## Key Features

- **Smart Query Suggestions**: Real-time auto-completion and search suggestions
- **Multi-language Support**: Built-in support for Japanese text processing with Kuromoji analyzer
- **Popular Words Analytics**: Track and analyze frequently searched terms

allows for transforming your data to serve unique data format requirements for each application. For example, a dataset created by an ecommerce application might include personally identifiable information (PII). When the same data is processed for analytics, PII should be redacted. However, if the same dataset is used for a marketing campaign, you might need to enrich the data with additional details, such as information from the customer loyalty database.

MinIO's Object Lambda, enables application...

     */
    public String hash;

    /**
     * Query identifier associated with the search that led to this document access.
     * This is required for tracking and analytics purposes.
     */
    @Required
    public String queryId;

    /**
     * Order or ranking position of the document in search results.
     * This optional field helps track which result position was clicked.

## Project Overview

**Fess Suggest** delivers auto-completion, search suggestions, and popular word analytics with multi-language support.

**Technology Stack:**
- Java 21+, Maven
- OpenSearch (provided dependency)
- Apache Lucene (query parsing, text analysis)
- ICU4J (Unicode text processing)
- JUnit 4 (testing)

**Repository:** https://github.com/codelibs/fess-suggest

---

 * This class handles user identification through cookies, session management, and query tracking.
 * It provides functionality for generating unique user codes, managing user sessions,
 * and tracking search result document IDs for analytics and personalization.
 *
 */
public class UserInfoHelper {

    /**
     * Default constructor for UserInfoHelper.
     */
    public UserInfoHelper() {
        // Default constructor
    }

import jakarta.annotation.Resource;

/**
 * Service class for managing search logs and related analytics.
 *
 * This service provides functionality for querying, aggregating, and managing
 * various types of search logs including search logs, click logs, favorite logs,
 * and user information logs. It supports different aggregation types for
 * analytics and reporting purposes.
 */
public class SearchLogService {

Designed for speed and scalability, it powers AI/ML, analytics, and data-intensive workloads with industry-leading performance.

- S3 API Compatible – Seamless integration with existing S3 tools
- Built for AI & Analytics – Optimized for large-scale data pipelines
- High Performance – Ideal for demanding storage workloads.

	app.Name = name
	app.Author = "MinIO, Inc."
	app.Version = ReleaseTag
	app.Usage = "High Performance Object Storage"
	app.Description = `Build high performance data infrastructure for machine learning, analytics and application data workloads with MinIO`
	app.Flags = GlobalFlags
	app.HideHelpCommand = true // Hide `help, h` command, we already have `minio --help`.
	app.Commands = commands

 *
 * This class provides pagination functionality for various types of search logs
 * including search logs, click logs, favorite logs, and user information logs.
 * It also supports different aggregation types for analytics and reporting.
 */
public class SearchLogPager implements Serializable {

    /** Serial version UID for serialization. */
    private static final long serialVersionUID = 1L;

		methods: []string{http.MethodDelete, http.MethodPut, http.MethodGet},
		queries: []string{"intelligent-tiering", ""},
	},
	{
		api:     "analytics",
		methods: []string{http.MethodDelete, http.MethodPut, http.MethodGet},
		queries: []string{"analytics", ""},
	},
}

// Set of s3 handler options as bit flags.
type s3HFlag uint8

const (
	// when provided, disables Gzip compression.