Flink :行时间属性不得位于常规连接的输入行中

使用 flink SQL API，我想将多个表连接在一起，并在时间窗口内进行一些计算。我有 3 个来自 CSV 文件的表格，一个来自 Kafka。在 Kafka 表中，我有一个字段timestampMs，我想将其用于我的时间窗口操作。

为此，我做了以下代码：

reamExecutionEnvironment env = ... ;
StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env);
TableSource table1 = CsvTableSource.builder()
        .path("path/to/file1.csv")
        .ignoreFirstLine()
        .fieldDelimiter(",")
        .field("id1", Types.STRING)
        .field("someInfo1", Types.FLOAT)
        .build();
TableSource table2 = CsvTableSource.builder()
        .path("path/to/file2.csv")
        .ignoreFirstLine()
        .fieldDelimiter(",")
        .field("id2", Types.STRING)
        .field("someInfo2", Types.STRING)
        .build();
TableSource table3 = CsvTableSource.builder()
        .path("path/to/file3.csv")
        .ignoreFirstLine()
        .fieldDelimiter(",")
        .field("id2", Types.STRING)
        .field("id1", Types.STRING)
        .field("someInfo3", Types.FLOAT)
        .build();
tableEnv.registerTableSource("Table1",table1);
tableEnv.registerTableSource("Table2",table2);
tableEnv.registerTableSource("Table3",table3);

Schema schemaExt = new Schema().schema(SOME_SCHEMA);
schemaExt = schemaExt.field("rowtime", Types.SQL_TIMESTAMP).rowtime(new Rowtime().timestampsFromField("timestampMs").watermarksPeriodicBounded(40000));
tableEnv.connect(new Kafka()
        .version("universal")
        .topic(MY_TOPIC)
        .properties(MY_PROPERTIES)
        .sinkPartitionerRoundRobin()
)
            .withFormat(...)
            .withSchema(schemaExt)
            .inAppendMode()
            .registerTableSource("KafkaInput");
Table joined = tableEnv.sqlQuery("SELECT * FROM table1 " +
        "join table3 on table1.id2 = table3.id2 " +
        "join table2 on table3.id1 = table2.id1 " +
        "join KafkaInput on table3.id2 = KafkaInput.id2");
tableEnv.registerTable("Joined", joined);
int windowWidth = 5;
int frequency = 2;
Table processed = tableEnv.sqlQuery("SELECT id1 FROM Joined " +
        "GROUP BY id1, HOP(rowtime, INTERVAL '10' SECOND, INTERVAL '30' SECOND)");

Sink s = createSink(this.esEndpoint, this.esPattern, this.schemaHandler.getSchemaStr());

tableEnv.registerTableSink("MySink", ...);
processed.insertInto("MySink");
env.execute();

但是当我运行它时，我有以下错误：

Exception in thread "main" org.apache.flink.table.api.TableException: Cannot generate a valid execution plan for the given query: 
Rowtime attributes must not be in the input rows of a regular join. As a workaround you can cast the time attributes of input tables to TIMESTAMP before.

但我不明白解决方法提示部分。如何创建时间属性并在联接表后进行一些窗口计算。

---编辑---

在上面的代码中，我替换了以下行：

Table joined = tableEnv.sqlQuery("SELECT * FROM table1 " +
        "join table3 on table1.id2 = table3.id2 " +
        "join table2 on table3.id1 = table2.id1 " +
        "join KafkaInput on table3.id2 = KafkaInput.id2");
tableEnv.registerTable("Joined", joined);

由：

Table staticJoined = tableEnv.sqlQuery("SELECT *, TIMESTAMP('1970-01-01 00:00:00') as rowtime FROM table1 " +
        "join table3 on table1.id2 = table3.id2 " +
        "join table2 on table3.id1 = table2.id1 ");
TemporalTableFunction temporalFunction = staticJoined.createTemporalTableFunction( "rowtime" , "id2");
tableEnv.registerFunction("CSVData", temporalFunction);
tableEnv.registerTable("Joined",
    tableEnv.sqlQuery("SELECT * FROM KafkaInput, LATERAL TABLE (CSVData(KafkaInput.rowtime)) as Statics WHERE Statics.id2 = KafkaInput.id2")
);

但是我得到一个错误时间表函数：

Exception in thread "main" java.lang.AssertionError: Cannot add expression of different type to set:
set type is RecordType(BIGINT genTimestampMs, BIGINT timestampMs, VARCHAR(65536) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary" streamId, VARCHAR(65536) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary" sdkConfId, VARCHAR(65536) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary" sdkId, FLOAT density, FLOAT count, FLOAT surface, TIMESTAMP(3) NOT NULL rowtime, VARCHAR(65536) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary" streamId0, VARCHAR(65536) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary" cameraName, VARCHAR(65536) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary" streamId00, VARCHAR(65536) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary" areaId, FLOAT coefficient, VARCHAR(65536) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary" areaId0, FLOAT thresholdLow, FLOAT thresholdMedium, VARCHAR(65536) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary" areaId1, VARCHAR(65536) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary" name, TIMESTAMP(3) rowtime0, VARCHAR(65536) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary" StationName) NOT NULL
expression type is RecordType(BIGINT genTimestampMs, BIGINT timestampMs, VARCHAR(65536) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary" streamId, VARCHAR(65536) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary" sdkConfId, VARCHAR(65536) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary" sdkId, FLOAT density, FLOAT count, FLOAT surface, TIMESTAMP(3) NOT NULL rowtime, VARCHAR(65536) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary" streamId0, VARCHAR(65536) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary" cameraName, VARCHAR(65536) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary" streamId00, VARCHAR(65536) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary" areaId, FLOAT coefficient, VARCHAR(65536) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary" areaId0, FLOAT thresholdLow, FLOAT thresholdMedium, VARCHAR(65536) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary" areaId1, VARCHAR(65536) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary" name, TIMESTAMP(0) NOT NULL rowtime0, VARCHAR(65536) CHARACTER SET "UTF-16LE" COLLATE "ISO-8859-1$en_US$primary" StationName) NOT NULL
set is rel#26:LogicalCorrelate.NONE(left=HepRelVertex#24,right=HepRelVertex#25,correlation=$cor0,joinType=inner,requiredColumns={8})
expression is LogicalTemporalTableJoin#32

其中"集合类型">

和"表达式类型"之间的两个字段不匹配。 TIMESTAMP(3) rowtime0和TIMESTAMP(0) NOT NULL rowtime0

问题是我没有名为 rowtime0 的字段。它看起来像是一个内部字段。我真的不明白这里发生了什么

查询定义常规联接，即没有临时联接约束的联接。由于 Flink 将所有表视为动态表(即假设它们将来可能会更改(，因此没有时间限制的常规连接不能保证行(大致(按时间戳顺序发出。但是，时间属性需要时间戳顺序，以确保可以在不完全具体化流的情况下生成后续操作(例如窗口聚合(。因此，Flink 不允许时间属性作为不保留时间顺序的常规连接的输入(因此也不允许输出(。

如果 Flink 知道 CSV 文件中的表是固定的而不是动态的，那么问题就不会存在。但是，尚不支持这种推理。

解决方法是将 CSV 表建模为时态表(不变(，并将其与 Kafka 表联接。

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