String to Date Conversion in PySpark DataFrames

Hello, in this blog post, we will explore the process of converting DataFrame column data types from string to Date and uncover the numerous methods available under PySpark functions. Before we delve into the methods, let's begin by creating a sample DataFrame to work with

<<please click on each image to see it clearly>>

Method 1: Using CAST() for Date Conversion

• CAST() is a powerful function accessible through pyspark.sql.Column API.
• This method allows you to create a new column with the desired datatype, making it ideal for converting date strings to Date format effortlessly

Syntax: cast(column: pyspark.sql.Column, Parameter: StringType)

Parameter: The type to convert the column to. It specifies the desired data type for the column conversion. For date conversion, the parameter should be "date" or "DateType()".

Method 2: Using to_date() for Date Conversion

1. PySpark SQL Functions offer the to_date() function to convert strings to Date datatype in a DataFrame column.
2. Syntax: to_date(col: "<column>", format: "<the format the data actually in the column>")

The format parameter is optional and allows you to specify the format of the date data present in the column.

In the below example, I have demonstrated both the simple use of to_date and the use of unix_timestamp in PySpark. Please note that in Synapse, when you have upgraded the Spark cluster to above 3.0, the "to_date" method may not work as expected. In such cases, you need to configure the Spark legacy property as shown below

 spark.conf.set("spark.sql.legacy.timeParserPolicy","Legacy")

Method 3: Python strptime() for Date Conversion

The strptime() function, available in Python, allows you to create a datetime object from a given string value.

Syntax: datetime.strptime("<string that needs to be converted to DateTime>", "<format Code the string is currently in>")

Now that we have explored different methods to convert strings to Date Data type in PySpark, it's important to understand that these functions behave differently when the underlying string data doesn't match the provided date format.

1. For Cast: If the underlying data doesn't conform to the specified format, it will return NULL.
2. For to_date(): it will return the converted data; otherwise, it will return NULL. here before returning NULL the function first attempts to truncate the values to match the specified format and outputs a valid date(but it will not be accurate).
3. For strptime(): Unlike the previous methods, strptime() will fail execution when the data doesn't match the given format. Additionally, it is time-consuming as it iterates through each value individually, making it less efficient for large datasets

Let us understand this with the below snapshots.

    

Thanks for reading the blog if any doubts or questions plz submit them in the comments section.

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