Hands-on Examples on Advanced Beginner

Environment Setup

d8lzz1gpw@mozmail.com (kimbenji) — Sat, 10 Jan 2026 00:00:00 +0000

TL;DR

Quickly set up Elasticsearch 8.11 + Kibana environment with Docker Compose

Complete integration setup with Spring Boot 3.2 + Spring Data Elasticsearch

Install Nori analyzer for Korean search

Total time required: approximately 15 minutes

Version Information

Elasticsearch / Kibana: 8.11.0

Spring Boot: 3.2.0

Spring Data Elasticsearch: 5.2.x (included in Spring Boot 3.2)

Java: 17+

Configure Elasticsearch + Kibana with Docker and set up a Spring Boot project.

Docker Environment Setup#

docker-compose.yml#

docker/elasticsearch/docker-compose.yml file:

Basic Examples

d8lzz1gpw@mozmail.com (kimbenji) — Sat, 10 Jan 2026 00:00:00 +0000

TL;DR

Implement Document CRUD and basic search using Spring Data Elasticsearch

Handle simple queries with Repository pattern, complex queries with ElasticsearchOperations

Choose field types based on purpose: Text (for search), Keyword (for filtering), Integer (for range queries)

Total time required: approximately 20 minutes

Implement Document CRUD and basic search using Spring Data Elasticsearch.

Project Structure#

src/main/java/com/example/
├── ElasticsearchApplication.java
├── config/
│ └── ElasticsearchConfig.java
├── domain/
│ └── Product.java
├── repository/
│ └── ProductRepository.java
├── service/
│ └── ProductService.java
└── controller/
 └── ProductController.java

Domain Class#

Product.java#

package com.example.domain;

import org.springframework.data.annotation.Id;
import org.springframework.data.elasticsearch.annotations.Document;
import org.springframework.data.elasticsearch.annotations.Field;
import org.springframework.data.elasticsearch.annotations.FieldType;
import org.springframework.data.elasticsearch.annotations.Setting;

@Document(indexName = "products")
@Setting(settingPath = "elasticsearch/settings.json") // Optional
public class Product {

 @Id
 private String id;

 @Field(type = FieldType.Text, analyzer = "standard")
 private String name;

 @Field(type = FieldType.Keyword)
 private String category;

 @Field(type = FieldType.Integer)
 private Integer price;

 @Field(type = FieldType.Text)
 private String description;

 @Field(type = FieldType.Boolean)
 private Boolean inStock;

 // Default constructor
 public Product() {}

 // All-args constructor
 public Product(String id, String name, String category,
 Integer price, String description, Boolean inStock) {
 this.id = id;
 this.name = name;
 this.category = category;
 this.price = price;
 this.description = description;
 this.inStock = inStock;
 }

 // Getter/Setter
 public String getId() { return id; }
 public void setId(String id) { this.id = id; }

 public String getName() { return name; }
 public void setName(String name) { this.name = name; }

 public String getCategory() { return category; }
 public void setCategory(String category) { this.category = category; }

 public Integer getPrice() { return price; }
 public void setPrice(Integer price) { this.price = price; }

 public String getDescription() { return description; }
 public void setDescription(String description) { this.description = description; }

 public Boolean getInStock() { return inStock; }
 public void setInStock(Boolean inStock) { this.inStock = inStock; }
}

Annotation Explanation#

Annotation	Description
`@Document`	Elasticsearch index mapping
`@Id`	Document unique ID field
`@Field`	Field type and analyzer settings
`@Setting`	Index settings file path

Why This Design?#

Field type selection rationale:

Product Search System

d8lzz1gpw@mozmail.com (kimbenji) — Sat, 10 Jan 2026 00:00:00 +0000

Complete Example Project
If you want to run this code immediately, use the complete Spring Boot project:

📁 examples/elasticsearch/product-search/

Instant Elasticsearch execution with docker-compose (including Nori)

Automatic sample data initialization

TL;DR

Apply Korean morphological analysis with Nori analyzer to enable search for “삼성” and “전자” from “삼성전자”

Implement autocomplete functionality with Edge N-gram

Provide filtering and facets with Bool Query + Aggregation

Highlight search terms with highlighting

Total time required: approximately 30 minutes

Implement a production-level product search system with Korean morphological analysis, autocomplete, and filtering.

Log Analysis System

d8lzz1gpw@mozmail.com (kimbenji) — Sat, 10 Jan 2026 00:00:00 +0000

Complete Example Project
If you want to run this code immediately, use the complete Spring Boot project:

📁 examples/elasticsearch/log-analysis/

Instant Elasticsearch + Kibana execution with docker-compose

Includes sample log generation API

TL;DR

Send application logs directly to Elasticsearch using Logback Appender

Ensure traceability by automatically including request ID and user ID in logs with MDC

Analyze error rates and response time percentiles with Aggregations

Automatically manage log lifecycle (Hot→Warm→Cold→Delete) with ILM

Total time required: approximately 40 minutes

Implement a system to collect, store, and analyze application logs using Elasticsearch.