Comments (9)
Cc: @tanmaykm
from dataframes.jl.
I was thinking of the following model for this:
- New objects:
DistributedDataVector
,DistributedDataFrame
,DistributedGroupedDataFrame
DistributedDataVector
: simplified 1D darrayDistributedDataFrame
: collection of remote refs toDataFrames
/DistributedDataVectors
DistributedGroupedDataFrame
: collection ofDistributedDataFrames
- To start with we can have an interface to read from files with rows split by row numbers. Can use mmap to map different portions of a single large file.
- Implement most operations on
DataFrame
andDataVector
as defined in operators.jl - Have convert methods to get all parts of a
DistributedDataVector
/DistributedDataFrame
locally asDataVector
/DataFrame
. - All operations implemented using
pmap
/pmapreduce
underneath
I can have a go at this if it sounds good. Would be glad to have any comments/discussions before I start.
from dataframes.jl.
I wonder if a design is possible without using Distributed
prefixes for everything. Right now, I can't think of an alternative.
from dataframes.jl.
This would be great. I'd suggest just building the data structures up first since I think we'll see what needs to be handled there as we go on.
As you go, please let us know when you find functions that should be defined in terms of AbstractDataFrame
so that DataFrame
and DistributedDataFrame
are handled together.
from dataframes.jl.
I thought of having just the DistributedDataVector
(with an abstract DataVector
), but was not sure if that would be enough to handle all functionalities.
from dataframes.jl.
I think we really want the rows of a DataFrame to be distributed, rather than the columns.
from dataframes.jl.
Yes, I agree.
I was wondering if it would it be any better to implement the DistributedDataFrame
as a collection of DistributedDataVectors
rather than a collection of remote DataFrames
.
from dataframes.jl.
Oh, definitely. So long as you can guarantee that each of the vectors is split in the same way, I think we should follow the existing definition of DataFrame
and define things in terms of columns.
from dataframes.jl.
See prototypes
branch for early implementation / inspiration.
from dataframes.jl.
Related Issues (20)
- Feature request: Pairs in stack HOT 2
- Grouped DataFrame with array elements fails to combine HOT 4
- error when combining a grouped empty dataframe using `first` HOT 6
- Short circuit && on subset? HOT 1
- Integer strings as colnames/selectors are error prone HOT 2
- Suggestion - Matrix Syntax for hcat (as well as vcat) HOT 4
- Document custom generation of column names in manual HOT 9
- `join` should not introduce `Missing` types to schema HOT 1
- Consider removing Tables.allocatecolumn in vcat
- DataFrame(t::Table) converts PooledVector columns HOT 2
- Sampling GroupedDataFrames (rand) HOT 5
- Julia 1.12.0-DEV: testing DataFrames throws a 'method dispatch ambiguities' error HOT 2
- Add options to `join` missing error? HOT 1
- Column types seem to change after inner-join between two DataFrames HOT 1
- using propertynames on GroupedDataFrame HOT 6
- Very slow to convert DBInterface (DuckDB) result HOT 1
- Add arbitrary matching function for joins HOT 3
- Add Tidier.jl to docs/src/man/querying_frameworks.md HOT 1
- join size warnings
- Type piracy of `reduce(vcat)` HOT 1
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