maropu commented on a change in pull request #30654:
URL: https://github.com/apache/spark/pull/30654#discussion_r537952407
##########
File path: docs/sql-migration-guide.md
##########
@@ -54,6 +54,8 @@ license: |
- In Spark 3.1, creating or altering a view will capture runtime SQL configs
and store them as view properties. These configs will be applied during the
parsing and analysis phases of the view resolution. To restore the behavior
before Spark 3.1, you can set `spark.sql.legacy.useCurrentConfigsForView` to
`true`.
+ - In Spark 3.1, CHAR/CHARACTER and VARCHAR types become individual types
from string. By default, they can only be used in table schema, not
functions/operators. To restore the behavior before Spark 3.1, where treats
them as string with length parameter simply ignored, you can set
`spark.sql.legacy.charVarcharAsString` to `true`.
Review comment:
how about `CHAR/CHARACTER and VARCHAR types become individual types from
string` -> `we support CHAR/CHARACTER and VARCHAR types in our type system
framework instead of replacing them with STRING types`?
##########
File path: docs/sql-migration-guide.md
##########
@@ -54,6 +54,8 @@ license: |
- In Spark 3.1, creating or altering a view will capture runtime SQL configs
and store them as view properties. These configs will be applied during the
parsing and analysis phases of the view resolution. To restore the behavior
before Spark 3.1, you can set `spark.sql.legacy.useCurrentConfigsForView` to
`true`.
+ - In Spark 3.1, CHAR/CHARACTER and VARCHAR types become individual types
from string. By default, they can only be used in table schema, not
functions/operators. To restore the behavior before Spark 3.1, where treats
them as string with length parameter simply ignored, you can set
`spark.sql.legacy.charVarcharAsString` to `true`.
Review comment:
`, where treats them as string with length parameter simply ignored,` ->
`, which treats them as STRING types and ignores a length parameter (e.g.,
CHAR(4)), `?
##########
File path: docs/sql-migration-guide.md
##########
@@ -54,6 +54,8 @@ license: |
- In Spark 3.1, creating or altering a view will capture runtime SQL configs
and store them as view properties. These configs will be applied during the
parsing and analysis phases of the view resolution. To restore the behavior
before Spark 3.1, you can set `spark.sql.legacy.useCurrentConfigsForView` to
`true`.
+ - In Spark 3.1, CHAR/CHARACTER and VARCHAR types become individual types
from string. By default, they can only be used in table schema, not
functions/operators. To restore the behavior before Spark 3.1, where treats
them as string with length parameter simply ignored, you can set
`spark.sql.legacy.charVarcharAsString` to `true`.
Review comment:
nit: `table schema` -> `a table schema`
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