@@ -21,8 +21,8 @@
 /**
  * Pushes Spark's nested schema pruning down to the native scan, and resolves the read schema against each file.
  *
- * <p>Columns and struct fields resolve by name under Spark's case sensitivity, so a file can store a struct's fields
- * in another order, in another case, or without some nullable fields, and still read correctly.
+ * <p>Columns and struct fields resolve by name under Spark's case sensitivity, so a file can store a struct's fields in
+ * another order, in another case, or without some nullable fields, and still read correctly.
  *
  * <p>Only struct fields are pruned and resolved by name. Structs inside arrays and maps, and extension types that
  * export as Arrow structs such as Variant, are read whole and by position, since projecting each element needs a
 
@@ -175,14 +175,19 @@ public void filesWithDifferentStructs(@TempDir Path tempDir) {
                 "[[0,[10,20,null]], [1,[11,21,null]], [2,[12,22,32]], [3,null]]");
         assertMatchesParquet(parquet, vortex, schema, data -> data.selectExpr("id", "c"));
         assertMatchesParquet(parquet, vortex, schema, data -> data.selectExpr("id", "c.y", "c.z"));
-        assertMatchesParquet(parquet, vortex, schema, data -> data.where("c.x > 10").selectExpr("id", "c.y"));
+        assertMatchesParquet(
+                parquet, vortex, schema, data -> data.where("c.x > 10").selectExpr("id", "c.y"));
     }
 
     @Test
     @DisplayName("A struct read over a field the file stores as another type fails and names the field")
     public void structOverAnotherType(@TempDir Path tempDir) {
         String path = tempDir.resolve("vortex").toString();
-        spark.range(2).selectExpr("id", "named_struct('a', id) AS s").write().format("vortex").save(path);
+        spark.range(2)
+                .selectExpr("id", "named_struct('a', id) AS s")
+                .write()
+                .format("vortex")
+                .save(path);
 
         Exception thrown = assertThrows(Exception.class, () -> spark.read()
                 .schema("id BIGINT, s STRUCT<a: STRUCT<x: BIGINT>>")
Original file line number	Diff line number	Diff line change
`@@ -21,8 +21,8 @@`
`21`	`21`	`/**`
`22`	`22`	`* Pushes Spark's nested schema pruning down to the native scan, and resolves the read schema against each file.`
`23`	`23`	`*`
`24`		`- * <p>Columns and struct fields resolve by name under Spark's case sensitivity, so a file can store a struct's fields`
`25`		`- * in another order, in another case, or without some nullable fields, and still read correctly.`
	`24`	`+ * <p>Columns and struct fields resolve by name under Spark's case sensitivity, so a file can store a struct's fields in`
	`25`	`+ * another order, in another case, or without some nullable fields, and still read correctly.`
`26`	`26`	`*`
`27`	`27`	`* <p>Only struct fields are pruned and resolved by name. Structs inside arrays and maps, and extension types that`
`28`	`28`	`* export as Arrow structs such as Variant, are read whole and by position, since projecting each element needs a`