Spark Legacy Configuration

[satyasyamnn]

net.jgp.books.spark.ch03/src/main/java/net/jgp/books/spark/ch03/lab320_dataset_books_to_dataframe/CsvToDatasetBookToDataframeApp.java

Line 110 in 1362aa6

to_date(df2.col("releaseDateAsString"), "yyyy-MM-dd"))

When this code is run using Spark version 3.1.2 I got an error

Caused by: org.apache.spark.SparkUpgradeException: You may get a different result due to the upgrading of Spark 3.0: Fail to parse '2065-10-6' in the new parser. You can set spark.sql.legacy.timeParserPolicy to LEGACY to restore the behavior before Spark 3.0, or set to CORRECTED and treat it as an invalid datetime string.
at org.apache.spark.sql.catalyst.util.DateTimeFormatterHelper$$anonfun$checkParsedDiff$1.applyOrElse(DateTimeFormatterHelper.scala:150)

The fix for this issue is to add the following lines of code

    SparkConf conf = new SparkConf().setAppName("Spark In Action").setMaster("local[*]");
    conf.set("spark.sql.legacy.timeParserPolicy", "LEGACY");

To make it work in Spark 3 what kind of formatting is required?