[jira] [Updated] (FLINK-25471) wrong result if table transfrom to DataStream then keyey sum in Batch Mode

2021-12-28 Thread zhangzh (Jira)


 [ 
https://issues.apache.org/jira/browse/FLINK-25471?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

zhangzh updated FLINK-25471:

Description: 
I have a dataStream with 6 lines datas like this:

Row.of("Alice"),
Row.of("alice"),
Row.of("Bob"),
Row.of("lily"),
Row.of("lily"),
Row.of("lily")

then  make it to  table  with one colums  "word"

then sql transform : select upper(word) from tmp_table

then change to dataStream

then keyby sum.

 

in batch mode:

I think correct result is:

> (BOB,1)
> (ALICE,2)
> (LILY,3)

 

but the result is :

> (BOB,1)

if i set different parallelism ,the result is different.

 

the source file  and pom is in attach.

 is  a bug?

pelease help me!!!

 

 

 

 

 

 

 

 

 

  was:
I have a dataStream with 6 lines datas like this:

Row.of("Alice"),
Row.of("alice"),
Row.of("Bob"),
Row.of("lily"),
Row.of("lily"),
Row.of("lily")

then  make it to  table  with one colums  "wrod"

then sql transform : select upper(word) from tmp_table

then change to dataStream

then keyby sum.

 

in batch mode:

I think correct result is:

> (BOB,1)
> (ALICE,2)
> (LILY,3)

 

but the result is :

> (BOB,1)

if i set different parallelism ,the result is different.

 

the source file  and pom is in attach.

 is  a bug?

pelease help me!!!

 

 

 

 

 

 

 

 

 


> wrong result if table transfrom to DataStream then keyey  sum in Batch Mode
> ---
>
> Key: FLINK-25471
> URL: https://issues.apache.org/jira/browse/FLINK-25471
> Project: Flink
>  Issue Type: Bug
>  Components: Table SQL / API, Table SQL / Runtime
>Affects Versions: 1.14.2
> Environment: mac book pro m1 
> jdk 8 
> scala 2.11
> flink 1.14.2
> idea 2020
>Reporter: zhangzh
>Priority: Critical
> Attachments: TableToDataStreamBatchWordCount-1.scala, pom.xml
>
>
> I have a dataStream with 6 lines datas like this:
> Row.of("Alice"),
> Row.of("alice"),
> Row.of("Bob"),
> Row.of("lily"),
> Row.of("lily"),
> Row.of("lily")
> then  make it to  table  with one colums  "word"
> then sql transform : select upper(word) from tmp_table
> then change to dataStream
> then keyby sum.
>  
> in batch mode:
> I think correct result is:
> > (BOB,1)
> > (ALICE,2)
> > (LILY,3)
>  
> but the result is :
> > (BOB,1)
> if i set different parallelism ,the result is different.
>  
> the source file  and pom is in attach.
>  is  a bug?
> pelease help me!!!
>  
>  
>  
>  
>  
>  
>  
>  
>  



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[jira] [Updated] (FLINK-25471) wrong result if table transfrom to DataStream then keyey sum in Batch Mode

2021-12-28 Thread zhangzh (Jira)


 [ 
https://issues.apache.org/jira/browse/FLINK-25471?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

zhangzh updated FLINK-25471:

Description: 
I have a dataStream with 6 lines datas like this:

Row.of("Alice"),
Row.of("alice"),
Row.of("Bob"),
Row.of("lily"),
Row.of("lily"),
Row.of("lily")

then  make it to  table  with one column "word"

then sql transform : select upper(word) from tmp_table

then change to dataStream

then keyby sum.

 

in batch mode:

I think correct result is:

> (BOB,1)
> (ALICE,2)
> (LILY,3)

 

but the result is :

> (BOB,1)

if i set different parallelism ,the result is different.

 

the source file  and pom is in attach.

 is  a bug?

pelease help me!!!

 

 

 

 

 

 

 

 

 

  was:
I have a dataStream with 6 lines datas like this:

Row.of("Alice"),
Row.of("alice"),
Row.of("Bob"),
Row.of("lily"),
Row.of("lily"),
Row.of("lily")

then  make it to  table  with one colums  "word"

then sql transform : select upper(word) from tmp_table

then change to dataStream

then keyby sum.

 

in batch mode:

I think correct result is:

> (BOB,1)
> (ALICE,2)
> (LILY,3)

 

but the result is :

> (BOB,1)

if i set different parallelism ,the result is different.

 

the source file  and pom is in attach.

 is  a bug?

pelease help me!!!

