Ondrej Kokes created SPARK-32766:
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Summary: s3a: bucket names with dots cannot be used
Key: SPARK-32766
URL: https://issues.apache.org/jira/browse/SPARK-32766
Project: Spark
Issue Type: Bug
Components: Input/Output
Affects Versions: 3.0.0
Reporter: Ondrej Kokes
Running vanilla spark with
{noformat}
--packages=org.apache.hadoop:hadoop-aws:x.y.z{noformat}
I cannot read from S3, if the bucket name contains a dot (a valid name).
A minimal reproducible example looks like this
{{from pyspark.sql import SparkSession}}
{{import pyspark.sql.functions as f}}
{{if __name__ == '__main__':}}
{{ spark = (SparkSession}}
{{ .builder}}
{{ .appName('my_app')}}
{{ .master("local[*]")}}
{{ .getOrCreate()}}
{{ )}}
{{ spark.read.csv("s3a://test-bucket-name-v1.0/foo.csv")}}
Or just launch a spark-shell with `--packages=(...)hadoop-aws(...)` and read
that CSV. I created the same bucket without the period and it worked fine.
*Now I'm not sure whether this is a thing of prepping the path names and
passing them to the aws-sdk, or whether the fault is within the SDK itself. I
am not Java savvy to investigate the issue further, but I tried to make the
repro as short as possible.*
----
I get different errors depending on which Hadoop distributions I use. If I use
the default PySpark distribution (which includes Hadoop 2), I get the following
(using hadoop-aws:2.7.4)
{{scala> spark.read.csv("s3a://okokes-test-v2.5/foo.csv").show()}}
{{java.lang.IllegalArgumentException: The bucketName parameter must be
specified.}}
{{ at
com.amazonaws.services.s3.AmazonS3Client.assertParameterNotNull(AmazonS3Client.java:2816)}}
{{ at
com.amazonaws.services.s3.AmazonS3Client.headBucket(AmazonS3Client.java:1026)}}
{{ at
com.amazonaws.services.s3.AmazonS3Client.doesBucketExist(AmazonS3Client.java:994)}}
{{ at
org.apache.hadoop.fs.s3a.S3AFileSystem.initialize(S3AFileSystem.java:297)}}
{{ at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:2669)}}
{{ at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:94)}}
{{ at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:2703)}}
{{ at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:2685)}}
{{ at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:373)}}
{{ at org.apache.hadoop.fs.Path.getFileSystem(Path.java:295)}}
{{ at
org.apache.spark.sql.execution.streaming.FileStreamSink$.hasMetadata(FileStreamSink.scala:46)}}
{{ at
org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:361)}}
{{ at
org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:279)}}
{{ at
org.apache.spark.sql.DataFrameReader.$anonfun$load$2(DataFrameReader.scala:268)}}
{{ at scala.Option.getOrElse(Option.scala:189)}}
{{ at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:268)}}
{{ at org.apache.spark.sql.DataFrameReader.csv(DataFrameReader.scala:705)}}
{{ at org.apache.spark.sql.DataFrameReader.csv(DataFrameReader.scala:535)}}
{{ ... 47 elided}}
When I downloaded 3.0.0 with Hadoop 3 and ran a spark-shell there, I got this
error (with hadoop-aws:3.2.0):
{{java.lang.NullPointerException: null uri host.}}
{{ at java.base/java.util.Objects.requireNonNull(Objects.java:246)}}
{{ at
org.apache.hadoop.fs.s3native.S3xLoginHelper.buildFSURI(S3xLoginHelper.java:71)}}
{{ at org.apache.hadoop.fs.s3a.S3AFileSystem.setUri(S3AFileSystem.java:470)}}
{{ at
org.apache.hadoop.fs.s3a.S3AFileSystem.initialize(S3AFileSystem.java:235)}}
{{ at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:3303)}}
{{ at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:124)}}
{{ at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:3352)}}
{{ at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:3320)}}
{{ at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:479)}}
{{ at org.apache.hadoop.fs.Path.getFileSystem(Path.java:361)}}
{{ at
org.apache.spark.sql.execution.streaming.FileStreamSink$.hasMetadata(FileStreamSink.scala:46)}}
{{ at
org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:361)}}
{{ at
org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:279)}}
{{ at
org.apache.spark.sql.DataFrameReader.$anonfun$load$2(DataFrameReader.scala:268)}}
{{ at scala.Option.getOrElse(Option.scala:189)}}
{{ at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:268)}}
{{ at org.apache.spark.sql.DataFrameReader.csv(DataFrameReader.scala:705)}}
{{ at org.apache.spark.sql.DataFrameReader.csv(DataFrameReader.scala:535)}}
{{ ... 47 elided}}
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