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 delitos_ocurridos_en_el_municipio_de_bucaramanga table in this repository, by referencing it like:
"datos-gov-co/delitos-ocurridos-en-el-municipio-de-bucaramanga-75fz-q98y:latest"."delitos_ocurridos_en_el_municipio_de_bucaramanga"or in a full query, like:
SELECT
":id", -- Socrata column ID
"ano", -- es el año de ocurrencia del delito
"latitud", -- es la latitud del punto georeferenciado
"longitud", -- es la longitud del punto georeferenciado
"movil_victima", -- en el momento de la agresion como se movilizaba la victima
"mes", -- son los meses de ocurrencia del delito en el año que los temenos identificados de la siguiente forma: 01. enero, 02. febrero, 03. marzo, 04. abril, 05. mayo, 06. junio, 07. julio, 08. agosto, 09. septiembre, 10. octubre, 11. noviembre, 12. diciembre
"orden", -- Consecutivo autonumérico
"estado_civil_persona", -- son los estados civiles de la victima que reporta la policia nacional y son: CASADO, DIVORCIADO, NO REPORTA, SEPARADO, SOLTERO, UNION LIBRE, VIUDO
"nom_comuna", -- son las comunas del municipio de Bucaramanga que son: 01. Norte, 02. Nor Oriental, 03. San Francisco, 04. Occidental, 05. García Rovira, 06. La Concordia, 07. La Ciudadela, 08. Sur Occidente, 09. La Pedregosa, 10. Provenza, 11. Sur, 12. Cabecera del Llano, 13. Oriental, 14. Morrorico, 15. Centro, 16. Lagos del Cacique, 17. Mutis, Corregimiento 1, Corregimiento 2, Corregimiento 3 y sin informacion
"genero", -- son el genero de la victima y son: MASCULINO, FEMENINO, NO REPORTA
"dia_semana", -- dia de la semana de la occurencia del delito, que son : lunes, martes, miércoles, jueves, viernes, sábado, domingo
"dia", -- dia de la ocurrencia del delito
"curso_de_vida", -- es la clasificacion de la edad de la victima según el ministerio de salud y proteccion social: 00. NO REPORTA, 01. Primera infancia, 02. Infancia, 03. Adolescencia, 04. Jovenes, 05. Adultez, 06. Persona Mayor
"movil_agresor", -- en el momento de la agresion como se movilizaba el agresor
"descripcion_conducta", -- es el numero del artículo del delito mas la descripcion de la conducta según la policia nacional
"conducta", -- es la descripcion de la conducta
"clasificaciones_delito", -- es la clasificacion del delito según medicina legal y son: Lesiones fatales, Lesiones no fatales, Violencia sexual
"zona", -- son las zonas que esta el barrio que son: OTROS, RURAL, URBANA
"armas_medios", -- descripcion del arma según listado suministrado por la policia nacional
"barrios_hecho" -- Son los barrios que se genero el delito y estan en el municipio de Bucaramanga. Estos municipios son suministrados por la policia nacional
FROM
"datos-gov-co/delitos-ocurridos-en-el-municipio-de-bucaramanga-75fz-q98y:latest"."delitos_ocurridos_en_el_municipio_de_bucaramanga"
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/delitos-ocurridos-en-el-municipio-de-bucaramanga-75fz-q98y 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/delitos-ocurridos-en-el-municipio-de-bucaramanga-75fz-q98y: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/delitos-ocurridos-en-el-municipio-de-bucaramanga-75fz-q98yCheckout 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/delitos-ocurridos-en-el-municipio-de-bucaramanga-75fz-q98y:latestThis will download all the objects for the latest tag of datos-gov-co/delitos-ocurridos-en-el-municipio-de-bucaramanga-75fz-q98y 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/delitos-ocurridos-en-el-municipio-de-bucaramanga-75fz-q98y: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/delitos-ocurridos-en-el-municipio-de-bucaramanga-75fz-q98y: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/delitos-ocurridos-en-el-municipio-de-bucaramanga-75fz-q98y is just another Postgres schema.