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 informacin_presupuestal_gastos_de_la
table in this repository, by referencing it like:
"datos-gov-co/informacin-presupuestal-gastos-de-la-xh8v-7377:latest"."informacin_presupuestal_gastos_de_la"
or in a full query, like:
SELECT
":id", -- Socrata column ID
"situacion", -- Corresponde a los giros realizados por la Dirección General de Crédito Público y del Tesoro Nacional a las cuentas de cada entidad con cargo al PAC y a la apropiación de la entidad.
"recurso", -- Tipo de recursos
"fuente", -- Donde provienen los recursos, para cubrir los gastos de funcionamiento y de inversión de la entidad,
"vigencia", -- Año al que corresponde la ejecución presupuestal
"rec", -- Es el código de la fuente de los recursos
"apropiaciondisponible_dep", -- Apropiación Vigente (-) Total CDP Gastos
"apropiacionvigente_dep_gsto", -- Es el monto máximo autorizado para asumir compromisos con un objeto determinado durante la vigencia fiscal, despues de efectuado las adiciones o reduciones a la apropiación.
"total_cdpdep_gstos", -- Documento con el cual se garantiza la existencia de apropiación presupuestal disponible y libre de afectación para la asumir de compromisos con cargo al presupuesto de la respectiva vigencia fiscal
"total_cdpmodificacion_dep", -- Son las diferentes adiciones o reduciones al CDP
"totalobligaciones_dep_gstos", -- Se entiende por obligación exigible de pago el monto adeudado por el ente público como consecuencia del perfeccionamiento y cumplimiento – total o parcial - de los compromisos adquiridos.
"totalordenes_de_pago_dep", -- Es el documento generado para realizar el desembolso de los recursos al beneficiario
"obligacionespor_ordenar_dep", -- Total Obligaciones (-) Total Ordenes de Pago
"total_reintegrosdep_gstos", -- Valores reintegrados a la entidad por mayor valor pagado
"concepto", -- Nombre del rubro
"totalcompromiso_dep_gstos", -- Es la imputación presupuestal mediante la cual se afecta en forma definitiva la apropiación, garantizando que ésta solo se utilizará para ese fin
"cdp_por_comprometerdep_gstos", -- Total CDP (-) Total Compromisos
"pagosdep_gstos", -- Es el desembolso realizado al beneficiario de la obligación
"ordenes_de_pagopor_pagar", -- Son aquellas Ordenes de pago que se encuentran en proceso de pago
"mes_consolidado", -- Periodo al que corresponde la ejecución presupuestal
"compromiso_por_obligardep" -- Total Compromiso (-) Total Obligaciones
FROM
"datos-gov-co/informacin-presupuestal-gastos-de-la-xh8v-7377:latest"."informacin_presupuestal_gastos_de_la"
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/informacin-presupuestal-gastos-de-la-xh8v-7377
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; sgr
can 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 clone
and sgr checkout
.
Cloning Data
Because datos-gov-co/informacin-presupuestal-gastos-de-la-xh8v-7377: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/informacin-presupuestal-gastos-de-la-xh8v-7377
Checkout 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/informacin-presupuestal-gastos-de-la-xh8v-7377:latest
This will download all the objects for the latest
tag of datos-gov-co/informacin-presupuestal-gastos-de-la-xh8v-7377
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/informacin-presupuestal-gastos-de-la-xh8v-7377: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/informacin-presupuestal-gastos-de-la-xh8v-7377:latest
This 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/informacin-presupuestal-gastos-de-la-xh8v-7377
is just another Postgres schema.