pyspark --packages org.apache.hadoop:hadoop-aws:2.7.3 didn’t work for me either (even building with -Phadoop-2.7). I guess I’ve been relying on an unsupported pattern and will need to figure something else out going forward in order to use s3a://.
On Fri, Jun 1, 2018 at 9:09 PM Marcelo Vanzin <van...@cloudera.com> wrote: > I have personally never tried to include hadoop-aws that way. But at > the very least, I'd try to use the same version of Hadoop as the Spark > build (2.7.3 IIRC). I don't really expect a different version to work, > and if it did in the past it definitely was not by design. > > On Fri, Jun 1, 2018 at 5:50 PM, Nicholas Chammas > <nicholas.cham...@gmail.com> wrote: > > Building with -Phadoop-2.7 didn’t help, and if I remember correctly, > > building with -Phadoop-2.8 worked with hadoop-aws in the 2.3.0 release, > so > > it appears something has changed since then. > > > > I wasn’t familiar with -Phadoop-cloud, but I can try that. > > > > My goal here is simply to confirm that this release of Spark works with > > hadoop-aws like past releases did, particularly for Flintrock users who > use > > Spark with S3A. > > > > We currently provide -hadoop2.6, -hadoop2.7, and -without-hadoop builds > with > > every Spark release. If the -hadoop2.7 release build won’t work with > > hadoop-aws anymore, are there plans to provide a new build type that > will? > > > > Apologies if the question is poorly formed. I’m batting a bit outside my > > league here. Again, my goal is simply to confirm that I/my users still > have > > a way to use s3a://. In the past, that way was simply to call pyspark > > --packages org.apache.hadoop:hadoop-aws:2.8.4 or something very similar. > If > > that will no longer work, I’m trying to confirm that the change of > behavior > > is intentional or acceptable (as a review for the Spark project) and > figure > > out what I need to change (as due diligence for Flintrock’s users). > > > > Nick > > > > > > On Fri, Jun 1, 2018 at 8:21 PM Marcelo Vanzin <van...@cloudera.com> > wrote: > >> > >> Using the hadoop-aws package is probably going to be a little more > >> complicated than that. The best bet is to use a custom build of Spark > >> that includes it (use -Phadoop-cloud). Otherwise you're probably > >> looking at some nasty dependency issues, especially if you end up > >> mixing different versions of Hadoop. > >> > >> On Fri, Jun 1, 2018 at 4:01 PM, Nicholas Chammas > >> <nicholas.cham...@gmail.com> wrote: > >> > I was able to successfully launch a Spark cluster on EC2 at 2.3.1 RC4 > >> > using > >> > Flintrock. However, trying to load the hadoop-aws package gave me some > >> > errors. > >> > > >> > $ pyspark --packages org.apache.hadoop:hadoop-aws:2.8.4 > >> > > >> > <snipped> > >> > > >> > :: problems summary :: > >> > :::: WARNINGS > >> > [NOT FOUND ] > >> > com.sun.jersey#jersey-json;1.9!jersey-json.jar(bundle) (2ms) > >> > ==== local-m2-cache: tried > >> > > >> > > >> > > file:/home/ec2-user/.m2/repository/com/sun/jersey/jersey-json/1.9/jersey-json-1.9.jar > >> > [NOT FOUND ] > >> > com.sun.jersey#jersey-server;1.9!jersey-server.jar(bundle) (0ms) > >> > ==== local-m2-cache: tried > >> > > >> > > >> > > file:/home/ec2-user/.m2/repository/com/sun/jersey/jersey-server/1.9/jersey-server-1.9.jar > >> > [NOT FOUND ] > >> > org.codehaus.jettison#jettison;1.1!jettison.jar(bundle) (1ms) > >> > ==== local-m2-cache: tried > >> > > >> > > >> > > file:/home/ec2-user/.m2/repository/org/codehaus/jettison/jettison/1.1/jettison-1.1.jar > >> > [NOT FOUND ] > >> > com.sun.xml.bind#jaxb-impl;2.2.3-1!jaxb-impl.jar (0ms) > >> > ==== local-m2-cache: tried > >> > > >> > > >> > > file:/home/ec2-user/.m2/repository/com/sun/xml/bind/jaxb-impl/2.2.3-1/jaxb-impl-2.2.3-1.jar > >> > > >> > I’d guess I’m probably using the wrong version of hadoop-aws, but I > >> > called > >> > make-distribution.sh with -Phadoop-2.8 so I’m not sure what else to > try. > >> > > >> > Any quick pointers? > >> > > >> > Nick > >> > > >> > > >> > On Fri, Jun 1, 2018 at 6:29 PM Marcelo Vanzin <van...