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Unpredictable behaviour with S3FileIO when column names contain # #10279

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dimas-b opened this issue May 6, 2024 · 0 comments 路 May be fixed by #10283 or #10329
Open

Unpredictable behaviour with S3FileIO when column names contain # #10279

dimas-b opened this issue May 6, 2024 · 0 comments 路 May be fixed by #10283 or #10329
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@dimas-b
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dimas-b commented May 6, 2024 •
edited

Apache Iceberg version

1.5.0

Query engine

Spark

Please describe the bug 馃悶

When a table is partitioned by a column that contains # in the name, some inserts / selects succeed, but some fail.

At the SQL level there is not obvious reason why some of the inserts work but others appear to corrupt the table.

Example:

  1. Run PosgreSQL to back the catalog: docker run --rm --name postgres -p 5432:5432 -e POSTGRES_PASSWORD=post123 postgres
  2. Run Spark SQL session:
$ bin/spark-sql \
  --packages org.apache.iceberg:iceberg-spark-runtime-3.5_2.12:1.5.0,org.apache.iceberg:iceberg-aws-bundle:1.5.0,org.postgresql:postgresql:42.7.3 \
  --conf spark.sql.extensions=org.apache.iceberg.spark.extensions.IcebergSparkSessionExtensions \
  --conf spark.sql.catalog.test.uri=http://127.0.0.1:8181/ \
  --conf spark.sql.catalog.test.type=jdbc \
  --conf spark.sql.catalog.test.uri=jdbc:postgresql://localhost/postgres \
  --conf spark.sql.catalog.test.jdbc.user=postgres \
  --conf spark.sql.catalog.test.jdbc.password=post123 \
  --conf spark.sql.catalog.test.warehouse=s3://EXAMPLE/test7/ \
  --conf spark.sql.catalog.test.io-impl=org.apache.iceberg.io.ResolvingFileIO \
  --conf spark.sql.catalog.test=org.apache.iceberg.spark.SparkCatalog \
  --master 'local[1]'
  1. Run SQL:
spark-sql (default)> create namespace test.ns;
24/05/06 17:44:44 WARN JdbcCatalog: JDBC catalog is initialized without view support. To auto-migrate the database's schema and enable view support, set jdbc.schema-version=V1
Time taken: 1.134 seconds
spark-sql (default)> create table test.ns.t8(`id#1` string not null, a int) partitioned by (`id#1`);
Time taken: 1.811 seconds
spark-sql (default)> insert into test.ns.t8 values ('1', 1);
Time taken: 3.082 seconds
spark-sql (default)> select * from test.ns.t8;
1	1
Time taken: 1.366 seconds, Fetched 1 row(s)
spark-sql (default)> insert into test.ns.t8 values ('2', 2);
Time taken: 1.22 seconds
spark-sql (default)> select * from test.ns.t8;
24/05/06 17:45:13 ERROR BaseReader: Error reading file(s): s3://EXAMPLE/test7/ns/t8/data/id#1=1/00000-1-39efedbe-86c5-4a15-a07c-dfe8742e9027-0-00001.parquet
java.lang.RuntimeException: org.apache.iceberg.parquet.ParquetIO$ParquetInputFile@32cf132a is not a Parquet file. Expected magic number at tail, but found [0, 80, 65, 82]

Full error output:

