About Tomasz Nurkiewicz

Java EE developer, Scala enthusiast. Enjoying data analysis and visualization. Strongly believes in the power of testing and automation.

Spring Data JDBC generic DAO implementation – most lightweight ORM ever

I am thrilled to announce first version of my Spring Data JDBC repository project. The purpose of this open source library is to provide generic, lightweight and easy to use DAO implementation for relational databases based on JdbcTemplate from Spring framework, compatible with Spring Data umbrella of projects.
 
 
 
 
 
 
 

Design objectives

  • Lightweight, fast and low-overhead. Only a handful of classes, no XML, annotations, reflection
  • This is not full-blown ORM. No relationship handling, lazy loading, dirty checking, caching
  • CRUD implemented in seconds
  • For small applications where JPA is an overkill
  • Use when simplicity is needed or when future migration e.g. to JPA is considered
  • Minimalistic support for database dialect differences (e.g. transparent paging of results)

Features

Each DAO provides built-in support for:

  • Mapping to/from domain objects through RowMapper abstraction
  • Generated and user-defined primary keys
  • Extracting generated key
  • Compound (multi-column) primary keys
  • Immutable domain objects
  • Paging (requesting subset of results)
  • Sorting over several columns (database agnostic)
  • Optional support for many-to-one relationships
  • Supported databases (continuously tested):
    • MySQL
    • PostgreSQL
    • H2
    • HSQLDB
    • Derby
    • …and most likely most of the others
  • Easily extendable to other database dialects via SqlGenerator class.
  • Easy retrieval of records by ID

API

Compatible with Spring Data PagingAndSortingRepository abstraction, all these methods are implemented for you:

public interface PagingAndSortingRepository<T, ID extends Serializable> extends CrudRepository<T, ID> {
             T  save(T entity);
    Iterable<T> save(Iterable<? extends T> entities);
             T  findOne(ID id);
        boolean exists(ID id);
    Iterable<T> findAll();
           long count();
           void delete(ID id);
           void delete(T entity);
           void delete(Iterable<? extends T> entities);
           void deleteAll();
    Iterable<T> findAll(Sort sort);
        Page<T> findAll(Pageable pageable);
}

Pageable and Sort parameters are also fully supported, which means you get paging and sorting by arbitrary properties for free. For example say you have userRepository extending PagingAndSortingRepository<User, String> interface (implemented for you by the library) and you request 5th page of USERS table, 10 per page, after applying some sorting:

Page<User> page = userRepository.findAll(
    new PageRequest(
        5, 10,
        new Sort(
            new Order(DESC, "reputation"),
            new Order(ASC, "user_name")
        )
    )
);

Spring Data JDBC repository library will translate this call into (PostgreSQL syntax):

SELECT *
FROM USERS
ORDER BY reputation DESC, user_name ASC
LIMIT 50 OFFSET 10

…or even (Derby syntax):

SELECT * FROM (
    SELECT ROW_NUMBER() OVER () AS ROW_NUM, t.*
    FROM (
        SELECT *
        FROM USERS
        ORDER BY reputation DESC, user_name ASC
        ) AS t
    ) AS a
WHERE ROW_NUM BETWEEN 51 AND 60

No matter which database you use, you’ll get Page<User> object in return (you still have to provide RowMapper<User> yourself to translate from ResultSet to domain object. If you don’t know Spring Data project yet, Page<T> is a wonderful abstraction, not only encapsulating List<User>, but also providing metadata such as total number of records, on which page we currently are, etc.

Reasons to use

  • You consider migration to JPA or even some NoSQL database in the future.Since your code will rely only on methods defined in PagingAndSortingRepository and CrudRepository from Spring Data Commons umbrella project you are free to switch from JdbcRepository implementation (from this project) to: JpaRepository, MongoRepository, GemfireRepository or GraphRepository. They all implement the same common API. Of course don’t expect that switching from JDBC to JPA or MongoDB will be as simple as switching imported JAR dependencies – but at least you minimize the impact by using same DAO API.
  • You need a fast, simple JDBC wrapper library. JPA or even MyBatis is an overkill
  • You want to have full control over generated SQL if needed
  • You want to work with objects, but don’t need lazy loading, relationship handling, multi-level caching, dirty checking… You need CRUD and not much more
  • You want to by DRY
  • You are already using Spring or maybe even JdbcTemplate, but still feel like there is too much manual work
  • You have very few database tables

Getting started

For more examples and working code don’t forget to examine project tests.

