Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We鈥檒l occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Unpredictable behaviour with S3FileIO when column names contain # #10279

Closed
dimas-b opened this issue May 6, 2024 · 0 comments 路 Fixed by #10329
Closed

Unpredictable behaviour with S3FileIO when column names contain # #10279

dimas-b opened this issue May 6, 2024 · 0 comments 路 Fixed by #10329
Labels
bug Something isn't working

Comments

@dimas-b
Copy link
Contributor

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 mentioned this issue May 8, 2024
Closed
@danielcweeks danielcweeks mentioned this issue May 13, 2024
Merged
This was referenced May 14, 2024
Merged
Open
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Assignees
No one assigned
Labels
bug Something isn't working
Projects
None yet
Milestone
No milestone
1 participant
@dimas-b