public class SimpleJsonParser {
    public static Person parsePerson(String json) {
        // Remove outer braces
        json = json.trim().substring(1, json.length() - 1);

        String name = null;
        int age = 0;

        // Split by comma (naive approach, doesn't handle nested objects)
        String[] pairs = json.split(",");

        for (String pair : pairs) {
            String[] keyValue = pair.split(":");
            String key = keyValue[0].trim().replace("\"", "");
            String value = keyValue[1].trim();

            if (key.equals("name")) {
                name = value.replace("\"", "");
            } else if (key.equals("age")) {
                age = Integer.parseInt(value);
            }
        }

        return new Person(name, age);
    }

    public static void main(String[] args) {
        String json = "{\"name\":\"Bob\",\"age\":25}";
        Person person = parsePerson(json);
        System.out.println("Name: " + person.getName() + ", Age: " + person.getAge());
        // Output: Name: Bob, Age: 25
    }
}

Warning: This naive parser fails with nested objects, arrays, or commas in string values. Production parsing requires state machines or recursive descent parsers.

Edge Cases and Null Handling

Handle null values, empty strings, and numbers correctly.

Pattern:

public class RobustJsonSerializer {
    public static String toJson(String name, Integer age, String email) {
        StringBuilder json = new StringBuilder("{");

        json.append("\"name\":");
        if (name == null) {
            json.append("null");
        } else {
            json.append("\"").append(JsonEscaper.escape(name)).append("\"");
        }

        json.append(",\"age\":");
        if (age == null) {
            json.append("null");
        } else {
            json.append(age);
        }

        json.append(",\"email\":");
        if (email == null) {
            json.append("null");
        } else if (email.isEmpty()) {
            json.append("\"\"");
        } else {
            json.append("\"").append(JsonEscaper.escape(email)).append("\"");
        }

        json.append("}");
        return json.toString();
    }

    public static void main(String[] args) {
        System.out.println(toJson("Alice", 30, "alice@example.com"));
        // Output: {"name":"Alice","age":30,"email":"alice@example.com"}

        System.out.println(toJson(null, null, ""));
        // Output: {"name":null,"age":null,"email":""}
    }
}

Problem: Null values and empty strings require different JSON representations.

Solution: Check for null explicitly, serialize as null (unquoted) vs "" (quoted empty string).

Why Manual Approach Doesn’t Scale

Manual JSON serialization becomes unmaintainable for production systems.

Limitations:

Parsing complexity: Requires state machine or recursive parser for nested structures
Error-prone: Easy to miss escape sequences or introduce syntax errors
No type safety: All manual string manipulation, no compile-time checks
Maintenance burden: Every object needs custom serialization code
No schema validation: Can’t verify JSON structure matches requirements
Performance: String concatenation inefficient for large objects

Real-world complexity:

// A production API response requires handling:
// - Deeply nested objects (5+ levels)
// - Collections of objects
// - Date/time serialization (ISO-8601 format)
// - BigDecimal for financial amounts
// - Polymorphic types (subclass serialization)
// - Circular reference detection
// - Performance optimization (bytecode generation)

// Manual approach would require 1000+ lines per entity.
// Libraries solve this with annotations and reflection.

When manual approach is acceptable:

Educational purposes (understanding JSON structure)
Trivial single-object serialization (less than 5 fields)
No dependencies constraint (embedded systems)

For production: Use javax.json or Jackson (covered next).

javax.json (JSON-P) - Standard API

javax.json (JSON Processing API, JSON-P) is Java’s standard specification for JSON processing, part of Jakarta EE (formerly Java EE).

Why javax.json matters:

Specification-based: Part of Jakarta EE standard, not vendor-specific
API independence: Write against specification, swap implementations
Government/enterprise compliance: Required in regulated environments
Streaming support: Efficient processing of large JSON documents

Trade-off: Verbose API compared to Jackson, requires external implementation.

Maven Dependency

javax.json requires an implementation (specification alone doesn’t provide code).

