ArcticDB
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ArcticDB is a high performance, serverless DataFrame database built for the Python Data Science ecosystem.
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**Is your feature request related to a problem? Please describe.** Our current benchmarks don't test realistic large scale use cases. **Describe the solution you'd like** A benchmarking suite which: -...
### Describe the bug Creating a symbol with column of array type containing arrays with different dtype succeeds and then prints out garbage. ### Steps/Code to Reproduce ```python from arcticdb...
v1 API, behaviour almost certainly the same with `finalize_staged_data` in the v2 API. Minimal repro: ``` lib.write(sym, pd.DataFrame({"col": ["hello"]}, index=[pd.Timestamp("2000-01-01")]), parallel=True) lib.write(sym, pd.DataFrame({"col": [None]}, index=[pd.Timestamp("2000-01-02")]), parallel=True) lib.compact_incomplete(sym, False, False) ```...
No longer required. Open question - what Pandas compat do we need? 3.6 build is the only one that tests Pandas 0.x compat. It would help the projects velocity to...
We would like to support Azure as a storage for our tests. This should be done in a similar way to the AWS S3 persistent storage support that already have....
How to do debug builds on conda? Julien's idea: We could setup a dedicated channels for Debug of RelWithDebInfo builds on conda-forge: ``` mamba install -c conda-forge/label/arcticdb_debuginfo arcticdb ``` ie,...
**Is your feature request related to a problem? Please describe.** Currently releases are painful because: 1. We occasionally discover issues/bugs during or after a release which is bad 2. The...
PR #1462 made a start on extending persistent storages test coverage. But the existing persistent storage tests run on a large matrix, checking interop between every 2 elements in this...
At the moment compaction is not safe to perform on quite a lot of data - essentially it only works for static schema. Ideally it should work more like downsampling...
