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https://issues.apache.org/jira/browse/FLINK-13611?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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godfrey he updated FLINK-13611:
-------------------------------
    Description: 
this issue aims to introduce a utility class to generate table & column 
statistics, the main steps include: 
1. generate sql, like
{code:sql}
select approx_count_distinct(a) as ndv, count(1) - count(a) as nullCount, 
avg(char_length(a)) as avgLen, max(char_lenght(a)) as maxLen, max(a) as 
maxValue, min(a) as minValue, ... from MyTable
{code}

2. execute the query

3. convert to the result to {{TableStats}} (maybe the source table is not a 
catalog table)

4. convert to {{TableStats}} to {{CatalogTableStatistics}} if needed

This issue does not involve DDL, however the DDL could use this utility class 
once it's supported.

  was:
this issue aims to introduce a utility class to generate table & column 
statistics, the main steps include: 
1. generate sql, like {{ select approx_count_distinct(a) as ndv, count(1) - 
count(a) as nullCount, avg(char_length(a)) as avgLen, max(char_lenght(a)) as 
maxLen, max(a) as maxValue, min(a) as minValue, ... from MyTable }}
2. execute the query
3. convert to the result to {{TableStats}} (maybe the source table is not a 
catalog table)
4. convert to {{TableStats}} to {{CatalogTableStatistics}} if needed

This issue does not involve DDL, however the DDL could use this utility class 
once it's supported.


> Introduce analyze statistic utility to generate table & column statistics
> -------------------------------------------------------------------------
>
>                 Key: FLINK-13611
>                 URL: https://issues.apache.org/jira/browse/FLINK-13611
>             Project: Flink
>          Issue Type: New Feature
>          Components: Table SQL / Planner
>            Reporter: godfrey he
>            Priority: Major
>             Fix For: 1.10.0
>
>
> this issue aims to introduce a utility class to generate table & column 
> statistics, the main steps include: 
> 1. generate sql, like
> {code:sql}
> select approx_count_distinct(a) as ndv, count(1) - count(a) as nullCount, 
> avg(char_length(a)) as avgLen, max(char_lenght(a)) as maxLen, max(a) as 
> maxValue, min(a) as minValue, ... from MyTable
> {code}
> 2. execute the query
> 3. convert to the result to {{TableStats}} (maybe the source table is not a 
> catalog table)
> 4. convert to {{TableStats}} to {{CatalogTableStatistics}} if needed
> This issue does not involve DDL, however the DDL could use this utility class 
> once it's supported.



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