开发一个flink消费kafka并存储到hbase的代码

以下是一个使用Apache Flink消费Kafka并将数据存储到HBase的示例代码：

import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.api.common.serialization.SimpleStringSchema;
import org.apache.flink.api.java.utils.ParameterTool;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.hbase.HBaseConfiguration;
import org.apache.hadoop.hbase.TableName;
import org.apache.hadoop.hbase.client.Connection;
import org.apache.hadoop.hbase.client.ConnectionFactory;
import org.apache.hadoop.hbase.client.Put;
import org.apache.hadoop.hbase.client.Table;
import org.apache.hadoop.hbase.util.Bytes;

import java.util.Properties;

public class KafkaToHBase {

    public static void main(String[] args) throws Exception {

        // 获取命令行参数
        final ParameterTool parameterTool = ParameterTool.fromArgs(args);

        // 设置运行环境
        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(1);

        // 设置Kafka消费者属性
        Properties props = new Properties();
        props.setProperty("bootstrap.servers", parameterTool.get("bootstrap.servers"));
        props.setProperty("group.id", parameterTool.get("group.id"));

        // 创建Kafka消费者
        FlinkKafkaConsumer<String> kafkaConsumer = new FlinkKafkaConsumer<>(
                parameterTool.get("topic"),
                new SimpleStringSchema(),
                props);

        // 从最新的数据开始消费
        kafkaConsumer.setStartFromLatest();

        // 从Kafka中读取数据
        DataStream<String> kafkaStream = env.addSource(kafkaConsumer);

        // 将数据写入HBase
        kafkaStream.map(new MapFunction<String, Put>() {
            @Override
            public Put map(String value) throws Exception {
                // 解析数据
                String[] fields = value.split(",");

                // 创建Put对象
                Put put = new Put(Bytes.toBytes(fields[0])); // rowkey

                // 添加列族和列
                put.addColumn(Bytes.toBytes("cf"), Bytes.toBytes("id"), Bytes.toBytes(fields[0]));
                put.addColumn(Bytes.toBytes("cf"), Bytes.toBytes("name"), Bytes.toBytes(fields[1]));
                put.addColumn(Bytes.toBytes("cf"), Bytes.toBytes("age"), Bytes.toBytes(fields[2]));

                return put;
            }
        }).addSink(new HBaseSink(parameterTool.get("hbase.table")));

        // 执行任务
        env.execute("KafkaToHBase");
    }

    /**
     * HBase Sink
     */
    public static class HBaseSink extends org.apache.flink.streaming.api.functions.sink.RichSinkFunction<Put> {

        private final String tableName;

        private transient Connection connection;
        private transient Table table;

        public HBaseSink(String tableName) {
            this.tableName = tableName;
        }

        @Override
        public void open(org.apache.flink.configuration.Configuration parameters) throws Exception {
            // 创建HBase连接
            Configuration config = HBaseConfiguration.create();
            config.set("hbase.zookeeper.quorum", "localhost"); // HBase的ZooKeeper地址
            config.set("hbase.zookeeper.property.clientPort", "2181"); // ZooKeeper端口
            config.set("hbase.client.write.buffer", "1000"); // 批量写入缓存大小

            connection = ConnectionFactory.createConnection(config);

            // 获取表对象
            table = connection.getTable(TableName.valueOf(tableName));
        }

        @Override
        public void invoke(Put put, Context context) throws Exception {
            // 将数据写入HBase
            table.put(put);
        }

        @Override
        public void close() throws Exception {
            // 关闭连接和表对象
            if (table != null) {
                table.close();
            }

            if (connection != null) {
                connection.close();
            }
        }
    }
}

在这个示例中，我们从Kafka中读取数据，然后使用`MapFunction`将数据转换为HBase的`Put`对象，并使用`HBaseSink`将数据写入HBase。在`HBaseSink`中，我们使用HBase的Java API创建连接和表对象，并在`invoke`方法中将数据写入HBase。最后，在`close`方法中关闭连接和表对象。