你可以使用一个技巧，将column.isNull（）转换为int，然后计算它们的和。如果和大于0，则为真。
PYSPARK WHEN a function used with PySpark in DataFrame to derive a column in a Spark DataFrame. It is also used to update an existing column in a DataFrame. Any existing column in a DataFrame can be updated with the when function based on certain conditions needed. PySpark DataFrame uses SQL...
在SQL中，IN需要一个元素列表，因此需要在元素两边加上括号
# create a new col based on another col's value data = data.withColumn('newCol', F.when(condition, value)) # multiple conditions data = data.withColumn("newCol", F.when(condition1, value1) .when(condition2, value2) .otherwise(value3)) 自定义函数(UDF) # 1. define a python function...
PySpark Where Filter Function | Multiple Conditions PySpark String Functions with Examples PySpark Column Class | Operators & Functions References In conclusion, PySpark Window functions are analytical functions that operate on a subset of rows, known as a window, within a larger result set. They are...
Add a column with multiple conditions To set a new column's values when using withColumn, use the when / otherwise idiom. Multiple when conditions can be chained together. from pyspark.sql.functions import col, when df = auto_df.withColumn( "mpg_class", when(col("mpg") <= 20, "low"...
To filter on multiple conditions, use logical operators. For example, & and | enable you to AND and OR conditions, respectively. The following example filters rows where the c_nationkey is equal to 20 and c_acctbal is greater than 1000.Python Копирај ...
PySpark When Otherwise and SQL Case When on DataFrame with Examples – Similar to SQL and programming languages, PySpark supports a way to check multiple conditions in sequence and returns a value when the first condition met by using SQL like case when and when().otherwise() expressions, ...
By default, StringIndexer throws an error when it comes across an unseen label. To handle such cases, you can set the handleInvalid1 parameter to 'skip', 'keep', or 'error', depending on your requirements. For instance, consider a dataset with a “Color” column containing the values “...
What I have found out is that under some conditions (e.g. when you rename fields in a Sqoop or Pig job), the resulting Parquet Files will differ in the fact that the Sqoop job will ALWAYS create Uppercase Field Names, where the corresponding Pig Job does not do th...