2. Drop Duplicate Columns After Join If you notice above Join DataFrameemp_idis duplicated on the result, In order to remove this duplicate column, specify the join column as an array type or string. The below example uses array type. Note:In order to use join columns as an array, you ...
A Left Semi Join in PySpark returns only the rows from the left DataFrame (the first DataFrame mentioned in the join operation) where there is a match with the right DataFrame (the second DataFrame). It does not include any columns from the right DataFrame in the resulting DataFrame. This j...
>>> df.join(df2,'name','inner').drop('age','height').collect()[Row(name=u'Bob')] New in version 1.4. dropDuplicates(subset=None)[source] Return a new DataFrame with duplicate rows removed, optionally only considering certain columns. ...
# Left join in another datasetdf=df.join(person_lookup_table,'person_id','left')# Match on different columns in left & right datasetsdf=df.join(other_table,df.id==other_table.person_id,'left')# Match on multiple columnsdf=df.join(other_table, ['first_name','last_name'],'left')...
# Labels columns (train_df.groupby('labels2').count().show()) (train_df.groupby('labels5').count().sort(sql.desc('count')).show()) +---+---+ |labels2|count| +---+---+ | normal|67343| | attack|58630| +---+---+ +---+---+ |labels5|count| +---+---+ | normal...