Re: Preparing for 0.17.0 Arrow release
I'm not able to reproduce the test-conda-python-3.7-kartothek-master failure locally with docker-compose, is that a flake or real? On Sat, Apr 11, 2020 at 7:29 AM Krisztián Szűcs wrote: > > On Sat, Apr 11, 2020 at 12:37 PM Antoine Pitrou wrote: > > > > > > Le 11/04/2020 à 12:34, Krisztián Szűcs a écrit : > > > - test-conda-python-3.7-turbodbc-latest: > > > - test-conda-python-3.7-turbodbc-master: > > > The latest is important here, because the release would break the > > > interoperability with turbodbc. > > > I need feedback on this from Uwe. > > > > For transparency, this was diagnosed and two issues were filed for turbodbc: > > https://github.com/blue-yonder/turbodbc/issues/251 > > https://github.com/blue-yonder/turbodbc/issues/250 > > > > I'm not sure there's anything Arrow can do to restore compatibility. If > > we relax array validation to avoid the validation failure that turbodbc > > is getting, the erroneously-constructed Arrow array could lead to > > further errors or crashes later on. > Than we shouldn't consider the turbodbc integration tests as blocker. > > Thanks Antoine! > > > > Regards > > > > Antoine.
[NIGHTLY] Arrow Build Report for Job nightly-2020-04-11-2
Arrow Build Report for Job nightly-2020-04-11-2 All tasks: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2 Failed Tasks: - conda-win-vs2015-py36: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-azure-conda-win-vs2015-py36 - conda-win-vs2015-py37: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-azure-conda-win-vs2015-py37 - conda-win-vs2015-py38: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-azure-conda-win-vs2015-py38 - gandiva-jar-trusty: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-travis-gandiva-jar-trusty - test-conda-cpp-hiveserver2: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-circle-test-conda-cpp-hiveserver2 - test-conda-python-3.7-hdfs-2.9.2: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-circle-test-conda-python-3.7-hdfs-2.9.2 - test-conda-python-3.7-turbodbc-latest: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-circle-test-conda-python-3.7-turbodbc-latest - test-conda-python-3.7-turbodbc-master: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-circle-test-conda-python-3.7-turbodbc-master - ubuntu-focal-amd64: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-github-ubuntu-focal-amd64 - wheel-osx-cp37m: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-travis-wheel-osx-cp37m - wheel-win-cp35m: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-appveyor-wheel-win-cp35m Pending Tasks: - test-conda-python-3.8-pandas-latest: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-circle-test-conda-python-3.8-pandas-latest - test-ubuntu-18.04-cpp-cmake32: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-circle-test-ubuntu-18.04-cpp-cmake32 Succeeded Tasks: - centos-6-amd64: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-github-centos-6-amd64 - centos-7-amd64: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-github-centos-7-amd64 - centos-8-amd64: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-github-centos-8-amd64 - conda-linux-gcc-py36: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-azure-conda-linux-gcc-py36 - conda-linux-gcc-py37: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-azure-conda-linux-gcc-py37 - conda-linux-gcc-py38: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-azure-conda-linux-gcc-py38 - conda-osx-clang-py36: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-azure-conda-osx-clang-py36 - conda-osx-clang-py37: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-azure-conda-osx-clang-py37 - conda-osx-clang-py38: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-azure-conda-osx-clang-py38 - debian-buster-amd64: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-github-debian-buster-amd64 - debian-stretch-amd64: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-github-debian-stretch-amd64 - gandiva-jar-osx: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-travis-gandiva-jar-osx - homebrew-cpp-autobrew: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-travis-homebrew-cpp-autobrew - homebrew-cpp: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-travis-homebrew-cpp - homebrew-r-autobrew: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-travis-homebrew-r-autobrew - test-conda-cpp-valgrind: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-circle-test-conda-cpp-valgrind - test-conda-cpp: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-circle-test-conda-cpp - test-conda-python-3.6: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-circle-test-conda-python-3.6 - test-conda-python-3.7-dask-latest: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-circle-test-conda-python-3.7-dask-latest - test-conda-python-3.7-kartothek-latest: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-circle-test-conda-python-3.7-kartothek-latest - test-conda-python-3.7-kartothek-master: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-2-circle-tes
[jira] [Created] (ARROW-8404) Read and write dataset description in both R and Python
Vincent Nijs created ARROW-8404: --- Summary: Read and write dataset description in both R and Python Key: ARROW-8404 URL: https://issues.apache.org/jira/browse/ARROW-8404 Project: Apache Arrow Issue Type: New Feature Reporter: Vincent Nijs Below a feature request for feather. Wes suggested opening an issue here. The idea is to add metadata to a data frame to store and display information about the data (e.g., variable descriptions, data source, main company contact about data, changes, etc. etc.). For a simple example in R (+ shiny) that uses a "description" attribute in markdown format and then renders it in HTML when loaded, see the link below. See the description for the diamonds data. [https://vnijs.shinyapps.io/radiant] Having a data format that works for both R and Python *and* maintains attributes like a data description would be great! [https://github.com/wesm/feather/issues/328] -- This message was sent by Atlassian Jira (v8.3.4#803005)
