map(x=>(x,null)).reduceByKey((x,y)=>x,numPartitions).map(_._1) 这个过程是,先通过map映射每个元素和null,然后通过key(此时是元素)统计{reduceByKey就是对元素为KV对的RDD中Key相同的元素的Value进行binary_function的reduce操作,因此,Key相同的多个元素的值被reduce为一个值,然后与原RDD中的Key组成一...
2. PySpark distinct() pyspark.sql.DataFrame.distinct()is used to get the unique rows from all the columns from DataFrame. This function doesn’t take any argument and by default applies distinct on all columns. 2.1 distinct Syntax Following is the syntax on PySpark distinct. Returns a new Da...
By using countDistinct() PySpark SQL function you can get the count distinct of the DataFrame that resulted from PySpark groupBy(). countDistinct() is used to get the count of unique values of the specified column. Advertisements When you perform group by, the data having the same key are ...
when we invoke thedistinct()method on the pyspark dataframe, the duplicate rows are dropped. After this, when we invoke thecount()method on the output of thedistinct()method, we get the number of distinct rows in the given pyspark dataframe. ...
• Trying to use INNER JOIN and GROUP BY SQL with SUM Function, Not Working • Multiple INNER JOIN SQL ACCESS • How to select all rows which have same value in some column • Eliminating duplicate values based on only one column of the table • How can I delete using INNER JOI...
In this PySpark SQL article, you have learneddistinct()the method that is used to get the distinct values of rows (all columns) and also learned how to usedropDuplicates()to get the distinct and finally learned to use dropDuplicates() function to get distinct multiple columns. ...