Handling Large JSON Documents with the Streaming API

Handling large JSON documents efficiently and effectively is crucial when working with big data or complex data structures. The Jackson library provides a powerful and efficient Streaming API that allows you to process large JSON documents in a streaming manner, reducing memory consumption and improving performance. In this article, we will explore how to handle large JSON documents using Jackson's Streaming API.

What is the Streaming API?

The Streaming API in Jackson is a low-level JSON processing API that allows you to read and write JSON documents as a stream of tokens. Instead of loading the entire JSON document into memory, the Streaming API processes the input or output JSON data incrementally, providing a more memory-efficient solution for handling large JSON documents.

Advantages of the Streaming API

  1. Reduced memory consumption: With the Streaming API, you can process large JSON documents without loading the entire document into memory. This significantly reduces memory usage, making it possible to handle even extremely large JSON files that wouldn't fit in memory otherwise.

  2. Improved performance: Since the Streaming API processes JSON data incrementally, it can start processing the data as soon as possible. This approach provides performance advantages, especially when dealing with large JSON documents, as you don't have to wait for the entire document to load before processing can begin.

Working with the Streaming API

To work with the Streaming API in Jackson, you need to follow these general steps:

  1. Create a JSON parser: Use JsonFactory to create a JSON parser object. This parser enables you to read JSON data incrementally as a series of tokens.

  2. Process the tokens: Iterate over the tokens provided by the JSON parser to access and manipulate the JSON data. The available tokens include JsonToken.START_OBJECT, JsonToken.START_ARRAY, JsonToken.FIELD_NAME, JsonToken.VALUE_STRING, and so on.

  3. Handle the tokens: Depending on the type of token encountered, you can perform various operations such as extracting values, modifying data, or generating a new JSON document.

  4. Close the parser: When you finish processing the JSON document, make sure to close the parser to release any resources associated with it.

Example Usage

Let's take a look at a simple example that demonstrates how to handle large JSON documents using the Streaming API in Jackson:

import com.fasterxml.jackson.core.JsonFactory;
import com.fasterxml.jackson.core.JsonParser;
import com.fasterxml.jackson.core.JsonToken;

import java.io.File;
import java.io.IOException;

public class JSONHandler {
    public static void main(String[] args) throws IOException {
        JsonFactory factory = new JsonFactory();
        JsonParser parser = factory.createParser(new File("large.json"));

        while (!parser.isClosed()) {
            JsonToken token = parser.nextToken();

            if (token == null)

            if (token == JsonToken.FIELD_NAME) {
                String fieldName = parser.getCurrentName();
                // Process the field name token
                System.out.println("Field Name: " + fieldName);
            } else if (token.isScalarValue()) {
                String value = parser.getText();
                // Process the scalar value token
                System.out.println("Value: " + value);


In this example, we create a JSON parser using JsonFactory and specify the JSON file to be processed. We then iterate over the tokens provided by the parser using a while loop, processing each token accordingly. If a field name token is encountered, we extract the field name using parser.getCurrentName(). If a scalar value token is encountered, we extract the value using parser.getText(). Finally, we close the parser using parser.close() when finished.


Handling large JSON documents can be challenging due to memory constraints and performance limitations. However, with Jackson's Streaming API, you can efficiently process large JSON files by reading and writing them as a stream of tokens. By following the steps outlined in this article, you can minimize memory usage, improve performance, and effectively handle large JSON documents in your applications.

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