Prerequisites

Maven coordinates:

<dependency>
    <groupId>com.blogspot.nurkiewicz</groupId>
    <artifactId>jdbcrepository</artifactId>
    <version>0.1</version>
</dependency>

Unfortunately the project is not yet in maven central repository. For the time being you can install the library in your local repository by cloning it:

$ git clone git://github.com/nurkiewicz/spring-data-jdbc-repository.git
$ git checkout 0.1
$ mvn javadoc:jar source:jar install

In order to start your project must have DataSource bean present and transaction management enabled. Here is a minimal MySQL configuration:

@EnableTransactionManagement
@Configuration
public class MinimalConfig {
 
    @Bean
    public PlatformTransactionManager transactionManager() {
        return new DataSourceTransactionManager(dataSource());
    }
 
    @Bean
    public DataSource dataSource() {
        MysqlConnectionPoolDataSource ds = new MysqlConnectionPoolDataSource();
        ds.setUser("user");
        ds.setPassword("secret");
        ds.setDatabaseName("db_name");
        return ds;
    }
 
}

Entity with auto-generated key

Say you have a following database table with auto-generated key (MySQL syntax):

CREATE TABLE COMMENTS (
    id INT AUTO_INCREMENT,
    user_name varchar(256),
    contents varchar(1000),
    created_time TIMESTAMP NOT NULL,
    PRIMARY KEY (id)
);

First you need to create domain object User mapping to that table (just like in any other ORM):

public class Comment implements Persistable<Integer> {
 
    private Integer id;
    private String userName;
    private String contents;
    private Date createdTime;
 
    @Override
    public Integer getId() {
        return id;
    }
 
    @Override
    public boolean isNew() {
        return id == null;
    }
 
    //getters/setters/constructors/...
}

Apart from standard Java boilerplate you should notice implementing Persistable<Integer> where Integer is the type of primary key. Persistable<T> is an interface coming from Spring Data project and it’s the only requirement we place on your domain object.

Finally we are ready to create our CommentRepository DAO:

@Repository
public class CommentRepository extends JdbcRepository<Comment, Integer> {
 
    public CommentRepository() {
        super(ROW_MAPPER, ROW_UNMAPPER, "COMMENTS");
    }
 
    public static final RowMapper<Comment> ROW_MAPPER = //see below
 
    private static final RowUnmapper<Comment> ROW_UNMAPPER = //see below
 
    @Override
    protected Comment postCreate(Comment entity, Number generatedId) {
        entity.setId(generatedId.intValue());
        return entity;
    }
}

First of all we use @Repository annotation to mark DAO bean. It enables persistence exception translation. Also such annotated beans are discovered by CLASSPATH scanning.

As you can see we extend JdbcRepository<Comment, Integer> which is the central class of this library, providing implementations of all PagingAndSortingRepository methods. Its constructor has three required dependencies: RowMapper, RowUnmapper and table name. You may also provide ID column name, otherwise default "id" is used.

If you ever used JdbcTemplate from Spring, you should be familiar with RowMapper interface. We need to somehow extract columns from ResultSet into an object. After all we don’t want to work with raw JDBC results. It’s quite straightforward:

public static final RowMapper<Comment> ROW_MAPPER = new RowMapper<Comment>() {
 
    @Override
    public Comment mapRow(ResultSet rs, int rowNum) throws SQLException {
        return new Comment(
                rs.getInt("id"),
                rs.getString("user_name"),
                rs.getString("contents"),
                rs.getTimestamp("created_time")
        );
    }
};

