Description on how to use a custom S3 endpoint (like Rados Gateway for Ceph)

custom_s3_endpoint_in_spark.md

Custom S3 endpoints with Spark

To be able to use custom endpoints with the latest Spark distribution, one needs to add an external package (hadoop-aws). Then, custum endpoints can be configured according to docs.

Use the hadoop-aws package

bin/spark-shell --packages org.apache.hadoop:hadoop-aws:2.7.2

SparkContext configuration

Add this to your application, or in the spark-shell:

sc.hadoopConfiguration.set("fs.s3a.endpoint", "<<ENDPOINT>>");
sc.hadoopConfiguration.set("fs.s3a.access.key","<<ACCESS_KEY>>");
sc.hadoopConfiguration.set("fs.s3a.secret.key","<<SECRET_KEY>>");

If your endpoint doesn't support HTTPS, then you'll need the following:

sc.hadoopConfiguration.set("fs.s3a.connection.ssl.enabled", "false");

S3 url usage

You can use s3a urls like this:

s3a://<<BUCKET>>/<<FOLDER>>/<<FILE>>

Also, it is possible to use the credentials in the path:

s3a://<<ACCESS_KEY>>:<<SECRET_KEY>>@<<BUCKET>>/<<FOLDER>>/<<FILE>>

Idk how common this use case is, but I have a pipeline that would be greatly simplified if I was able to use multiple S3 endpoints in a single spark submit. That is, I have a minio endpoint along with a standard aws s3 endpoint. Is there a way to configure the session on the fly such that I can use both?

@jamesthegiantpeach: I have a similar use case. How did you solve this problem in your case?

I am getting this error when I am reading S3 local instance.

The confs I have set are -

val sparkConf = new SparkConf().setAppName("testing") .set("fs.s3a.endpoint", "http://127.0.0.1:9090") .set("fs.s3a.multipart.size", "104857600) .set("fs.s3a.connection.ssl.enabled", "false") .set("fs.s3a.access.key", "adfadf") .set("fs.s3a.secret.key", "qerqer")

java.lang.IllegalArgumentException
at java.base/java.util.concurrent.ThreadPoolExecutor.(ThreadPoolExecutor.java:1293)
at java.base/java.util.concurrent.ThreadPoolExecutor.(ThreadPoolExecutor.java:1215)
at org.apache.hadoop.fs.s3a.S3AFileSystem.initialize(S3AFileSystem.java:280)

You have to set the style because it is a different from retrieving from AWS directly
.set("fs.s3a.path.style.access", "true")