I have a tab separated file like this   Copyright details 2021 ID \t NUMBER \t ADDRESS \t ZIPCODE 10 \t 9877777777 \t India \t 400322 13 \t 2983359852 \t AUS \t 84534 26 \t 7832724424 34 \t 8238444294 \t RSA \t 74363 Here the first row is a comment and the row with ID 26 doesn't have ending columns values. Even it doesn't have \t at the end . So I need to read file skipping first line and handle missing delimiters at end. I tried this import org.apache.spark.sql.DataFrame val sqlContext = new org.apache.spark.sql.SQLContext(sc) import sqlContext.implicits._ val data = sc.textFile("sample_badtsv.txt") val comments = data.first() val fdata = data.filter(x => x != comments) val header = fdata.filter(x => x.split("\t")(1) == "NUMBER").collect().mkString val df = fdata.filter(x => x.split("\t")(1) != "NUMBER") .map(x => x.split("\t")) .map(x => (x(0),x(1),x(2),x(3))) .toDF(header.split("\t"): _*)     Since I have missing \t at the end of lines if empty, I am getting ArrayIndexoutofBoundsException. because when converting the rdd to dataframe we have less records for some rows.   Please provide me a better solution so that I can skip first line and read the file correctly (even there are no \t the code needs to consider it as NULL values at the end like below)   ID NUMBER ADDRESS ZIPCODE 10 9877777777 India 400322 13 2983359852 AUS 84534 26 7832724424 NULL NULL 34 8238444294 RSA 74363   ... View more