Hi Jark,
The matrix I see is SQL cast. If we need bring another conversion matrix
that is different from SQL cast, I don't understand the benefits. It makes
me difficult to understand.
And It seems bad to change the timestamp of different time zones to the
same value silently.
I have seen a lot of timestamp formats, SQL, ISO, RFC. I can think that a
"timestampFormat" could help them to deal with various formats.
What way do you think can solve all the problems?
Best,
Jingsong Lee
On Wed, Feb 26, 2020 at 10:45 PM Jark Wu <imj...@gmail.com> wrote:
> Hi Jingsong,
>
> I don't think it should follow SQL CAST semantics, because it is out of
> SQL, it happens in connectors which converts users'/external's format into
> SQL types.
> I also doubt "timestampFormat" may not work in some cases, because the
> timestamp format maybe various and mixed in a topic.
>
> Best,
> Jark
>
> On Wed, 26 Feb 2020 at 22:20, Jingsong Li <jingsongl...@gmail.com> wrote:
>
>> Thanks all for your discussion.
>>
>> Hi Dawid,
>>
>> +1 to apply the logic of parsing a SQL timestamp literal.
>>
>> I don't fully understand the matrix your list. Should this be the
>> semantics of SQL cast?
>> Do you mean this is implicit cast in JSON parser?
>> I doubt that because these implicit casts are not support
>> in LogicalTypeCasts. And it is not so good to understand when it occur
>> silently.
>>
>> How about add "timestampFormat" property to JSON parser? Its default
>> value is SQL timestamp literal format. And user can configure this.
>>
>> Best,
>> Jingsong Lee
>>
>> On Wed, Feb 26, 2020 at 6:39 PM Jark Wu <imj...@gmail.com> wrote:
>>
>>> Hi Dawid,
>>>
>>> I agree with you. If we want to loosen the format constraint, the
>>> important piece is the conversion matrix.
>>>
>>> The conversion matrix you listed makes sense to me. From my
>>> understanding,
>>> there should be 6 combination.
>>> We can add WITHOUT TIMEZONE => WITHOUT TIMEZONE and WITH TIMEZONE => WITH
>>> TIMEZONE to make the matrix complete.
>>> When the community reach an agreement on this, we should write it down on
>>> the documentation and follow the matrix in all text-based formats.
>>>
>>> Regarding to the RFC 3339 compatibility mode switch, it also sounds good
>>> to
>>> me.
>>>
>>> Best,
>>> Jark
>>>
>>> On Wed, 26 Feb 2020 at 17:44, Dawid Wysakowicz <dwysakow...@apache.org>
>>> wrote:
>>>
>>> > Hi all,
>>> >
>>> > @NiYanchun Thank you for reporting this. Yes I think we could improve
>>> the
>>> > behaviour of the JSON format.
>>> >
>>> > @Jark First of all I do agree we could/should improve the
>>> > "user-friendliness" of the JSON format (and unify the behavior across
>>> text
>>> > based formats). I am not sure though if it is as simple as just ignore
>>> the
>>> > time zone here.
>>> >
>>> > My suggestion would be rather to apply the logic of parsing a SQL
>>> > timestamp literal (if the expected type is of
>>> LogicalTypeFamily.TIMESTAMP),
>>> > which would actually also derive the "stored" type of the timestamp
>>> (either
>>> > WITHOUT TIMEZONE or WITH TIMEZONE) and then apply a proper sql
>>> conversion.
>>> > Therefore if the
>>> >
>>> > parsed type | requested type |
>>> behaviour
>>> >
>>> > WITHOUT TIMEZONE | WITH TIMEZONE | store the local
>>> > timezone with the data
>>> >
>>> > WITHOUT TIMEZONE | WITH LOCAL TIMEZONE | do nothing in the
>>> data,
>>> > interpret the time in local timezone
>>> >
>>> > WITH TIMEZONE | WITH LOCAL TIMEZONE | convert the
>>> timestamp
>>> > to local timezone and drop the time zone information
>>> >
>>> > WITH TIMEZONE | WITHOUT TIMEZONE | drop the time
>>> zone
>>> > information
>>> >
>>> > It might just boil down to what you said "being more lenient with
>>> regards
>>> > to parsing the time zone". Nevertheless I think this way it is a bit
>>> better
>>> > defined behaviour, especially as it has a defined behaviour when
>>> converting
>>> > between representation with or without time zone.
>>> >
>>> > An implementation note. I think we should aim to base the
>>> implementation
>>> > on the DataTypes already rather than going back to the TypeInformation.
