Jark Wu created FLINK-11961:
-------------------------------
Summary: Clear up and refactor the code generation of scalar
functions and operators
Key: FLINK-11961
URL: https://issues.apache.org/jira/browse/FLINK-11961
Project: Flink
Issue Type: Improvement
Components: SQL / Planner
Reporter: Jark Wu
Currently, the code generation of scalar functions and operators are complex
and messy.
There are several ways to support codegen for a function/operator:
(1) Implement {{generate...}} in {{ScalarOperatorGens}} and invoke it in the
big match pattern of {{ExprCodeGenerator}}.
(2) Implement a {{CallGenerator}} and add it to {{FunctionGenerator}}.
(3) Implement a util method and add it to {{BuiltinMethods}} and
{{FunctionGenerator}}.
It will confuse developer which is the most efficient way to implement a
function.
In this issue, we will propose a unified way to code generate
functions/operators.
Some initial idea:
1. Introduce an {{ExprCodeGen}} interface, and all the function/operators
should extend this to implement the {{codegen}} method. It's like a combination
of {{PlannerExpression}} and {{CallGenerator}}.
2. Rename {{ExprCodeGenerator}} to {{RexCodeGenerator}}.
3. Use a big match pattern to mapping {{RexCall}} to specific {{ExprCodeGen}}
{code:scala}
trait ExprCodeGen {
def operands: Seq[GeneratedExpression]
def resultType: InternalType
def codegen(ctx: CodeGeneratorContext): GeneratedExpression
}
case class ConcatCodeGen(operands: Seq[GeneratedExpression]) extends
ExprCodeGen {
override def resultType: InternalType = InternalTypes.STRING
override def codegen(ctx: CodeGeneratorContext): GeneratedExpression = {
nullSafeCodeGen(ctx) {
terms => s"$BINARY_STRING.concat(${terms.mkString(", ")})"
}
}
}
{code}
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