如何修复数据表的“无法读取未定义的属性'样式'”

如何解决如何修复数据表的“无法读取未定义的属性'样式'”

我在Datatables上使用Ajax，但是我隐藏了第一列。问题是该表必须通过另一个选项进行更新。因此，当我快速更改选项值时，会出现此错误：

from pyspark.sql import SparkSession
import pyspark.sql.functions as psf
from pyspark.sql.types import *
import io
import fastavro

def deserialize_avro(serialized_msg):
    bytes_io = io.BytesIO(serialized_msg)
    bytes_io.seek(0)
    avro_schema = {
                    "type": "record","name": "struct","fields": [
                      {"name": "col1","type": "long"},{"name": "col2","type": "string"}
                    ]
                  }

    deserialized_msg = fastavro.schemaless_reader(bytes_io,avro_schema)

    return (    deserialized_msg["col1"],deserialized_msg["col2"]
            )

if __name__=="__main__":
  spark = SparkSession \
        .builder \
        .appName("consume kafka message") \
        .getOrCreate()

  kafka_df = spark \
              .readStream \
              .format("kafka") \
              .option("kafka.bootstrap.servers","kafka01-broker:9092") \
              .option("subscribe","topic_name") \
              .option("stopGracefullyOnShutdown","true") \
              .load()

  df_schema = StructType([
              StructField("col1",LongType(),True),StructField("col2",StringType(),True)
          ])

  avro_deserialize_udf = psf.udf(deserialize_avro,returnType=df_schema)
  parsed_df = kafka_df.withColumn("avro",avro_deserialize_udf(psf.col("value"))).select("avro.*")

  query = parsed_df.writeStream.format("console").option("truncate","true").start()
  query.awaitTermination()

并且数据表的样式已损坏。显示了第一列，我不需要什么，整个表很奇怪。 这是我的代码：

Cannot read property 'style' of undefined
    at _fnCalculateColumnWidths
    at _fnAdjustColumnSizing
    at _fnInitComplete

如何解决？ 谢谢