>>> >
>>> > I would still try to leave the RFC 3339 compatibility mode, but maybe
>>> for
>>> > that mode it would make sense to not support any types WITHOUT
>>> TIMEZONE?
>>> > This would be enabled with a switch (disabled by default). As I
>>> understand
>>> > the RFC, making the time zone mandatory is actually a big part of the
>>> > standard as it makes time types unambiguous.
>>> >
>>> > What do you think?
>>> >
>>> > Ps. I cross posted this on the dev ML.
>>> >
>>> > Best,
>>> >
>>> > Dawid
>>> >
>>> >
>>> > On 26/02/2020 03:45, Jark Wu wrote:
>>> >
>>> > Yes, I'm also in favor of loosen the datetime format constraint.
>>> > I guess most of the users don't know there is a JSON standard which
>>> > follows RFC 3339.
>>> >
>>> > Best,
>>> > Jark
>>> >
>>> > On Wed, 26 Feb 2020 at 10:06, NiYanchun <niyanc...@outlook.com> wrote:
>>> >
>>> >> Yes, these Types definition are general. As a user/developer, I would
>>> >> support “loosen it for usability”. If not, may add some explanation
>>> >> about JSON.
>>> >>
>>> >>
>>> >>
>>> >> Original Message
>>> >> *Sender:* Jark Wu<imj...@gmail.com>
>>> >> *Recipient:* Outlook<niyanc...@outlook.com>; Dawid Wysakowicz<
>>> >> dwysakow...@apache.org>
>>> >> *Cc:* godfrey he<godfre...@gmail.com>; Leonard Xu<xbjt...@gmail.com>;
>>> >> user<user@flink.apache.org>
>>> >> *Date:* Wednesday, Feb 26, 2020 09:55
>>> >> *Subject:* Re: TIME/TIMESTAMP parse in Flink TABLE/SQL API
>>> >>
>>> >> Hi Outlook,
>>> >>
>>> >> The explanation in DataTypes is correct, it is compliant to SQL
>>> standard.
>>> >> The problem is that JsonRowDeserializationSchema only support
>>> RFC-3339.
>>> >> On the other hand, CsvRowDeserializationSchema supports to parse
>>> >> "2019-07-09 02:02:00.040".
>>> >>
>>> >> So the question is shall we insist on the RFC-3339 "standard"? Shall
>>> we
>>> >> loosen it for usability?
>>> >> What do you think @Dawid Wysakowicz <dwysakow...@apache.org> ?
>>> >>
>>> >> Best,
>>> >> Jark
>>> >>
>>> >> On Wed, 26 Feb 2020 at 09:29, Outlook <niyanc...@outlook.com> wrote:
>>> >>
>>> >>> Thanks Godfrey and Leonard, I tried your answers, result is OK.
>>> >>>
>>> >>>
>>> >>> BTW, I think if only accept such format for a long time, the TIME
>>> and
>>> >>> TIMESTAMP methods' doc in `org.apache.flink.table.api.DataTypes` may
>>> be
>>> >>> better to update,
>>> >>>
>>> >>> because the document now is not what the method really support. For
>>> >>> example,
>>> >>>
>>> >>>
>>> >>> ```
>>> >>> /**
>>> >>> * Data type of a time WITHOUT time zone {@code TIME} with no
>>> fractional
>>> >>> seconds by default.
>>> >>> *
>>> >>> * <p>An instance consists of {@code hour:minute:second} with up to
>>> >>> second precision
>>> >>> * and values ranging from {@code 00:00:00} to {@code 23:59:59}.
>>> >>> *
>>> >>> * <p>Compared to the SQL standard, leap seconds (23:59:60 and
>>> 23:59:61)
>>> >>> are not supported as the
>>> >>> * semantics are closer to {@link java.time.LocalTime}. A time WITH
>>> time
>>> >>> zone is not provided.
>>> >>> *
>>> >>> * @see #TIME(int)
>>> >>> * @see TimeType
>>> >>> */
>>> >>> public static DataType TIME() {
>>> >>> return new AtomicDataType(new TimeType());
>>> >>>
>>> >>> }```
>>> >>>
>>> >>>
>>> >>> Thanks again.
