将数据框架构从 int 更改为 double 时出现问题

Question

我有一个数据框标签，我想将数据框的架构从整数更改为双精度

数据框的模式是

label.printSchema

root |-- value: integer (nullable = false)

我使用的命令是

label = label.withColumn('value', label.value.cast('double'))

我收到的错误是：

error: unclosed character literal

Answer 1

from pyspark.sql.types import DoubleType,IntegerType
cSchema = StructType([StructField("value",IntegerType())])
test_list = [[1],[2]]
df = spark.createDataFrame(test_list,schema=cSchema) 
df.printSchema()
castedDF = df.withColumn("value", df["value"].cast("double"))
castedDF.printSchema()
castedDF.show()

而且，输出是（如预期的那样）

root
 |-- value: integer (nullable = true)
root
 |-- value: double (nullable = true)
+-----+
|value|
+-----+
|  1.0|
|  2.0|
+-----+

Answer 2

label = label.withColumn("value", label("value").cast(DoubleType))

将数据框架构从 int 更改为 double 时出现问题

Issue in changing the dataframe schema from int to double

apache-spark

pyspark

spark-dataframe