RowUnmapper comes from this library and it’s essentially the opposite of RowMapper: takes an object and turns it into a Map. This map is later used by the library to construct SQL CREATE/UPDATE queries:

private static final RowUnmapper<Comment> ROW_UNMAPPER = new RowUnmapper<Comment>() {
    @Override
    public Map<String, Object> mapColumns(Comment comment) {
        Map<String, Object> mapping = new LinkedHashMap<String, Object>();
        mapping.put("id", comment.getId());
        mapping.put("user_name", comment.getUserName());
        mapping.put("contents", comment.getContents());
        mapping.put("created_time", new java.sql.Timestamp(comment.getCreatedTime().getTime()));
        return mapping;
    }
};

If you never update your database table (just reading some reference data inserted elsewhere) you may skip RowUnmapper parameter or use MissingRowUnmapper.

Last piece of the puzzle is the postCreate() callback method which is called after an object was inserted. You can use it to retrieve generated primary key and update your domain object (or return new one if your domain objects are immutable). If you don’t need it, just don’t override postCreate(). Check out JdbcRepositoryGeneratedKeyTest for a working code based on this example.

By now you might have a feeling that, compared to JPA or Hibernate, there is quite a lot of manual work. However various JPA implementations and other ORM frameworks are notoriously known for introducing significant overhead and manifesting some learning curve. This tiny library intentionally leaves some responsibilities to the user in order to avoid complex mappings, reflection, annotations… all the implicitness that is not always desired. This project is not intending to replace mature and stable ORM frameworks. Instead it tries to fill in a niche between raw JDBC and ORM where simplicity and low overhead are key features.

Entity with manually assigned key

In this example we’ll see how entities with user-defined primary keys are handled. Let’s start from database model:

CREATE TABLE USERS (
    user_name varchar(255),
    date_of_birth TIMESTAMP NOT NULL,
    enabled BIT(1) NOT NULL,
    PRIMARY KEY (user_name)
);

…and User domain model:

public class User implements Persistable<String> {
 
    private transient boolean persisted;
 
    private String userName;
    private Date dateOfBirth;
    private boolean enabled;
 
    @Override
    public String getId() {
        return userName;
    }
 
    @Override
    public boolean isNew() {
        return !persisted;
    }
 
    public User withPersisted(boolean persisted) {
        this.persisted = persisted;
        return this;
    }
 
    //getters/setters/constructors/...
 
}

Notice that special persisted transient flag was added. Contract of CrudRepository.save() from Spring Data project requires that an entity knows whether it was already saved or not (isNew()) method – there are no separate create() and update() methods. Implementing isNew() is simple for auto-generated keys (see Comment above) but in this case we need an extra transient field. If you hate this workaround and you only insert data and never update, you’ll get away with return true all the time from isNew().

And finally our DAO, UserRepository bean:

@Repository
public class UserRepository extends JdbcRepository<User, String> {
 
    public UserRepository() {
        super(ROW_MAPPER, ROW_UNMAPPER, "USERS", "user_name");
    }
 
    public static final RowMapper<User> ROW_MAPPER = //...
 
    public static final RowUnmapper<User> ROW_UNMAPPER = //...
 
    @Override
    protected User postUpdate(User entity) {
        return entity.withPersisted(true);
    }
 
    @Override
    protected User postCreate(User entity, Number generatedId) {
        return entity.withPersisted(true);
    }
}

"USERS" and "user_name" parameters designate table name and primary key column name. I’ll leave the details of mapper and unmapper (see source code). But please notice postUpdate() and postCreate() methods. They ensure that once object was persisted, persisted flag is set so that subsequent calls to save() will update existing entity rather than trying to reinsert it.

Check out JdbcRepositoryManualKeyTest for a working code based on this example.

Compound primary key

We also support compound primary keys (primary keys consisting of several columns). Take this table as an example:

CREATE TABLE BOARDING_PASS (
    flight_no VARCHAR(8) NOT NULL,
    seq_no INT NOT NULL,
    passenger VARCHAR(1000),
    seat CHAR(3),
    PRIMARY KEY (flight_no, seq_no)
);

I would like you to notice the type of primary key in Peristable<T>:

public class BoardingPass implements Persistable<Object[]> {
 
    private transient boolean persisted;
 
    private String flightNo;
    private int seqNo;
    private String passenger;
    private String seat;
 
    @Override
    public Object[] getId() {
        return pk(flightNo, seqNo);
    }
 
    @Override
    public boolean isNew() {
        return !persisted;
    }
 
    //getters/setters/constructors/...
 