>>> >>>
>>> >>> Original Message
>>> >>> *Sender:* Leonard Xu<xbjt...@gmail.com>
>>> >>> *Recipient:* godfrey he<godfre...@gmail.com>
>>> >>> *Cc:* Outlook<niyanc...@outlook.com>; user<user@flink.apache.org>
>>> >>> *Date:* Tuesday, Feb 25, 2020 22:56
>>> >>> *Subject:* Re: TIME/TIMESTAMP parse in Flink TABLE/SQL API
>>> >>>
>>> >>> Hi，Outlook
>>> >>> Godfrey is right, you should follow the json format[1] when you parse
>>> >>> your json message.
>>> >>> You can use following code to produce a json data-time String.
>>> >>> ```
>>> >>>
>>> >>> Long time = System.currentTimeMillis();DateFormat dateFormat = new
>>> SimpleDateFormat("yyyy-MM-dd'T'HH:mm:ss.SSS'Z'");Date date = new
>>> Date(time);String jsonSchemaDate = dateFormat.format(date);
>>> >>>
>>> >>> ```
>>> >>> [1]
>>> >>>
>>> https://json-schema.org/understanding-json-schema/reference/string.html#dates-and-times
>>> >>>
>>> >>> 在 2020年2月25日，22:15，godfrey he <godfre...@gmail.com> 写道：
>>> >>>
>>> >>> hi, I find that JsonRowDeserializationSchema only supports date-time
>>> >>> with timezone according to RFC 3339. So you need add timezone to
>>> time data
>>> >>> (like 14:02:00Z) and timestamp data(2019-07-09T02:02:00.040Z). Hope
>>> it can
>>> >>> help you.
>>> >>>
>>> >>> Bests,
>>> >>> godfrey
>>> >>>
>>> >>> Outlook <niyanc...@outlook.com> 于2020年2月25日周二 下午5:49写道：
>>> >>>
>>> >>>> By the way, my flink version is 1.10.0.
>>> >>>>
>>> >>>> Original Message
>>> >>>> *Sender:* Outlook<niyanc...@outlook.com>
>>> >>>> *Recipient:* user<user@flink.apache.org>
>>> >>>> *Date:* Tuesday, Feb 25, 2020 17:43
>>> >>>> *Subject:* TIME/TIMESTAMP parse in Flink TABLE/SQL API
>>> >>>>
>>> >>>> Hi all,
>>> >>>>
>>> >>>> I read json data from kafka, and print to console. When I do this,
>>> some
>>> >>>> error occurs when time/timestamp deserialization.
>>> >>>>
>>> >>>> json data in Kafka:
>>> >>>>
>>> >>>> ```
>>> >>>> {
>>> >>>> "server_date": "2019-07-09",
>>> >>>> "server_time": "14:02:00",
>>> >>>> "reqsndtime_c": "2019-07-09 02:02:00.040"
>>> >>>> }
>>> >>>> ```
>>> >>>>
>>> >>>> flink code:
>>> >>>>
>>> >>>> ```
>>> >>>> bsTableEnv.connect(
>>> >>>> new Kafka()
>>> >>>> .version("universal")
>>> >>>> .topic("xxx")
>>> >>>> .property("bootstrap.servers", "localhost:9092")
>>> >>>> .property("zookeeper.connect", "localhost:2181")
>>> >>>> .property("group.id", "g1")
>>> >>>> .startFromEarliest()
>>> >>>> ).withFormat(
>>> >>>> new Json()
>>> >>>> .failOnMissingField(false)
>>> >>>> ).withSchema(
>>> >>>> new Schema()
>>> >>>> .field("server_date", DataTypes.DATE())
>>> >>>> .field("server_time", DataTypes.TIME())
>>> >>>> .field("reqsndtime_c", DataTypes.TIMESTAMP(3))
>>> >>>> ).inAppendMode()
>>> >>>> .createTemporaryTable("xxx”);
>>> >>>> ```
>>> >>>>
>>> >>>>
>>> >>>> server_date with format is ok, but server_time with
>>> DataTypes.DATE()
>>> >>>> and reqsndtime_c with DataTypes.TIMESTAMP(3) cause error. If I
>>> change them
>>> >>>> to DataTypes.STRING(), everything will be OK.
