pyspark split string into rows

I understand your pain. Using split() can work, but can also lead to breaks. Let's take your df and make a slight change to it: df = spark.createDa Aggregate function: returns the average of the values in a group. Lets see with an example Collection function: returns an array of the elements in the union of col1 and col2, without duplicates. Returns a new row for each element in the given array or map. Substring starts at pos and is of length len when str is String type or returns the slice of byte array that starts at pos in byte and is of length len when str is Binary type. Returns an array of elements after applying a transformation to each element in the input array. Returns the hex string result of SHA-2 family of hash functions (SHA-224, SHA-256, SHA-384, and SHA-512). In this example we will create a dataframe containing three columns, one column is Name contains the name of students, the other column is Age contains the age of students, and the last and third column Courses_enrolled contains the courses enrolled by these students. If you do not need the original column, use drop() to remove the column. Convert time string with given pattern (yyyy-MM-dd HH:mm:ss, by default) to Unix time stamp (in seconds), using the default timezone and the default locale, return null if fail. One can have multiple phone numbers where they are separated by ,: Create a Dataframe with column names name, ssn and phone_number. A Computer Science portal for geeks. Aggregate function: returns the number of items in a group. @udf ("map

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