常用的ArrayType类型列操作: array(将两个表合并成array)、array_contains、array_distinct、array_except(两个array的差集)、array_intersect(两个array的交集不去重)、array_join、array_max、array_min、array_position(返回指定元素在array中的索引,索引值从1开始,若不存在则返回0)、array_remove、array_repeat、a...
from pyspark.sql.functions import col df_casted = df_customer.withColumn("c_custkey", col("c_custkey").cast(StringType())) print(type(df_casted)) Remove columnsTo remove columns, you can omit columns during a select or select(*) except or you can use the drop method:Python Копи...
可以在窗口上对ignorenulls=True使用first函数。但是您需要标识manufacturer的组,以便按该group进行分区。 因为您没有给出任何ID列,所以我使用monotonically_increasing_id和累积条件和来创建一个组列: from pyspark.sql import functions as Fdf1 = df.withColumn( "row_id", F.monotonically_increasing_id()).withCo...
.array_distinct('my_array'))# Map over & transform array elements – F.transform(col, func: col -> col)df=df.withColumn('elem_ids',F.transform(F.col('my_array'),lambdax:x.getField('id')))# Return a row per array element – F.explode(col)df=df.select(F.explode('my_array')...
from pyspark.sql.functions import asc, desc_nulls_last expressions = dict(horsepower="avg", weight="max", displacement="max") orderings = [ desc_nulls_last("max(displacement)"), desc_nulls_last("avg(horsepower)"), asc("max(weight)"), ] df = auto_df.groupBy("modelyear").agg(express...
class pyspark.sql.types.BinaryType[source] Binary (byte array) data type. class pyspark.sql.types.BooleanType[source] Boolean data type. class pyspark.sql.types.DateType[source] Date (datetime.date) data type. EPOCH_ORDINAL = 719163 fromInternal(v)[source] needConversion()[source] ...
from pyspark.sql.functions import col df_casted = df_customer.withColumn("c_custkey", col("c_custkey").cast(StringType())) print(type(df_casted)) Remove columnsTo remove columns, you can omit columns during a select or select(*) except or you can use the drop method:Python...
from pyspark.sql.functions import asc, desc_nulls_last expressions = dict(horsepower="avg", weight="max", displacement="max") orderings = [ desc_nulls_last("max(displacement)"), desc_nulls_last("avg(horsepower)"), asc("max(weight)"), ] df = auto_df.groupBy("modelyear").agg(express...