JuliaDB.jl
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JuliaData
Parallel analytical database in pure Julia
```julia A = ndsparse((numid=1:10,), (a=1:10,b=1:10); chunks=2) B = map(v->v.a+1,A) ``` seems to work, but assigns wrong type parameter `typeof(B)` ``` JuliaDB.DNDSparse{NamedTuple{(:numid,),Tuple{Int64}},NamedTuple{(:a, :b),Tuple{Int64,Int64}}} ``` which makes ```julia C = filter(isodd, B)...
``` @everywhere using JuliaDB indicesA = (S=[0.6, 0.7], T=[1,2.0]) indicesB = (S=[1.6, 1.7], T=[2,5.0]) valsAscalar = (u=[1, 2], t=[2, 3]) valsBscalar = (u=[30, 50], t=[4, 5]) Ascalar = ndsparse(indicesA, valsAscalar)...
I would expect: ```julia using JuliaDB t1 = table( [1:5; 1:5], 11:20, 31:40, names = [:a, :b, :c]) t2= filter(row-> (row.a==3 && row.b==13) | (row.a==5 && row.b==20),t1) join(t1,t2,how=:anti,lkey=(:a,:b), rkey=(:a,:b)) ```...
**Update** **On Julia 1.2 I get the below** I have included a MWE that can actually run by downloading the Fannie data direct from https://docs.rapids.ai/datasets/mortgage-data However, loading the data takes...
I tried loadtable with a csv file which contained one column having date values in dd/mm/yyyy format. The command threw error stating that day is invalid. I tried excluding that...
```julia using Distributed addprocs(4) @everywhere using JuliaDB loadtable("some.csv", chunks=4) # distributed table with 1 chunk ``` I was expecting more than one chunk. As mentioned on slack.
This issue follows a [question](https://discourse.julialang.org/t/juliadb-parallel-distributed-computing/25991/5) on Discourse about a U.S. Census [data set]( https://www2.census.gov/programs-surveys/acs/data/pums/2017/5-Year/csv_pus.zip): I first split the 4 CSVs, because otherwise `loadtable` throws and out-of-memory error: ``` files =...
This [post](https://discourse.julialang.org/t/juliadb-questions-issues/24785/5) documents a problem with a very basic use case of JuliaDB. This [issue](https://github.com/JuliaComputing/TextParse.jl/issues/137) offers more details to problem below: ``` using JuliaDB acs = loadtable("psam_pusa.csv", type_detect_rows=200) save(acs, "test")...
If I `loadtable` with `filenamecol = :source_file` this creates a new **first** column. Then `indexcols` and `datacols` need to be shifted by one index, which is a bit impractical. So,...