Re:

[Enrico Minack]

Looks like the schema of some files is unexpected.

You could either run parquet-tools on each of the files and extract the 
schema to find the problematic files:

|hdfs |||-stat "%n"| 
|hdfs://ip-172-24-89-229.blaah.com:8020/user/hadoop/origdata/part-*.parquet 
<http://ip-172-24-89-229.blaah.com:8020/user/hadoop/origdata/part-00000-8b83989a-e387-4f64-8ac5-22b16770095e-c000.snappy.parquet>| 
while read file
do
   echo -n "$file: "
   hadoop jar parquet-tools-1.9.0.jar schema $file
done

https://confusedcoders.com/data-engineering/hadoop/how-to-view-content-of-parquet-files-on-s3hdfs-from-hadoop-cluster-using-parquet-tools

||


Or you can use Spark to investigate the parquet files in parallel:

spark.sparkContext
  .binaryFiles("||hdfs://ip-172-24-89-229.blaah.com:8020/user/hadoop/origdata/part-*.parquet 
<http://ip-172-24-89-229.blaah.com:8020/user/hadoop/origdata/part-00000-8b83989a-e387-4f64-8ac5-22b16770095e-c000.snappy.parquet>")
  .map {case (path, _) =>
    import collection.JavaConverters._
val file = HadoopInputFile.fromPath(new Path(path), new Configuration())
    val reader = ParquetFileReader.open(file)
    try {
      val schema = reader.getFileMetaData().getSchema
      (
        schema.getName, schema.getFields.asScala.map(f => (
          Option(f.getId).map(_.intValue()), f.getName, 
Option(f.getOriginalType).map(_.name()), Option(f.getRepetition).map(_.name()))
        ).toArray
      )
    }finally {
      reader.close()
    }
  }
  .toDF("schema name", "fields")
  .show(false)

.binaryFiles provides you all filenames that match the given pattern as 
an RDD, so the following .map is executed on the Spark executors.
The map then opens each parquet file via ParquetFileReader and provides 
access to its schema and data.

I hope this points you in the right direction.

Enrico


Am 01.03.20 um 22:56 schrieb Hamish Whittal:
Hi there,

I have an hdfs directory with thousands of files. It seems that some 
of them - and I don't know which ones - have a problem with their 
schema and it's causing my Spark application to fail with this error:

Caused by: org.apache.spark.sql.execution.QueryExecutionException: 
Parquet column cannot be converted in file 
hdfs://ip-172-24-89-229.blaah.com:8020/user/hadoop/origdata/part-00000-8b83989a-e387-4f64-8ac5-22b16770095e-c000.snappy.parquet 
<http://ip-172-24-89-229.blaah.com:8020/user/hadoop/origdata/part-00000-8b83989a-e387-4f64-8ac5-22b16770095e-c000.snappy.parquet>. 
Column: [price], Expected: double, Found: FIXED_LEN_BYTE_ARRAY

The problem is not only that it's causing the application to fail, but 
every time if does fail, I have to copy that file out of the directory 
and start the app again.

I thought of trying to use try-except, but I can't seem to get that to 
work.

Is there any advice anyone can give me because I really can't see 
myself going through thousands of files trying to figure out which 
ones are broken.

Thanks in advance,

hamish