Skip to content

Latest commit

 

History

History
59 lines (47 loc) · 2.49 KB

README.md

File metadata and controls

59 lines (47 loc) · 2.49 KB
Raw

Embedded services

Maven Central covarage

This project allows you to easily start your project with the embedded database (PostgreSQL, MongoDB) services and connect them with the embedded ElasticSearch instance for full text indexing and search.

Why?

It's very easy to incorporate the embedded MongoDB/PostgreSQL within your test process.

Maven

Add the following dependency to your pom.xml:

    <dependency>
        <groupId>ru.yandex.qatools.embed</groupId>
        <artifactId>embedded-services</artifactId>
        <version>1.21</version>
    </dependency>

How to run embedded MongoDB with ElasticSearch

        // Starting the embedded services within temporary dir
        MongoEmbeddedService mongo = new MongoEmbeddedService(
                "localhost:27017", "dbname", "username", "password", "localreplica"
        );
        mongo.start();
        ElasticMongoIndexingService elastic = new ElasticMongoIndexingService(
                "localhost:27017", "dbname", "username", "password"
        );
        elastic.start();
        
        // Indexing collection `posts`
        elastic.addToIndex("posts");
        
        // Searching within collection `posts` using Elastic (IndexingResult contains id of each post)
        List<IndexingResult> posts = elastic.search("posts", "body:(lorem AND NOT ipsum)")

How to run embedded PostgreSQL with ElasticSearch

        // Starting the embedded services within temporary dir
        PostgresEmbeddedService postgres = new PostgresEmbeddedService(
                "localhost", 5429, "username", "password",  "dbname"
        );
        postgres.start();
        ElasticPostgresIndexingService elastic = new ElasticPostgresIndexingService(
                Driver.class, "postgresql", "", "localhost", 5429, "username", "password", "dbname"
        );
        elastic.start();
        
        // Indexing table `posts`
        elastic.addToIndex("posts");
        
        // Searching within table `posts` using Elastic (IndexingResult contains id of each post)
        List<IndexingResult> posts = elastic.search("posts", "body:(lorem AND NOT ipsum)")