| tag | c37d0116e86e29cf53596d6915de7bc1e61f8230 | |
|---|---|---|
| tagger | github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> | Fri Apr 16 19:02:01 2021 +0000 |
| object | 1af27ba8acc137509d6d7bc2882177d77115359a |
## Arrow v1.4.0 [Diff since v1.3.0](https://github.com/JuliaData/Arrow.jl/compare/v1.3.0...v1.4.0) **Closed issues:** - reconsidering the current type registration/serialization mechanism (and its internal usage) (#88) - provide mechanism to free metadata stored in OBJ_METADATA? (#90) - Arrow.write slow perf with ZonedDateTime (#95) - Implement DataAPI pool/dict encoding methods for DictEncoded (#120) - Slower materialization Feather vs Arrow (#131) - Usage with MPI (#151) - Reading CSV (#157) - Reading an Arrow file with no message batches after the schema seems to produce a partly initialized Table? (#158) - DictEncoded methods for refpool, refarray and levels (#159) - MethodError `Int64(::Arrow.Timestamp...` when reading arrow file saved by `pandas`. (#166) - Improve printing? (#168) **Merged pull requests:** - Add refpool, refarray and levels for DictEncoded (#161) (@dmbates) - Tweak promoteunion to always avoid abstract types (#162) (@quinnj) - Restructure ArrowTypes so it can be registered as its own package (#163) (@quinnj) - DataAPI methods (#164) (@quinnj) - Don't store table metadata globally (#165) (@quinnj) - document guarantee that `getmetadata` returns alias not copy (#169) (@jrevels) - add missing setmedata! method for Arrow.Table (#170) (@jrevels) - use actual deprecation for `registertype!` (#171) (@ericphanson) - Warn when converting Arrow.Timestamps to Dates.DateTime or ZonedDateTime (#172) (@quinnj) - Introduce Arrow.ToTimestamp for performant ZonedDateTime encoding (#173) (@quinnj) - Fix () -> {} typo in docs (#174) (@etpinard) - Fix case when ipc stream has no record batches, only schema (#175) (@quinnj) - Fix slight perf hit when checking validity bitmap (#176) (@quinnj)
| commit | 1af27ba8acc137509d6d7bc2882177d77115359a | [log] [tgz] |
|---|---|---|
| author | Jacob Quinn <quinn.jacobd@gmail.com> | Fri Apr 16 12:37:50 2021 -0600 |
| committer | GitHub <noreply@github.com> | Fri Apr 16 12:37:50 2021 -0600 |
| tree | 9820b26ac436a09b8aed2da8489fc9412cc0aab1 | |
| parent | bdd0e5473cffe0f1eec6c0752f909dcdf77cac07 [diff] |
Bump version
This is a pure Julia implementation of the Apache Arrow data standard. This package provides Julia AbstractVector objects for referencing data that conforms to the Arrow standard. This allows users to seamlessly interface Arrow formatted data with a great deal of existing Julia code.
Please see this document for a description of the Arrow memory layout.
The package can be installed by typing in the following in a Julia REPL:
julia> using Pkg; Pkg.add("Arrow")
or to use the official-apache code that follows the official apache release process, you can do:
julia> using Pkg; Pkg.add(url="https://github.com/apache/arrow", subdir="julia/Arrow.jl")
The code in the apache/arrow repository is officially part of the apache/arrow project and as such follows the regulated release cadence of the entire project, following standard community voting protocols. The JuliaData/Arrow.jl repository can be viewed as a sort of “dev” or “latest” branch of this code that may release more frequently, but without following official apache release guidelines. The two repositories are synced, however, so any bugfix patches in JuliaData will be upstreamed to apache/arrow for each release.
This implementation supports the 1.0 version of the specification, including support for:
It currently doesn't include support for:
Third-party data formats:
See the full documentation for details on reading and writing arrow data.