Spark unable to read parquet file from partitioned S3 bucket - scala

Question

I have my S3 bucket partitioned like this:
bucket
|--2018
|--2019
|--01
|--02
|--01
|--files.parquet
...
It works fine when I read using this command (Spark 2.1.1):
val dfo = sqlContext.read.parquet("s3://bucket/2019/04/03/*")
but it hits an error when I try to add a partition variable to the path:
val dfo = sqlContext.read.parquet("s3://bucket/2019/04/day=03/*")
or
val dfo = sqlContext.read.parquet("s3://bucket/y=2019/m=04/day=03")
Error:
Name: org.apache.spark.sql.AnalysisException
Message: Path does not exist: s3://bucket/2019/04/day=03/*;
StackTrace: at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$14.apply(DataSource.scala:377)
at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$14.apply(DataSource.scala:370)
at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
at scala.collection.immutable.List.foreach(List.scala:381)
at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:241)
at scala.collection.immutable.List.flatMap(List.scala:344)
at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:370)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:152)
at org.apache.spark.sql.DataFrameReader.parquet(DataFrameReader.scala:441)
at org.apache.spark.sql.DataFrameReader.parquet(DataFrameReader.scala:425)