[jira] [Created] (ARROW-8403) [C++] Add ToString() to ChunkedArray, Table and RecordBatch
Kouhei Sutou created ARROW-8403: --- Summary: [C++] Add ToString() to ChunkedArray, Table and RecordBatch Key: ARROW-8403 URL: https://issues.apache.org/jira/browse/ARROW-8403 Project: Apache Arrow Issue Type: Improvement Components: C++ Reporter: Kouhei Sutou Assignee: Kouhei Sutou -- This message was sent by Atlassian Jira (v8.3.4#803005)
[NIGHTLY] Arrow Build Report for Job nightly-2020-04-11-1
Arrow Build Report for Job nightly-2020-04-11-1 All tasks: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1 Failed Tasks: - conda-win-vs2015-py36: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-azure-conda-win-vs2015-py36 - conda-win-vs2015-py37: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-azure-conda-win-vs2015-py37 - conda-win-vs2015-py38: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-azure-conda-win-vs2015-py38 - gandiva-jar-trusty: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-travis-gandiva-jar-trusty - test-conda-cpp-hiveserver2: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-circle-test-conda-cpp-hiveserver2 - test-conda-python-3.7-hdfs-2.9.2: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-circle-test-conda-python-3.7-hdfs-2.9.2 - test-conda-python-3.7-turbodbc-latest: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-circle-test-conda-python-3.7-turbodbc-latest - test-conda-python-3.7-turbodbc-master: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-circle-test-conda-python-3.7-turbodbc-master - ubuntu-focal-amd64: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-github-ubuntu-focal-amd64 - wheel-osx-cp37m: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-travis-wheel-osx-cp37m - wheel-osx-cp38: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-travis-wheel-osx-cp38 - wheel-win-cp35m: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-appveyor-wheel-win-cp35m Succeeded Tasks: - centos-6-amd64: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-github-centos-6-amd64 - centos-7-amd64: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-github-centos-7-amd64 - centos-8-amd64: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-github-centos-8-amd64 - conda-linux-gcc-py36: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-azure-conda-linux-gcc-py36 - conda-linux-gcc-py37: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-azure-conda-linux-gcc-py37 - conda-linux-gcc-py38: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-azure-conda-linux-gcc-py38 - conda-osx-clang-py36: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-azure-conda-osx-clang-py36 - conda-osx-clang-py37: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-azure-conda-osx-clang-py37 - conda-osx-clang-py38: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-azure-conda-osx-clang-py38 - debian-buster-amd64: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-github-debian-buster-amd64 - debian-stretch-amd64: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-github-debian-stretch-amd64 - gandiva-jar-osx: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-travis-gandiva-jar-osx - homebrew-cpp-autobrew: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-travis-homebrew-cpp-autobrew - homebrew-cpp: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-travis-homebrew-cpp - homebrew-r-autobrew: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-travis-homebrew-r-autobrew - test-conda-cpp-valgrind: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-circle-test-conda-cpp-valgrind - test-conda-cpp: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-circle-test-conda-cpp - test-conda-python-3.6: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-circle-test-conda-python-3.6 - test-conda-python-3.7-dask-latest: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-circle-test-conda-python-3.7-dask-latest - test-conda-python-3.7-kartothek-latest: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-circle-test-conda-python-3.7-kartothek-latest - test-conda-python-3.7-kartothek-master: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-circle-test-conda-python-3.7-kartothek-master - test-conda-python-3.7-pandas-latest: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-1-circle-test-conda-python-3.7-pandas-latest - test-con
[jira] [Created] (ARROW-8402) [Java] Support ValidateFull methods in Java
Liya Fan created ARROW-8402: --- Summary: [Java] Support ValidateFull methods in Java Key: ARROW-8402 URL: https://issues.apache.org/jira/browse/ARROW-8402 Project: Apache Arrow Issue Type: New Feature Components: Java Reporter: Liya Fan Assignee: Liya Fan We need to support ValidateFull methods in Java, just like we do in C++. This is required by ARROW-5926. -- This message was sent by Atlassian Jira (v8.3.4#803005)
Re: Preparing for 0.17.0 Arrow release
On Sat, Apr 11, 2020 at 12:37 PM Antoine Pitrou wrote: > > > Le 11/04/2020 à 12:34, Krisztián Szűcs a écrit : > > - test-conda-python-3.7-turbodbc-latest: > > - test-conda-python-3.7-turbodbc-master: > > The latest is important here, because the release would break the > > interoperability with turbodbc. > > I need feedback on this from Uwe. > > For transparency, this was diagnosed and two issues were filed for turbodbc: > https://github.com/blue-yonder/turbodbc/issues/251 > https://github.com/blue-yonder/turbodbc/issues/250 > > I'm not sure there's anything Arrow can do to restore compatibility. If > we relax array validation to avoid the validation failure that turbodbc > is getting, the erroneously-constructed Arrow array could lead to > further errors or crashes later on. Than we shouldn't consider the turbodbc integration tests as blocker. Thanks Antoine! > > Regards > > Antoine.
