Spark 2.3.0 Read Text File With Header Option Not Working

Question

The code below is working and creates a Spark dataframe from a text file. However, I'm trying to use the header option to use the first column as header and for some reason it doesn't seem to be happening. I cannot understand why! It must be something stupid but I cannot solve this.

>>>from pyspark.sql import SparkSession
>>>spark = SparkSession.builder.master("local").appName("Word Count")\
    .config("spark.some.config.option", "some-value")\
    .getOrCreate()
>>>df = spark.read.option("header", "true")\
    .option("delimiter", ",")\
    .option("inferSchema", "true")\
    .text("StockData/ETFs/aadr.us.txt")
>>>df.take(3)

Returns the following:

[Row(value=u'Date,Open,High,Low,Close,Volume,OpenInt'), Row(value=u'2010-07-21,24.333,24.333,23.946,23.946,43321,0'), Row(value=u'2010-07-22,24.644,24.644,24.362,24.487,18031,0')]

>>>df.columns

Returns the following:

['value']

Answer 1

Issue

The issue is that you are using .text api call instead of .csv or .load. If you read the .text api documentation, it says

def text(self, paths): """Loads text files and returns a :class:DataFrame whose schema starts with a string column named "value", and followed by partitioned columns if there are any. Each line in the text file is a new row in the resulting DataFrame. :param paths: string, or list of strings, for input path(s). df = spark.read.text('python/test_support/sql/text-test.txt') df.collect() [Row(value=u'hello'), Row(value=u'this')] """

Solution using .csv

Change the .text function call to .csv and you should be fine as

df = spark.read.option("header", "true") \
    .option("delimiter", ",") \
    .option("inferSchema", "true") \
    .csv("StockData/ETFs/aadr.us.txt")

df.show(2, truncate=False)

which should give you

+-------------------+------+------+------+------+------+-------+
|Date               |Open  |High  |Low   |Close |Volume|OpenInt|
+-------------------+------+------+------+------+------+-------+
|2010-07-21 00:00:00|24.333|24.333|23.946|23.946|43321 |0      |
|2010-07-22 00:00:00|24.644|24.644|24.362|24.487|18031 |0      |
+-------------------+------+------+------+------+------+-------+

Solution using .load

.load would assume the file to be of parquet format if a format option is not defined. So you would need a format option to be defined as well

df = spark.read\
    .format("com.databricks.spark.csv")\
    .option("header", "true") \
    .option("delimiter", ",") \
    .option("inferSchema", "true") \
    .load("StockData/ETFs/aadr.us.txt")

df.show(2, truncate=False)

I hope the answer is helpful