viirya commented on a change in pull request #35534:
URL: https://github.com/apache/spark/pull/35534#discussion_r809703070
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/FunctionRegistry.scala
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@@ -324,7 +326,36 @@ object FunctionRegistry {
val FUNC_ALIAS = TreeNodeTag[String]("functionAliasName")
- // Note: Whenever we add a new entry here, make sure we also update
ExpressionToSQLSuite
+ //
==============================================================================================
+ // The guideline for adding SQL functions
+ //
==============================================================================================
+ // To add a SQL function, we usually need to create a new `Expression` for
the function, and
+ // implement the function logic in both the interpretation code path and
codegen code path of the
+ // `Expression`. We also need to define the type coercion behavior for the
function inputs, by
+ // extending `ImplicitCastInputTypes` or updating type coercion rules
directly.
+ //
+ // It's much simpler if the SQL function can be implemented with existing
expression(s). There are
+ // a few cases:
+ // - The function is simply an alias of another function. We can just
register the same
+ // expression with a different function name, e.g.
`expression[Rand]("random", true)`.
+ // - The function is mostly the same with another function, but has a
different parameter list.
+ // We can use `RuntimeReplaceable` to create a new expression, which can
customize the
+ // parameter list and analysis behavior (type coercion). The
`RuntimeReplaceable` expression
+ // will be replaced by the actual expression at the end of analysis. See
`Left` as an example.
Review comment:
Is `RuntimeReplaceable` replaced by the optimizer or the analyzer? Below
it says by optimizer, but here seems by the analyzer?
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