java.lang.RuntimeException: org.apache.iceberg.parquet.ParquetIO$ParquetInputFile@32cf132a is not a Parquet file. Expected magic number at tail, but found [0, 80, 65, 82]
	at org.apache.iceberg.shaded.org.apache.parquet.hadoop.ParquetFileReader.readFooter(ParquetFileReader.java:565)
	at org.apache.iceberg.shaded.org.apache.parquet.hadoop.ParquetFileReader.<init>(ParquetFileReader.java:799)
	at org.apache.iceberg.shaded.org.apache.parquet.hadoop.ParquetFileReader.open(ParquetFileReader.java:666)
	at org.apache.iceberg.parquet.ReadConf.newReader(ReadConf.java:238)
	at org.apache.iceberg.parquet.ReadConf.<init>(ReadConf.java:81)
	at org.apache.iceberg.parquet.VectorizedParquetReader.init(VectorizedParquetReader.java:90)
	at org.apache.iceberg.parquet.VectorizedParquetReader.iterator(VectorizedParquetReader.java:99)
	at org.apache.iceberg.spark.source.BatchDataReader.open(BatchDataReader.java:109)
	at org.apache.iceberg.spark.source.BatchDataReader.open(BatchDataReader.java:41)
	at org.apache.iceberg.spark.source.BaseReader.next(BaseReader.java:143)
	at org.apache.spark.sql.execution.datasources.v2.PartitionIterator.hasNext(DataSourceRDD.scala:120)
	at org.apache.spark.sql.execution.datasources.v2.MetricsIterator.hasNext(DataSourceRDD.scala:158)
	at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD$$anon$1.$anonfun$hasNext$1(DataSourceRDD.scala:63)
	at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD$$anon$1.$anonfun$hasNext$1$adapted(DataSourceRDD.scala:63)
	at scala.Option.exists(Option.scala:376)
	at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD$$anon$1.hasNext(DataSourceRDD.scala:63)
	at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD$$anon$1.advanceToNextIter(DataSourceRDD.scala:97)
	at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD$$anon$1.hasNext(DataSourceRDD.scala:63)
	at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
	at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.columnartorow_nextBatch_0$(Unknown Source)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
	at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
	at org.apache.spark.sql.execution.WholeStageCodegenEvaluatorFactory$WholeStageCodegenPartitionEvaluator$$anon$1.hasNext(WholeStageCodegenEvaluatorFactory.scala:43)
	at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:388)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:893)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:893)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:367)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:331)
	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:93)
	at org.apache.spark.TaskContext.runTaskWithListeners(TaskContext.scala:166)
	at org.apache.spark.scheduler.Task.run(Task.scala:141)
	at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$4(Executor.scala:620)
	at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally(SparkErrorUtils.scala:64)
	at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally$(SparkErrorUtils.scala:61)
	at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:94)
	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:623)
	at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
	at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
	at java.base/java.lang.Thread.run(Thread.java:829)
24/05/06 17:45:13 ERROR Executor: Exception in task 0.0 in stage 7.0 (TID 5)
java.lang.RuntimeException: org.apache.iceberg.parquet.ParquetIO$ParquetInputFile@32cf132a is not a Parquet file. Expected magic number at tail, but found [0, 80, 65, 82]
	at org.apache.iceberg.shaded.org.apache.parquet.hadoop.ParquetFileReader.readFooter(ParquetFileReader.java:565)
	at org.apache.iceberg.shaded.org.apache.parquet.hadoop.ParquetFileReader.<init>(ParquetFileReader.java:799)
	at org.apache.iceberg.shaded.org.apache.parquet.hadoop.ParquetFileReader.open(ParquetFileReader.java:666)
	at org.apache.iceberg.parquet.ReadConf.newReader(ReadConf.java:238)
	at org.apache.iceberg.parquet.ReadConf.<init>(ReadConf.java:81)
	at org.apache.iceberg.parquet.VectorizedParquetReader.init(VectorizedParquetReader.java:90)
	at org.apache.iceberg.parquet.VectorizedParquetReader.iterator(VectorizedParquetReader.java:99)
	at org.apache.iceberg.spark.source.BatchDataReader.open(BatchDataReader.java:109)
	at org.apache.iceberg.spark.source.BatchDataReader.open(BatchDataReader.java:41)
	at org.apache.iceberg.spark.source.BaseReader.next(BaseReader.java:143)
	at org.apache.spark.sql.execution.datasources.v2.PartitionIterator.hasNext(DataSourceRDD.scala:120)
	at org.apache.spark.sql.execution.datasources.v2.MetricsIterator.hasNext(DataSourceRDD.scala:158)
	at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD$$anon$1.$anonfun$hasNext$1(DataSourceRDD.scala:63)
	at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD$$anon$1.$anonfun$hasNext$1$adapted(DataSourceRDD.scala:63)
	at scala.Option.exists(Option.scala:376)
	at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD$$anon$1.hasNext(DataSourceRDD.scala:63)
