scala – 从Apache Spark中的Avro文件读取不受支持的联合类型组

import com.databricks.spark.avro._
val sqlContext = new org.apache.spark.sql.SQLContext(sc)
val df = sqlContext.read.avro("gs://logs.xyz.com/raw/2016/04/20/div1/div2/2016-04-20-08-28-35.UTC.blah-blah.avro")

并得到

java.lang.UnsupportedOperationException: This mix of union types is not supported (see README): ArrayBuffer(STRING)

自述文件清楚地说明：

This library supports reading all Avro types,with the exception of
complex union types. It uses the following mapping from Avro types to
Spark SQL types:

当我尝试对同一个文件进行文本读取时,我可以看到模式

val df = sc.textFile("gs://logs.xyz.com/raw/2016/04/20/div1/div2/2016-04-20-08-28-35.UTC.blah-blah.avro")
df.take(2).foreach(println)

{“name”:”log_record”,”type”:”record”,”fields”:[{“name”:”request”,”type”:{“type”:”record”,”name”:”request_data”,”fields”:[{“name”:”datetime”,”type”:”string”},{“name”:”ip”,{“name”:”host”,{“name”:”uri”,{“name”:”request_uri”,{“name”:”referer”,{“name”:”useragent”,”type”:”string”}]}}

<——- an excerpt of the full reply ——->

因为我几乎没有控制我得到这些文件的格式,
我的问题在这里 – 有没有一个测试和可以推荐的解决方法？

我用gc dataproc

MASTER=yarn-cluster spark-shell –num-executors 4 –executor-memory 4G –executor-cores 4 –packages com.databricks:spark-avro_2.10:2.0.1,com.databricks:spark-csv_2.11:1.3.0

任何帮助将不胜感激…..