>>> >>>>
>>> >>>> Error message:
>>> >>>> ```
>>> >>>> Exception in thread "main" java.util.concurrent.ExecutionException:
>>> >>>> org.apache.flink.client.program.ProgramInvocationException: Job
>>> failed
>>> >>>> (JobID: 395d1ba3d41f92734d4ef25aa5f9b4a1)
>>> >>>> at
>>> >>>>
>>> java.util.concurrent.CompletableFuture.reportGet(CompletableFuture.java:357)
>>> >>>> at
>>> >>>>
>>> java.util.concurrent.CompletableFuture.get(CompletableFuture.java:1895)
>>> >>>> at
>>> >>>>
>>> org.apache.flink.streaming.api.environment.StreamExecutionEnvironment.execute(StreamExecutionEnvironment.java:1640)
>>> >>>> at
>>> >>>>
>>> org.apache.flink.streaming.api.environment.LocalStreamEnvironment.execute(LocalStreamEnvironment.java:74)
>>> >>>> at
>>> >>>>
>>> org.apache.flink.streaming.api.environment.StreamExecutionEnvironment.execute(StreamExecutionEnvironment.java:1620)
>>> >>>> at
>>> >>>>
>>> org.apache.flink.table.planner.delegation.StreamExecutor.execute(StreamExecutor.java:42)
>>> >>>> at
>>> >>>>
>>> org.apache.flink.table.api.internal.TableEnvironmentImpl.execute(TableEnvironmentImpl.java:643)
>>> >>>> at cn.com.agree.Main.main(Main.java:122)
>>> >>>> Caused by:
>>> org.apache.flink.client.program.ProgramInvocationException:
>>> >>>> Job failed (JobID: 395d1ba3d41f92734d4ef25aa5f9b4a1)
>>> >>>> at
>>> >>>>
>>> org.apache.flink.client.deployment.ClusterClientJobClientAdapter.lambda$null$6(ClusterClientJobClientAdapter.java:112)
>>> >>>> at
>>> >>>>
>>> java.util.concurrent.CompletableFuture.uniApply(CompletableFuture.java:602)
>>> >>>> at
>>> >>>>
>>> java.util.concurrent.CompletableFuture$UniApply.tryFire(CompletableFuture.java:577)
>>> >>>> at
>>> >>>>
>>> java.util.concurrent.CompletableFuture.postComplete(CompletableFuture.java:474)
>>> >>>> at
>>> >>>>
>>> java.util.concurrent.CompletableFuture.complete(CompletableFuture.java:1962)
>>> >>>> at
>>> >>>>
>>> org.apache.flink.runtime.concurrent.FutureUtils$1.onComplete(FutureUtils.java:874)
>>> >>>> at akka.dispatch.OnComplete.internal(Future.scala:264)
>>> >>>> at akka.dispatch.OnComplete.internal(Future.scala:261)
>>> >>>> at akka.dispatch.japi$CallbackBridge.apply(Future.scala:191)
>>> >>>> at akka.dispatch.japi$CallbackBridge.apply(Future.scala:188)
>>> >>>> at scala.concurrent.impl.CallbackRunnable.run(Promise.scala:36)
>>> >>>> at
>>> >>>>
>>> org.apache.flink.runtime.concurrent.Executors$DirectExecutionContext.execute(Executors.java:74)
>>> >>>> at
>>> >>>>
>>> scala.concurrent.impl.CallbackRunnable.executeWithValue(Promise.scala:44)
>>> >>>> at
>>> >>>>
>>> scala.concurrent.impl.Promise$DefaultPromise.tryComplete(Promise.scala:252)
>>> >>>> at akka.pattern.PromiseActorRef.$bang(AskSupport.scala:572)
>>> >>>> at
>>> >>>>
>>> akka.pattern.PipeToSupport$PipeableFuture$$anonfun$pipeTo$1.applyOrElse(PipeToSupport.scala:22)
>>> >>>> at
>>> >>>>
>>> akka.pattern.PipeToSupport$PipeableFuture$$anonfun$pipeTo$1.applyOrElse(PipeToSupport.scala:21)
>>> >>>> at
>>> scala.concurrent.Future$$anonfun$andThen$1.apply(Future.scala:436)
>>> >>>> at
>>> scala.concurrent.Future$$anonfun$andThen$1.apply(Future.scala:435)
>>> >>>> at scala.concurrent.impl.CallbackRunnable.run(Promise.scala:36)
>>> >>>> at
>>> >>>>
>>> akka.dispatch.BatchingExecutor$AbstractBatch.processBatch(BatchingExecutor.scala:55)
>>> >>>> at
>>> >>>>
>>> akka.dispatch.BatchingExecutor$BlockableBatch$$anonfun$run$1.apply$mcV$sp(BatchingExecutor.scala:91)
>>> >>>> at
>>> >>>>
>>> akka.dispatch.BatchingExecutor$BlockableBatch$$anonfun$run$1.apply(BatchingExecutor.scala:91)
>>> >>>> at
>>> >>>>
>>> akka.dispatch.BatchingExecutor$BlockableBatch$$anonfun$run$1.apply(BatchingExecutor.scala:91)
>>> >>>> at
>>> >>>>
>>> scala.concurrent.BlockContext$.withBlockContext(BlockContext.scala:72)
>>> >>>> at
>>> >>>>
>>> akka.dispatch.BatchingExecutor$BlockableBatch.run(BatchingExecutor.scala:90)
>>> >>>> at akka.dispatch.TaskInvocation.run(AbstractDispatcher.scala:40)
>>> >>>> at
>>> >>>>
>>> akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(ForkJoinExecutorConfigurator.scala:44)
>>> >>>> at akka.dispatch.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
>>> >>>> at
>>> >>>>
>>> akka.dispatch.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
>>> >>>> at
>>> akka.dispatch.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
>>> >>>> at
>>> >>>>
>>> akka.dispatch.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
>>> >>>> Caused by: org.apache.flink.runtime.client.JobExecutionException:
>>> Job
>>> >>>> execution failed.