	at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD$$anon$1.advanceToNextIter(DataSourceRDD.scala:97)
	at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD$$anon$1.hasNext(DataSourceRDD.scala:63)
	at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
	at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.columnartorow_nextBatch_0$(Unknown Source)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
	at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
	at org.apache.spark.sql.execution.WholeStageCodegenEvaluatorFactory$WholeStageCodegenPartitionEvaluator$$anon$1.hasNext(WholeStageCodegenEvaluatorFactory.scala:43)
	at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:388)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:893)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:893)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:367)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:331)
	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:93)
	at org.apache.spark.TaskContext.runTaskWithListeners(TaskContext.scala:166)
	at org.apache.spark.scheduler.Task.run(Task.scala:141)
	at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$4(Executor.scala:620)
	at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally(SparkErrorUtils.scala:64)
	at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally$(SparkErrorUtils.scala:61)
	at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:94)
	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:623)
	at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
	at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
	at java.base/java.lang.Thread.run(Thread.java:829)
24/05/06 17:45:13 WARN TaskSetManager: Lost task 0.0 in stage 7.0 (TID 5) (192.168.68.56 executor driver): java.lang.RuntimeException: org.apache.iceberg.parquet.ParquetIO$ParquetInputFile@32cf132a is not a Parquet file. Expected magic number at tail, but found [0, 80, 65, 82]
	at org.apache.iceberg.shaded.org.apache.parquet.hadoop.ParquetFileReader.readFooter(ParquetFileReader.java:565)
	at org.apache.iceberg.shaded.org.apache.parquet.hadoop.ParquetFileReader.<init>(ParquetFileReader.java:799)
	at org.apache.iceberg.shaded.org.apache.parquet.hadoop.ParquetFileReader.open(ParquetFileReader.java:666)
	at org.apache.iceberg.parquet.ReadConf.newReader(ReadConf.java:238)
	at org.apache.iceberg.parquet.ReadConf.<init>(ReadConf.java:81)
	at org.apache.iceberg.parquet.VectorizedParquetReader.init(VectorizedParquetReader.java:90)
	at org.apache.iceberg.parquet.VectorizedParquetReader.iterator(VectorizedParquetReader.java:99)
	at org.apache.iceberg.spark.source.BatchDataReader.open(BatchDataReader.java:109)
	at org.apache.iceberg.spark.source.BatchDataReader.open(BatchDataReader.java:41)
	at org.apache.iceberg.spark.source.BaseReader.next(BaseReader.java:143)
	at org.apache.spark.sql.execution.datasources.v2.PartitionIterator.hasNext(DataSourceRDD.scala:120)
	at org.apache.spark.sql.execution.datasources.v2.MetricsIterator.hasNext(DataSourceRDD.scala:158)
	at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD$$anon$1.$anonfun$hasNext$1(DataSourceRDD.scala:63)
	at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD$$anon$1.$anonfun$hasNext$1$adapted(DataSourceRDD.scala:63)
	at scala.Option.exists(Option.scala:376)
	at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD$$anon$1.hasNext(DataSourceRDD.scala:63)
	at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD$$anon$1.advanceToNextIter(DataSourceRDD.scala:97)
	at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD$$anon$1.hasNext(DataSourceRDD.scala:63)
	at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
	at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.columnartorow_nextBatch_0$(Unknown Source)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
	at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
	at org.apache.spark.sql.execution.WholeStageCodegenEvaluatorFactory$WholeStageCodegenPartitionEvaluator$$anon$1.hasNext(WholeStageCodegenEvaluatorFactory.scala:43)
	at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:388)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:893)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:893)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:367)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:331)
	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:93)
	at org.apache.spark.TaskContext.runTaskWithListeners(TaskContext.scala:166)
	at org.apache.spark.scheduler.Task.run(Task.scala:141)
	at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$4(Executor.scala:620)
	at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally(SparkErrorUtils.scala:64)
	at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally$(SparkErrorUtils.scala:61)
	at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:94)
	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:623)
	at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
	at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
	at java.base/java.lang.Thread.run(Thread.java:829)

