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Github user gatorsmile commented on the issue:
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LGTM
The PR title is not right. BTW, we might need a release note for this PR.
This will change the behaviors.
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retest this please
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retest this please
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Github user gatorsmile commented on the issue:
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Just for your reference, below is the conversion charts of MS SQL Server.
It includes both implicit and explicit conversion rules.
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retest this please
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retest this please
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Github user dasbipulkumar commented on the issue:
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@gatorsmile
configuration flag would be good approach.
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Github user gatorsmile commented on the issue:
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The [official Hive
document](https://cwiki.apache.org/confluence/display/Hive/LanguageManual+Types#LanguageManualTypes-AllowedImplicitConversions)
explains the implicit type casting rules.
Github user gatorsmile commented on the issue:
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In the future, more code changes might break Hive compatibility
accidentally or intentionally.
Maybe, we can introduce a configuration flag. For example, in DB2, we have
a flag like
Github user dasbipulkumar commented on the issue:
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yes. As a Dev we can handle these things, but as Spark Sql is moving
towards more abstracted APIs, it can be painful for general users. I hope that
handing these issues can be planned in
Github user cloud-fan commented on the issue:
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I agree implicit cast is kind of evil, and for the example in SPARK-18489,
it's better to follow postgres and fail the query because we can't cast "s" to
integer. But this will break hive
Github user dasbipulkumar commented on the issue:
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Please refer this bug
https://issues.apache.org/jira/browse/SPARK-18489
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Github user cloud-fan commented on the issue:
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`BinaryComparison` is special and we have special rules for it. For UDF we
only apply the normal implicit type conversions. Have you met any problem with
UDF?
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@cloud-fan
Will this handle UDFs?
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Github user cloud-fan commented on the issue:
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to be safe, how about we retargeting this ticket to 2.2?
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Github user rxin commented on the issue:
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+1 on the postgres approach
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+1 on the postgres approach
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+1 on the postgres approach
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+1 on the postgres approach
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Github user cloud-fan commented on the issue:
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Ok we need to make a decision here, to follow hive and give a warning
message, or to follow postgres and cast string to the type of the other side.
Personally I prefer the postgres way, I
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Below contains a section of `Implicit Data Conversion` in Oracle:
https://docs.oracle.com/cd/B19306_01/server.102/b14200/sql_elements002.htm
It clearly documents the potential changes in
Github user dongjoon-hyun commented on the issue:
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Hi, @cloud-fan . What about just showing warning for that?
For Hive 1.2.1 and 2.1.0, it's `true` like the old Spark.
```sql
hive> SELECT 19157170390056973L = "19157170390056971";
Github user hvanhovell commented on the issue:
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Yeah, you are totally right about that. I like this approach, the only
bothering me is that this breaks backwards compatibility.
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We can only know if this string is castable at runtime. BTW, other
databases(like MySQL) have special implicit type conversion rules for
constants, should we follow them?
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Github user hvanhovell commented on the issue:
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This might be a bad idea: should we follow the old casting strategy if we
cannot cast from string to atomic datatype?
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cc @yhuai @gatorsmile
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