Great that Hadoop has done it (which, btw, probably means that Spark won't work with that version of Hadoop yet), but Hive also depends on Guava, and last time I tried, even Hive 3.x did not work with Guava 27.
(Newer Hadoop versions also have a new artifact that shades a lot of dependencies, which would be great for Spark. But since Spark uses some test artifacts from Hadoop, that may be a bit tricky, since I don't believe those are shaded.) On Sun, Dec 15, 2019 at 8:08 AM Sean Owen <sro...@gmail.com> wrote: > > See for example: > > https://github.com/apache/spark/pull/25932#issuecomment-565822573 > https://issues.apache.org/jira/browse/SPARK-23897 > > This is a dicey dependency that we have been reluctant to update as a) > Hadoop used an old version and b) Guava versions are incompatible > after a few releases. > > But Hadoop is going all the way from 11 to 27 in Hadoop 3.2.1. Time to > match that? I haven't assessed how much internal change it requires. > If it's a lot, well, that makes it hard, as we need to stay compatible > with Hadoop 2 / Guava 11-14. But then that causes a problem updating > past Hadoop 3.2.0. > > --------------------------------------------------------------------- > To unsubscribe e-mail: dev-unsubscr...@spark.apache.org > -- Marcelo --------------------------------------------------------------------- To unsubscribe e-mail: dev-unsubscr...@spark.apache.org
