删除空列[PySpark]的快速方法

Question

是否有一种简单的方法可以在pyspark中删除巨大数据集（300+ col> 100k行）的空列？例如Python中的df.dropna(axis=1,how='all')

Answer 1

是，您可以简单地使用：

import pyspark.sql.functions as F

# Sample data
df = pd.DataFrame({'x1': ['a', '1', '2'],
                   'x2': ['b', None, '2'],
                   'x3': ['c', '0', '3'] })
df = sqlContext.createDataFrame(df)
df.show()

def drop_null_columns(df):
    """
    This function drops all columns which contain null values.
    :param df: A PySpark DataFrame
    """
    null_counts = df.select([F.count(F.when(F.col(c).isNull(), c)).alias(c) for c in df.columns]).collect()[0].asDict()
    to_drop = [k for k, v in null_counts.items() if v > 0]
    df = df.drop(*to_drop)
    return df

# Drops column b2, because it contains null values
drop_null_columns(df).show()

输出

+---+---+
| x1| x3|
+---+---+
|  a|  c|
|  1|  0|
|  2|  3|
+---+---+

x2列已删除