In this article, you have learned how to add a new column and multiple columns to Spark DataFrame using withColumn(), select(), lit(), map() functions by working with Scala example. The complete source code is available at GitHub project 7. Continue to define any other column properties in the Column Properties tab. Note You can change the default value in the Options dialog box under Database Tools. Data type is a required value, and is assigned the default value if you don't choose one. When(col("Salary") >=40000 & col("Salary") 1, "b" -> 2))) Press the TAB key to go to the Data Type cell and select a data type from the dropdown list. If you closely look at the above snippet, DataFrame has 3 columns and we are deriving multiple columns dynamically from existing columns by applying transformations, this can be a split() function or any custom UDF and finally dropping an existing column. And store these column vlaues into c5,c6,c7,c8,c9,10 Apply transformation on these columns and derive multiple columns Let's assume DF has just 3 columns c1,c2,c3 I will update this once I have a Scala example. By the way, I prefer to name such a column HistoryId, so it matches the names of the columns in foreign key relationships. The more complicated constraint index is useful when you actually want to change the options. I don’t have a real-time scenario to add multiple columns, below is just a skeleton on how to use. CREATE TABLE History ( ID int primary key IDENTITY(1,1) NOT NULL. However, sometimes you may need to add multiple columns after applying some transformations n that case you can use either map() or foldLeft(). You can add multiple columns to Spark DataFrame in several ways if you wanted to add a known set of columns you can easily do by chaining withColumn() or on select(). |EmpId|Salary|lit_value1|lit_value2|typedLit_seq| typedLit_map|typedLit_struct| |- typedLit_struct: struct (nullable = false) ![]() | |- value: integer (valueContainsNull = false) | |- element: integer (containsNull = false) ![]() |- typedLit_seq: array (nullable = false)
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