Github user andrewor14 commented on a diff in the pull request:
https://github.com/apache/spark/pull/12117#discussion_r58282309
--- Diff:
sql/hive/src/main/scala/org/apache/spark/sql/hive/HiveSessionCatalog.scala ---
@@ -112,4 +124,121 @@ class HiveSessionCatalog(
metastoreCatalog.cachedDataSourceTables.getIfPresent(key)
}
+ override def makeFunctionBuilder(funcName: String, className: String):
FunctionBuilder = {
+ makeFunctionBuilder(funcName, Utils.classForName(className))
+ }
+
+ /**
+ * Construct a [[FunctionBuilder]] based on the provided class that
represents a function.
+ */
+ private def makeFunctionBuilder(name: String, clazz: Class[_]):
FunctionBuilder = {
+ // When we instantiate hive UDF wrapper class, we may throw exception
if the input
+ // expressions don't satisfy the hive UDF, such as type mismatch,
input number
+ // mismatch, etc. Here we catch the exception and throw
AnalysisException instead.
+ (children: Seq[Expression]) => {
+ try {
+ if (classOf[UDF].isAssignableFrom(clazz)) {
+ val udf = HiveSimpleUDF(name, new
HiveFunctionWrapper(clazz.getName), children)
+ udf.dataType // Force it to check input data types.
+ udf
+ } else if (classOf[GenericUDF].isAssignableFrom(clazz)) {
+ val udf = HiveGenericUDF(name, new
HiveFunctionWrapper(clazz.getName), children)
+ udf.dataType // Force it to check input data types.
+ udf
+ } else if
(classOf[AbstractGenericUDAFResolver].isAssignableFrom(clazz)) {
+ val udaf = HiveUDAFFunction(name, new
HiveFunctionWrapper(clazz.getName), children)
+ udaf.dataType // Force it to check input data types.
+ udaf
+ } else if (classOf[UDAF].isAssignableFrom(clazz)) {
+ val udaf = HiveUDAFFunction(
+ name,
+ new HiveFunctionWrapper(clazz.getName),
+ children,
+ isUDAFBridgeRequired = true)
+ udaf.dataType // Force it to check input data types.
+ udaf
+ } else if (classOf[GenericUDTF].isAssignableFrom(clazz)) {
+ val udtf = HiveGenericUDTF(name, new
HiveFunctionWrapper(clazz.getName), children)
+ udtf.elementTypes // Force it to check input data types.
+ udtf
+ } else {
+ throw new AnalysisException(s"No handler for Hive UDF
'${clazz.getCanonicalName}'")
+ }
+ } catch {
+ case ae: AnalysisException =>
+ throw ae
+ case NonFatal(e) =>
+ val analysisException =
+ new AnalysisException(s"No handler for Hive UDF
'${clazz.getCanonicalName}': $e")
+ analysisException.setStackTrace(e.getStackTrace)
+ throw analysisException
+ }
+ }
+ }
+
+ // We have a list of Hive built-in functions that we do not support. So,
we will check
+ // Hive's function registry and lazily load needed functions into our
own function registry.
+ // Those Hive built-in functions are
+ // assert_true, collect_list, collect_set, compute_stats,
context_ngrams, create_union,
+ // current_user ,elt, ewah_bitmap, ewah_bitmap_and, ewah_bitmap_empty,
ewah_bitmap_or, field,
+ // histogram_numeric, in_file, index, inline, java_method, map_keys,
map_values,
+ // matchpath, ngrams, noop, noopstreaming, noopwithmap,
noopwithmapstreaming,
+ // parse_url, parse_url_tuple, percentile, percentile_approx,
posexplode, reflect, reflect2,
+ // regexp, sentences, stack, std, str_to_map, windowingtablefunction,
xpath, xpath_boolean,
+ // xpath_double, xpath_float, xpath_int, xpath_long, xpath_number,
+ // xpath_short, and xpath_string.
+ override def lookupFunction(name: String, children: Seq[Expression]):
Expression = {
+ Try(super.lookupFunction(name, children)) match {
+ case Success(expr) => expr
+ case Failure(error) =>
+ if (functionRegistry.functionExists(name)) {
+ // If the function actually exists in functionRegistry, it means
that there is an
+ // error when we create the Expression using the given children.
+ // We need to throw the original exception.
+ throw error
--- End diff --
This pattern is kind of weird. We don't need to do a `Try` here and then
turn around and check the `functionRegistry`. Just check the registry directly,
then, if it does not contain `name`, then ask Hive assuming it's a built-in
function.
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