Create Document Index with GroupDocs.Search for Java: A Complete Guide

In today’s digital age, being able to create document index quickly and search through it efficiently is a game‑changer for any organization. Whether you’re building a document management system or a custom search engine, GroupDocs.Search for Java gives you the tools to extract text, serialize data, and perform full‑text search Java operations with ease. This tutorial walks you through every step—from extracting PDF text to adding data to index and searching indexed documents.

Quick Answers

  • What is the main purpose? To create a searchable document index using GroupDocs.Search for Java.
  • Which library version? GroupDocs.Search 25.4 (or the latest release).
  • Do I need a license? A free trial works for development; a full license is required for production.
  • Can I index PDFs? Yes—extract pdf text and add it to the index.
  • How do I run a search? Use the index.search(query) method after adding data.

What is a Document Index?

A document index is a structured collection of searchable terms extracted from your files. By creating a document index, you enable rapid full‑text searches across large repositories, dramatically improving retrieval speed and accuracy.

Why Use GroupDocs.Search for Java?

  • Robust extraction – Handles PDFs, Word, Excel, and more.
  • Easy serialization – Store extracted data as byte arrays for later reuse.
  • Scalable indexing – Efficiently index millions of documents.
  • Powerful query language – Supports complex full‑text search Java queries.

Prerequisites

  • GroupDocs.Search for Java (Version 25.4 or newer).
  • Java Development Kit (JDK) compatible with your GroupDocs version.
  • An IDE such as IntelliJ IDEA or Eclipse.
  • Maven for dependency management.

Setting Up GroupDocs.Search for Java

First, add the library to your project.

Maven Setup
Include the following in your pom.xml file:

<repositories>
    <repository>
        <id>repository.groupdocs.com</id>
        <name>GroupDocs Repository</name>
        <url>https://releases.groupdocs.com/search/java/</url>
    </repository>
</repositories>

<dependencies>
    <dependency>
        <groupId>com.groupdocs</groupId>
        <artifactId>groupdocs-search</artifactId>
        <version>25.4</version>
    </dependency>
</dependencies>

Direct Download
Alternatively, download the latest version from GroupDocs.Search for Java releases.

License Acquisition

  • Free Trial – Test all features with a temporary license.
  • Purchase – Get full access and priority support.

Step‑by‑Step Implementation

How to extract text from PDFs (and other documents)

Extracting raw or formatted text is the first step toward creating a document index.

String documentPath = "YOUR_DOCUMENT_DIRECTORY/Lorem ipsum.pdf";
Extractor extractor = new Extractor();
Document document = Document.createFromFile(documentPath);

ExtractionOptions extractionOptions = new ExtractionOptions();
extractionOptions.setUseRawTextExtraction(false); // Extract with formatting
ExtractedData extractedData = extractor.extract(document, extractionOptions);

Tip: Set setUseRawTextExtraction(true) if you need plain text without formatting.

How to serialize extracted data

Serialization lets you store the extracted data for later indexing.

ByteArrayOutputStream outputStream = new ByteArrayOutputStream();
extractedData.serialize(outputStream);
byte[] serializedArray = outputStream.toByteArray();

How to deserialize extracted data

When you’re ready to build the index, convert the byte array back into an object.

ByteArrayInputStream inputStream = new ByteArrayInputStream(serializedArray);
ExtractedData deserializedData = ExtractedData.deserialize(inputStream);

How to create document index

Now that you have deserializedData, you can create the index that will hold searchable terms.

String indexFolder = "YOUR_OUTPUT_DIRECTORY/AdvancedUsage/Indexing/SeparateDataExtraction";
com.groupdocs.search.Index index = new com.groupdocs.search.Index(indexFolder);

Adding data and querying the index completes the create document index workflow.

ExtractedData[] dataToIndex = new ExtractedData[] { deserializedData };
index.add(dataToIndex, new IndexingOptions());

String query = "ipsum";
SearchResult result = index.search(query);

Pro tip: Use index.search("your query", SearchOptions) to fine‑tune relevance ranking.

Common Use Cases

  1. Document Management Systems – Quickly locate contracts, invoices, or policies.
  2. Content‑Based Search Engines – Power internal knowledge bases with full‑text search Java capabilities.
  3. Data Archiving Solutions – Index historic records for instant retrieval.

Performance Considerations

  • Memory Management: Adjust JVM heap size for large document batches.
  • Indexing Options: Disable unnecessary features (e.g., term vectors) to speed up indexing.
  • Regular Updates: Keep GroupDocs.Search up‑to‑date to benefit from performance patches.

Frequently Asked Questions

Q: How do I handle very large PDF files efficiently?
A: Stream the file using Extractor and process it in chunks; also increase the JVM heap if needed.

Q: Can I customize the search query syntax?
A: Yes—GroupDocs.Search supports Boolean operators, wildcards, and proximity searches.

Q: What should I do if serialization fails?
A: Verify that all objects implement Serializable and catch IOException to log details.

Q: Is it possible to index only specific sections of a document?
A: Absolutely—configure ExtractionOptions to filter pages or sections before indexing.

Q: How do I upgrade to a newer GroupDocs.Search version?
A: Update the version number in your pom.xml and run mvn clean install; review the migration guide for breaking changes.

Resources

Last Updated: 2025-12-18
Tested With: GroupDocs.Search 25.4 for Java
Author: GroupDocs