[ 
https://issues.apache.org/jira/browse/SPARK-31030?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Yuanjian Li updated SPARK-31030:
--------------------------------
    Description: 
*Background*

In Spark version 2.4 and earlier, datetime parsing, formatting and conversion 
are performed by using the hybrid calendar ([Julian + 
Gregorian|https://docs.oracle.com/javase/7/docs/api/java/util/GregorianCalendar.html]).
 

Since the Proleptic Gregorian calendar is de-facto calendar worldwide, as well 
as the chosen one in ANSI SQL standard, Spark 3.0 switches to it by using Java 
8 API classes (the java.time packages that are based on [ISO 
chronology|https://docs.oracle.com/javase/8/docs/api/java/time/chrono/IsoChronology.html]
 ).

The switching job is completed in SPARK-26651. 

 

*Problem*

Switching to Java 8 datetime API breaks the backward compatibility of Spark 2.4 
and earlier when parsing datetime. Spark need its own patters definition on 
datetime parsing and formatting.

 

*Solution*

To avoid unexpected result changes after the underlying datetime API switch, we 
propose the following solution. 
 * Introduce the fallback mechanism: when the Java 8-based parser fails, we 
need to detect these behavior differences by falling back to the legacy parser, 
and fail with a user-friendly error message to tell users what gets changed and 
how to fix the pattern.

 * Document the Spark’s datetime patterns: The date-time formatter of Spark is 
decoupled with the Java patterns. The Spark’s patterns are mainly based on the 
[Java 7’s 
pattern|https://docs.oracle.com/javase/7/docs/api/java/text/SimpleDateFormat.html]
 (for better backward compatibility) with the customized logic (caused by the 
breaking changes between [Java 
7|https://docs.oracle.com/javase/7/docs/api/java/text/SimpleDateFormat.html] 
and [Java 
8|https://docs.oracle.com/javase/8/docs/api/java/time/format/DateTimeFormatter.html]
 pattern string). Below are the customized rules:

||Pattern||Java 7||Java 8|| Example||Rule||
|u|Day number of week (1 = Monday, ..., 7 = Sunday)|Year (Different with y, u 
accept a negative value to represent BC, while y should be used together with G 
to do the same thing.)|!image-2020-03-04-10-54-05-208.png!  |Substitute ‘u’ to 
‘e’ and use Java 8 parser to parse the string. If parsable, return the result; 
otherwise, fall back to ‘u’, and then use the legacy Java 7 parser to parse. 
When it is successfully parsed, throw an exception and ask users to change the 
pattern strings or turn on the legacy mode; otherwise, return NULL as what 
Spark 2.4 does.|
| z| General time zone which also accepts
 [RFC 822 time zones|#rfc822timezone]]|Only accept time-zone name, e.g. Pacific 
Standard Time; PST|!image-2020-03-04-10-54-13-238.png!  |The semantics of ‘z’ 
are different between Java 7 and Java 8. Here, Spark 3.0 follows the semantics 
of Java 8. 
 Use Java 8 to parse the string. If parsable, return the result; otherwise, use 
the legacy Java 7 parser to parse. When it is successfully parsed, throw an 
exception and ask users to change the pattern strings or turn on the legacy 
mode; otherwise, return NULL as what Spark 2.4 does.|

 

 

 

  was:
*Background*

In Spark version 2.4 and earlier, datetime parsing, formatting and conversion 
are performed by using the hybrid calendar ([Julian + 
Gregorian|https://docs.oracle.com/javase/7/docs/api/java/util/GregorianCalendar.html]).
 

Since the Proleptic Gregorian calendar is de-facto calendar worldwide, as well 
as the chosen one in ANSI SQL standard, Spark 3.0 switches to it by using Java 
8 API classes (the java.time packages that are based on [ISO 
chronology|https://docs.oracle.com/javase/8/docs/api/java/time/chrono/IsoChronology.html]
 ).

The switching job is completed in SPARK-26651. 

 

*Problem*

Switching to Java 8 datetime API breaks the backward compatibility of Spark 2.4 
and earlier when parsing datetime. Moreover, for the build-in SQL expressions 
like to_date, to_timestamp and etc,  in the existing implementation of Spark 
3.0 will catch all the exceptions and return `null` when hitting the parsing 
errors. This will cause the silent result changes, which are hard to debug for 
end-users when the data volume is huge and business logics are complex.

 

*Solution*

To avoid unexpected result changes after the underlying datetime API switch, we 
propose the following solution. 
 * Introduce the fallback mechanism: when the Java 8-based parser fails, we 
need to detect these behavior differences by falling back to the legacy parser, 
and fail with a user-friendly error message to tell users what gets changed and 
how to fix the pattern.

