dh376 opened a new issue #1571: URL: https://github.com/apache/incubator-hudi/issues/1571
**_Tips before filing an issue_** - Have you gone through our [FAQs](https://cwiki.apache.org/confluence/display/HUDI/FAQ)? - Join the mailing list to engage in conversations and get faster support at [email protected]. - If you have triaged this as a bug, then file an [issue](https://issues.apache.org/jira/projects/HUDI/issues) directly. **Describe the problem you faced** I'm getting IllegalArgumentException: Wrong FS error, and I don't know why. **To Reproduce** Steps to reproduce the behavior: 0. Spin up EMR (emr-5.29.0, Spark 2.4.4, Ganglia 3.7.2, Zeppelin 0.8.2, JupyterHub 1.0.0, Hive 2.3.6, Presto 0.227, Tez 0.9.2, Hadoop distribution:Amazon 2.8.5) 1. Start Spark Shell env with ``` spark-shell --conf "spark.serializer=org.apache.spark.serializer.KryoSerializer" --conf "spark.sql.hive.convertMetastoreParquet=false" --jars /usr/lib/hudi/hudi-spark-bundle.jar,/usr/lib/spark/external/lib/spark-avro.jar ``` 2. Basic Upsert which creates Hudi table ``` scala> val hudiOptions = Map[String,String]( | HoodieWriteConfig.TABLE_NAME -> "my_hudi_table", | DataSourceWriteOptions.HIVE_TABLE_OPT_KEY -> "my_hudi_table", | DataSourceWriteOptions.STORAGE_TYPE_OPT_KEY -> "COPY_ON_WRITE", | DataSourceWriteOptions.RECORDKEY_FIELD_OPT_KEY -> "uid", | DataSourceWriteOptions.PARTITIONPATH_FIELD_OPT_KEY ->"publisher", | DataSourceWriteOptions.PRECOMBINE_FIELD_OPT_KEY -> "acquired_at", | DataSourceWriteOptions.HIVE_SYNC_ENABLED_OPT_KEY -> "true", | DataSourceWriteOptions.HIVE_PARTITION_FIELDS_OPT_KEY -> "publisher", | DataSourceWriteOptions.HIVE_PARTITION_EXTRACTOR_CLASS_OPT_KEY -> classOf[MultiPartKeysValueExtractor].getName | ) df.write .format("org.apache.hudi") .option(DataSourceWriteOptions.OPERATION_OPT_KEY, DataSourceWriteOptions.UPSERT_OPERATION_OPT_VAL) .options(hudiOptions) .mode(SaveMode.Append) .save("s3://qadv2p0/exp/") ``` 3. End the spark shell session 4. Start new spark shell session 5. Do upsert ``` val hudiOptions = Map[String,String]( | HoodieWriteConfig.TABLE_NAME -> "my_hudi_table", | DataSourceWriteOptions.HIVE_TABLE_OPT_KEY -> "my_hudi_table", | DataSourceWriteOptions.STORAGE_TYPE_OPT_KEY -> "COPY_ON_WRITE", | DataSourceWriteOptions.RECORDKEY_FIELD_OPT_KEY -> "uid", | DataSourceWriteOptions.PARTITIONPATH_FIELD_OPT_KEY ->"publisher", | DataSourceWriteOptions.PRECOMBINE_FIELD_OPT_KEY -> "acquired_at", | DataSourceWriteOptions.HIVE_SYNC_ENABLED_OPT_KEY -> "true", | DataSourceWriteOptions.HIVE_PARTITION_FIELDS_OPT_KEY -> "publisher", | DataSourceWriteOptions.HIVE_PARTITION_EXTRACTOR_CLASS_OPT_KEY -> classOf[MultiPartKeysValueExtractor].getName | ) toDeleteDf.write .format("org.apache.hudi") .option(DataSourceWriteOptions.OPERATION_OPT_KEY, DataSourceWriteOptions.UPSERT_OPERATION_OPT_VAL) .option(DataSourceWriteOptions.PAYLOAD_CLASS_OPT_KEY, "org.apache.hudi.EmptyHoodieRecordPayload") .options(hudiOptions) .mode(SaveMode.Append) .save("s3://qadv2p0/exp/") ``` **Expected behavior** A clear and concise description of what you expected to happen. I got error: ``` ip-10-0-129-85.ec2.internal, executor 23): java.lang.IllegalArgumentException: Wrong FS: s3://facebook.com/inspirationhut, expected: s3://qadv2p0 at org.apache.hadoop.fs.FileSystem.checkPath(FileSystem.java:669) at org.apache.hadoop.fs.FileSystem.makeQualified(FileSystem.java:487) at com.amazon.ws.emr.hadoop.fs.staging.DefaultStagingMechanism.isStagingDirectoryPath(DefaultStagingMechanism.java:38) at com.amazon.ws.emr.hadoop.fs.s3n.S3NativeFileSystem.getFileStatus(S3NativeFileSystem.java:842) at org.apache.hadoop.fs.FileSystem.exists(FileSystem.java:1440) at com.amazon.ws.emr.hadoop.fs.EmrFileSystem.exists(EmrFileSystem.java:352) at org.apache.hudi.common.io.storage.HoodieWrapperFileSystem.exists(HoodieWrapperFileSystem.java:459) at org.apache.hudi.common.util.FSUtils.createPathIfNotExists(FSUtils.java:517) at org.apache.hudi.common.table.view.AbstractTableFileSystemView.lambda$ensurePartitionLoadedCorrectly$5(AbstractTableFileSystemView.java:221) at java.util.concurrent.ConcurrentHashMap.computeIfAbsent(ConcurrentHashMap.java:1660) at org.apache.hudi.common.table.view.AbstractTableFileSystemView.ensurePartitionLoadedCorrectly(AbstractTableFileSystemView.java:212) at org.apache.hudi.common.table.view.AbstractTableFileSystemView.getLatestDataFilesBeforeOrOn(AbstractTableFileSystemView.java:351) at org.apache.hudi.index.bloom.HoodieBloomIndex.lambda$loadInvolvedFiles$19c2c1bb$1(HoodieBloomIndex.java:247) at org.apache.spark.api.java.JavaRDDLike$$anonfun$fn$1$1.apply(JavaRDDLike.scala:125) at org.apache.spark.api.java.JavaRDDLike$$anonfun$fn$1$1.apply(JavaRDDLike.scala:125) at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:435) at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:441) at scala.collection.Iterator$class.foreach(Iterator.scala:891) at scala.collection.AbstractIterator.foreach(Iterator.scala:1334) at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59) at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104) at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48) at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310) at scala.collection.AbstractIterator.to(Iterator.scala:1334) at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302) at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1334) at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289) at scala.collection.AbstractIterator.toArray(Iterator.scala:1334) at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$13.apply(RDD.scala:945) at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$13.apply(RDD.scala:945) at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2101) at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2101) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) at org.apache.spark.scheduler.Task.run(Task.scala:123) at org.apache.spark.executor.Executor$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) ``` **Environment Description** * Hudi version : The version of Hudi installed with Amazon EMR 5.29.0 is 0.5.0-incubating. * Spark version : 2.4.4, * Hive version : 2.3.6 * Hadoop version : Hadoop distribution:Amazon 2.8.5 * Storage (HDFS/S3/GCS..) : s3 * Running on Docker? (yes/no) : no **Additional context** Add any other context about the problem here. **Stacktrace** ```Add the stacktrace of the error.``` ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: [email protected]
