* Represents a field facet with its name and value counts.
     * Each field facet contains multiple values with their respective document counts.
     */
    public static class Field {
        /**
         * Map containing field values and their document counts.
         * Keys are field values as strings, values are document counts.
         */
        protected Map<String, Long> valueCountMap = new LinkedHashMap<>();

        /**

    //                                                                      ==============
    /**
     * Handles document redirection requests.
     * Validates the document ID, logs click events if enabled, and redirects
     * to the target URL or serves file content directly if configured.
     *
     * @param form the go form containing document ID and tracking parameters
     * @return action response for redirection or content streaming

        assertTrue(content.contains("title"));
        assertTrue(content.contains("Sample Document"));
        assertTrue(content.contains("author"));
        assertTrue(content.contains("John Doe"));

        // Verify metadata extraction
        assertNotNull(extractData.getValues("title"));
        assertEquals("Sample Document", extractData.getValues("title")[0]);
        assertNotNull(extractData.getValues("author"));

---
title: Sample Markdown Document
author: John Doe
date: 2025-01-15
tags:
  - crawler
  - extractor
  - markdown
---

# Introduction

This is a sample Markdown document for testing the MarkdownExtractor.

## Features

The extractor should handle:

- YAML front matter extraction
- Heading structure
- **Bold text** and *italic text*
- Lists and other formatting

### Code Examples

     */
    protected void saveModifications(UpgradeContext context, Map<Path, Document> pomMap) {
        context.info("");
        context.info("Saving modified POMs...");

        for (Map.Entry<Path, Document> entry : pomMap.entrySet()) {
            Path pomPath = entry.getKey();
            Document document = entry.getValue();
            try {
                // Use domtrip for perfect formatting preservation

		a query. AND operator matches documents where both terms exist
		anywhere in the text of a single document.
		<pre>Fess AND CodeLibs</pre>
	</dd>
	</dd>
	<dt>OR</dt>
	<dd>
		OR operator matches documents where any terms exist anywhere in the
		text of a single document.
		<pre>Fess OR CodeLibs</pre>
	</dd>
	<dt>Wildcard</dt>
	<dd>

{
  "title": "Sample Document",
  "author": "John Doe",
  "version": "1.0",
  "published": "2025-01-15",
  "tags": ["crawler", "extractor", "json"],
  "content": {
    "summary": "This is a sample JSON document for testing",
    "body": "The extractor should handle nested objects and arrays properly"
  },
  "metadata": {
    "created_at": "2025-01-01T00:00:00Z",
    "updated_at": "2025-01-15T12:00:00Z"
  }

### Index from Existing Documents

```java
import org.codelibs.fess.suggest.index.contents.document.ESSourceReader;

// Index suggestions from existing Elasticsearch documents
DocumentReader reader = new ESSourceReader(
    client,
    suggester.settings(),
    "content-index",        // source index
    "document"             // document type
);

suggester.indexer()

        final Map<String, String> params = new HashMap<>();
        params.put(ExtractData.RESOURCE_NAME_KEY, "test-document.pdf");

        final ExtractData result = filenameExtractor.getText(in, params);

        assertNotNull(result);
        assertEquals("test-document.pdf", result.getContent());
    }

    /**
     * Test extraction with null parameters map.
     */

    //                                                                      ==============

    /**
     * Returns the OSDD document.
     *
     * @return the OSDD document as a stream response
     */
    @Execute
    public ActionResponse index() {
        if (isLoginRequired()) {
            return redirectToLogin();
        }