rxjava-jdbc



Maven Central

Efficient execution, concise code, and functional composition of database calls using JDBC and RxJava Observable.

Status: Released to Maven Central

See also rxjava2-jdbc for RxJava 2.x with non-blocking connection pools!

Release Notes

Features

Maven site reports are here including javadoc.

Table of Contents

Todo

Build instructions

git clone https://github.com/davidmoten/rxjava-jdbc.git
cd rxjava-jdbc
mvn clean install

Getting started

Include this maven dependency in your pom (available in Maven Central):

<dependency>
    <groupId>com.github.davidmoten</groupId>
    <artifactId>rxjava-jdbc</artifactId>
    <version>0.7.11</version>
</dependency>

After using RxJava on a work project and being very impressed with it (even without Java 8 lambdas!), I wondered what it could offer for JDBC usage. The answer is lots!

Here's a simple example:

Database db = Database.from(url);
List<String> names = db
        .select("select name from person where name > ? order by name")
        .parameter("ALEX")
        .getAs(String.class)
        .toList().toBlocking().single();
System.out.println(names);

output:

[FRED, JOSEPH, MARMADUKE]

Without using rxjava-jdbc:

String sql = "select name from person where name > ? order by name";
try (Connection con = nextConnection();
     PreparedStatement ps = con.prepareStatement(sql);) {
    ps.setObject(1, "ALEX");
    List<String> list = new ArrayList<String>();
    try (ResultSet rs = ps.executeQuery()) {
        while (rs.next()) {
            list.add(rs.getString(1));
        }
    }
    System.out.println(list);
} catch (SQLException e) {
    throw new RuntimeException(e);
}

Query types

The Database.select() method is used for

The Database.update() method is used for

Examples of all of the above methods are found in the sections below.

Functional composition of JDBC calls

Here's an example, wonderfully brief compared to normal JDBC usage:

import com.github.davidmoten.rx.jdbc.Database;
import rx.Observable;

// use composition to find the first person alphabetically with
// a score less than the person with the last name alphabetically
// whose name is not XAVIER. Two threads and connections will be used.

Database db = new Database(connectionProvider);
Observable<Integer> score = db
        .select("select score from person where name <> ? order by name")
        .parameter("XAVIER")
        .getAs(Integer.class)
        .last();
String name = db
        .select("select name from person where score < ? order by name")
        .parameters(score)
        .getAs(String.class)
        .first()
        .toBlocking().single();
assertEquals("FRED", name);

or alternatively using the Observable.compose() method to chain everything in one command:

String name = db
    .select("select score from person where name <> ? order by name")
    .parameter("XAVIER")
    .getAs(Integer.class)
    .last()
    .compose(db.select("select name from person where score < ? order by name")
            .parameterTransformer()
            .getAs(String.class))
    .first()
    .toBlocking().single();

About toBlocking

You'll see toBlocking() used in the examples in this page and in the unit tests but in your application code you should try to avoid using it. The most benefit from the reactive style is obtained by not leaving the monad. That is, stay in Observable land and make the most of it. Chain everything together and leave toBlocking to an endpoint or better still just subscribe with a Subscriber.

Dependencies

You can setup chains of dependencies that will determine the order of running of queries.

To indicate that a query cannot be run before one or more other Observables have been completed use the dependsOn() method. Here's an example:

Observable<Integer> insert = db
        .update("insert into person(name,score) values(?,?)")
        .parameters("JOHN", 45)
        .count()
        .map(Util.<Integer> delay(500));
int count = db
        .select("select name from person")
        .dependsOn(insert)
        .get()
        .count()
        .toBlocking().single();
assertEquals(4, count);

Note that when you pass the output of a query as a parameter to another query there is an implicit dependency established.

Mixing explicit and Observable parameters

Example:

String name= db
    .select("select name from person where name > ?  and score < ? order by name")
    .parameter("BARRY")
    .parameters(Observable.just(100))
    .getAs(String.class)
    .first()
    .toBlocking().single();
assertEquals("FRED",name);

Passing multiple parameter sets to a query

Given a sequence of parameters, each chunk of parameters will be run with the query and the results appended. In the example below there is only one parameter in the sql statement yet two parameters are specified. This causes the statement to be run twice.

