How to specify schema while reading parquet file with pyspark?

While reading a parquet file stored in hadoop with either scala or pyspark an error occurs:

#scala    
var dff = spark.read.parquet("/super/important/df")
    org.apache.spark.sql.AnalysisException: Unable to infer schema for Parquet. It must be specified manually.;
      at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$8.apply(DataSource.scala:189)
      at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$8.apply(DataSource.scala:189)
      at scala.Option.getOrElse(Option.scala:121)
      at org.apache.spark.sql.execution.datasources.DataSource.org$apache$spark$sql$execution$datasources$DataSource$$getOrInferFileFormatSchema(DataSource.scala:188)
  at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:387)
  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)
  ... 52 elided

or

sql_context.read.parquet(output_file)

results in the same error.

Error message is pretty clear about what has to be done: Unable to infer schema for Parquet. It must be specified manually.;. But where can I specify it?

Spark 2.1.1, Hadoop 2.5, dataframes are created with a help of pyspark. Files are partitioned into 10 peaces.