24/05/06 17:45:13 ERROR TaskSetManager: Task 0 in stage 7.0 failed 1 times; aborting job
Job aborted due to stage failure: Task 0 in stage 7.0 failed 1 times, most recent failure: Lost task 0.0 in stage 7.0 (TID 5) (192.168.68.56 executor driver): java.lang.RuntimeException: org.apache.iceberg.parquet.ParquetIO$ParquetInputFile@32cf132a is not a Parquet file. Expected magic number at tail, but found [0, 80, 65, 82]
	at org.apache.iceberg.shaded.org.apache.parquet.hadoop.ParquetFileReader.readFooter(ParquetFileReader.java:565)
	at org.apache.iceberg.shaded.org.apache.parquet.hadoop.ParquetFileReader.<init>(ParquetFileReader.java:799)
	at org.apache.iceberg.shaded.org.apache.parquet.hadoop.ParquetFileReader.open(ParquetFileReader.java:666)
	at org.apache.iceberg.parquet.ReadConf.newReader(ReadConf.java:238)
	at org.apache.iceberg.parquet.ReadConf.<init>(ReadConf.java:81)
	at org.apache.iceberg.parquet.VectorizedParquetReader.init(VectorizedParquetReader.java:90)
	at org.apache.iceberg.parquet.VectorizedParquetReader.iterator(VectorizedParquetReader.java:99)
	at org.apache.iceberg.spark.source.BatchDataReader.open(BatchDataReader.java:109)
	at org.apache.iceberg.spark.source.BatchDataReader.open(BatchDataReader.java:41)
	at org.apache.iceberg.spark.source.BaseReader.next(BaseReader.java:143)
	at org.apache.spark.sql.execution.datasources.v2.PartitionIterator.hasNext(DataSourceRDD.scala:120)
	at org.apache.spark.sql.execution.datasources.v2.MetricsIterator.hasNext(DataSourceRDD.scala:158)
	at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD$$anon$1.$anonfun$hasNext$1(DataSourceRDD.scala:63)
	at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD$$anon$1.$anonfun$hasNext$1$adapted(DataSourceRDD.scala:63)
	at scala.Option.exists(Option.scala:376)
	at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD$$anon$1.hasNext(DataSourceRDD.scala:63)
	at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD$$anon$1.advanceToNextIter(DataSourceRDD.scala:97)
	at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD$$anon$1.hasNext(DataSourceRDD.scala:63)
	at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
	at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.columnartorow_nextBatch_0$(Unknown Source)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
	at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
	at org.apache.spark.sql.execution.WholeStageCodegenEvaluatorFactory$WholeStageCodegenPartitionEvaluator$$anon$1.hasNext(WholeStageCodegenEvaluatorFactory.scala:43)
	at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:388)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:893)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:893)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:367)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:331)
	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:93)
	at org.apache.spark.TaskContext.runTaskWithListeners(TaskContext.scala:166)
	at org.apache.spark.scheduler.Task.run(Task.scala:141)
	at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$4(Executor.scala:620)
	at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally(SparkErrorUtils.scala:64)
	at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally$(SparkErrorUtils.scala:61)
	at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:94)
	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:623)
	at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
	at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
	at java.base/java.lang.Thread.run(Thread.java:829)

