This project's goal is to provide a full asyncronous approach to handle databases.
At the lowest level, the communication with a database is an IO operation. Under the hood, the way to do it would be using a Socket
to connect to the database server and exchanging messages, following the proprietary protocol of the database. The nature of this communication is asynchronous, given the principle of sending/receiving messages.
However, that's not how most of IO APIs behave. They return synchronously, blocking the current Thread. What does it mean? Consider the following code:
import java.io.*;
import java.nio.file.*;
File file = File.createTempFile("file", "txt");
List<String> lines = Files.readAllLines(Paths.get(file.toURI()));
For small files, this code wouldn't be a problem. Now let's assume that file.txt
has more than 20 gbs. Dealing with such a large file, the code will stop at this line, waiting for all the lines to be read. A better approach to solve this problem is necessary.
Future
is an abstraction to deal with asynchronicity without blocking threads. The primary usage for Future
s on the JVM is to perform IO operations. Bringing this idea to the previous example, the code would be something like:
Future<List<String>> lines = Files.readAllLines(Paths.get(file.toURI()));
In simple words, a Future
is the abstraction that allows the code to carry on instead of keep waiting for results, a promise that the expected result will be in place eventually. NDBC is written using Trane.io Future, a High-performance Future implementation for the JVM.
How can be this knowledge about Future
s useful when it comes to deal with the database?
As mentioned before, like most of IO APIs, JDBC is synchronous. Working with JDBC, when a query is executed, the return is a ResultSet
. Even wrapping this code with Future
s is not enough to make it properly asynchronous, JDBC specification is blocking by definition.
NDBC otherwise, was designed to solve this problem.
import io.trane.future.Future;
import io.trane.ndbc.*;
import io.trane.ndbc.postgres.*;
import java.time.Duration;
import java.util.List;
// Create a Config with an Embedded Postgres
Config config = Config.create("io.trane.ndbc.postgres.netty4.DataSourceSupplier", "localhost", 0, "user")
.database("test_schema")
.password("test")
.embedded("io.trane.ndbc.postgres.embedded.EmbeddedSupplier");
// Create a DataSource
DataSource<PreparedStatement, Row> ds = DataSource.fromConfig(config);
// Define a timeout
Duration timeout = Duration.ofSeconds(10);
// Send a query to the db defining a timeout and receiving back a List
List<Row> rows = ds.query("SELECT 1 AS value").get(timeout);
// iterate over awesome strongly typed rows
rows.forEach(row -> System.out.println(row.getLong("value")));
The library binaries are distributed through maven central. Click on the maven central badge for information on how to add the library dependency to your project:
Please refer to the Javadoc for detailed information about the library and its features:
Properties p = new Properties();
p.setProperty("db.dataSourceSupplierClass", "io.trane.ndbc.postgres.netty4.DataSourceSupplier");
p.setProperty("db.host", "localhost");
p.setProperty("db.port", Integer.toString(5432));
p.setProperty("db.user", "user");
p.setProperty("db.password", "5tr0ngP@ssW0rd");
p.setProperty("db.database", "schema");
DataSource<PreparedStatement, Row> ds = DataSource.fromProperties("db", p);
Using the Properties
from previous example:
import java.io.File;
import java.io.FileOutputStream;
File file = File.createTempFile("config", "fromPropertiesFile");
p.store(new FileOutputStream(file), "");
DataSource<PreparedStatement, Row> ds = DataSource.fromPropertiesFile("db", file.getAbsolutePath());
Similar to the first example, but getting the system properties with getProperties
:
Properties p = System.getProperties();
p.setProperty("db.dataSourceSupplierClass", "io.trane.ndbc.postgres.netty4.DataSourceSupplier");
p.setProperty("db.host", "localhost");
p.setProperty("db.port", Integer.toString(0));
p.setProperty("db.user", "user");
p.setProperty("db.password", "5tr0ngP@ssW0rd");
p.setProperty("db.database", "schema");
DataSource<PreparedStatement, Row> ds = DataSource.fromSystemProperties("db");
DataSource<PreparedStatement, Row> ds = DataSource.fromJdbcUrl("jdbc:postgresql://user:5tr0ngP@ssW0rd@localhost:5432/schema");
Property | Expected value |
---|---|
dataSourceSupplierClass (required) |
io.trane.ndbc.postgres.netty4.DataSourceSupplier or io.trane.ndbc.mysql.netty4.DataSourceSupplier |
host (required) |
database host |
port (required) |
database port |
user (required) |
user accessing the database |
password |
password of the user accessing the database |
database |
schema name |
charset |
character encoding. If not informed, the default charset of the JVM will be used |
poolMaxSize |
maximum number of connections in the pool |
poolMaxWaiters |
maximum number of waiters for a connection |
poolValidationIntervalSeconds |
frequency to test connections in the pool |
connectionTimeoutSeconds |
maximum time that a connection can remain idle. After that, the pool can close the connection |
queryTimeoutSeconds |
maximum time to execute a query |
encodingClasses |
|
nioThreads |
|
embedded |
|
ssl |
Let's use the pre-populated table table_1
as an example:
id | description |
---|---|
1 | The Amazing Spiderman |
2 | Batman the Dark Knight |
DataSource<PreparedStatement, Row> ds = DataSource.fromConfig(config);
ds.execute("CREATE TABLE table_1 (id integer, description varchar)").get(timeout);
ds.execute("INSERT INTO table_1 VALUES (1, 'The Amazing Spiderman')").get(timeout);
ds.execute("INSERT INTO table_1 VALUES (2, 'Batman the Dark Knight')").get(timeout);
Future<List<Row>> rows = ds.query("SELECT * from table_1");
PreparedStatement ps = PreparedStatement.create("SELECT * FROM table_1");
Future<List<Row>> rows = ds.query(ps);
PreparedStatement ps = PreparedStatement.create("SELECT * FROM table_1 WHERE id = ?").setInteger(1);
Future<List<Row>> rows = ds.query(ps);
The code to execute actions is similar to the one for queries, the only difference is that instead of using query
, we will use execute
, which always returns a Future<Long>
, with the number of affected rows.
Future<Long> futureInsertedRows = ds.execute("INSERT INTO table_1 VALUES (10, 'Avengers Assemble!')")
Future<Long> futureUpdatedRows = ds.execute("UPDATE table_1 SET description = 'Go Go Power Rangers'")
Future<Long> futureDeletedRows = ds.execute("DELETE FROM table_1 WHERE id = 10")
PreparedStatement ps = PreparedStatement.create("DELETE FROM table_1");
Future<Long> affectedRows = ds.execute(ps);
PreparedStatement ps = PreparedStatement.create("DELETE FROM table_1 WHERE id = ?").setInteger(2);
Future<Long> affectedRows = ds.execute(ps);
PreparedStatement ps = PreparedStatement.create("DELETE FROM table_1 WHERE id = ?").setInteger(2);
Future<Long> affectedRows = ds.transactional(() -> ds.execute(ps));
Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms. See CODE_OF_CONDUCT.md for details.
See the LICENSE file for details.