}

Unfortunately we don’t support small value classes encapsulating all ID values in one object (like JPA does with @IdClass), so you have to live with Object[] array. Defining DAO class is similar to what we’ve already seen:

public class BoardingPassRepository extends JdbcRepository<BoardingPass, Object[]> {
    public BoardingPassRepository() {
        this("BOARDING_PASS");
    }
 
    public BoardingPassRepository(String tableName) {
        super(MAPPER, UNMAPPER, new TableDescription(tableName, null, "flight_no", "seq_no")
        );
    }
 
    public static final RowMapper<BoardingPass> ROW_MAPPER = //...
 
    public static final RowUnmapper<BoardingPass> UNMAPPER = //...
 
}

Two things to notice: we extend JdbcRepository<BoardingPass, Object[]> and we provide two ID column names just as expected: "flight_no", "seq_no". We query such DAO by providing both flight_no and seq_no (necessarily in that order) values wrapped by Object[]:

BoardingPass pass = repository.findOne(new Object[] {"FOO-1022", 42});

No doubts, this is cumbersome in practice, so we provide tiny helper method which you can statically import:

import static com.blogspot.nurkiewicz.jdbcrepository.JdbcRepository.pk;
//...
 
BoardingPass foundFlight = repository.findOne(pk("FOO-1022", 42));

Check out JdbcRepositoryCompoundPkTest for a working code based on this example.

Transactions

This library is completely orthogonal to transaction management. Every method of each repository requires running transaction and it’s up to you to set it up. Typically you would place @Transactional on service layer (calling DAO beans). I don’t recommend placing @Transactional over every DAO bean.

Caching

Spring Data JDBC repository library is not providing any caching abstraction or support. However adding @Cacheable layer on top of your DAOs or services using caching abstraction in Spring is quite straightforward. See also: @Cacheable overhead in Spring.

Contributions

..are always welcome. Don’t hesitate to submit bug reports and pull requests. Biggest missing feature now is support for MSSQL and Oracle databases. It would be terrific if someone could have a look at it.

Testing

This library is continuously tested using Travis (Build Status). Test suite consists of 265 tests (53 distinct tests each run against 5 different databases: MySQL, PostgreSQL, H2, HSQLDB and Derby.

When filling bug reports or submitting new features please try including supporting test cases. Each pull request is automatically tested on a separate branch.

Building

After forking the official repository building is as simple as running:

$ mvn install

You’ll notice plenty of exceptions during JUnit test execution. This is normal. Some of the tests run against MySQL and PostgreSQL available only on Travis CI server. When these database servers are unavailable, whole test is simply skipped:
Results :

Tests run: 265, Failures: 0, Errors: 0, Skipped: 106

Exception stack traces come from root AbstractIntegrationTest.

Design

Library consists of only a handful of classes, highlighted in the diagram below:

UML diagram

JdbcRepository is the most important class that implements all PagingAndSortingRepository methods. Each user repository has to extend this class. Also each such repository must at least implement RowMapper and RowUnmapper (only if you want to modify table data).

SQL generation is delegated to SqlGenerator. PostgreSqlGenerator. and DerbySqlGenerator are provided for databases that don’t work with standard generator.

License

This project is released under version 2.0 of the Apache License (same as Spring framework).
 

Reference: Probability distribution for programmers from our JCG partner Tomasz Nurkiewicz at the NoBlogDefFound blog.

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One Response to "Spring Data JDBC generic DAO implementation – most lightweight ORM ever"

  1. after adding

    org.apache.velocity
    velocity
    1.7

    to the pom i’m still stuck here

    Caused by: java.lang.NoClassDefFoundError: org/apache/velocity/context/Context

    what should I do?

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