Driver stacktrace:
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 7.0 failed 1 times, most recent failure: Lost task 0.0 in stage 7.0 (TID 5) (192.168.68.56 executor driver): java.lang.RuntimeException: org.apache.iceberg.parquet.ParquetIO$ParquetInputFile@32cf132a is not a Parquet file. Expected magic number at tail, but found [0, 80, 65, 82]
	at org.apache.iceberg.shaded.org.apache.parquet.hadoop.ParquetFileReader.readFooter(ParquetFileReader.java:565)
	at org.apache.iceberg.shaded.org.apache.parquet.hadoop.ParquetFileReader.<init>(ParquetFileReader.java:799)
	at org.apache.iceberg.shaded.org.apache.parquet.hadoop.ParquetFileReader.open(ParquetFileReader.java:666)
	at org.apache.iceberg.parquet.ReadConf.newReader(ReadConf.java:238)
	at org.apache.iceberg.parquet.ReadConf.<init>(ReadConf.java:81)
	at org.apache.iceberg.parquet.VectorizedParquetReader.init(VectorizedParquetReader.java:90)
	at org.apache.iceberg.parquet.VectorizedParquetReader.iterator(VectorizedParquetReader.java:99)
	at org.apache.iceberg.spark.source.BatchDataReader.open(BatchDataReader.java:109)
	at org.apache.iceberg.spark.source.BatchDataReader.open(BatchDataReader.java:41)
	at org.apache.iceberg.spark.source.BaseReader.next(BaseReader.java:143)
	at org.apache.spark.sql.execution.datasources.v2.PartitionIterator.hasNext(DataSourceRDD.scala:120)
	at org.apache.spark.sql.execution.datasources.v2.MetricsIterator.hasNext(DataSourceRDD.scala:158)
	at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD$$anon$1.$anonfun$hasNext$1(DataSourceRDD.scala:63)
	at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD$$anon$1.$anonfun$hasNext$1$adapted(DataSourceRDD.scala:63)
	at scala.Option.exists(Option.scala:376)
	at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD$$anon$1.hasNext(DataSourceRDD.scala:63)
	at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD$$anon$1.advanceToNextIter(DataSourceRDD.scala:97)
	at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD$$anon$1.hasNext(DataSourceRDD.scala:63)
	at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
	at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.columnartorow_nextBatch_0$(Unknown Source)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
	at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
	at org.apache.spark.sql.execution.WholeStageCodegenEvaluatorFactory$WholeStageCodegenPartitionEvaluator$$anon$1.hasNext(WholeStageCodegenEvaluatorFactory.scala:43)
	at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:388)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:893)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:893)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:367)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:331)
	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:93)
	at org.apache.spark.TaskContext.runTaskWithListeners(TaskContext.scala:166)
	at org.apache.spark.scheduler.Task.run(Task.scala:141)
	at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$4(Executor.scala:620)
	at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally(SparkErrorUtils.scala:64)
	at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally$(SparkErrorUtils.scala:61)
	at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:94)
	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:623)
	at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
	at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
	at java.base/java.lang.Thread.run(Thread.java:829)