>>> >>>> at
>>> >>>>
>>> org.apache.flink.runtime.jobmaster.JobResult.toJobExecutionResult(JobResult.java:147)
>>> >>>> at
>>> >>>>
>>> org.apache.flink.client.deployment.ClusterClientJobClientAdapter.lambda$null$6(ClusterClientJobClientAdapter.java:110)
>>> >>>> ... 31 more
>>> >>>> Caused by: org.apache.flink.runtime.JobException: Recovery is
>>> >>>> suppressed by NoRestartBackoffTimeStrategy
>>> >>>> at
>>> >>>>
>>> org.apache.flink.runtime.executiongraph.failover.flip1.ExecutionFailureHandler.handleFailure(ExecutionFailureHandler.java:110)
>>> >>>> at
>>> >>>>
>>> org.apache.flink.runtime.executiongraph.failover.flip1.ExecutionFailureHandler.getFailureHandlingResult(ExecutionFailureHandler.java:76)
>>> >>>> at
>>> >>>>
>>> org.apache.flink.runtime.scheduler.DefaultScheduler.handleTaskFailure(DefaultScheduler.java:192)
>>> >>>> at
>>> >>>>
>>> org.apache.flink.runtime.scheduler.DefaultScheduler.maybeHandleTaskFailure(DefaultScheduler.java:186)
>>> >>>> at
>>> >>>>
>>> org.apache.flink.runtime.scheduler.DefaultScheduler.updateTaskExecutionStateInternal(DefaultScheduler.java:180)
>>> >>>> at
>>> >>>>
>>> org.apache.flink.runtime.scheduler.SchedulerBase.updateTaskExecutionState(SchedulerBase.java:484)
>>> >>>> at
>>> >>>>
>>> org.apache.flink.runtime.jobmaster.JobMaster.updateTaskExecutionState(JobMaster.java:380)
>>> >>>> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>>> >>>> at
>>> >>>>
>>> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
>>> >>>> at
>>> >>>>
>>> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
>>> >>>> at java.lang.reflect.Method.invoke(Method.java:498)
>>> >>>> at
>>> >>>>
>>> org.apache.flink.runtime.rpc.akka.AkkaRpcActor.handleRpcInvocation(AkkaRpcActor.java:279)
>>> >>>> at
>>> >>>>
>>> org.apache.flink.runtime.rpc.akka.AkkaRpcActor.handleRpcMessage(AkkaRpcActor.java:194)
>>> >>>> at
>>> >>>>
>>> org.apache.flink.runtime.rpc.akka.FencedAkkaRpcActor.handleRpcMessage(FencedAkkaRpcActor.java:74)
>>> >>>> at
>>> >>>>
>>> org.apache.flink.runtime.rpc.akka.AkkaRpcActor.handleMessage(AkkaRpcActor.java:152)
>>> >>>> at akka.japi.pf.UnitCaseStatement.apply(CaseStatements.scala:26)
>>> >>>> at akka.japi.pf.UnitCaseStatement.apply(CaseStatements.scala:21)
>>> >>>> at
>>> scala.PartialFunction$class.applyOrElse(PartialFunction.scala:123)
>>> >>>> at akka.japi.pf
>>> .UnitCaseStatement.applyOrElse(CaseStatements.scala:21)
>>> >>>> at
>>> scala.PartialFunction$OrElse.applyOrElse(PartialFunction.scala:170)
>>> >>>> at
>>> scala.PartialFunction$OrElse.applyOrElse(PartialFunction.scala:171)
>>> >>>> at
>>> scala.PartialFunction$OrElse.applyOrElse(PartialFunction.scala:171)
>>> >>>> at akka.actor.Actor$class.aroundReceive(Actor.scala:517)
>>> >>>> at akka.actor.AbstractActor.aroundReceive(AbstractActor.scala:225)
>>> >>>> at akka.actor.ActorCell.receiveMessage(ActorCell.scala:592)
>>> >>>> at akka.actor.ActorCell.invoke(ActorCell.scala:561)
>>> >>>> at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:258)
>>> >>>> at akka.dispatch.Mailbox.run(Mailbox.scala:225)
>>> >>>> at akka.dispatch.Mailbox.exec(Mailbox.scala:235)
>>> >>>> ... 4 more
>>> >>>> Caused by: java.io.IOException: Failed to deserialize JSON object.
