下面是一个使用 Flink DataStream 监控 MySQL 表并将数据以 upsert 方式写入 Kafka 的示例代码:
import org.apache.flink.api.common.serialization.SimpleStringSchema;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.configuration.Configuration;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.source.RichSourceFunction;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer;
import org.apache.flink.streaming.util.serialization.JSONKeyValueDeserializationSchema;
import java.sql.*;
import java.util.HashMap;
import java.util.Map;
public class MySQLTableMonitor {
public static void main(String[] args) throws Exception {
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
// 设置Kafka相关配置
String kafkaBootstrapServers = "localhost:9092";
String kafkaTopic = "my_topic";
// 添加自定义的MySQL监控源
DataStream<Tuple2<String, Map<String, Object>>> mysqlDataStream = env.addSource(new MySQLTableSource());
// 使用upsert模式写入Kafka
mysqlDataStream.addSink(new FlinkKafkaProducer<>(kafkaBootstrapServers,
kafkaTopic,
new JSONKeyValueDeserializationSchema(true),
new SimpleStringSchema()));
env.execute("MySQL Table Monitor");
}
// 自定义MySQL监控源
public static class MySQLTableSource extends RichSourceFunction<Tuple2<String, Map<String, Object>>>> {
private Connection connection;
private Statement statement;
@Override
public void open(Configuration parameters) throws Exception {
super.open(parameters);
// 连接到MySQL数据库
Class.forName("com.mysql.jdbc.Driver");
String url = "jdbc:mysql://localhost:3306/my_database";
String username = "my_user";
String password = "my_password";
connection = DriverManager.getConnection(url, username, password);
// 创建Statement对象
statement = connection.createStatement();
}
@Override
public void run(SourceContext<Tuple2<String, Map<String, Object>>> ctx) throws Exception {
while (true) {
// 查询MySQL表,这里假设要监控的表名是table1和table2
String[] tables = {"table1", "table2"};
for (String table : tables) {
ResultSet resultSet = statement.executeQuery("SELECT * FROM " + table);
ResultSetMetaData metaData = resultSet.getMetaData();
int columnCount = metaData.getColumnCount();
while (resultSet.next()) {
Map<String, Object> rowMap = new HashMap<>();
for (int i = 1; i <= columnCount; i++) {
String columnName = metaData.getColumnLabel(i);
Object value = resultSet.getObject(i);
rowMap.put(columnName, value);
}
ctx.collect(new Tuple2<>(table, rowMap));
}
resultSet.close();
}
Thread.sleep(5000); // 每隔5秒查询一次
}
}
@Override
public void cancel() {
try {
if (statement != null) {
statement.close();
}
if (connection != null) {
connection.close();
}
} catch (SQLException e) {
e.printStackTrace();
}
}
}
}
在代码中,需要修改以下部分:
- 设置
kafkaBootstrapServers
为你的 Kafka 服务器地址。 - 设置
kafkaTopic
为你要写入的 Kafka 主题。 - 修改连接 MySQL 数据库的相关信息:
url
、username
和password
。 - 在
MySQLTableSource
类中的run
方法中,修改要监控的 MySQL 表名。
请注意,该示例代码仅为演示目的,可能需要根据你的具体情况进行进一步的调整和改进。
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