Difference between two syntaxes of join (pyspark)

I have a question about the difference two syntaxes of join in PySpark,

For example, I have these two dataframes

DF1

ID	NAME
1	OLIVER
2	MICHAEL
3	JUSTIN

DF2

ID	address
1	BRAZIL
1	FRANCE
2	PORTUGAL
2	ARGENTINA
3	MEXICO

Usually I use:

df1.join(df2, (col('df1.ID') == col('df2.ID')), 'left')

But sometimes I see people using:

df1.join(df2, 'ID', 'left')

So, my question is, what is the difference between this two codes?

I'm trying to understand the difference between the first and second syntax of join.

Solution

All of the following mean the same thing:

Join	Desc	Type of second arg `on`
`df1.join(df2, 'ID')`	a string for the join column name	`str`
`df1.join(df2, ['ID'])`	a list of column names	`List[str]`
`df1.join(df2, col('df1.ID') == col('df2.ID'))`	a join expression (Column)	`pyspark.sql.column.Column`
`df1.join(df2, df1.ID == df2.ID)`	a join expression (Column)	`pyspark.sql.column.Column`

If you had a composite key of two columns (ck1, ck2) instead of single ID. All of the following mean the same thing:

Join	Desc	Type of second arg `on`
`df1.join(df2, ['ck1', 'ck1'])`	a list of column names	`List[str]`
`df1.join(df2, [col('df1.pk1') == col('df2.pk1'), col('df1.pk2') == col('df2.pk2')])`	list of join expressions	`List[pyspark.sql.column.Column]`
`df1.join(df2, [df1.ck1 == df2.ck1, df1.ck2 == df2.ck2])`	list of join expressions	`List[pyspark.sql.column.Column]`

Ignoring the how='left' as it's same

As documentation of DataFrame.join() says:

DataFrame.join(other: pyspark.sql.dataframe.DataFrame, 
               on: Union[
                       str,
                       List[str],
                       pyspark.sql.column.Column,
                       List[pyspark.sql.column.Column],
                       None
                    ] = None,
               how: Optional[str] = None
            ) → pyspark.sql.dataframe.DataFrame[source]

on: str, list or Column, optional

a string for the join column name,

a list of column names,

a join expression (Column), or

a list of Columns.

If on is a string or a list of strings indicating the name of the join column(s), the column(s) must exist on both sides, and >this performs an equi-join.