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https://issues.apache.org/jira/browse/NIFI-6640?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Tamas Palfy updated NIFI-6640:
------------------------------
Attachment: NIFI-6640.xml
> UNION/CHOICE types not handled correctly
> ----------------------------------------
>
> Key: NIFI-6640
> URL: https://issues.apache.org/jira/browse/NIFI-6640
> Project: Apache NiFi
> Issue Type: Bug
> Components: Core Framework
> Reporter: Tamas Palfy
> Assignee: Tamas Palfy
> Priority: Major
>
> When reading the following CSV:
> {code}
> Id|Value
> 1|3
> 2|3.75
> 3|3.85
> 4|8
> 5|2.0
> 6|4.0
> 7|some_string
> {code}
> And try to channel through a {{ConvertRecord}} processor, the following
> exception is thrown:
> {code}
> 2019-09-06 18:25:48,936 ERROR [Timer-Driven Process Thread-2]
> o.a.n.processors.standard.ConvertRecord
> ConvertRecord[id=07635c71-016d-1000-3847-ff916164b32a] Failed to process
> StandardFlowFileRecord[uuid=4b4ab01a-b349-4f83-9b25-6a58d0b29
> 7c1,claim=StandardContentClaim
> [resourceClaim=StandardResourceClaim[id=1567786888281-1, container=default,
> section=1], offset=326669,
> length=56],offset=0,name=4b4ab01a-b349-4f83-9b25-6a58d0b297c1,size=56]; will
> route to failure: org.apa
> che.nifi.processor.exception.ProcessException: Could not parse incoming data
> org.apache.nifi.processor.exception.ProcessException: Could not parse
> incoming data
> at
> org.apache.nifi.processors.standard.AbstractRecordProcessor$1.process(AbstractRecordProcessor.java:170)
> at
> org.apache.nifi.controller.repository.StandardProcessSession.write(StandardProcessSession.java:2925)
> at
> org.apache.nifi.processors.standard.AbstractRecordProcessor.onTrigger(AbstractRecordProcessor.java:122)
> at
> org.apache.nifi.processor.AbstractProcessor.onTrigger(AbstractProcessor.java:27)
> at
> org.apache.nifi.controller.StandardProcessorNode.onTrigger(StandardProcessorNode.java:1162)
> at
> org.apache.nifi.controller.tasks.ConnectableTask.invoke(ConnectableTask.java:205)
> at
> org.apache.nifi.controller.scheduling.TimerDrivenSchedulingAgent$1.run(TimerDrivenSchedulingAgent.java:117)
> at
> java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
> at java.util.concurrent.FutureTask.runAndReset(FutureTask.java:308)
> at
> java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$301(ScheduledThreadPoolExecutor.java:180)
> at
> java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:294)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
> at java.lang.Thread.run(Thread.java:748)
> Caused by: org.apache.nifi.serialization.MalformedRecordException: Error
> while getting next record. Root cause:
> org.apache.nifi.serialization.record.util.IllegalTypeConversionException:
> Cannot convert value [some_string] of type class j
> ava.lang.String for field Value to any of the following available Sub-Types
> for a Choice: [FLOAT, INT]
> at
> org.apache.nifi.csv.CSVRecordReader.nextRecord(CSVRecordReader.java:119)
> at
> org.apache.nifi.serialization.RecordReader.nextRecord(RecordReader.java:50)
> at
> org.apache.nifi.processors.standard.AbstractRecordProcessor$1.process(AbstractRecordProcessor.java:156)
> ... 13 common frames omitted
> Caused by:
> org.apache.nifi.serialization.record.util.IllegalTypeConversionException:
> Cannot convert value [some_string] of type class java.lang.String for field
> Value to any of the following available Sub-Types for a Choice: [FLOAT, INT
> ]
> at
> org.apache.nifi.serialization.record.util.DataTypeUtils.convertType(DataTypeUtils.java:166)
> at
> org.apache.nifi.serialization.record.util.DataTypeUtils.convertType(DataTypeUtils.java:116)
> at
> org.apache.nifi.csv.AbstractCSVRecordReader.convert(AbstractCSVRecordReader.java:86)
> at
> org.apache.nifi.csv.CSVRecordReader.nextRecord(CSVRecordReader.java:105)
> ... 15 common frames omitted
> {code}
> The problem is that {{FieldTypeInference}} has both a list of
> {{possibleDataTypes}} and a {{singleDataType}} and as long as an added
> dataType is not in a "wider" relationship with the previous types it is added
> to the {{possibleDataTypes}}. But once a "wider" type is added, it actually
> gets set as the {{singleDataType}} and the {{possibleDataTypes}} remains
> intact.
> However when we try to determine the actual dataType, if the
> {{possibleDataTypes}} is not null then it will be used and the
> {{singleDataType}} will be _ignored_.
> So in our example a {{FieldTypeInference}} with (FLOAT, INT) as
> {{possibleDataTypes}} and STRING as {{singleDataType}} will be created, the
> FLOAT or INT will be chosen and "some_string" will be tried being written as
> a float or integer.
> ----
> Also there is an issue with the handling of multiple datatypes when _writing_
> data.
> When multiple datatypes are possible, a so-called CHOICE datatype is assigned
> in the inferred schema. This contains the possible datatypes in a list.
> However most (if not all) of the times when choose a concrete datatype for a
> given value when writing it (tested with JSON and Avro writers), the first
> matching type is selected from the list. And in the current implementation,
> all number types are matching for all numbers, so 3.75 may be written as an
> INT, resulting in data loss.
> The problem is that the type list is not in any particular order _and_ the
> first matching type is chosen.
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