Describe the bug

19/09/23 21:18:44 ERROR Executor: Exception in task 17.0 in stage 22.0 (TID 12628)
java.net.MalformedURLException: unknown protocol: filedesc
        at java.net.URL.<init>(URL.java:607)
        at java.net.URL.<init>(URL.java:497)
        at java.net.URL.<init>(URL.java:446)
        at io.archivesunleashed.package$WARecordRDD$$anonfun$38.apply(package.scala:448)
        at io.archivesunleashed.package$WARecordRDD$$anonfun$38.apply(package.scala:444)
        at scala.collection.Iterator$$anon$11.next(Iterator.scala:410)
        at scala.collection.Iterator$$anon$11.next(Iterator.scala:410)
        at scala.collection.Iterator$$anon$11.next(Iterator.scala:410)
        at scala.collection.Iterator$$anon$11.next(Iterator.scala:410)
        at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
        at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
        at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$13$$anon$1.hasNext(WholeStageCodegenExec.scala:636)
        at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
        at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:409)
        at org.apache.spark.util.random.SamplingUtils$.reservoirSampleAndCount(SamplingUtils.scala:41)
        at org.apache.spark.RangePartitioner$$anonfun$13.apply(Partitioner.scala:306)
        at org.apache.spark.RangePartitioner$$anonfun$13.apply(Partitioner.scala:304)
        at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsWithIndex$1$$anonfun$apply$25.apply(RDD.scala:853)
        at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsWithIndex$1$$anonfun$apply$25.apply(RDD.scala:853)
        at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
        at org.apache.spark.scheduler.Task.run(Task.scala:123)
        at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
        at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at java.lang.Thread.run(Thread.java:748)

To Reproduce

import io.archivesunleashed._
import io.archivesunleashed.df._

val df = RecordLoader.loadArchives("/data/banq-datathon/PQ-2012/warcs/*gz", sc).extractTextFilesDetailsDF();
val res = df.select($"url", $"filename", $"extension", $"mime_type_web_server", $"mime_type_tika", $"md5").orderBy(desc("md5")).write.csv("/data/banq-datathon/PQ-2012/derivatives/dataframes/text/pq-2012-text")

val df_txt = RecordLoader.loadArchives("/data/banq-datathon/PQ-2012/warcs/*gz", sc).extractTextFilesDetailsDF();
val res_txt = df_txt.select($"bytes", $"extension").saveToDisk("bytes", "/data/banq-datathon/PQ-2012/derivatives/binaries/text/pq-2012-text", "extension")

sys.exit

Expected behavior

We should probably just capture and log that error. I remember it coming up in testing with GeoCities, but it went away with all the Tika processing.

Environment information

• AUT version: 0.18.0
• OS: Ubuntu 18.04
• Java version: OpenJDK8
• Apache Spark version: 2.4.4
• Apache Spark w/aut: --packages
• Apache Spark command used to run AUT: /home/ubuntu/aut/spark-2.4.4-bin-hadoop2.7/bin/spark-shell --master local[30] --driver-memory 105g --conf spark.network.timeout=100000000 --conf spark.executor.heartbeatInterval=6000s --conf spark.driver.maxResultSize=100g --conf spark.rdd.compress=true --conf spark.serializer=org.apache.spark.serializer.KryoSerializer --conf spark.shuffle.compress=true --conf spark.kryoserializer.buffer.max=2000m --packages "io.archivesunleashed:aut:0.18.0"