Maven (reference implementation):

<dependency>
    <groupId>org.glassfish</groupId>
    <artifactId>jakarta.json</artifactId>
    <version>2.0.1</version>
</dependency>

Alternative implementations: Apache Johnzon, JSON-B.

Creating JSON Objects

Build JSON objects with JsonObjectBuilder for type-safe construction.

Pattern:

import jakarta.json.*;
import java.io.StringWriter;

public class JsonObjectExample {
    public static void main(String[] args) {
        // Build JSON object
        JsonObject person = Json.createObjectBuilder()
            .add("name", "Alice")
            .add("age", 30)
            .add("email", "alice@example.com")
            .build();

        // Convert to string
        StringWriter writer = new StringWriter();
        Json.createWriter(writer).write(person);
        String json = writer.toString();

        System.out.println(json);
        // Output: {"name":"Alice","age":30,"email":"alice@example.com"}
    }
}

Before: Manual StringBuilder with escaping After: Type-safe builder with automatic escaping

Creating JSON Arrays

Build JSON arrays with JsonArrayBuilder.

Pattern:

import jakarta.json.*;
import java.io.StringWriter;

public class JsonArrayExample {
    public static void main(String[] args) {
        // Build JSON array
        JsonArray names = Json.createArrayBuilder()
            .add("Alice")
            .add("Bob")
            .add("Charlie")
            .build();

        // Convert to string
        StringWriter writer = new StringWriter();
        Json.createWriter(writer).write(names);
        String json = writer.toString();

        System.out.println(json);
        // Output: ["Alice","Bob","Charlie"]
    }
}

Problem: Manual array construction requires comma management.

Solution: JsonArrayBuilder handles comma separation automatically.

Nested Structures

Create nested JSON structures with builder composition.

Pattern:

import jakarta.json.*;
import java.io.StringWriter;

public class NestedJsonExample {
    public static void main(String[] args) {
        // Build nested structure
        JsonObject person = Json.createObjectBuilder()
            .add("name", "Alice")
            .add("age", 30)
            .add("address", Json.createObjectBuilder()
                .add("street", "123 Main St")
                .add("city", "New York")
                .add("zipCode", "10001"))
            .add("phoneNumbers", Json.createArrayBuilder()
                .add("555-1234")
                .add("555-5678"))
            .build();

        // Convert to string
        StringWriter writer = new StringWriter();
        Json.createWriter(writer).write(person);
        String json = writer.toString();

        System.out.println(json);
        // Output: {"name":"Alice","age":30,"address":{"street":"123 Main St",...},"phoneNumbers":["555-1234","555-5678"]}
    }
}

Before: Manual nesting requires careful string concatenation After: Builder composition handles nesting automatically

Reading JSON

Parse JSON strings with JsonReader.

Pattern:

import jakarta.json.*;
import java.io.StringReader;

public class JsonReaderExample {
    public static void main(String[] args) {
        String jsonString = "{\"name\":\"Bob\",\"age\":25,\"email\":\"bob@example.com\"}";

        // Parse JSON
        JsonReader reader = Json.createReader(new StringReader(jsonString));
        JsonObject person = reader.readObject();
        reader.close();

        // Extract values
        String name = person.getString("name");
        int age = person.getInt("age");
        String email = person.getString("email");

        System.out.println("Name: " + name + ", Age: " + age + ", Email: " + email);
        // Output: Name: Bob, Age: 25, Email: bob@example.com
    }
}

Before: Manual string parsing with split operations After: Type-safe value extraction with JsonObject API

Navigating JSON with JsonPointer

JsonPointer provides path-based navigation for nested structures (RFC 6901).

Pattern:

import jakarta.json.*;
import java.io.StringReader;

public class JsonPointerExample {
    public static void main(String[] args) {
        String jsonString = "{\"person\":{\"name\":\"Alice\",\"address\":{\"city\":\"New York\"}}}";

        JsonReader reader = Json.createReader(new StringReader(jsonString));
        JsonObject json = reader.readObject();
        reader.close();

        // Navigate with JsonPointer
        JsonPointer pointer1 = Json.createPointer("/person/name");
        JsonValue name = pointer1.getValue(json);
        System.out.println("Name: " + ((JsonString) name).getString());
        // Output: Name: Alice

        JsonPointer pointer2 = Json.createPointer("/person/address/city");
        JsonValue city = pointer2.getValue(json);
        System.out.println("City: " + ((JsonString) city).getString());
        // Output: City: New York
    }
}

Problem: Nested navigation requires multiple getJsonObject() calls.

