public class OverWindowTableApiTest {     public static void main(String[] args) throws Exception {         StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();         env.setParallelism(1);         StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env);          DataStreamSource streamSource = env.socketTextStream("hadoop102", 7777);         SingleOutputStreamOperator map = streamSource.map(new MapFunction() {             @Override             public WaterSensor map(String value) throws Exception {                 String[] splits = value.split(",");                  WaterSensor waterSensor = new WaterSensor(splits[0], Long.valueOf(splits[1]), Integer.valueOf(splits[2]));                 return waterSensor;             }         });           // 流转表（指定表结构）         Schema schema = Schema.newBuilder()                 .column("id", "STRING")                 .column("ts", "BIGINT")                 .column("vc", "INT")                 .columnByExpression("pt" , "PROCTIME()")                 .columnByExpression("et", "TO_TIMESTAMP_LTZ(ts, 3)")                 //.watermark("et" , "source_watermark()") // 沿用流中的水位线                 .watermark("et" , "et - INTERVAL '1' SECOND ") // 重新定义水位线                 .build();         Table table = tableEnv.fromDataStream(map, schema);          // API式开窗         OverWindow w1 = Over.partitionBy($("id")).orderBy($("pt")).preceding(UNBOUNDED_ROW).following(CURRENT_ROW).as("w");          table.window(w1)                 .select(                     $("id"), $("ts"), $("vc"), $("et"), $("vc").sum().over($("w")).as("sum_vc")         ).execute().print();          env.execute();     } }

再次运行

成功！