 * Document the Spark’s datetime patterns: The date-time formatter of Spark is 
decoupled with the Java patterns. The Spark’s patterns are mainly based on the 
[Java 7’s 
pattern|https://docs.oracle.com/javase/7/docs/api/java/text/SimpleDateFormat.html]
 (for better backward compatibility) with the customized logic (caused by the 
breaking changes between [Java 
7|https://docs.oracle.com/javase/7/docs/api/java/text/SimpleDateFormat.html] 
and [Java 
8|https://docs.oracle.com/javase/8/docs/api/java/time/format/DateTimeFormatter.html]
 pattern string). Below are the customized rules:

||Pattern||Java 7||Java 8|| Example||Rule||
|u|Day number of week (1 = Monday, ..., 7 = Sunday)|Year (Different with y, u 
accept a negative value to represent BC, while y should be used together with G 
to do the same thing.)|!image-2020-03-04-10-54-05-208.png!  |Substitute ‘u’ to 
‘e’ and use Java 8 parser to parse the string. If parsable, return the result; 
otherwise, fall back to ‘u’, and then use the legacy Java 7 parser to parse. 
When it is successfully parsed, throw an exception and ask users to change the 
pattern strings or turn on the legacy mode; otherwise, return NULL as what 
Spark 2.4 does.|
| z| General time zone which also accepts
 [RFC 822 time zones|#rfc822timezone]]|Only accept time-zone name, e.g. Pacific 
Standard Time; PST|!image-2020-03-04-10-54-13-238.png!  |The semantics of ‘z’ 
are different between Java 7 and Java 8. Here, Spark 3.0 follows the semantics 
of Java 8. 
 Use Java 8 to parse the string. If parsable, return the result; otherwise, use 
the legacy Java 7 parser to parse. When it is successfully parsed, throw an 
exception and ask users to change the pattern strings or turn on the legacy 
mode; otherwise, return NULL as what Spark 2.4 does.|

 

 

 


> Backward Compatibility for Parsing Datetime
> -------------------------------------------
>
>                 Key: SPARK-31030
>                 URL: https://issues.apache.org/jira/browse/SPARK-31030
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>    Affects Versions: 3.0.0
>            Reporter: Yuanjian Li
>            Priority: Major
>         Attachments: image-2020-03-04-10-54-05-208.png, 
> image-2020-03-04-10-54-13-238.png
>
>
> *Background*
> In Spark version 2.4 and earlier, datetime parsing, formatting and conversion 
> are performed by using the hybrid calendar ([Julian + 
> Gregorian|https://docs.oracle.com/javase/7/docs/api/java/util/GregorianCalendar.html]).
>  
> Since the Proleptic Gregorian calendar is de-facto calendar worldwide, as 
> well as the chosen one in ANSI SQL standard, Spark 3.0 switches to it by 
> using Java 8 API classes (the java.time packages that are based on [ISO 
> chronology|https://docs.oracle.com/javase/8/docs/api/java/time/chrono/IsoChronology.html]
>  ).
> The switching job is completed in SPARK-26651. 
>  
> *Problem*
> Switching to Java 8 datetime API breaks the backward compatibility of Spark 
> 2.4 and earlier when parsing datetime. Spark need its own patters definition 
> on datetime parsing and formatting.
>  
> *Solution*
> To avoid unexpected result changes after the underlying datetime API switch, 
> we propose the following solution. 
>  * Introduce the fallback mechanism: when the Java 8-based parser fails, we 
> need to detect these behavior differences by falling back to the legacy 
> parser, and fail with a user-friendly error message to tell users what gets 
> changed and how to fix the pattern.
>  * Document the Spark’s datetime patterns: The date-time formatter of Spark 
> is decoupled with the Java patterns. The Spark’s patterns are mainly based on 
> the [Java 7’s 
> pattern|https://docs.oracle.com/javase/7/docs/api/java/text/SimpleDateFormat.html]
>  (for better backward compatibility) with the customized logic (caused by the 
> breaking changes between [Java 
> 7|https://docs.oracle.com/javase/7/docs/api/java/text/SimpleDateFormat.html] 
> and [Java 
> 8|https://docs.oracle.com/javase/8/docs/api/java/time/format/DateTimeFormatter.html]
>  pattern string). Below are the customized rules:
> ||Pattern||Java 7||Java 8|| Example||Rule||
> |u|Day number of week (1 = Monday, ..., 7 = Sunday)|Year (Different with y, u 
> accept a negative value to represent BC, while y should be used together with 
> G to do the same thing.)|!image-2020-03-04-10-54-05-208.png!  |Substitute ‘u’ 
> to ‘e’ and use Java 8 parser to parse the string. If parsable, return the 
> result; otherwise, fall back to ‘u’, and then use the legacy Java 7 parser to 
> parse. When it is successfully parsed, throw an exception and ask users to 
> change the pattern strings or turn on the legacy mode; otherwise, return NULL 
> as what Spark 2.4 does.|
> | z| General time zone which also accepts
>  [RFC 822 time zones|#rfc822timezone]]|Only accept time-zone name, e.g. 
> Pacific Standard Time; PST|!image-2020-03-04-10-54-13-238.png!  |The 
> semantics of ‘z’ are different between Java 7 and Java 8. Here, Spark 3.0 
> follows the semantics of Java 8. 
>  Use Java 8 to parse the string. If parsable, return the result; otherwise, 
> use the legacy Java 7 parser to parse. When it is successfully parsed, throw 
> an exception and ask users to change the pattern strings or turn on the 
> legacy mode; otherwise, return NULL as what Spark 2.4 does.|
>  
>  
>  



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