 

 

 

 

 

 

 

 

 


> wrong result if table transfrom to DataStream then keyey  sum in Batch Mode
> ---
>
> Key: FLINK-25471
> URL: https://issues.apache.org/jira/browse/FLINK-25471
> Project: Flink
>  Issue Type: Bug
>  Components: Table SQL / API, Table SQL / Runtime
>Affects Versions: 1.14.2
> Environment: mac book pro m1 
> jdk 8 
> scala 2.11
> flink 1.14.2
> idea 2020
>Reporter: zhangzh
>Priority: Critical
> Attachments: TableToDataStreamBatchWordCount-1.scala, pom.xml
>
>
> I have a dataStream with 6 lines datas like this:
> Row.of("Alice"),
> Row.of("alice"),
> Row.of("Bob"),
> Row.of("lily"),
> Row.of("lily"),
> Row.of("lily")
> then  make it to  table  with one column "word"
> then sql transform : select upper(word) from tmp_table
> then change to dataStream
> then keyby sum.
>  
> in batch mode:
> I think correct result is:
> > (BOB,1)
> > (ALICE,2)
> > (LILY,3)
>  
> but the result is :
> > (BOB,1)
> if i set different parallelism ,the result is different.
>  
> the source file  and pom is in attach.
>  is  a bug?
> pelease help me!!!
>  
>  
>  
>  
>  
>  
>  
>  
>  



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(v8.20.1#820001)


[jira] [Updated] (FLINK-25471) wrong result if table transfrom to DataStream then keyey sum in Batch Mode

2021-12-28 Thread zhangzh (Jira)


 [ 
https://issues.apache.org/jira/browse/FLINK-25471?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

zhangzh updated FLINK-25471:

Environment: 
mac book pro m1 

jdk 8 

scala 2.11

flink 1.14.2

idea 2020

  was:
mac book pro m1 

jdk 8 

scala 2.11

flink 14.2

idea 2020


> wrong result if table transfrom to DataStream then keyey  sum in Batch Mode
> ---
>
> Key: FLINK-25471
> URL: https://issues.apache.org/jira/browse/FLINK-25471
> Project: Flink
>  Issue Type: Bug
>  Components: Table SQL / API, Table SQL / Runtime
>Affects Versions: 1.14.2
> Environment: mac book pro m1 
> jdk 8 
> scala 2.11
> flink 1.14.2
> idea 2020
>Reporter: zhangzh
>Priority: Critical
> Attachments: TableToDataStreamBatchWordCount-1.scala, pom.xml
>
>
> I have a dataStream with 6 lines datas like this:
> Row.of("Alice"),
> Row.of("alice"),
> Row.of("Bob"),
> Row.of("lily"),
> Row.of("lily"),
> Row.of("lily")
> then  make it to  table  with one colums  "wrod"
> then sql transform : select upper(word) from tmp_table
> then change to dataStream
> then keyby sum.
>  
> in batch mode:
> I think correct result is:
> > (BOB,1)
> > (ALICE,2)
> > (LILY,3)
>  
> but the result is :
> > (BOB,1)
> if i set different parallelism ,the result is different.
>  
> the source file  and pom is in attach.
>  is  a bug?
> pelease help me!!!
>  
>  
>  
>  
>  
>  
>  
>  
>  



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This message was sent by Atlassian Jira
(v8.20.1#820001)


[jira] [Updated] (FLINK-25471) wrong result if table transfrom to DataStream then keyey sum in Batch Mode

2021-12-28 Thread zhangzh (Jira)


 [ 
https://issues.apache.org/jira/browse/FLINK-25471?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

zhangzh updated FLINK-25471:

Summary: wrong result if table transfrom to DataStream then keyey  sum in 
Batch Mode  (was: wrong result if table toDataStream then keyey  sum in Batch 
Mode)

> wrong result if table transfrom to DataStream then keyey  sum in Batch Mode
> ---
>
> Key: FLINK-25471
> URL: https://issues.apache.org/jira/browse/FLINK-25471
> Project: Flink
>  Issue Type: Bug
>  Components: Table SQL / API, Table SQL / Runtime
>Affects Versions: 1.14.2
> Environment: mac book pro m1 
> jdk 8 
> scala 2.11
> flink 14.2
> idea 2020
>Reporter: zhangzh
>Priority: Critical
> Attachments: TableToDataStreamBatchWordCount-1.scala, pom.xml
>
>
> I have a dataStream with 6 lines datas like this:
> Row.of("Alice"),
> Row.of("alice"),
> Row.of("Bob"),
> Row.of("lily"),
> Row.of("lily"),
> Row.of("lily")
> then  make it to  table  with one colums  "wrod"
> then sql transform : select upper(word) from tmp_table
> then change to dataStream
> then keyby sum.
>  
> in batch mode:
> I think correct result is:
> > (BOB,1)
> > (ALICE,2)
> > (LILY,3)
>  
> but the result is :
> > (BOB,1)
> if i set different parallelism ,the result is different.
>  
> the source file  and pom is in attach.
>  is  a bug?
> pelease help me!!!
>  
>  
>  
>  
>  
>  
>  
>  
>  



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