@cloudera.com> > >> > wrote: > >> >> > >> >> Starting with my own +1 (binding). > >> >> > >> >> On Fri, Jun 1, 2018 at 3:28 PM, Marcelo Vanzin <van...@cloudera.com> > >> >> wrote: > >> >> > Please vote on releasing the following candidate as Apache Spark > >> >> > version > >> >> > 2.3.1. > >> >> > > >> >> > Given that I expect at least a few people to be busy with Spark > >> >> > Summit > >> >> > next > >> >> > week, I'm taking the liberty of setting an extended voting period. > >> >> > The > >> >> > vote > >> >> > will be open until Friday, June 8th, at 19:00 UTC (that's 12:00 > PDT). > >> >> > > >> >> > It passes with a majority of +1 votes, which must include at least > 3 > >> >> > +1 > >> >> > votes > >> >> > from the PMC. > >> >> > > >> >> > [ ] +1 Release this package as Apache Spark 2.3.1 > >> >> > [ ] -1 Do not release this package because ... > >> >> > > >> >> > To learn more about Apache Spark, please see > http://spark.apache.org/ > >> >> > > >> >> > The tag to be voted on is v2.3.1-rc4 (commit 30aaa5a3): > >> >> > https://github.com/apache/spark/tree/v2.3.1-rc4 > >> >> > > >> >> > The release files, including signatures, digests, etc. can be found > >> >> > at: > >> >> > https://dist.apache.org/repos/dist/dev/spark/v2.3.1-rc4-bin/ > >> >> > > >> >> > Signatures used for Spark RCs can be found in this file: > >> >> > https://dist.apache.org/repos/dist/dev/spark/KEYS > >> >> > > >> >> > The staging repository for this release can be found at: > >> >> > > >> >> > > https://repository.apache.org/content/repositories/orgapachespark-1272/ > >> >> > > >> >> > The documentation corresponding to this release can be found at: > >> >> > https://dist.apache.org/repos/dist/dev/spark/v2.3.1-rc4-docs/ > >> >> > > >> >> > The list of bug fixes going into 2.3.1 can be found at the > following > >> >> > URL: > >> >> > https://issues.apache.org/jira/projects/SPARK/versions/12342432 > >> >> > > >> >> > FAQ > >> >> > > >> >> > ========================= > >> >> > How can I help test this release? > >> >> > ========================= > >> >> > > >> >> > If you are a Spark user, you can help us test this release by > taking > >> >> > an existing Spark workload and running on this release candidate, > >> >> > then > >> >> > reporting any regressions. > >> >> > > >> >> > If you're working in PySpark you can set up a virtual env and > install > >> >> > the current RC and see if anything important breaks, in the > >> >> > Java/Scala > >> >> > you can add the staging repository to your projects resolvers and > >> >> > test > >> >> > with the RC (make sure to clean up the artifact cache before/after > so > >> >> > you don't end up building with a out of date RC going forward). > >> >> > > >> >> > =========================================== > >> >> > What should happen to JIRA tickets still targeting 2.3.1? > >> >> > =========================================== > >> >> > > >> >> > The current list of open tickets targeted at 2.3.1 can be found at: > >> >> > https://s.apache.org/Q3Uo > >> >> > > >> >> > Committers should look at those and triage. Extremely important bug > >> >> > fixes, documentation, and API tweaks that impact compatibility > should > >> >> > be worked on immediately. Everything else please retarget to an > >> >> > appropriate release. > >> >> > > >> >> > ================== > >> >> > But my bug isn't fixed? > >> >> > ================== > >> >> > > >> >> > In order to make timely releases, we will typically not hold the > >> >> > release unless the bug in question is a regression from the > previous > >> >> > release. That being said, if there is something which is a > regression > >> >> > that has not been correctly targeted please ping me or a committer > to > >> >> > help target the issue. > >> >> > > >> >> > > >> >> > -- > >> >> > Marcelo > >> >> > >> >> > >> >> > >> >> -- > >> >> Marcelo > >> >> > >> >> --------------------------------------------------------------------- > >> >> To unsubscribe e-mail: dev-unsubscr...@spark.apache.org > >> >> > >> > > >> > >> > >> > >> -- > >> Marcelo > > > > -- > Marcelo >
