To count the values in a column of a pyspark dataframe, we will first select the particular column using theselect()method by passing the column name as input to theselect()method. Next, we will use thecount()method to count the number of values in the selected column as shown in the ...
column_name is the column to get the total number of rows (count). Example 1: Single Column This example will get the count from the height column in the PySpark dataframe. #import the pyspark module import pyspark #import SparkSession for creating a session from pyspark.sql import SparkSess...
In this PySpark article, you have learned how to get the number of unique values of groupBy results by using countDistinct(), distinct().count() and SQL . All these methods are used to get the count of distinct values of the specified column and apply this to group by results to get ...
In PySpark, you can usedistinct().count()of DataFrame orcountDistinct()SQL function to get the count distinct. Advertisements distinct()eliminates duplicate records(matching all columns of a Row) from DataFrame, count() returns the count of records on DataFrame. By chaining these you can get t...
写在前面的话：用了好久group by，今天早上一觉醒来，突然感觉group by好陌生，总有个筋别不过来，...
使用tuple unpacking传递值
frompyspark.sqlimportfunctionsasF# 统计distinct数量distinct_count=data.select(target_column).distinct().count()# 使用collect_set收集所有唯一值unique_values=data.select(F.collect_set(target_column)).first()[0]# 输出结果print(f"Distinct count of{target_column}:{distinct_count}")print(f"Unique val...
importpysparkfrompyspark.sqlimportSparkSession sc=SparkSession.builder.master("local")\ .appName('first_name1')\ .config('spark.executor.memory','2g')\ .config('spark.driver.memory','2g')\ .enableHiveSupport()\ .getOrCreate() sc.sql('''drop table test_youhua.test_avg_medium_freq'''...
# 需要导入模块: from pyspark.sql import functions [as 别名]# 或者: from pyspark.sql.functions importcountDistinct[as 别名]defis_unique(self):""" Return boolean if values in the object are unique Returns --- is_unique : boolean >>> ...
from pyspark.sql import SparkSession sc=SparkSession.builder.master("local")\ .appName('first_name1')\ .config('spark.executor.memory','2g')\ .config('spark.driver.memory','2g')\ .enableHiveSupport()\ .getOrCreate()sc.sql(''' drop table test_youhua.test_avg_medium_freq ''')sc....