ShardingSphere does not provide support for driverClassName of com.facebook.presto.jdbc.PrestoDriver by default.
ShardingSphere’s support for Presto JDBC Driver is in an optional module.
To use a jdbcUrl like jdbc:presto://localhost:8080/iceberg/demo_ds_0 for the data node in the ShardingSphere configuration file,
Possible Maven dependencies are as follows,
<dependencies>
<dependency>
<groupId>org.apache.shardingsphere</groupId>
<artifactId>shardingsphere-jdbc</artifactId>
<version>${shardingsphere.version}</version>
</dependency>
<dependency>
<groupId>org.apache.shardingsphere</groupId>
<artifactId>shardingsphere-parser-sql-presto</artifactId>
<version>${shardingsphere.version}</version>
</dependency>
<dependency>
<groupId>com.facebook.presto</groupId>
<artifactId>presto-jdbc</artifactId>
<version>0.292</version>
</dependency>
</dependencies>
Write a Docker Compose file to start Presto. This will start a Presto node that is both a coordinator and a worker node, and configure the Iceberg Connector for the node. In addition, this Iceberg Connector will start a Hive Metastore Server using a local file system directory.
services:
presto:
image: prestodb/presto:0.292
ports:
- "8080:8080"
volumes:
- ./iceberg.properties:/opt/presto-server/etc/catalog/iceberg.properties
The same folder contains the file iceberg.properties, the contents are as follows,
connector.name=iceberg
iceberg.catalog.type=hive
hive.metastore=file
hive.metastore.catalog.dir=file:/home/iceberg_data
Use third-party tools to create business-related schemas, databases, and tables in Presto. Taking DBeaver Community as an example, if you use Ubuntu 24.04, you can quickly install it through Snapcraft.
sudo apt update && sudo apt upgrade -y
sudo snap install dbeaver-ce
snap run dbeaver-ce
In DBeaver Community, use jdbcUrl of jdbc:presto://localhost:8080/iceberg, username of test to connect to Presto, and leave password blank.
Execute the following SQL,
-- noinspection SqlNoDataSourceInspectionForFile
CREATE SCHEMA iceberg.demo_ds_0;
CREATE SCHEMA iceberg.demo_ds_1;
CREATE SCHEMA iceberg.demo_ds_2;
Use the jdbcUrl of jdbc:presto://localhost:8080/iceberg/demo_ds_0,
jdbc:presto://localhost:8080/iceberg/demo_ds_1 and jdbc:presto://localhost:8080/iceberg/demo_ds_2 to connect to Presto and execute the following SQL,
-- noinspection SqlNoDataSourceInspectionForFile
CREATE TABLE IF NOT EXISTS t_order (
order_id BIGINT NOT NULL,
order_type INTEGER,
user_id INTEGER NOT NULL,
address_id BIGINT NOT NULL,
status VARCHAR(50)
);
truncate table t_order;
After the business project introduces the dependencies involved in Prerequisites,
write the ShardingSphere data source configuration file demo.yaml on the classpath of the business project.
dataSources:
ds_0:
dataSourceClassName: com.zaxxer.hikari.HikariDataSource
driverClassName: com.facebook.presto.jdbc.PrestoDriver
jdbcUrl: jdbc:presto://localhost:8080/iceberg/demo_ds_0
username: test
ds_1:
dataSourceClassName: com.zaxxer.hikari.HikariDataSource
driverClassName: com.facebook.presto.jdbc.PrestoDriver
jdbcUrl: jdbc:presto://localhost:8080/iceberg/demo_ds_1
username: test
ds_2:
dataSourceClassName: com.zaxxer.hikari.HikariDataSource
driverClassName: com.facebook.presto.jdbc.PrestoDriver
jdbcUrl: jdbc:presto://localhost:8080/iceberg/demo_ds_2
username: test
rules:
- !SHARDING
tables:
t_order:
actualDataNodes: <LITERAL>ds_0.t_order, ds_1.t_order, ds_2.t_order
keyGenerateStrategy:
column: order_id
keyGeneratorName: snowflake
defaultDatabaseStrategy:
standard:
shardingColumn: user_id
shardingAlgorithmName: inline
shardingAlgorithms:
inline:
type: INLINE
props:
algorithm-expression: ds_${user_id % 2}
keyGenerators:
snowflake:
type: SNOWFLAKE
Create a ShardingSphere data source to enjoy integration,
import com.zaxxer.hikari.HikariConfig;
import com.zaxxer.hikari.HikariDataSource;
import java.sql.Connection;
import java.sql.SQLException;
import java.sql.Statement;
public class ExampleUtils {
void test() throws SQLException {
HikariConfig config = new HikariConfig();
config.setJdbcUrl("jdbc:shardingsphere:classpath:demo.yaml");
config.setDriverClassName("org.apache.shardingsphere.driver.ShardingSphereDriver");
try (HikariDataSource dataSource = new HikariDataSource(config);
Connection connection = dataSource.getConnection();
Statement statement = connection.createStatement()) {
statement.execute("INSERT INTO t_order (user_id, order_type, address_id, status) VALUES (1, 1, 1, 'INSERT_TEST')");
statement.executeQuery("SELECT * FROM t_order");
statement.execute("DELETE FROM t_order WHERE user_id=1");
statement.execute("DROP TABLE IF EXISTS t_order");
}
}
}
ShardingSphere JDBC DataSource does not yet support the execution of Presto’s create table and truncate table statements.
Presto does not support local transactions, XA transactions, or Seata’s AT mode transactions at the ShardingSphere integration level.
There are known issues on the ShardingSphere side for Presto’s local transactions at the ShardingSphere integration level.
Affected by https://github.com/prestodb/presto/issues/23226 , there are known issues with the health check of the Presto Memory connector, developers should not connect to the Presto Memory connector in the ShardingSphere configuration file.