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flink-jdbc-driver

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# Installation Guide

1. Get the code

git clone https://github.com/ververica/flink-jdbc-driver

Downloads the entire project code from GitHub to your computer.

cd flink-jdbc-driver

Moves into the project folder you just downloaded.

2. Maven (Java)

Medium Recommended

Prerequisites

Git Needed to download the project code from GitHub.
JDK (Java) Required to build and run Java projects.
Maven The build tool used for the mvn command.

mvn clean install

Installs dependencies and builds the project using Maven.

✅ A BUILD SUCCESS message means it worked. The output is created under target/.

// repository documentation

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# Flink JDBC Driver

Flink JDBC driver is a Java library for accessing and manipulating [Apache Flink](https://flink.apache.org/) clusters by connecting to a [Flink SQL gateway](https://github.com/ververica/flink-sql-gateway) as the JDBC server.

This project is at an early stage. Feel free to file an issue if you meet any problems or have any suggestions.

# Usage

Before using Flink JDBC driver, you need to start a [Flink SQL gateway](https://github.com/ververica/flink-sql-gateway) as the JDBC server and binds it with your Flink cluster. We now assume that you have a gateway started and connected to a running Flink cluster.

## Use with a JDBC Tool
### Use with Beeline

Beeline is the command line tool for accessing [Apache Hive](https://hive.apache.org/), but it also supports general JDBC drivers. To install Hive and beeline, see [Hive documentation](https://cwiki.apache.org/confluence/display/Hive/GettingStarted#GettingStarted-InstallationandConfiguration).

1. Download flink-jdbc-driver-(VERSION).jar from the [download page](https://github.com/ververica/flink-jdbc-driver/releases) and add it to `$HIVE_HOME/lib`.
2. Run beeline and connect to a Flink SQL gateway. You can specify the planner (`blink` or `old`) in the query parameter of the url. As Flink SQL gateway currently ignores user names and passwords, just leave them empty.
    ```
    beeline> !connect jdbc:flink://localhost:8083?planner=blink
    ```
3. Execute any statement you want.

**Sample Commands**
```
Beeline version 2.2.0 by Apache Hive
beeline> !connect jdbc:flink://localhost:8083?planner=blink
Connecting to jdbc:flink://localhost:8083?planner=blink
Enter username for jdbc:flink://localhost:8083?planner=blink: 
Enter password for jdbc:flink://localhost:8083?planner=blink: 
Connected to: Apache Flink (version 1.10.0)
Driver: Flink Driver (version 0.1)
Transaction isolation: TRANSACTION_REPEATABLE_READ
0: jdbc:flink://localhost:8083> CREATE TABLE T(
. . . . . . . . . . . . . . . >   a INT,
. . . . . . . . . . . . . . . >   b VARCHAR(10)
. . . . . . . . . . . . . . . > ) WITH (
. . . . . . . . . . . . . . . >   'connector.type' = 'filesystem',
. . . . . . . . . . . . . . . >   'connector.path' = 'file:///tmp/T.csv',
. . . . . . . . . . . . . . . >   'format.type' = 'csv',
. . . . . . . . . . . . . . . >   'format.derive-schema' = 'true'
. . . . . . . . . . . . . . . > );
No rows affected (0.158 seconds)
0: jdbc:flink://localhost:8083> INSERT INTO T VALUES (1, 'Hi'), (2, 'Hello');
No rows affected (4.747 seconds)
0: jdbc:flink://localhost:8083> SELECT * FROM T;
+----+--------+--+
| a  |   b    |
+----+--------+--+
| 1  | Hi     |
| 2  | Hello  |
+----+--------+--+
2 rows selected (0.994 seconds)
0: jdbc:flink://localhost:8083> 
```

### Use with Tableau
[Tableau](https://www.tableau.com/) is an interactive data visualization software. It supports *Other Database (JDBC)* connection from version 2018.3. You'll need Tableau with version >= 2018.3 to use Flink JDBC driver. For general usage of *Other Database (JDBC)* in Tableau, see [Tableau documentation](https://help.tableau.com/current/pro/desktop/en-us/examples_otherdatabases_jdbc.htm).

1. Download flink-jdbc-driver-(VERSION).jar from the [download page](https://github.com/ververica/flink-jdbc-driver/releases) and add it to Tableau driver path.
    * Windows: `C:\Program Files\Tableau\Drivers`
    * Mac: `~/Library/Tableau/Drivers`
    * Linux: `/opt/tableau/tableau_driver/jdbc`
2. Select *Other Database (JDBC)* under *Connect* and fill in the url of Flink SQL gateway. You can specify the planner (`blink` or `old`) in the query parameter of the url. Select *SQL92* dialect and leave user name and password empty.
3. Hit *Login* button and use Tableau as usual.

### Use with other JDBC Tools
Flink JDBC driver is a library for accessing Flink clusters through the JDBC API. Any tool supporting JDBC API can be used with Flink JDBC driver and [Flink SQL gateway](https://github.com/ververica/flink-sql-gateway). See the documentation of your desired tool on how to use a JDBC driver.

## Use with Java

Flink JDBC driver is a library for accessing Flink clusters through the JDBC API. For the general usage of JDBC in Java, see [JDBC tutorial](https://docs.oracle.com/javase/tutorial/jdbc/index.html) or [Oracle JDBC documentation](https://www.oracle.com/technetwork/java/javase/tech/index-jsp-136101.html).

1. Download flink-jdbc-driver-(VERSION).jar from the [download page](https://github.com/ververica/flink-jdbc-driver/releases) and add it to your classpath.
2. Connect to a Flink SQL gateway in your Java code. You can specify the planner (`blink` or `old`) in the query parameter of the url.
3. Execute any statement you want.

**Sample.java**
```java
import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.ResultSet;
import java.sql.Statement;

public class Sample {
	public static void main(String[] args) throws Exception {
		Connection connection = DriverManager.getConnection("jdbc:flink://localhost:8083?planner=blink");
		Statement statement = connection.createStatement();

statement.executeUpdate("CREATE TABLE T(\n" +
			"  a INT,\n" +
			"  b VARCHAR(10)\n" +
			") WITH (\n" +
			"  'connector.type' = 'filesystem',\n" +
			"  'connector.path' = 'file:///tmp/T.csv',\n" +
			"  'format.type' = 'csv',\n" +
			"  'format.derive-schema' = 'true'\n" +
			")");
		statement.executeUpdate("INSERT INTO T VALUES (1, 'Hi'), (2, 'Hello')");
		ResultSet rs = statement.executeQuery("SELECT * FROM T");
		while (rs.next()) {
			System.out.println(rs.getInt(1) + ", " + rs.getString(2));
		}

statement.close();
		connection.close();
	}
}
```

**Output**
```
1, Hi
2, Hello
```