Solution: JsonPointer uses path strings for direct access (/path/to/field).

Handling Missing and Null Values

Distinguish between missing fields, null values, and empty strings.

Pattern:

import jakarta.json.*;
import java.io.StringReader;

public class NullHandlingExample {
    public static void main(String[] args) {
        String jsonString = "{\"name\":\"Alice\",\"age\":null,\"email\":\"\"}";

        JsonReader reader = Json.createReader(new StringReader(jsonString));
        JsonObject person = reader.readObject();
        reader.close();

        // Check field presence
        boolean hasName = person.containsKey("name");
        boolean hasPhone = person.containsKey("phone");

        System.out.println("Has name: " + hasName);        // true
        System.out.println("Has phone: " + hasPhone);      // false

        // Check null vs empty string
        JsonValue ageValue = person.get("age");
        boolean ageIsNull = ageValue.equals(JsonValue.NULL);

        String email = person.getString("email", "default@example.com");

        System.out.println("Age is null: " + ageIsNull);   // true
        System.out.println("Email: " + email);             // ""
    }
}

Problem: JSON has three states: missing field, null value, empty string.

Solution: containsKey() checks presence, equals(JsonValue.NULL) checks null, getString() extracts values.

javax.json vs Jackson Trade-offs

Feature	javax.json (JSON-P)	Jackson
Specification	Jakarta EE standard	De facto community standard
API Style	Builder-based, verbose	Annotation-based, concise
Object Mapping	Manual (no auto POJO mapping)	Automatic with ObjectMapper
Performance	Good	Excellent (bytecode generation)
Spring Integration	Manual setup	Zero-configuration default
Learning Curve	Moderate	Moderate
Streaming	Yes (JsonParser)	Yes (StreamingAPI)
When to Use	Standards compliance required	Production applications (default)

javax.json strengths:

Specification-based (vendor independence)
Required in Jakarta EE environments
Good for manual JSON construction

Jackson strengths:

Spring Boot default (zero configuration)
Performance (bytecode generation)
Automatic POJO mapping (less boilerplate)
Rich annotation system

Recommendation: Use javax.json when standards compliance is mandatory (government, regulated industries). Use Jackson for most production applications (better Spring integration, performance, less code).

Jackson - Production Standard (External Library)

Jackson is Java’s de facto standard for JSON processing, providing object mapping, streaming, and tree model APIs. It powers Spring Boot, JAX-RS, and most Java REST frameworks.

Why Jackson dominates:

Performance: Faster than alternatives through bytecode generation
Spring Boot default: Zero configuration in Spring applications
Feature-rich: Annotations, custom serializers, tree models
Battle-tested: Mature library with extensive ecosystem

Core Components

Jackson has three main APIs for different use cases:

ObjectMapper (Object Mapping): Convert POJOs to/from JSON automatically
JsonNode (Tree Model): Navigate JSON structure without predefined classes
Streaming API: Memory-efficient processing for large JSON files

Object Mapping Patterns

Object mapping automatically converts Java objects to JSON and vice versa using reflection and annotations.

Basic Serialization (Java Object → JSON)

Convert Java objects to JSON strings with writeValueAsString().

Pattern:

ObjectMapper mapper = new ObjectMapper();
Person person = new Person("Alice", 30);
String json = mapper.writeValueAsString(person);

Before: Manual string building "{\"name\":\"" + name + "\",\"age\":" + age + "}" After: Type-safe one-liner with automatic field mapping

Basic Deserialization (JSON → Java Object)

Parse JSON strings into Java objects with readValue().

