chore: Refactor cast module temporal types#3624
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andygrove merged 6 commits intoapache:mainfrom Mar 4, 2026
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coderfender
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@andygrove , this should be the last PR re cast module refactor. I will rebase the changes once #3623 is merged to close out on #3459 |
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Fixed merge conflicts with main |
parthchandra
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Mar 3, 2026
| use std::sync::Arc; | ||
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| /// Check if DataFusion cast from integer types is Spark compatible | ||
| pub(crate) fn is_df_cast_from_int_spark_compatible(to_type: &DataType) -> bool { |
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Could the is_*_spark_compatible functions be inline?
andygrove
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Mar 4, 2026
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Thank you @parthchandra @andygrove |
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Which issue does this PR close?
Closes #3459 .
This should be the final part of cast modularization and split them up by their source data types. Complex types repeatedly call
cast_arraywhich might not make the functions good candidates to make up their own file apart from the relatively less volume . However, if things do change, we could always revisit and move things out to a new file.Rationale for this change
What changes are included in this PR?
is_df_cast_from_date/timestamp_spark_compatibleto move out the df related cast match argumentto temporal.rstemporal.rsHow are these changes tested?