[
https://issues.apache.org/jira/browse/HADOOP-17241?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Steve Loughran resolved HADOOP-17241.
-------------------------------------
Resolution: Duplicate
I'm afraid you've just discovered the harsh truth which is the AWS Bucket
naming policy is a proper superset of that of which we can talk to the through
the S3A connector and the AWS SDK.
bq. When I checked AWS' handling of this case, they seem to be using authority
for all s3:// paths -
https://github.com/aws/aws-sdk-java/blob/master/aws-java-sdk-s3/src/main/java/com/amazonaws/services/s3/AmazonS3URI.java#L85.
we don't do that. No real reason other than historical -the code expects that
hostname == bucketname, and it goes very deep into the code.
bq. Oh and this is indeed a bucket name. Not only did I create it in the
console, but there's also enough documentation on the topic -
https://docs.aws.amazon.com/AmazonS3/latest/dev/BucketRestrictions.html#bucketnamingrules
Yes, but see also:
https://aws.amazon.com/blogs/aws/amazon-s3-path-deprecation-plan-the-rest-of-the-story/
you won't be able to reference any bucket created after sept 20 through the S3A
connector as buckets created with a "." in their name don't support the virtual
hostname option (https certs, see) and the new buckets won't support
"fs.s3a.path.style.access=true"
This is important: even if you bypassed all of the S3A code and worked directly
with the AWS SDK -by the end of the month you will not be able to interact with
any new buckets created with a dot in the name.
closing as a duplicate of HADOOP-16360, which is itself a wontfix.
> s3a: bucket names which aren't parseable hostnames unsupported
> --------------------------------------------------------------
>
> Key: HADOOP-17241
> URL: https://issues.apache.org/jira/browse/HADOOP-17241
> Project: Hadoop Common
> Issue Type: Bug
> Components: fs/s3
> Affects Versions: 2.7.4, 3.2.0
> Reporter: Ondrej Kokes
> Priority: Minor
>
> Hi there,
> I'm using Spark to read some data from S3 and I encountered an error when
> reading from a bucket that contains a period (e.g.
> `s3a://okokes-test-v1.1/foo.csv`). I have close to zero Java experience, but
> I've tried to trace this as well as I can. Apologies for any misunderstanding
> on my part.
> _Edit: the title is a little misleading - buckets can contain dots and s3a
> will work, but only if these bucket names conform to hostname restrictions -
> e.g. `s3a://foo.bar/bak.csv` would work, but my case - `okokes-test-v1.1`
> does not, because `1` is not conform to a top level domain pattern._
> Using hadoop-aws:3.2.0, I get the following:
> {code:java}
> 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{code}
> hadoop-aws:2.7.4 did lead to a similar outcome
> {code:java}
> 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{code}
> I investigated the issue a little bit and found buildFSURI to require the
> host to be not null - [see
> S3xLoginHelper.java|https://github.com/apache/hadoop/blob/trunk/hadoop-tools/hadoop-aws/src/main/java/org/apache/hadoop/fs/s3native/S3xLoginHelper.java#L70]
> - but in my case the host is null and the authority part of the URL should
> be used. When I checked AWS' handling of this case, they seem to be using
> authority for all s3:// paths -
> [https://github.com/aws/aws-sdk-java/blob/master/aws-java-sdk-s3/src/main/java/com/amazonaws/services/s3/AmazonS3URI.java#L85].
> I verified this URI in a Scala shell (openjdk 1.8.0_252)
>
> {code:java}
> scala> (new URI("s3a://okokes-test-v1.1/foo.csv")).getHost()
> val res1: String = null
> scala> (new URI("s3a://okokes-test-v1.1/foo.csv")).getAuthority()
> val res2: String = okokes-test-v1.1
> {code}
>
> Oh and this is indeed a bucket name. Not only did I create it in the console,
> but there's also enough documentation on the topic -
> [https://docs.aws.amazon.com/AmazonS3/latest/dev/BucketRestrictions.html#bucketnamingrules]
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