ganeshashree commented on code in PR #57888:
URL: https://github.com/apache/spark/pull/57888#discussion_r3751203876
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sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/json/JsonExpressionEvalUtils.scala:
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@@ -483,6 +483,36 @@ case class JsonTableEvaluator(containerPath:
Seq[PathInstruction], explodeRoot:
}
}
+ /**
+ * Resolves `containerPath` against a single JSON value, preserving the
missing / JSON-null /
+ * found distinction that [[evaluate]] collapses. Returns:
+ *
+ * - `None` if the input is not a single well-formed JSON value (malformed
/ trailing garbage /
+ * empty);
+ * - `Some(Missing)` if the path matches nothing;
+ * - `Some(NullValue)` if the path matches an explicit JSON `null`;
+ * - `Some(Found(raw))` if the path matches a value, where `raw` is its
verbatim JSON text
+ * (strings keep their enclosing quotes; an object/array is the whole
fragment).
+ *
+ * A `null` input is the caller's responsibility. `explodeRoot` is ignored:
this is a single-value
+ * lookup, so construct the evaluator with `explodeRoot = false`.
+ */
+ final def lookup(json: UTF8String): Option[JsonPathResult] = {
+ if (!isSingleWellFormedValue(json)) return None
Review Comment:
Done. lookup now uses a single parser: it navigates to and serializes the
matched value, then drainToRootEnd consumes the rest of the root and rejects
any trailing content, so malformed/trailing-garbage inputs are caught without
the second O(document size) pass.
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