lirui-apache commented on a change in pull request #13144:
URL: https://github.com/apache/flink/pull/13144#discussion_r475425845
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File path:
flink-connectors/flink-connector-hive/src/main/java/org/apache/flink/table/functions/hive/HiveScalarFunction.java
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@@ -104,4 +142,62 @@ public Object eval(Object... args) {
* Evaluation logical, args will be wrapped when is a single array.
*/
protected abstract Object evalInternal(Object[] args);
+
+ private Tuple2<Object[], DataType[]> getConstantArgAndTypes(CallContext
callContext) {
+ DataType[] inputTypes =
callContext.getArgumentDataTypes().toArray(new DataType[0]);
+ Object[] constantArgs = new Object[inputTypes.length];
+ for (int i = 0; i < constantArgs.length; i++) {
+ if (callContext.isArgumentLiteral(i)) {
+ constantArgs[i] = callContext.getArgumentValue(
+ i,
ClassLogicalTypeConverter.getDefaultExternalClassForType(inputTypes[i].getLogicalType()))
+ .orElse(null);
+ }
+ }
+ return Tuple2.of(constantArgs, inputTypes);
+ }
+
+ /**
+ * Validate input argument types and decide result type.
+ */
+ protected abstract DataType validateInputTypes(DataType[] argTypes)
throws UDFArgumentException;
+
+ private class HiveUDFOutputStrategy implements TypeStrategy {
+
+ @Override
+ public Optional<DataType> inferType(CallContext callContext) {
+ Tuple2<Object[], DataType[]> constantArgAndTypes =
getConstantArgAndTypes(callContext);
+ return
Optional.ofNullable(getHiveResultType(constantArgAndTypes.f0,
constantArgAndTypes.f1));
+ }
+ }
+
+ private class HiveUDFInputStrategy implements InputTypeStrategy {
Review comment:
I think this is needed for input type validation. For example, according
to the API contract, a `ValidationException` can be thrown if the input is
invalid, but this should only happen during input inference rather than output
inference.
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