Pattern:

String jsonInput = "{\"name\":\"Bob\",\"age\":25}";
Person person = mapper.readValue(jsonInput, Person.class);

Before: Manual parsing with string splitting and type conversion After: Type-safe parsing with compile-time checking

Field Mapping with Annotations

Control JSON field names and visibility with Jackson annotations.

Common annotations:

@JsonProperty("field_name"): Map to different JSON field name
@JsonIgnore: Exclude field from JSON serialization
@JsonFormat: Control date/number formatting
@JsonInclude: Control null value handling

Pattern:

class Person {
    private String name;

    @JsonProperty("email_address")
    private String email;

    @JsonIgnore
    private String password;
}

Problem: JSON APIs use snake_case, Java uses camelCase. Sensitive fields need exclusion.

Solution: @JsonProperty maps field names, @JsonIgnore excludes sensitive data.

Collection Serialization

Jackson handles collections (List, Set, Map) automatically.

Pattern:

List<Person> people = Arrays.asList(
    new Person("Alice", 30),
    new Person("Bob", 25)
);
String jsonArray = mapper.writeValueAsString(people);

Result: [{"name":"Alice","age":30},{"name":"Bob","age":25}]

Collection Deserialization

Generic type erasure requires TypeFactory for deserializing collections.

Pattern:

List<Person> people = mapper.readValue(
    jsonArray,
    mapper.getTypeFactory().constructCollectionType(List.class, Person.class)
);

Problem: Java erases generics at runtime - List<Person> becomes just List.

Solution: TypeFactory provides type information Jackson needs for proper deserialization.

Tree Model for Dynamic JSON

Tree model parses JSON to navigable structure without predefined classes. Use when JSON structure is unknown or varies at runtime.

Reading JSON Trees

Parse JSON to JsonNode for flexible navigation.

Pattern:

JsonNode root = mapper.readTree(jsonInput);
String name = root.get("name").asText();
int age = root.get("age").asInt();

Use cases:

External APIs with changing schemas
Configuration files with optional fields
Debugging JSON structure
Partial data extraction

Before: Define POJO for every JSON structure variant After: Navigate JSON dynamically without classes

Creating JSON Trees

Build JSON programmatically with ObjectNode.

Pattern:

ObjectNode node = mapper.createObjectNode();
node.put("name", "Charlie");
node.put("age", 35);
String json = mapper.writeValueAsString(node);

Use cases:

Dynamic JSON generation
Partial object updates
JSON transformation
Testing and mocking

Performance Considerations

Jackson achieves high performance through bytecode generation and optimized parsers.

Performance characteristics:

Serialization: Fast through bytecode generation (faster than Gson’s reflection)
Deserialization: Requires reflection or bytecode generation
Memory: Moderate overhead for object creation
Streaming: Low memory for large files (not covered here)

Benchmark results (approximate, varies by use case):

Jackson ObjectMapper: 100% baseline
Gson: 60-70% of Jackson speed
javax.json: 40-50% of Jackson speed
Manual StringBuilder: Fastest but error-prone

When performance matters:

High-throughput REST APIs (thousands of requests/second)
Real-time data processing
Large batch operations
Mobile applications with limited resources

Security Considerations

JSON deserialization can create security vulnerabilities if not handled properly.

Key risks:

Arbitrary class instantiation: Deserializing untrusted JSON can instantiate any class
Denial of service: Large or deeply nested JSON consumes memory/CPU
Injection attacks: JSON values used in SQL/commands without validation

CVE-2017-7525 (Jackson vulnerability): Polymorphic type handling allowed arbitrary code execution through crafted JSON. Fixed in Jackson 2.8.9+.

