在Flink中读取HBase数据可以通过Flink的Table API和Flink的DataStream API来实现。
使用Table API:
- 首先,需要添加HBase Connector的依赖:
org.apache.flink flink-connector-hbase_2.11 ${flink.version}
- 然后,在Flink的TableEnvironment中注册HBase表:
TableConfig tableConfig = new TableConfig(); tableConfig.setConnector("hbase"); tableConfig.getConfiguration().put("connector.table-name", "your_hbase_table_name"); tableConfig.getConfiguration().put("connector.zookeeper.quorum", "zookeeper_host"); tableConfig.getConfiguration().put("connector.zookeeper.znode.parent", "/hbase"); tableConfig.getConfiguration().put("connector.write.buffer-flush.max-size", "1mb"); EnvironmentSettings settings = EnvironmentSettings.newInstance().useBlinkPlanner().inStreamingMode().build(); TableEnvironment tableEnv = TableEnvironment.create(settings); tableEnv.getConfig().setTableConfig(tableConfig); tableEnv.executeSql("CREATE TABLE hbase_table (\n" + " rowkey STRING,\n" + " cf1 ROW,\n" + " cf2 ROW \n" + ") WITH (\n" + " 'connector' = 'hbase'\n" + ")");
- 最后,通过Table API查询HBase表数据:
Table result = tableEnv.sqlQuery("SELECT * FROM hbase_table"); tableEnv.toRetractStream(result, Row.class).print();
使用DataStream API:
- 首先,创建一个HBase数据源:
final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment(); DeserializationSchemadeserializer = new HBaseRowDeserializationSchema("your_hbase_table_name"); HBaseInputFormat hbaseInputFormat = new HBaseInputFormat("zookeeper_host", "your_hbase_table_name", new String[]{"cf1", "cf2"}, new TypeInformation[]{Types.STRING, Types.INT, Types.DOUBLE}); DataStream
hbaseData = https://www.yisu.com/ask/env.createInput(hbaseInputFormat, deserializer);>
- 然后,对HBase数据进行处理:
hbaseData.map(new MapFunction() { @Override public String map(Row value) throws Exception { return value.toString(); } }).print();
以上是通过Flink读取HBase数据的基本步骤,具体的操作可以根据实际需求进行调整和优化。