由于您没有指定您遇到的错误，我假设您看到的内容与我看到的类似：

pyspark.errors.exceptions.captured.AnalysisException: Since Spark 2.3, the queries from raw JSON/CSV files are disallowed when the
referenced columns only include the internal corrupt record column
(named _corrupt_record by default). For example:
spark.read.schema(schema).csv(file).filter($"_corrupt_record".isNotNull).count()
and spark.read.schema(schema).csv(file).select("_corrupt_record").show().
Instead, you can cache or save the parsed results and then send the same query.
For example, val df = spark.read.schema(schema).csv(file).cache() and then
df.filter($"_corrupt_record".isNotNull).count().

要修复它，您需要使用以下命令：

spark.read.option("multiline","true").json("json file path")

下面是一个例子：

cat /Users/yuri/test.json 
{
    "name": "Yuri",
    "gender": "male"
}

下面是pyspark代码：

df = spark.read.option("multiline","true").json("/Users/yuri/test.json")
df.printSchema()
df.show(truncate=False)

下面是输出：

>>> df.printSchema()
root
 |-- gender: string (nullable = true)
 |-- name: string (nullable = true)

>>> df.show(truncate=False)
+------+----+
|gender|name|
+------+----+
|male  |Yuri|
+------+----+