【大数据面试题】33 手写一个 Flink SQL 样例

一步一个脚印，一天一道大数据面试题
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我们来看看 Flink SQL大概流程和样例：

流程：

1.创建流处理环境 StreamExecutionEnvironment env

2.创建表环境 StreamTableEnvironment.create(env);

3.创建 source表，sink 表

4.用 table API 编写查询 SQL（返回 Table 对象）

5.执行 sink executeInsert("sink")

代码样例：

java 复制代码

import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.api.EnvironmentSettings;
import org.apache.flink.table.api.Table;
import org.apache.flink.table.api.TableEnvironment;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;

import static org.apache.flink.table.api.Expressions.$;

public class SqlDemo2 {
    public static void main(String[] args) {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        // 1.创建表环境
        // 1.1 方法 1
//        EnvironmentSettings settings = EnvironmentSettings.newInstance()
//                .inStreamingMode()
//                .build();
//        TableEnvironment tableEnv = TableEnvironment.create(settings);

        // 1.2 方法 2
        StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env);

        // 创建表
        // 用 datagen 生成随机数据作为 source
        tableEnv.executeSql("CREATE TABLE source (\n" +
                "    id INT\n" +
                "    ,ts BIGINT\n" +
                "    ,vc INT\n" +
                ") WITH (\n" +
                "    'connector' = 'datagen'\n" +
                "    ,'rows-per-second'='1'\n" +
                "    ,'fields.id.kind'='random'\n" +
                "    ,'fields.id.min'='1'\n" +
                "    ,'fields.id.max'='10'\n" +
                "    ,'fields.ts.kind'='sequence'\n" +
                "    ,'fields.ts.min'='1'\n" +
                "    ,'fields.ts.max'='1000000'\n" +
                "    ,'fields.vc.kind'='random'\n" +
                "    ,'fields.vc.min'='1'\n" +
                "    ,'fields.vc.max'='100'\n" +
                ");\n");

        tableEnv.executeSql("CREATE TABLE sink(\n" +
                "    id INT,\n" +
                "    sumVC INT,\n" +
                ") WITH (\n" +
                "'connector'='print'\n" +
                ");\n");

        // 执行查询
        Table source = tableEnv.from("source");
        Table select = source.where($("id").isGreater(5))
                .groupBy($("id"))
                .aggregate($("vc").sum().as("sumVC"))
                .select($("id"), $("sumVC"));

        // 执行 sink
        select.executeInsert("sink");

    }
}

运行截图：

我是近未来，祝你变得更强！