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IndexedTables.jl

IndexedTables provides tabular data structures where some of the columns form a sorted index. It provides the backend to JuliaDB, but can be used on its own for efficient in-memory data processing and analytics.

Data Structures

• The two table types in IndexedTables differ in how data is accessed.
• There is no performance difference between table types for operations such as selecting, filtering, and map/reduce.

First let's create some data to work with.

using Dates

city = vcat(fill("New York", 3), fill("Boston", 3))

dates = repeat(Date(2016,7,6):Day(1):Date(2016,7,8), 2)

values = [91, 89, 91, 95, 83, 76]

Table

• Data is accessed as a Vector of NamedTuples.
  
• Sorted by primary key(s), pkey. ``` using IndexedTables

julia> t1 = table((city = city, dates = dates, values = values); pkey = [:city, :dates]) Table with 6 rows, 3 columns: city dates values ────────────────────────────── "Boston" 2016-07-06 95 "Boston" 2016-07-07 83 "Boston" 2016-07-08 76 "New York" 2016-07-06 91 "New York" 2016-07-07 89 "New York" 2016-07-08 91

julia> t11

julia> first(t1) (city = "Boston", dates = 2016-07-06, values = 95)

### NDSparse

- Data is accessed as an N-dimensional sparse array with arbitrary indexes.
- Sorted by index variables (first argument).

julia> t2 = ndsparse(@NT(city=city, dates=dates), @NT(value=values)) 2-d NDSparse with 6 values (1 field named tuples): city dates │ value ───────────────────────┼────── "Boston" 2016-07-06 │ 95 "Boston" 2016-07-07 │ 83 "Boston" 2016-07-08 │ 76 "New York" 2016-07-06 │ 91 "New York" 2016-07-07 │ 89 "New York" 2016-07-08 │ 91

julia> t2"Boston", Date(2016, 7, 6)

julia> first(t2) (value = 95)

As with other multi-dimensional arrays, dimensions can be permuted to change the sort order:

julia> permutedims(t2, [2,1]) 2-d NDSparse with 6 values (1 field named tuples): dates city │ value ───────────────────────┼────── 2016-07-06 "Boston" │ 95 2016-07-06 "New York" │ 91 2016-07-07 "Boston" │ 83 2016-07-07 "New York" │ 89 2016-07-08 "Boston" │ 76 2016-07-08 "New York" │ 91

## Get started

For more information, check out the [JuliaDB API Reference](http://juliadb.org/latest/api/datastructures.html).