Mention Temporal.jl integration

queryverse · Jun 7, 2017 · 5c3f017 · 5c3f017
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diff --git a/README.md b/README.md
@@ -21,6 +21,7 @@ any array,
 [DataTables](https://github.com/JuliaData/DataTables.jl),
 [IndexedTables](https://github.com/JuliaComputing/IndexedTables.jl),
 [TimeSeries](https://github.com/JuliaStats/TimeSeries.jl),
+[Temporal](https://github.com/dysonance/Temporal.jl),
 [TypedTables](https://github.com/FugroRoames/TypedTables.jl) and
 [DifferentialEquations](https://github.com/JuliaDiffEq/DifferentialEquations.jl) (any ``DESolution``).
 
@@ -48,8 +49,8 @@ Please ask any usage question in the [Data Domain](https://discourse.julialang.o
 ## Highlights
 
 - Query is an almost complete implementation of the query expression section of the C# specification, with some additional julia specific features added in.
-- The package supports a large number of data sources: DataFrames, DataStreams (including CSV, Feather, SQLite, ODBC), DataTables, IndexedTables, TimeSeries, TypedTables, DifferentialEquations (any DESolution), arrays any type that can be iterated.
-- The results of a query can be materialized into a range of different data structures: iterators, DataFrames, DataTables, IndexedTables, TimeSeries, TypedTables, arrays, dictionaries or any DataStream sink (this includes CSV and Feather files).
+- The package supports a large number of data sources: DataFrames, DataStreams (including CSV, Feather, SQLite, ODBC), DataTables, IndexedTables, TimeSeries, Temporal, TypedTables, DifferentialEquations (any DESolution), arrays any type that can be iterated.
+- The results of a query can be materialized into a range of different data structures: iterators, DataFrames, DataTables, IndexedTables, TimeSeries, Temporal, TypedTables, arrays, dictionaries or any DataStream sink (this includes CSV and Feather files).
 - One can mix and match almost all sources and sinks within one query. For example, one can easily perform a join of a DataFrame with a CSV file and write the results into a Feather file, all within one query.
 - The type instability problems that one can run into with DataFrames do not affect Query, i.e. queries against DataFrames are completely type stable.
 - There are three different APIs that package authors can use to make their data sources queryable with this package. The most simple API only requires a data source to provide an iterator. Another API provides a data source with a complete graph representation of the query and the data source can e.g. rewrite that query graph as a SQL statement to execute the query. The final API allows a data source to provide its own data structures that can represent a query graph.

diff --git a/docs/src/index.md b/docs/src/index.md
@@ -13,6 +13,7 @@ any array,
 [DataTables](https://github.com/JuliaData/DataTables.jl),
 [IndexedTables](https://github.com/JuliaComputing/IndexedTables.jl),
 [TimeSeries](https://github.com/JuliaStats/TimeSeries.jl),
+[Temporal](https://github.com/dysonance/Temporal.jl),
 [TypedTables](https://github.com/FugroRoames/TypedTables.jl) and
 [DifferentialEquations](https://github.com/JuliaDiffEq/DifferentialEquations.jl) (any `DESolution`).
 
@@ -30,8 +31,8 @@ Pkg.add("Query")
 ## Highlights
 
 - Query is an almost complete implementation of the query expression section of the C# specification, with some additional julia specific features added in.
-- The package supports a large number of data sources: DataFrames, DataStreams (including CSV, Feather, SQLite, ODBC), DataTables, IndexedTables, TimeSeries, TypedTables, DifferentialEquations (any DESolution), arrays any type that can be iterated.
-- The results of a query can be materialized into a range of different data structures: iterators, DataFrames, DataTables, IndexedTables, TimeSeries, TypedTables, arrays, dictionaries or any DataStream sink (this includes CSV and Feather files).
+- The package supports a large number of data sources: DataFrames, DataStreams (including CSV, Feather, SQLite, ODBC), DataTables, IndexedTables, TimeSeries, Temporal, TypedTables, DifferentialEquations (any DESolution), arrays any type that can be iterated.
+- The results of a query can be materialized into a range of different data structures: iterators, DataFrames, DataTables, IndexedTables, TimeSeries, Temporal, TypedTables, arrays, dictionaries or any DataStream sink (this includes CSV and Feather files).
 - One can mix and match almost all sources and sinks within one query. For example, one can easily perform a join of a DataFrame with a CSV file and write the results into a Feather file, all within one query.
 - The type instability problems that one can run into with DataFrames do not affect Query, i.e. queries against DataFrames are completely type stable.
 - There are three different APIs that package authors can use to make their data sources queryable with this package. The most simple API only requires a data source to provide an iterator. Another API provides a data source with a complete graph representation of the query and the data source can e.g. rewrite that query graph as a SQL statement to execute the query. The final API allows a data source to provide its own data structures that can represent a query graph.

diff --git a/docs/src/sinks.md b/docs/src/sinks.md
@@ -105,6 +105,19 @@ the `TimeArray` type.
 
 [TODO]
 
+## Temporal
+
+The statement `@collect TS` will materialize the query results into
+a new `Temporal.TS` instance. This statement only works if the
+last projection statement transformed the results into a `NamedTuple`,
+for example by using the `{}` syntax, and this `NamedTuple` has one field
+named `Index` that is of a type that can be used as a time index in
+the `TS` type.
+
+### Example
+
+[TODO]
+
 ## IndexedTable
 
 The statement `@collect IndexedTable` will materialize the query results