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java - 如何定义具有行时间属性的 apache flink 表

问题描述

我有 json 行作为我的数据，我想用它创建一个表。

StreamTableEnvironment fsTableEnv = StreamTableEnvironment.create(streamExecutionEnvironment, fsSettings);
String allEventsTable = "allEventsTable";
        fsTableEnv.connect(new Kafka()
                            .version("0.11")
                            .topic("events")
                            .property("bootstrap.servers", "localhost:9092")
                            .property("group.id", "dummyquery").startFromLatest())
                .withSchema(new Schema()
                    .field("rule_id", Types.INT)
                    .field("sourceAddress", Types.STRING)
                    .field("deviceProduct", Types.STRING)
                    .field("destHost", Types.STRING)
                    .field("extra", Types.STRING)
                    .field("rowtime", Types.SQL_TIMESTAMP)
                        .rowtime(new Rowtime().timestampsFromField("rowtime").watermarksPeriodicBounded(2000))

                )
                .withFormat(new Json().failOnMissingField(false).deriveSchema())
                .inAppendMode()
                .registerTableSource(allEventsTable);

         Table result = fsTableEnv.sqlQuery("select * from allEventsTable where sourceAddress='12345431'");

        DataStream alert = fsTableEnv.toAppendStream(result, Row.class);
        alert.print();

但是，在运行作业时出现错误

Exception in thread "main" org.apache.flink.table.api.ValidationException: Field 'rowtime' could not be resolved by the field mapping.
    at org.apache.flink.table.sources.TableSourceValidation.resolveField(TableSourceValidation.java:245)
    at org.apache.flink.table.sources.TableSourceValidation.lambda$validateTimestampExtractorArguments$6(TableSourceValidation.java:202)
    at java.util.stream.ReferencePipeline$3$1.accept(ReferencePipeline.java:193)
    at java.util.Spliterators$ArraySpliterator.forEachRemaining(Spliterators.java:948)
    at java.util.stream.AbstractPipeline.copyInto(AbstractPipeline.java:481)
    at java.util.stream.AbstractPipeline.wrapAndCopyInto(AbstractPipeline.java:471)
    at java.util.stream.AbstractPipeline.evaluate(AbstractPipeline.java:545)
    at java.util.stream.AbstractPipeline.evaluateToArrayNode(AbstractPipeline.java:260)
    at java.util.stream.ReferencePipeline.toArray(ReferencePipeline.java:438)

附言。我正在使用 flink 1.9

我放入kafka主题事件的json数据就像

{"rule_id":"", "rowtime":"2020-07-23 13:10:13","sourceAddress":"12345433","deviceProduct":"234r5t", "destHost":"876543", "extra":"dummy"}

标签： javaapache-flinkflink-streamingflink-sql

解决方案

恐怕这是一个错误。我创建了https://issues.apache.org/jira/browse/FLINK-15801来跟踪它。

如果您更改行时间定义中的字段名称之一，您应该能够解决它。更改逻辑字段的名称：

.field("timeAttribute", Types.SQL_TIMESTAMP)
    .rowtime(new Rowtime().timestampsFromField("rowtime").watermarksPeriodicBounded(2000))

或起源的物理场：

.field("rowtime", Types.SQL_TIMESTAMP)
    .rowtime(new Rowtime().timestampsFromField("timestamp").watermarksPeriodicBounded(2000))

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