Driver stacktrace:
	at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2856)
	at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2792)
	at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2791)
	at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
	at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
	at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
	at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2791)
	at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1247)
	at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1247)
	at scala.Option.foreach(Option.scala:407)
	at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1247)
	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:3060)
	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2994)
	at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2983)
	at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
	at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:989)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:2398)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:2419)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:2438)
	at org.apache.spark.SparkContext.runJob(SparkContext.scala:2463)
	at org.apache.spark.rdd.RDD.$anonfun$collect$1(RDD.scala:1049)
	at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
	at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
	at org.apache.spark.rdd.RDD.withScope(RDD.scala:410)
	at org.apache.spark.rdd.RDD.collect(RDD.scala:1048)
	at org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:448)
	at org.apache.spark.sql.execution.SparkPlan.executeCollectPublic(SparkPlan.scala:475)
	at org.apache.spark.sql.execution.HiveResult$.hiveResultString(HiveResult.scala:76)
	at org.apache.spark.sql.hive.thriftserver.SparkSQLDriver.$anonfun$run$2(SparkSQLDriver.scala:76)
	at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$6(SQLExecution.scala:125)
	at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:201)
	at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:108)
	at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:900)
	at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:66)
	at org.apache.spark.sql.hive.thriftserver.SparkSQLDriver.run(SparkSQLDriver.scala:76)
	at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.processCmd(SparkSQLCLIDriver.scala:501)
	at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.$anonfun$processLine$1(SparkSQLCLIDriver.scala:619)
	at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.$anonfun$processLine$1$adapted(SparkSQLCLIDriver.scala:613)
	at scala.collection.Iterator.foreach(Iterator.scala:943)
	at scala.collection.Iterator.foreach$(Iterator.scala:943)
	at scala.collection.AbstractIterator.foreach(Iterator.scala:1431)
	at scala.collection.IterableLike.foreach(IterableLike.scala:74)
	at scala.collection.IterableLike.foreach$(IterableLike.scala:73)
	at scala.collection.AbstractIterable.foreach(Iterable.scala:56)
	at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.processLine(SparkSQLCLIDriver.scala:613)
	at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver$.main(SparkSQLCLIDriver.scala:310)
	at org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.main(SparkSQLCLIDriver.scala)
	at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
	at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
	at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
	at java.base/java.lang.reflect.Method.invoke(Method.java:566)
	at org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52)
	at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:1029)
	at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:194)
	at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:217)
	at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:91)
	at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:1120)
	at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:1129)
	at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.lang.RuntimeException: org.apache.iceberg.parquet.ParquetIO$ParquetInputFile@32cf132a is not a Parquet file. Expected magic number at tail, but found [0, 80, 65, 82]
	at org.apache.iceberg.shaded.org.apache.parquet.hadoop.ParquetFileReader.readFooter(ParquetFileReader.java:565)
	at org.apache.iceberg.shaded.org.apache.parquet.hadoop.ParquetFileReader.<init>(ParquetFileReader.java:799)
	at org.apache.iceberg.shaded.org.apache.parquet.hadoop.ParquetFileReader.open(ParquetFileReader.java:666)
	at org.apache.iceberg.parquet.ReadConf.newReader(ReadConf.java:238)
	at org.apache.iceberg.parquet.ReadConf.<init>(ReadConf.java:81)
	at org.apache.iceberg.parquet.VectorizedParquetReader.init(VectorizedParquetReader.java:90)
	at org.apache.iceberg.parquet.VectorizedParquetReader.iterator(VectorizedParquetReader.java:99)
	at org.apache.iceberg.spark.source.BatchDataReader.open(BatchDataReader.java:109)
	at org.apache.iceberg.spark.source.BatchDataReader.open(BatchDataReader.java:41)
	at org.apache.iceberg.spark.source.BaseReader.next(BaseReader.java:143)
	at org.apache.spark.sql.execution.datasources.v2.PartitionIterator.hasNext(DataSourceRDD.scala:120)
	at org.apache.spark.sql.execution.datasources.v2.MetricsIterator.hasNext(DataSourceRDD.scala:158)
	at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD$$anon$1.$anonfun$hasNext$1(DataSourceRDD.scala:63)
	at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD$$anon$1.$anonfun$hasNext$1$adapted(DataSourceRDD.scala:63)
	at scala.Option.exists(Option.scala:376)
	at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD$$anon$1.hasNext(DataSourceRDD.scala:63)
	at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD$$anon$1.advanceToNextIter(DataSourceRDD.scala:97)
	at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD$$anon$1.hasNext(DataSourceRDD.scala:63)
	at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
	at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.columnartorow_nextBatch_0$(Unknown Source)
	at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
	at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
	at org.apache.spark.sql.execution.WholeStageCodegenEvaluatorFactory$WholeStageCodegenPartitionEvaluator$$anon$1.hasNext(WholeStageCodegenEvaluatorFactory.scala:43)
	at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:388)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:893)
	at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:893)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:367)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:331)
	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:93)
	at org.apache.spark.TaskContext.runTaskWithListeners(TaskContext.scala:166)
	at org.apache.spark.scheduler.Task.run(Task.scala:141)
	at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$4(Executor.scala:620)
	at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally(SparkErrorUtils.scala:64)
	at org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally$(SparkErrorUtils.scala:61)
	at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:94)
	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:623)
	at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
	at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
	at java.base/java.lang.Thread.run(Thread.java:829)

Note: this is related to #10168
@dimas-b dimas-b added the bug Something isn't working label May 6, 2024
@dimas-b dimas-b mentioned this issue May 6, 2024
Closed
dimas-b added a commit to dimas-b/iceberg that referenced this issue May 8, 2024
@dimas-b
Support special chars in S3URI
61383e1 
* Remove code that interpreted URI query and fragments parts according
  to RFC 3986. In practice, S3 locations do not encode special chars
  and, therefore, do not really have query and fragment parts.

* Add TestS3FileIOMinio for a small subset of tests using Minio as
  a realistic S3 protocol implementation for validating the handling
  of special chars.

Fixes apache#10279
@dimas-b dimas-b linked a pull request May 8, 2024 that will close this issue
Open
@danielcweeks danielcweeks linked a pull request May 13, 2024 that will close this issue
Open
This was referenced May 14, 2024
Merged
Open
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