List<Integer> list = 
    db.select("select score from person where name=?")
        .parameter("FRED").parameter("JOSEPH")
        .getAs(Integer.class).toList().toBlocking().single();
assertEquals(Arrays.asList(21,34),list);

Named parameters

Examples:

Observable<String> names = db
    .select("select name from person where score >= :min and score <=:max")
    .parameter("min", 24)
    .parameter("max", 26)
    .getAs(String.class);

Using a map of parameters:

Map<String, Integer> map = new HashMap<String, Integer>();
map.put("min", 24);
map.put("max", 26);
Observable<String> names = db
    .select("select name from person where score >= :min and score <=:max")
    .parameters(map)
    .getAs(String.class);

Using an Observable of maps:

Observable<String> names = db
    .select("select name from person where score >= :min and score <=:max")
    .parameters(Observable.just(map1, map2))
    .getAs(String.class);

Processing a ResultSet

Many operators in rxjava process items pushed to them asynchronously. Given this it is important that ResultSet query results are processed before being emitted to a consuming operator. This means that the select query needs to be passed a function that converts a ResultSet to a result that does not depend on an open java.sql.Connection. Use the get(), getAs(), getTuple?(), and autoMap() methods to specify this function as below.

Observable<Integer> scores = db.select("select score from person where name=?")
        .parameter("FRED")
        .getAs(Integer.class);

Mapping

A common requirement is to map the rows of a ResultSet to an object. There are two main options: explicit mapping and automap.

Explicit mapping

Using get you can map the ResultSet as you wish:

db.select("select name, score from person")
  .get( rs -> new Person(rs.getString(1), rs.getInt(2)));

Automap

automap does more for you than explicit mapping. You can provide just an annotated interface and objects will be created that implement that interface and types will be converted for you (See Auto mappings section below).

There is some reflection overhead with using auto mapping. Use your own benchmarks to determine if its important to you (the reflection overhead may not be significant compared to the network latencies involved in database calls).

The autoMap method maps result set rows to instances of the class you nominate.

If you nominate an interface then dynamic proxies (a java reflection feature) are used to build instances.

If you nominate a concrete class then the columns of the result set are mapped to parameters in the constructor (again using reflection).

Automap using an interface

Create an annotated interface (introduced in rxjava-jdbc 0.5.8):

public interface Person {

    @Column("name")
    String name();

    @Column("score")
    int score();
}

Then run

Observable<Person> persons = db
                 .select("select name, score from person order by name")
                 .autoMap(Person.class);

Easy eh!

An alternative is to annotate the interface with the indexes of the columns in the result set row:

public interface Person {

    @Index(1)
    String name();

    @Index(2)
    int score();
}

Camel cased method names will be converted to underscore by default (since 0.5.11):

public interface Address {

    @Column // maps to address_id 
    int addressId();

    @Column // maps to full_address
    String fullAddress();
}

You can also specify the sql to be run in the annotation:

@Query("select name, score from person order by name")
public interface Person {

    @Column
    String name();

    @Column
    int score();
}

Then run like this:

Observable<Person> persons = db
                 .select().autoMap(Person.class);

Automap using a concrete class

Given this class:

static class Person {
    private final String name;
    private final double score;
    private final Long dateOfBirth;
    private final Long registered;

    Person(String name, Double score, Long dateOfBirth,
            Long registered) {
            ...

Then run

Observable<Person> persons = db
                .select("select name,score,dob,registered from person order by name")
                .autoMap(Person.class);

The main requirement is that the number of columns in the select statement must match the number of columns in a constructor of Person and that the column types can be automatically mapped to the types in the constructor.

Auto mappings

The automatic mappings below of objects are used in the autoMap() method and for typed getAs() calls.

Note that automappings do not occur to primitives so use Long instead of long.

Tuples

Typed tuples can be returned in an Observable:

Tuple2

Tuple2<String, Integer> tuple = db
        .select("select name,score from person where name >? order by name")
        .parameter("ALEX").create()
        .getAs(String.class, Integer.class).last()
        .toBlocking().single();
assertEquals("MARMADUKE", tuple.value1());
assertEquals(25, (int) tuple.value2());

Similarly for Tuple3, Tuple4, Tuple5, Tuple6, Tuple7, and finally

TupleN

TupleN<String> tuple = db
        .select("select name, lower(name) from person order by name")
        .create()
        .getTupleN(String.class).first()
        .toBlocking().single();
assertEquals("FRED", tuple.values().get(0));
assertEquals("fred", tuple.values().get(1));

Returning generated keys

If you insert into a table that say in h2 is of type auto_increment then you don't need to specify a value but you may want to know what value was inserted in the generated key field.

Given a table like this

create table note(
    id bigint auto_increment primary key,
    text varchar(255)
)

This code inserts two rows into the note table and returns the two generated keys:

Observable<Integer> keys = 
    db.update("insert into note(text) values(?)")
      .parameter("hello", "there")
      .returnGeneratedKeys()
      .getAs(Integer.class);

The returnGeneratedKeys method also supports returning multiple keys per row so the builder offers methods just like select to do explicit mapping or auto mapping.