Re: Preparing for 0.17.0 Arrow release
Le 11/04/2020 à 12:34, Krisztián Szűcs a écrit : > - test-conda-python-3.7-turbodbc-latest: > - test-conda-python-3.7-turbodbc-master: > The latest is important here, because the release would break the > interoperability with turbodbc. > I need feedback on this from Uwe. For transparency, this was diagnosed and two issues were filed for turbodbc: https://github.com/blue-yonder/turbodbc/issues/251 https://github.com/blue-yonder/turbodbc/issues/250 I'm not sure there's anything Arrow can do to restore compatibility. If we relax array validation to avoid the validation failure that turbodbc is getting, the erroneously-constructed Arrow array could lead to further errors or crashes later on. Regards Antoine.
Re: Preparing for 0.17.0 Arrow release
We'll receive three nightly reports per day until the release, see the failing tasks there. Failed Tasks: - conda-osx-*: - conda-win-*: - wheel-osx-cp38: - wheel-win-*: Python dataset tests are failing, possible related to silently ignoring paths when reading via the new ParquetDataset. Not trivial to reproduce. - test-conda-python-3.7-hdfs-2.9.2: Unable to download hadoop from the apache mirror, probably not a blocker but would be nice to see that hdfs tests are passing. - test-conda-python-3.7-kartothek-master: - test-conda-python-3.7-turbodbc-latest: - test-conda-python-3.7-turbodbc-master: The latest is important here, because the release would break the interoperability with turbodbc. I need feedback on this from Uwe. On Fri, Apr 10, 2020 at 10:18 PM Wes McKinney wrote: > > None of the open issues look like they should prevent a release > candidate from being cut. > > Fixing the nightly and packaging builds seems like the last remaining > task, but some of them need to be tracked by JIRA issues. Can you > write a list here of what's definitely currently broken? > > On Fri, Apr 10, 2020 at 1:35 PM Krisztián Szűcs > wrote: > > > > We still have 12 open issues, about half of them are not essential. > > The more pressing problem is the number of failing builds including > > packaging builds (see the nightly reports). > > > > Releasing today doesn't look realistic, but if we're able to resolve > > the issues over the weekend I can start the release procedure on > > Monday. > > > > Thanks, Krisztian > > > > On Tue, Apr 7, 2020 at 4:31 AM Andy Grove wrote: > > > > > > There are two trivial Rust PRs pending that I would like to see merged for > > > the release. > > > > > > ARROW-7794: [Rust] Support releasing arrow-flight > > > > > > https://github.com/apache/arrow/pull/6858 > > > > > > ARROW-8357: [Rust] [DataFusion] Dockerfile for CLI is missing format dir > > > > > > https://github.com/apache/arrow/pull/6860 > > > > > > Thanks, > > > > > > Andy. > > > > > > > > > On Mon, Apr 6, 2020 at 6:55 AM Antoine Pitrou wrote: > > > > > > > > > > > Also nice to have perhaps (PR available and several back-and-forths > > > > already): > > > > > > > > * ARROW-7610: [Java] Finish support for 64 bit int allocations > > > > > > > > Needs a Java committer to decide... > > > > > > > > Regards > > > > > > > > Antoine. > > > > > > > > > > > > Le 06/04/2020 à 00:24, Wes McKinney a écrit : > > > > > We are getting close to the 0.17.0 endgame. > > > > > > > > > > Here are the 18 JIRAs still in the 0.17.0 milestone. There are a few > > > > > issues without patches yet so we should decide quickly whether they > > > > > need to be included. Are they any blocking issues not accounted for in > > > > > the milestone? > > > > > > > > > > * ARROW-6947 [Rust] [DataFusion] Add support for scalar UDFs > > > > > > > > > > Patch available > > > > > > > > > > * ARROW-7794 [Rust] cargo publish fails for arrow-flight due to > > > > > relative path to Flight.proto > > > > > > > > > > No patch yet > > > > > > > > > > * ARROW-7222 [Python][Release] Wipe any existing generated Python API > > > > > documentation when updating website > > > > > > > > > > This issue needs to be addressed by the release manager and the > > > > > Confluence instructions must be updated. > > > > > > > > > > * ARROW-7891 [C++] RecordBatch->Equals should also have a > > > > > check_metadata argument > > > > > > > > > > Patch available that needs to be reviewed and approved > > > > > > > > > > * ARROW-8164: [C++][Dataset] Let datasets be viewable with > > > > > non-identical > > > > schema > > > > > > > > > > Patch available, but failures to be resolved > > > > > > > > > > * ARROW-7965: [Python] Hold a reference to the dataset factory for > > > > > later > > > > reuse > > > > > > > > > > Depends on ARROW-8164, will require rebase > > > > > > > > > > * ARROW-8039: [Python][Dataset] Support using dataset API in > > > > > pyarrow.parquet with a minimal ParquetDataset shim > > > > > > > > > > Patch pending > > > > > > > > > > * ARROW-8047: [Python][Documentation] Document migration from > > > > > ParquetDataset to pyarrow.datasets > > > > > > > > > > May be tackled beyond 0.17.0 > > > > > > > > > > * ARROW-8063: [Python] Add user guide documentation for Datasets API > > > > > > > > > > May be tackled beyond 0.17.0 > > > > > > > > > > * ARROW-8149 [C++/Python] Enable CUDA Support in conda recipes > > > > > > > > > > Does not seem strictly necessary for release, since a packaging issue > > > > > > > > > > * ARROW-8162: [Format][Python] Add serialization for CSF sparse > > > > > tensors > > > > > > > > > > Patch available, but needs review. May > > > > > > > > > > * ARROW-8213: [Python][Dataset] Opening a dataset with a local > > > > > incorrect path gives confusing error message > > > > > > > > > > Nice to have, but not essential > > > > > > > > > > * ARROW-8266: [C++] Add backup mirrors for external project source > > > > downloads > > > > > > > > > > Patch av
[NIGHTLY] Arrow Build Report for Job nightly-2020-04-11-0
Arrow Build Report for Job nightly-2020-04-11-0 All tasks: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0 Failed Tasks: - conda-osx-clang-py36: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-azure-conda-osx-clang-py36 - conda-win-vs2015-py36: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-azure-conda-win-vs2015-py36 - conda-win-vs2015-py37: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-azure-conda-win-vs2015-py37 - conda-win-vs2015-py38: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-azure-conda-win-vs2015-py38 - gandiva-jar-trusty: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-travis-gandiva-jar-trusty - test-conda-cpp-hiveserver2: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-circle-test-conda-cpp-hiveserver2 - test-conda-python-3.7-hdfs-2.9.2: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-circle-test-conda-python-3.7-hdfs-2.9.2 - test-conda-python-3.7-kartothek-master: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-circle-test-conda-python-3.7-kartothek-master - test-conda-python-3.7-turbodbc-latest: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-circle-test-conda-python-3.7-turbodbc-latest - test-conda-python-3.7-turbodbc-master: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-circle-test-conda-python-3.7-turbodbc-master - test-ubuntu-16.04-cpp: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-circle-test-ubuntu-16.04-cpp - ubuntu-focal-amd64: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-github-ubuntu-focal-amd64 - wheel-manylinux1-cp36m: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-azure-wheel-manylinux1-cp36m - wheel-osx-cp35m: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-travis-wheel-osx-cp35m - wheel-osx-cp38: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-travis-wheel-osx-cp38 - wheel-win-cp35m: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-appveyor-wheel-win-cp35m Succeeded Tasks: - centos-6-amd64: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-github-centos-6-amd64 - centos-7-amd64: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-github-centos-7-amd64 - centos-8-amd64: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-github-centos-8-amd64 - conda-linux-gcc-py36: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-azure-conda-linux-gcc-py36 - conda-linux-gcc-py37: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-azure-conda-linux-gcc-py37 - conda-linux-gcc-py38: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-azure-conda-linux-gcc-py38 - conda-osx-clang-py37: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-azure-conda-osx-clang-py37 - conda-osx-clang-py38: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-azure-conda-osx-clang-py38 - debian-buster-amd64: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-github-debian-buster-amd64 - debian-stretch-amd64: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-github-debian-stretch-amd64 - gandiva-jar-osx: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-travis-gandiva-jar-osx - homebrew-cpp-autobrew: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-travis-homebrew-cpp-autobrew - homebrew-cpp: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-travis-homebrew-cpp - homebrew-r-autobrew: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-travis-homebrew-r-autobrew - test-conda-cpp-valgrind: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-circle-test-conda-cpp-valgrind - test-conda-cpp: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-circle-test-conda-cpp - test-conda-python-3.6: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-circle-test-conda-python-3.6 - test-conda-python-3.7-dask-latest: URL: https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-04-11-0-circle-test-conda-python-3.7-dask-latest - test-conda-python-3.7-kartothek-latest: URL: https://github.com/ur
