So if there are different version of Python on the cluster machines I think that's already unsupported so I'm not worried about that.
I'd suggest going to the highest released version since there appear to be some useful fixes between 0.4.2 & 0.5.2 Also lets try to keep track in our commit messages which version of cloudpickle we end up upgrading to. On Thu, Jan 18, 2018 at 5:45 PM, Bryan Cutler <cutl...@gmail.com> wrote: > Thanks for all the details and background Hyukjin! Regarding the pickle > protocol change, if I understand correctly, it is currently at level 2 in > Spark which is good for backwards compatibility for all of Python 2. > Choosing HIGHEST_PROTOCOL, which is the default for cloudpickle 0.5.0 and > above, will pick a level determined by your Python version. So is the > concern here for Spark if someone has different versions of Python in their > cluster, like 3.5 and 3.3, then different protocols will be used and > deserialization might fail? Is it an option to match the latest version of > cloudpickle and still set protocol level 2? > > I agree that upgrading to try and match version 0.4.2 would be a good > starting point. Unless no one objects, I will open up a JIRA and try to do > this. > > Thanks, > Bryan > > On Mon, Jan 15, 2018 at 7:57 PM, Hyukjin Kwon <gurwls...@gmail.com> wrote: > >> Hi Bryan, >> >> Yup, I support to match the version. I pushed it forward before to match >> it with https://github.com/cloudpipe/cloudpickle >> before few times in Spark's copy and also cloudpickle itself with few >> fixes. I believe our copy is closest to 0.4.1. >> >> I have been trying to follow up the changes in cloudpipe/cloudpickle for >> which version we should match, I think we should match >> it with 0.4.2 first (I need to double check) because IMHO they have been >> adding rather radical changes from 0.5.0, including >> pickle protocol change (by default). >> >> Personally, I would like to match it with the latest because there have >> been some important changes. For >> example, see this too - https://github.com/cloudpipe/cloudpickle/pull/138 >> (it's pending for reviewing yet) eventually but 0.4.2 should be >> a good start point. >> >> For the strategy, I think we can match it and follow 0.4.x within Spark >> for the conservative and safe choice + minimal cost. >> >> >> I tried to leave few explicit answers to the questions from you, Bryan: >> >> > Spark is currently using a forked version and it seems like updates >> are made every now and then when >> > needed, but it's not really clear where the current state is and how >> much it has diverged. >> >> I am quite sure our cloudpickle copy is closer to 0.4.1 IIRC. >> >> >> > Are there any known issues with recent changes from those that follow >> cloudpickle dev? >> >> I am technically involved in cloudpickle dev although less active. >> They changed default pickle protocol (https://github.com/cloudpipe/ >> cloudpickle/pull/127). So, if we target 0.5.x+, we should double check >> the potential compatibility issue, or fix the protocol, which I believe >> is introduced from 0.5.x. >> >> >> >> 2018-01-16 11:43 GMT+09:00 Bryan Cutler <cutl...@gmail.com>: >> >>> Hi All, >>> >>> I've seen a couple issues lately related to cloudpickle, notably >>> https://issues.apache.org/jira/browse/SPARK-22674, and would like to >>> get some feedback on updating the version in PySpark which should fix these >>> issues and allow us to remove some workarounds. Spark is currently using a >>> forked version and it seems like updates are made every now and then when >>> needed, but it's not really clear where the current state is and how much >>> it has diverged. This makes back-porting fixes difficult. There was a >>> previous discussion on moving it to a dependency here >>> <http://apache-spark-developers-list.1001551.n3.nabble.com/PYTHON-DISCUSS-Moving-to-cloudpickle-and-or-Py4J-as-a-dependencies-td20954.html>, >>> but given the status right now I think it would be best to do another >>> update and bring things closer to upstream before we talk about completely >>> moving it outside of Spark. Before starting another update, it might be >>> good to discuss the strategy a little. Should the version in Spark be >>> derived from a release or at least tied to a specific commit? It would >>> also be good if we can document where it has diverged. Are there any known >>> issues with recent changes from those that follow cloudpickle dev? Any >>> other thoughts or concerns? >>> >>> Thanks, >>> Bryan >>> >> >> > -- Twitter: https://twitter.com/holdenkarau
