spring-data-relational

Files

Jens Schauder 36b419e712 DATAJDBC-386 - Polishing.

Tests that used the `@Column` annotation to map multiple properties to a single database column failed.
Mapping multiple values to one column is possible to allow for entities inside an aggregate to have the id of the aggregate as ID or as part of the ID.

The reason for the test failures was that columns get referred to by different ways:
Once per DerivedSqlIdentifier (i.e. with normalized spelling).
And Once per `@Column` annotation.

SqlIdentifier from an `@Column` annotation have always the same spelling, while the normalized version depends on the `Dialect`.

In order to make the tests work for all databases all references to the column in question had to get a `@Column` annotation.
This in turn required the create scripts to also use quoting when the normal case of the database did not match the case chosen in the annotation.

Finally there were some tests that used hand coded SQL which now uses `SqlIdentifier` and an injected `Dialect` to arrive at the correct SQL syntax.

Removed a couple of `@Ignore` annotations that got left in the code.

Original pull request: #182.

2020-01-28 13:55:19 +01:00

src

DATAJDBC-386 - Polishing.

2020-01-28 13:55:19 +01:00

pom.xml

DATAJDBC-473 - Prepare next development iteration.

2020-01-17 09:47:49 +01:00

README.adoc

DATAJDBC-391 - Revise readme for a consistent structure.

2019-07-09 11:19:19 +02:00

README.adoc

image:https://spring.io/badges/spring-data-jdbc/ga.svg["Spring Data JDBC", link="https://spring.io/projects/spring-data-jdbc#learn"]
image:https://spring.io/badges/spring-data-jdbc/snapshot.svg["Spring Data JDBC", link="https://spring.io/projects/spring-data-jdbc#learn"]

= Spring Data JDBC

The primary goal of the https://projects.spring.io/spring-data[Spring Data] project is to make it easier to build Spring-powered applications that use data access technologies. *Spring Data JDBC* offers the popular Repository abstraction based on JDBC.

It aims at being conceptually easy.
In order to achieve this it does NOT offer caching, lazy loading, write behind or many other features of JPA.
This makes Spring Data JDBC a simple, limited, opinionated ORM.

== Features

* Implementation of CRUD methods for Aggregates.
* `@Query` annotation
* Support for transparent auditing (created, last changed)
* Events for persistence events
* Possibility to integrate custom repository code
* JavaConfig based repository configuration by introducing `EnableJdbcRepository`
* Integration with MyBatis

== Getting Help

If you are new to Spring Data JDBC read the following two articles https://spring.io/blog/2018/09/17/introducing-spring-data-jdbc["Introducing Spring Data JDBC"] and https://spring.io/blog/2018/09/24/spring-data-jdbc-references-and-aggregates["Spring Data JDBC, References, and Aggregates"]

There are also examples in the https://github.com/spring-projects/spring-data-examples/tree/master/jdbc[Spring Data Examples] project.

A very good source of information is the source code in this repository.
Especially the integration tests (if you are reading this on github, type `t` and then `IntegrationTests.java`)

We are keeping an eye on the (soon to be created) https://stackoverflow.com/questions/tagged/spring-data-jdbc[spring-data-jdbc tag on stackoverflow].

If you think you found a bug, or have a feature request please https://jira.spring.io/browse/DATAJDBC/?selectedTab=com.atlassian.jira.jira-projects-plugin:summary-panel[create a ticket in our issue tracker].

== Execute Tests

=== Fast running tests

Fast running tests can be executed with a simple

[source]
----
mvn test
----

This will execute unit tests and integration tests using an in-memory database.

=== Running tests with a real database

In order to run the integration tests against a specific database you need to have a local Docker installation available, and then execute.

[source]
----
mvn test -Dspring.profiles.active=<databasetype>
----

This will also execute the unit tests.

Currently the following _databasetypes_ are available:

* hsql (default, does not require a running database)
* mysql
* postgres
* mariadb
* mssql

Testing with Microsoft SQL Server requires you to accept the EULA of the Microsoft SQL Server Docker image, so the build may download and run it for you.
In order to accept the EULA please add a file named `container-license-acceptance.txt` to the classpath, i.e. `src/test/resources` with the content:

```
microsoft/mssql-server-linux:2017-CU6
```

=== Run tests with all databases

[source]
----
mvn test -Pall-dbs
----

This will execute the unit tests, and all the integration tests with all the databases we currently support for testing. Running the integration-tests depends on Docker.