Mitigation strategies:

Update Jackson regularly: Security patches released frequently
Disable default typing: enableDefaultTyping() is dangerous
Validate input: Check JSON structure before deserialization
Use allowlists: Restrict deserialization to known classes
Limit JSON size: Prevent DoS with size/depth limits

When to Use Jackson vs Alternatives

Use Jackson when:

Building Spring Boot applications (zero configuration)
Performance is critical (high-throughput APIs)
Need advanced features (annotations, custom serializers)
Working with complex object graphs

Use Gson when:

Prefer simpler API over performance
Not using Spring (no framework lock-in)
Legacy codebase already uses Gson

Use javax.json (JSON-P) when:

Standards compliance required
Jakarta EE environment
Willing to accept verbosity for specification

Use Manual StringBuilder when:

Zero-dependency constraint
Trivial JSON structure
Educational purposes only

Use Tree Model when:

JSON structure unknown at compile time
Partial data extraction from large JSON
Dynamic JSON manipulation
External APIs with frequent changes

Best Practices

1. Reuse ObjectMapper Instances

ObjectMapper is thread-safe after configuration. Create once and reuse.

Before: Creating new ObjectMapper per operation (expensive) After: Singleton or application-scoped ObjectMapper

2. Configure Fail-On-Unknown-Properties

Decide whether unknown JSON fields should fail deserialization.

Strict mode (fail on unknown): mapper.configure(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES, true) Lenient mode (ignore unknown): mapper.configure(DeserializationFeature.FAIL_ON_UNKNOWN_PROPERTIES, false)

Trade-off: Strict catches API changes early but breaks on backward-compatible additions.

3. Use Immutable Objects

Jackson supports immutable classes with constructor injection (Java 17+ records work well).

Before: Mutable POJOs with setters (violates immutability) After: Records or constructor-based deserialization with @JsonCreator

4. Handle Null Values Explicitly

Configure null handling based on API requirements.

Pattern: @JsonInclude(JsonInclude.Include.NON_NULL) excludes null fields from JSON.

5. Version Your JSON APIs

JSON schema evolution requires careful handling of field additions/removals.

Strategy: Use @JsonProperty aliases, lenient parsing, and API versioning.

Integration Patterns

REST Client Integration

Jackson integrates seamlessly with HTTP clients for REST API consumption.

Pattern (with HttpClient):

HttpClient client = HttpClient.newHttpClient();
HttpRequest request = HttpRequest.newBuilder()
    .uri(URI.create("https://api.example.com/users/1"))
    .build();

HttpResponse<String> response = client.send(request,
    HttpResponse.BodyHandlers.ofString());

Person person = mapper.readValue(response.body(), Person.class);

Use cases:

Consuming third-party REST APIs
Microservice communication
External data integration

Configuration File Loading

Load application configuration from JSON files.

Pattern:

AppConfig config = mapper.readValue(
    new File("config.json"),
    AppConfig.class
);

Advantages: Human-readable, supports comments (with extensions), version-controllable.

Message Queue Integration

Serialize objects for message queues (Kafka, RabbitMQ).

Pattern:

String message = mapper.writeValueAsString(event);
producer.send(topic, message);

Consideration: Message size affects network and storage costs.

JSON and API Integration

Why JSON Processing Matters

Approach Comparison

Manual JSON Serialization (Standard Library)

Basic Object to JSON String

Escaping Special Characters

JSON Arrays and Collections

Nested Objects

Parsing JSON String to Object

Edge Cases and Null Handling

Why Manual Approach Doesn’t Scale

javax.json (JSON-P) - Standard API

Maven Dependency

Creating JSON Objects

Creating JSON Arrays

Nested Structures

Reading JSON

Navigating JSON with JsonPointer

Handling Missing and Null Values

javax.json vs Jackson Trade-offs

Jackson - Production Standard (External Library)

Core Components

Object Mapping Patterns

Basic Serialization (Java Object → JSON)

Basic Deserialization (JSON → Java Object)

Field Mapping with Annotations

Collection Serialization

Collection Deserialization

Tree Model for Dynamic JSON

Reading JSON Trees

Creating JSON Trees

Performance Considerations

Security Considerations

When to Use Jackson vs Alternatives

Best Practices

1. Reuse ObjectMapper Instances

2. Configure Fail-On-Unknown-Properties

3. Use Immutable Objects

4. Handle Null Values Explicitly

5. Version Your JSON APIs

Integration Patterns

REST Client Integration

Configuration File Loading

Message Queue Integration

Related Content

Core Java Topics

External Resources