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 dsny_monthly_tonnage_data table in this repository, by referencing it like:
"cityofnewyork-us/dsny-monthly-tonnage-data-ebb7-mvp5:latest"."dsny_monthly_tonnage_data"or in a full query, like:
SELECT
":id", -- Socrata column ID
"xmastreetons", -- Tons of Christmas trees collected curbside by DSNY from NYC residents in January. Within DSNY, the code for Christmas Trees is 54.
"refusetonscollected", -- Tons of trash or refuse collected from NYC residences and institutions serviced by the NYC Department of Sanitation. Within DSNY, the code for refuse is 01.
"schoolorganictons", -- Tons of source-separated organics collected from NYC schools serviced by the NYC Department of Sanitation. Only schools within certain areas in NYC receive this service. School organics includes food scraps, food-soiled paper and yard waste. "Source separated" means that materials are separated by schools before they are set out for collection. Within DSNY, the code for school organics is 46.
"mgptonscollected", -- Tons of source-separated recyclable metal, glass, plastic, and beverage cartons collected from NYC residences and institutions serviced by the NYC Department of Sanitation. "Source separated" means that materials are separated by residents before they are set out for collection. Within DSNY, the code for metal, glass, plastic (MGP) is 33.
"papertonscollected", -- Tons of source-separated recyclable paper collected from NYC residences and institutions serviced by the NYC Department of Sanitation. "Source separated" means that materials are separated by residents before they are set out for collection. Within DSNY, the code for paper is 31.
"borough_id", -- ID used to identify NYC boroughs. 1 = Manhattan; 2 = Bronx; 3 = Brooklyn; 4 = Queens; 5 = Staten Island
"leavesorganictons", -- Tons of source-separated leaves collected in November and December from NYC residences and institutions within certain neighborhoods serviced by the NYC Department of Sanitation. "Source separated" means that materials are separated by residents before they are set out for collection. Within DSNY, the code for leaves is 52.
"resorganicstons", -- Tons of source-separated residential organics collected from NYC residences serviced by the NYC Department of Sanitation. Only certain areas within NYC receive this service. Residential organics includes food scraps, food-soiled paper and yard waste. "Source separated" means that materials are separated by residents before they are set out for collection. Within DSNY, the code for residential organics is 45.
"communitydistrict", -- One of NYC's 59 community districts which correspond to Sanitation districts.
"borough", -- One of the 5 boroughs within NYC
"month" -- Year and Month
FROM
"cityofnewyork-us/dsny-monthly-tonnage-data-ebb7-mvp5:latest"."dsny_monthly_tonnage_data"
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 cityofnewyork-us/dsny-monthly-tonnage-data-ebb7-mvp5 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 cityofnewyork-us/dsny-monthly-tonnage-data-ebb7-mvp5: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 cityofnewyork-us/dsny-monthly-tonnage-data-ebb7-mvp5Checkout 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 cityofnewyork-us/dsny-monthly-tonnage-data-ebb7-mvp5:latestThis will download all the objects for the latest tag of cityofnewyork-us/dsny-monthly-tonnage-data-ebb7-mvp5 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 cityofnewyork-us/dsny-monthly-tonnage-data-ebb7-mvp5: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 cityofnewyork-us/dsny-monthly-tonnage-data-ebb7-mvp5: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, cityofnewyork-us/dsny-monthly-tonnage-data-ebb7-mvp5 is just another Postgres schema.