实际应用中, 时间字段最常用的就是Long类型的毫秒时间戳, 难道这个不支持么.
在 2019-09-05 14:06:08，"pengcheng...@bonc.com.cn" <pengcheng...@bonc.com.cn> 写道：
>FLINK 应该不能把输入的eventTime的long类型转成SQL_TIMESTAMP类型
>
>
>发件人： hb
>发送时间： 2019-09-05 14:24
>收件人： user-zh
>主题： Flink 1.9 Blink planner 时间字段问题
>代码里定义了kafka connectorDescriptor , 从kafka读取json格式数据, 生成Table
>schema
>.field("_rowtime", Types.SQL_TIMESTAMP())
>.rowtime(
>new Rowtime()
>.timestampsFromField("eventTime")
>.watermarksPeriodicBounded(1000))
>kafka输入: {"eventTime": 100000, "id":1,"name":"hb"} 会报错,
>
>输入 {"eventTime": "2019-09-02T09:56:16.484Z", "id":1,"name":"hb"} 结果显示正确,
>eventTime 字段怎么不支持数值输入呢.
>
>
>错误提示:
>```
>Caused by: java.lang.Exception: java.io.IOException: Failed to deserialize
>JSON object.
>at
>org.apache.flink.streaming.runtime.tasks.SourceStreamTask$LegacySourceFunctionThread.checkThrowSourceExecutionException(SourceStreamTask.java:212)
>at
>org.apache.flink.streaming.runtime.tasks.SourceStreamTask.performDefaultAction(SourceStreamTask.java:132)
>at org.apache.flink.streaming.runtime.tasks.StreamTask.run(StreamTask.java:298)
>at
>org.apache.flink.streaming.runtime.tasks.StreamTask.invoke(StreamTask.java:403)
>at org.apache.flink.runtime.taskmanager.Task.doRun(Task.java:705)
>at org.apache.flink.runtime.taskmanager.Task.run(Task.java:530)
>at java.lang.Thread.run(Thread.java:748)
>Caused by: java.io.IOException: Failed to deserialize JSON object.
>at
>org.apache.flink.formats.json.JsonRowDeserializationSchema.deserialize(JsonRowDeserializationSchema.java:129)
>at
>org.apache.flink.formats.json.JsonRowDeserializationSchema.deserialize(JsonRowDeserializationSchema.java:72)
>at
>org.apache.flink.streaming.connectors.kafka.internals.KafkaDeserializationSchemaWrapper.deserialize(KafkaDeserializationSchemaWrapper.java:45)
>at
>org.apache.flink.streaming.connectors.kafka.internal.Kafka09Fetcher.runFetchLoop(Kafka09Fetcher.java:146)
>at
>org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumerBase.run(FlinkKafkaConsumerBase.java:715)
>at
>org.apache.flink.streaming.api.operators.StreamSource.run(StreamSource.java:100)
>at
>org.apache.flink.streaming.api.operators.StreamSource.run(StreamSource.java:63)
>at
>org.apache.flink.streaming.runtime.tasks.SourceStreamTask$LegacySourceFunctionThread.run(SourceStreamTask.java:202)
>Caused by: java.time.format.DateTimeParseException: Text '100000' could not be
>parsed at index 0
>at
>java.time.format.DateTimeFormatter.parseResolved0(DateTimeFormatter.java:1949)
>at java.time.format.DateTimeFormatter.parse(DateTimeFormatter.java:1777)
>at
>org.apache.flink.formats.json.JsonRowDeserializationSchema.lambda$createTimestampConverter$1dee6515$1(JsonRowDeserializationSchema.java:334)
>at
>org.apache.flink.formats.json.JsonRowDeserializationSchema.lambda$wrapIntoNullableConverter$d586c97$1(JsonRowDeserializationSchema.java:232)
>at
>org.apache.flink.formats.json.JsonRowDeserializationSchema.convertField(JsonRowDeserializationSchema.java:403)
>at
>org.apache.flink.formats.json.JsonRowDeserializationSchema.lambda$assembleRowConverter$77f7700$1(JsonRowDeserializationSchema.java:382)
>at
>org.apache.flink.formats.json.JsonRowDeserializationSchema.lambda$wrapIntoNullableConverter$d586c97$1(JsonRowDeserializationSchema.java:232)
>at
>org.apache.flink.formats.json.JsonRowDeserializationSchema.deserialize(JsonRowDeserializationSchema.java:127)
>... 7 more
>```
>
>
>
>
>源码:
>```
> val env = StreamExecutionEnvironment.getExecutionEnvironment
> val conf =
> EnvironmentSettings.newInstance().useBlinkPlanner().inStreamingMode().build()
> val tEnv = StreamTableEnvironment.create(env, conf)
> env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime)
>
>
> val kafkaIn = new Kafka()
> .version("0.11")
> .topic("hbtest111")
> .property("bootstrap.servers", "192.168.1.160:19092")
> .property("group.id", "test2")
>
>
> val json = new Json().deriveSchema()
>
>
> val schema = new Schema()
> .field("id", Types.INT())
> .field("name", Types.STRING())
>
>
> schema.field("_proctime", Types.SQL_TIMESTAMP()).proctime()
> schema
> .field("_rowtime", Types.SQL_TIMESTAMP())
> .rowtime(
> new Rowtime()
> .timestampsFromField("eventTime")
> .watermarksPeriodicBounded(1000)
> )
>
>
>
> tEnv.connect(kafkaIn).withFormat(json).withSchema(schema).inAppendMode().registerTableSource("table_from_kafka")
> val t = tEnv.sqlQuery("select * from table_from_kafka")
> t.printSchema()
>
>
> t.toRetractStream[Row].print()
> tEnv.execute("")
>```