Large objects support

Blob and Clobs are straightforward to handle.

Insert a Clob

Here's how to insert a String value into a Clob (document column below is of type CLOB):

String document = ...
Observable<Integer> count = db
        .update("insert into person_clob(name,document) values(?,?)")
        .parameter("FRED")
        .parameter(Database.toSentinelIfNull(document)).count();

(Note the use of the Database.toSentinelIfNull(String) method to handle the null case correctly)

or using a java.io.Reader:

Reader reader = ...;
Observable<Integer> count = db
        .update("insert into person_clob(name,document) values(?,?)")
        .parameter("FRED")
        .parameter(reader).count();

Insert a Null Clob

This requires either a special call (parameterClob(String)) to identify the parameter as a CLOB:

Observable<Integer> count = db
        .update("insert into person_clob(name,document) values(?,?)")
        .parameter("FRED")
        .parameterClob(null).count();

or use the null Sentinel object for Clobs:

Observable<Integer> count = db
        .update("insert into person_clob(name,document) values(?,?)")
        .parameter("FRED")
        .parameter(Database.NULL_CLOB).count();

or wrap the String parameter with Database.toSentinelIfNull(String) as above in the Insert a Clob section.

Read a Clob

Observable<String> document = db.select("select document from person_clob")
                .getAs(String.class);

or

Observable<Reader> document = db.select("select document from person_clob")
                .getAs(Reader.class);

Insert a Blob

Similarly for Blobs (document column below is of type BLOB):

byte[] bytes = ...
Observable<Integer> count = db
        .update("insert into person_blob(name,document) values(?,?)")
        .parameter("FRED")
        .parameter(Database.toSentinelIfNull(bytes)).count();

Insert a Null Blob

This requires either a special call (parameterBlob(String) to identify the parameter as a CLOB:

Observable<Integer> count = db
        .update("insert into person_blob(name,document) values(?,?)")
        .parameter("FRED")
        .parameterBlob(null).count();

or use the null Sentinel object for Blobs:

Observable<Integer> count = db
        .update("insert into person_clob(name,document) values(?,?)")
        .parameter("FRED")
        .parameter(Database.NULL_BLOB).count();

or wrap the byte[] parameter with Database.toSentinelIfNull(byte[]) as above in the Insert a Blob section.

Read a Blob

Observable<byte[]> document = db.select("select document from person_clob")
                .getAs(byte[].class);

or

Observable<InputStream> document = db.select("select document from person_clob")
                .getAs(InputStream.class);

Compose

Using the Observable.compose() method you can perform multiple queries without breaking method chaining. Observable.compose() requires a Transformer parameter which are available via

Example: 

Observable<Integer> score = Observable
    // parameters for coming update
    .just(4, "FRED")
    // update Fred's score to 4
    .compose(db.update("update person set score=? where name=?")
            //parameters are pushed
            .parameterTransformer())
    // update everyone with score of 4 to 14
    .compose(db.update("update person set score=? where score=?")
            .parameters(14, 4)
            //wait for completion of previous observable
            .dependsOnTransformer())
    // get Fred's score
    .compose(db.select("select score from person where name=?")
            .parameters("FRED")
            //wait for completion of previous observable
            .dependsOnTransformer()
            .getAs(Integer.class));

Note that conditional evaluation of a query is obtained using the parameterTransformer() method (no parameters means no query run) whereas using dependsOnTransformer() just waits for the dependency to complete and ignores how many items the dependency emits.

If the query does not require parameters you can push it an empty list and use the parameterListTransformer() to force execution.

Example:

Observable<Integer> rowsAffected = Observable
    //generate two integers
    .range(1,2)
    //replace the integers with empty observables
    .map(toEmpty())
    //execute the update twice with an empty list
    .compose(db.update("update person set score = score + 1")
            .parameterListTransformer())
    // flatten
    .compose(RxUtil.<Integer> flatten())
    // total the affected records
    .compose(SUM_INTEGER);

Transactions

When you want a statement to participate in a transaction then either it should

Transactions as dependency

Observable<Boolean> begin = db.beginTransaction();
Observable<Integer> updateCount = db
    // set everyones score to 99
    .update("update person set score=?")
    // is within transaction
    .dependsOn(begin)
    // new score
    .parameter(99)
    // execute
    .count();
Observable<Boolean> commit = db.commit(updateCount);
long count = db
    .select("select count(*) from person where score=?")
    // set score
    .parameter(99)
    // depends on
    .dependsOn(commit)
    // return as Long
    .getAs(Long.class)
    // log
    .doOnEach(RxUtil.log())
    // get answer
    .toBlocking().single();
assertEquals(3, count);

