HyukjinKwon commented on code in PR #45692:
URL: https://github.com/apache/spark/pull/45692#discussion_r1538390049
##########
sql/core/src/test/scala/org/apache/spark/sql/CsvFunctionsSuite.scala:
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@@ -768,4 +768,32 @@ class CsvFunctionsSuite extends QueryTest with
SharedSparkSession {
context = ExpectedContext(fragment = "to_csv",
getCurrentClassCallSitePattern)
)
}
+
+ test("SPARK-47497: to_csv support the data of nested structure as pretty
strings") {
+ // The item of the Array is a Map
+ val rows = new java.util.ArrayList[Row]()
+ rows.add(Row(1L, Row(2L, "Alice",
+ Array(Map("math" -> 100L, "english" -> 200L, "science" -> null),
+ Map("math" -> 300L, "english" -> 400L, "science" -> 500L)))))
+
+ val valueSchema = StructType(Seq(
+ StructField("age", LongType),
+ StructField("name", StringType),
+ StructField("scores", ArrayType(MapType(StringType, LongType)))))
+ val schema = StructType(Seq(
+ StructField("key", LongType),
+ StructField("value", valueSchema)))
+
+ val df = spark.createDataFrame(rows, schema)
+ val actual1 = df.select(to_csv($"value"))
+ checkAnswer(actual1, Row("2,Alice," +
+ "\"[{math -> 100, english -> 200, science ->}, " +
Review Comment:
What about Spark Connect with Python?
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