Elasticsearch Client for Swift (iOS/macOS): Integration and Examples

Elasticsearch Client for Swift (iOS/macOS)

Elasticsearch is a powerful distributed search engine built on top of Apache Lucene. For iOS and macOS developers, the official elasticsearch-swift client is available, providing a convenient interface for working with Elasticsearch from Swift applications. The library fully supports the Elasticsearch REST API, including indexing, search, aggregations, and cluster management.

Installation and Setup

The client is distributed via Swift Package Manager (SPM). To add it to your project:

// In Package.swiftdependencies: [    .package(url: "https://github.com/elastic/elasticsearch-swift.git", from: "8.10.0")]

Or via Xcode: File → Add Packages → enter the repository URL. After installation, import the library:

import Elasticsearch

Main Features

• Document Indexing — adding, updating, and deleting records in indices.
• Search — full-text, field-specific, with filters and sorting.
• Aggregations — statistical calculations, groupings, histograms.
• Cluster Management — creating/deleting indices, configuring shards and replicas.
• async/await Support — asynchronous requests using the modern Swift Concurrency model.

Usage Example: Connection and Indexing

Let's create a client and index several documents:

import Elasticsearch

let client = ElasticsearchClient(    host: "https://your-cluster-url:9200",    apiKey: "your-api-key")

struct Book: Codable {    let id: String    let title: String    let author: String    let year: Int}

let books = [    Book(id: "1", title: "Swift Programming", author: "John Doe", year: 2023),    Book(id: "2", title: "iOS Development", author: "Jane Smith", year: 2024)]

for book in books {    let response = try await client.index(        index: "books",        id: book.id,        body: book    )    print("Indexed: \\(response.result)")}

Search Using Query DSL

Elasticsearch supports a powerful query language. Example of full-text search:

import Elasticsearch

let query: [String: Any] = [    "query": [        "bool": [            "must": [                ["match": ["title": "Swift"]]            ],            "filter": [                ["range": ["year": ["gte": 2023]]]            ]        ]    ]]

let searchResponse = try await client.search(    index: "books",    body: query)

if let hits = searchResponse.hits?.hits {    for hit in hits {        if let source = hit.source {            let book = try JSONDecoder().decode(Book.self, from: source)            print("Found: \\(book.title) by \\(book.author)")        }    }}

Aggregations for Analytics

Example of counting books by year:

let aggregationQuery: [String: Any] = [    "size": 0,    "aggs": [        "by_year": [            "terms": ["field": "year", "size": 10]        ]    ]]

let aggResponse = try await client.search(    index: "books",    body: aggregationQuery)

if let buckets = aggResponse.aggregations?["by_year"] as? [String: Any],   let bucketList = buckets["buckets"] as? [[String: Any]] {    for bucket in bucketList {        let year = bucket["key"] as? Int ?? 0        let count = bucket["doc_count"] as? Int ?? 0        print("\\(year): \\(count) books")    }}

Index Management

Creating and deleting an index with settings:

let settings: [String: Any] = [    "settings": [        "number_of_shards": 2,        "number_of_replicas": 1    ],    "mappings": [        "pro