onNext Transactions

List<Integer> mins = Observable
    // do 3 times
    .just(11, 12, 13)
    // begin transaction for each item
    .compose(db.beginTransactionOnNext_())
    // update all scores to the item
    .compose(db.update("update person set score=?").parameterTransformer())
    // to empty parameter list
    .map(toEmpty())
    // increase score
    .compose(db.update("update person set score=score + 5").parameterListTransformer())
    //only expect one result so can flatten
    .compose(RxUtil.<Integer>flatten())
    // commit transaction
    .compose(db.commitOnNext_())
    // to empty lists
    .map(toEmpty())
    // return count
    .compose(db.select("select min(score) from person").parameterListTransformer()
            .getAs(Integer.class))
    // list the results
    .toList()
    // block and get
    .toBlocking().single();
assertEquals(Arrays.asList(16, 17, 18), mins);

Note that for each commit* method there is an corresponding rollback method as well.

Asynchronous queries

Unless run within a transaction all queries are synchronous by default. However, if you request an asynchronous version of the database using Database.asynchronous() or if you use asynchronous Transformers then watch out because this means that something like the code below could produce unpredictable results:

Database adb = db.asynchronous();
Observable
    .just(1, 2, 3)
    .compose(adb.update("update person set score = ?")
            .parameterTransformer());

After running this code you have no guarantee that the update person set score=1 ran before the update person set score=2. To run those queries synchronously either use a transaction:

Database adb = db.asynchronous();
Observable
   .just(1, 2, 3)
   .compose(adb.update("update person set score = ?")
           .dependsOn(db.beginTransaction())
           .parameterTransformer())
    .compose(adb.commitOnComplete_());

or use the default version of the Database object that schedules queries using Schedulers.trampoline().

Observable.just(1, 2, 3)
          .compose(db.update("update person set score = ?")
                  .parameterTransformer());

Backpressure

Database.select supports reactive pull backpressure as introduced in RxJava 0.20.0. This means that the pushing of items from the results of a query can be optionally slowed down by the operators downstream to assist in preventing out of memory exceptions or thread starvation.

Logging

Logging is handled by slf4j which bridges to the logging framework of your choice. Add the dependency for your logging framework as a maven dependency and you are sorted. See the test scoped log4j example in rxjava-jdbc/pom.xml.

Database Connection Pools

Include the dependency below:

<dependency>
    <groupId>com.zaxxer</groupId>
    <artifactId>HikariCP-java6</artifactId>
    <version>2.3.2</version>
</dependency>

and you can use a Hikari database connection pool like so:

Database db = Database.builder().url(url).pool(minPoolSize,maxPoolSize).build();

Once finished with a Database that has used a connection pool you should call 

db.close();

This will close the connection pool and release its resources.

Using a custom connection pool

If Hikari doesn't suit you or you have container imposed constraints this is how you can use a different connection pool.

Write an implmentation of the ConnectionProvider interface (two methods, getConnection() and close()) and use it like so:

ConnectionProvider cp = new CustomConnectionProvider();
Database db = Database.builder().connectionProvider(cp).build();

This method could be used to supply a JNDI datasource for example.

Use a single Connection

A Database can be instantiated from a single java.sql.Connection which will be used for all queries in companion with the current thread Scheduler (Schedulers.trampoline()). The connection is wrapped in a ConnectionNonClosing which suppresses close calls so that the connection will still be open for all queries and will remain open after use of the Database object.

Example:

 Database db = Database.from(con);

Fetch Size

The fetch size setting in statements allows to specify how many rows should be fetched from the database at once. In other words, instead of fetching all data in the ResultSet at once, potentially consuming a lot of memory in the heap, the fetch size setting allows to trade time, due to multiple round-trips to the database, in exchange for lower memory consumption.

Example:

db
    .select("select * from person")
    // set fetch size
    .fetchSize(10)
    //
    .autoMap(Person.class)
    // 
    .take(20)
    // log
    .doOnEach(RxUtil.log());

In this case, the JDBC driver will do two round trips, each time fetching 10 rows and transforming each row to an instance of Person.

Note for SQLite Users

rxjava-jdbc does support SQLite. But due to the SQLite architecture there are limitations particularly with write operations (CREATE, INSERT, UPDATE, DELETE). If your application has any write operations, use a single connection. If a source Observable pushes emissions through a series of database read/write operations, always collect emissions and flatten them between each database read/write operation. This will prevent a SQLITE_INTERRUPT exception by never having more than one query open at a time. 

Observable<MyItem> = Observable.just(itemstoInsert)
        .compose(executeInsertsAndGetKeys())
        .toList().concatMap(Observable::from)
        .compose(selectAndAutoMap());