Query the Data Delivery Network
Query the DDNThe easiest way to query any data on Splitgraph is via the "Data Delivery Network" (DDN). The DDN is a single endpoint that speaks the PostgreSQL wire protocol. Any Splitgraph user can connect to it at data.splitgraph.com:5432 and query any version of over 40,000 datasets that are hosted or proxied by Splitgraph.
For example, you can query the distritos_de_adecuacin_de_tierras_punto table in this repository, by referencing it like:
"datos-gov-co/distritos-de-adecuacin-de-tierras-punto-k86y-kva3:latest"."distritos_de_adecuacin_de_tierras_punto"or in a full query, like:
SELECT
":id", -- Socrata column ID
"vereda", -- Nombre de la vereda
"etapa_dat", -- Etapa del Distrito de adecuación de tierras
"mcpio", -- Nombre del municipio
"id", -- Identificador del distrito según UPRA
"cod_shz", -- Código de Sub zona hidrográfica
"the_geom",
"funciona", -- ¿El Distrito en funcionamiento?
"escala", -- Escala del distrito
"ubic_punto", -- Entidad fuente responsable de la ubicación del Distrito de adecuación de tierras
"altitud", -- Altura en metros sobre el nivel del mar donde se encuentra ubicado el Distrito de adecuación de Tierras
"asoc_usuar", -- Nombre de la Asociación de usuarios administradora del distrito de adecuación de tierras
"usuarios", -- Número de usuarios beneficiados
"cod_mcpio", -- Código Dane del municipio
"area_bruta", -- Área bruta del distrito en hectáreas
"id_incoder", -- Identificador del distrito según INCODER
"area_neta", -- Área neta del distrito en hectáreas
"cultivos", -- Usos actuales del distrito (Cultivos)
"cod_depto", -- Código Dane del departamento
"depto", -- Nombre del departamento
"concesion", -- ¿El distrito se encuentra en concesión?
"poligono", -- ¿El distrito tiene representación tipo polígono?
"tipo_dat", -- Tipo de Distrito de adecuación de tierras
"nom_dat", -- Nombre Distrito de adecuación de tierras
"fuent_hidr", -- Fuentes hídricas asociadas al Distrito
"nom_szh", -- Nombre de la subzona hidrográfica asociada al Distrito de adecuación de tierras
"longitud", -- Coordenada de longitud
"car", -- Corporación Autónoma Regional asociada al distrito
"latitud", -- Coordenada de latitud
"resol_asoc", -- Resolución de creación del distrito
"admin" -- Tipo de entidad que administra el distrito
FROM
"datos-gov-co/distritos-de-adecuacin-de-tierras-punto-k86y-kva3:latest"."distritos_de_adecuacin_de_tierras_punto"
LIMIT 100;Connecting to the DDN is easy. All you need is an existing SQL client that can connect to Postgres. As long as you have a SQL client ready, you'll be able to query datos-gov-co/distritos-de-adecuacin-de-tierras-punto-k86y-kva3 with SQL in under 60 seconds.
Query Your Local Engine
bash -c "$(curl -sL https://github.com/splitgraph/splitgraph/releases/latest/download/install.sh)"Read the installation docs.
Splitgraph Cloud is built around Splitgraph Core (GitHub), which includes a local Splitgraph Engine packaged as a Docker image. Splitgraph Cloud is basically a scaled-up version of that local Engine. When you query the Data Delivery Network or the REST API, we mount the relevant datasets in an Engine on our servers and execute your query on it.
It's possible to run this engine locally. You'll need a Mac, Windows or Linux system to install sgr, and a Docker installation to run the engine. You don't need to know how to actually use Docker; sgrcan manage the image, container and volume for you.
There are a few ways to ingest data into the local engine.
For external repositories, the Splitgraph Engine can "mount" upstream data sources by using sgr mount. This feature is built around Postgres Foreign Data Wrappers (FDW). You can write custom "mount handlers" for any upstream data source. For an example, we blogged about making a custom mount handler for HackerNews stories.
For hosted datasets (like this repository), where the author has pushed Splitgraph Images to the repository, you can "clone" and/or "checkout" the data using sgr cloneand sgr checkout.
Cloning Data
Because datos-gov-co/distritos-de-adecuacin-de-tierras-punto-k86y-kva3:latest is a Splitgraph Image, you can clone the data from Spltgraph Cloud to your local engine, where you can query it like any other Postgres database, using any of your existing tools.
First, install Splitgraph if you haven't already.
Clone the metadata with sgr clone
This will be quick, and does not download the actual data.
sgr clone datos-gov-co/distritos-de-adecuacin-de-tierras-punto-k86y-kva3Checkout the data
Once you've cloned the data, you need to "checkout" the tag that you want. For example, to checkout the latest tag:
sgr checkout datos-gov-co/distritos-de-adecuacin-de-tierras-punto-k86y-kva3:latestThis will download all the objects for the latest tag of datos-gov-co/distritos-de-adecuacin-de-tierras-punto-k86y-kva3 and load them into the Splitgraph Engine. Depending on your connection speed and the size of the data, you will need to wait for the checkout to complete. Once it's complete, you will be able to query the data like you would any other Postgres database.
Alternatively, use "layered checkout" to avoid downloading all the data
The data in datos-gov-co/distritos-de-adecuacin-de-tierras-punto-k86y-kva3:latest is 0 bytes. If this is too big to download all at once, or perhaps you only need to query a subset of it, you can use a layered checkout.:
sgr checkout --layered datos-gov-co/distritos-de-adecuacin-de-tierras-punto-k86y-kva3:latestThis will not download all the data, but it will create a schema comprised of foreign tables, that you can query as you would any other data. Splitgraph will lazily download the required objects as you query the data. In some cases, this might be faster or more efficient than a regular checkout.
Read the layered querying documentation to learn about when and why you might want to use layered queries.
Query the data with your existing tools
Once you've loaded the data into your local Splitgraph Engine, you can query it with any of your existing tools. As far as they're concerned, datos-gov-co/distritos-de-adecuacin-de-tierras-punto-k86y-kva3 is just another Postgres schema.