[英]Pyspark - How to set the schema when reading parquet file from another DF?
我有带架构的 DF1:
df1 = spark.read.parquet(load_path1)
df1.printSchema()
root
|-- PRODUCT_OFFERING_ID: string (nullable = true)
|-- CREATED_BY: string (nullable = true)
|-- CREATION_DATE: string (nullable = true)
和DF2:
df2 = spark.read.parquet(load_path2)
df2.printSchema()
root
|-- PRODUCT_OFFERING_ID: decimal(38,10) (nullable = true)
|-- CREATED_BY: decimal(38,10) (nullable = true)
|-- CREATION_DATE: timestamp (nullable = true)
现在我想联合这两个数据框..
有时,当我尝试联合这两个 DF 时,它会因为不同的模式而出错..
如何将 DF2 设置为与 DF1 具有完全相同的架构(在加载期间)?
我试过:
df2 = spark.read.parquet(load_path2).schema(df1.schema)
获取错误:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: 'StructType' object is not callable
或者我应该改为 CAST (一旦 DF2 被读取)?
谢谢。
在.parquet()
.schema()
之前移动.schema()
然后 spark 将读取具有指定架构的 parquet 文件
df2 = spark.read.schema(df1.schema).parquet(load_path2)
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