>>> >>>> at
>>> >>>>
>>> org.apache.flink.formats.json.JsonRowDeserializationSchema.deserialize(JsonRowDeserializationSchema.java:133)
>>> >>>> at
>>> >>>>
>>> org.apache.flink.formats.json.JsonRowDeserializationSchema.deserialize(JsonRowDeserializationSchema.java:76)
>>> >>>> at
>>> >>>>
>>> org.apache.flink.streaming.connectors.kafka.internals.KafkaDeserializationSchemaWrapper.deserialize(KafkaDeserializationSchemaWrapper.java:45)
>>> >>>> at
>>> >>>>
>>> org.apache.flink.streaming.connectors.kafka.internal.KafkaFetcher.runFetchLoop(KafkaFetcher.java:140)
>>> >>>> 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$LegacySourceFunctionThread.run(SourceStreamTask.java:196)
>>> >>>> Caused by: java.time.format.DateTimeParseException: *Text '14:02:00'
>>> >>>> could not be parsed at index 8*
>>> >>>> at
>>> >>>>
>>> java.time.format.DateTimeFormatter.parseResolved0(DateTimeFormatter.java:1949)
>>> >>>> at
>>> java.time.format.DateTimeFormatter.parse(DateTimeFormatter.java:1777)
>>> >>>> at
>>> >>>>
>>> org.apache.flink.formats.json.JsonRowDeserializationSchema.convertToLocalTime(JsonRowDeserializationSchema.java:390)
>>> >>>> at
>>> >>>>
>>> org.apache.flink.formats.json.JsonRowDeserializationSchema.lambda$wrapIntoNullableConverter$d586c97$1(JsonRowDeserializationSchema.java:236)
>>> >>>> at
>>> >>>>
>>> org.apache.flink.formats.json.JsonRowDeserializationSchema.convertField(JsonRowDeserializationSchema.java:439)
>>> >>>> at
>>> >>>>
>>> org.apache.flink.formats.json.JsonRowDeserializationSchema.lambda$assembleRowConverter$77f7700$1(JsonRowDeserializationSchema.java:418)
>>> >>>> at
>>> >>>>
>>> org.apache.flink.formats.json.JsonRowDeserializationSchema.lambda$wrapIntoNullableConverter$d586c97$1(JsonRowDeserializationSchema.java:236)
>>> >>>> at
>>> >>>>
>>> org.apache.flink.formats.json.JsonRowDeserializationSchema.deserialize(JsonRowDeserializationSchema.java:131)
>>> >>>> ... 7 more
>>> >>>>
>>> >>>> Process finished with exit code 1
>>> >>>> ```
>>> >>>>
>>> >>>> reqsndtime_c with DataTypes.TIMESTAMP(3) has similar exception. I
>>> see
>>> >>>> the doc, DataTypes.TIME() value range is from {@code 00:00:00} to
>>> {@code
>>> >>>> 23:59:59} , DataTypes.TIMESTAMP value range is from {@code
>>> 0000-01-01
>>> >>>> 00:00:00.000000000} to
>>> >>>> * {@code 9999-12-31 23:59:59.999999999}. And my value is in the
>>> range,
>>> >>>> I don’t know why. And I see this may be bug in java 8, I change
>>> jdk to 11,
>>> >>>>
>>> >>>> error still occurs.
>>> >>>>
>>> >>>> Can someone give me some help, thanks in advance.
>>> >>>>
>>> >>>
>>> >>>
>>>
>>
>>
>> --
>> Best, Jingsong Lee
>>
>
--
Best, Jingsong Lee
