[SPARK-31261][SQL] Avoid npe when reading bad csv input with `columnN…

…ameCorruptRecord` specified

### What changes were proposed in this pull request?

SPARK-25387 avoids npe for bad csv input, but when reading bad csv input with `columnNameCorruptRecord` specified, `getCurrentInput` is called and it still throws npe.

### Why are the changes needed?

Bug fix.

### Does this PR introduce any user-facing change?

No.

### How was this patch tested?

Add a test.

Closes #28029 from wzhfy/corrupt_column_npe.

Authored-by: Zhenhua Wang <wzh_zju@163.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
(cherry picked from commit 791d2ba)
Signed-off-by: HyukjinKwon <gurwls223@apache.org>

sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/csv/UnivocityParser.scala

@@ -82,7 +82,8 @@ class UnivocityParser(
 
   // Retrieve the raw record string.
   private def getCurrentInput: UTF8String = {
-    UTF8String.fromString(tokenizer.getContext.currentParsedContent().stripLineEnd)
+    val currentContent = tokenizer.getContext.currentParsedContent()
+    if (currentContent == null) null else UTF8String.fromString(currentContent.stripLineEnd)
   }
 
   // This parser first picks some tokens from the input tokens, according to the required schema,

sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/csv/CSVSuite.scala

@@ -1822,6 +1822,20 @@ class CSVSuite extends QueryTest with SharedSQLContext with SQLTestUtils with Te
     assert(spark.read.csv(input).collect().toSet == Set(Row()))
   }
 
+  test("SPARK-31261: bad csv input with `columnNameCorruptRecord` should not cause NPE") {
+    val schema = StructType(
+      StructField("a", IntegerType) :: StructField("_corrupt_record", StringType) :: Nil)
+    val input = spark.createDataset(Seq("\u0000\u0000\u0001234"))
+
+    checkAnswer(
+      spark.read
+        .option("columnNameOfCorruptRecord", "_corrupt_record")
+        .schema(schema)
+        .csv(input),
+      Row(null, null))
+    assert(spark.read.csv(input).collect().toSet == Set(Row()))
+  }
+
   test("field names of inferred schema shouldn't compare to the first row") {
     val input = Seq("1,2").toDS()
     val df = spark.read.option("enforceSchema", false).csv(input)