AttributeError：“StructField”对象没有属性“_get_object_id”：使用自定义模式加载镶木地板文件

Question

我正在尝试使用 PySpark 使用自定义架构读取镶木地板文件组，但它给出 AttributeError: 'StructField' object has no attribute '_get_object_id' 错误。

这是我的示例代码：

import pyspark
from pyspark.sql import SQLContext, SparkSession
from pyspark.sql import Row
import pyspark.sql.functions as func
from pyspark.sql.types import *

sc = pyspark.SparkContext()
spark = SparkSession(sc)
sqlContext = SQLContext(sc)

l = [('1',31200,'Execute',140,'ABC'),('2',31201,'Execute',140,'ABC'),('3',31202,'Execute',142,'ABC'),
     ('4',31103,'Execute',149,'DEF'),('5',31204,'Execute',145,'DEF'),('6',31205,'Execute',149,'DEF')]
rdd = sc.parallelize(l)
trades = rdd.map(lambda x: Row(global_order_id=int(x[0]), nanos=int(x[1]),message_type=x[2], price=int(x[3]),symbol=x[4]))
trades_df = sqlContext.createDataFrame(trades)
trades_df.printSchema()
trades_df.write.parquet('trades_parquet')

trades_df_Parquet = sqlContext.read.parquet('trades_parquet')
trades_df_Parquet.printSchema()

# The schema is encoded in a string.
schemaString = "global_order_id message_type nanos price symbol"

fields = [StructField(field_name, StringType(), True) for field_name in schemaString.split()]
schema = StructType(fields)

trades_df_Parquet_n = spark.read.format('parquet').load('trades_parquet',schema,inferSchema =False)
#trades_df_Parquet_n = spark.read.parquet('trades_parquet',schema)
trades_df_Parquet_n.printSchema()

谁能帮我提一下你的建议。

Answer 1

指定选项名称schema，这样它就知道不是@​​987654322@：

Signature: trades_df_Parquet_n.load(path=None, format=None, schema=None, **options)

你得到：

trades_df_Parquet_n = spark.read.format('parquet').load('trades_parquet',schema=schema, inferSchema=False)