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 supplemental_nutrition_assistance_program table in this repository, by referencing it like:
"pa-gov/supplemental-nutrition-assistance-program-kd9x-cq7y:latest"."supplemental_nutrition_assistance_program"or in a full query, like:
SELECT
":id", -- Socrata column ID
"year", -- Calendar Year Number
"geocoded_column_1", -- Georeferenced column as a point used for creating visuals such as maps. A generic point for each county is supplied so a map can be created.
"longitude", -- Longitude generic point for each county.
"snap_individuals", -- A SNAP person is an individual who is applying for SNAP benefits and have been deemed eligible for SNAP benefits. These numbers include adults & children. An EBT (Electronic Benefits Transfer) card is issued to the client to buy their food. They can only spend the amount that's on the card. In July 2014, duplication of persons moving from county to county was eliminated.
"county_fips", -- The Federal Information Processing Standard (FIPS) code, used by the United States government to uniquely identify counties, is provided with each entry. FIPS codes are five-digit numbers; for Pennsylvania the codes start with 42 and are completed with the three-digit county code. The County FIPS is the last three digits of the five digit FIPS and the code 000 is for statewide.
"date", -- Combination of calendar month and year, formatted as MM/YYYY.
"latitude", -- Latitude generic point for each county.
"snap_dollars", -- Benefits issued for SNAP for a given month. These benefits are used to buy food to help low-income households.
"fiscal_year", -- State Fiscal Year that corresponds with the Month of the data being reported.
"county_cd", -- There are 67 counties in Pennsylvania. They're numbered 01 thru 67, and 00 identifies the statewide total.
"month_name", -- Calendar Month Name
"state_code", -- The Federal Information Processing Standard (FIPS) code, used by the United States government to uniquely identify states and counties. FIPS codes are five-digit numbers; for Pennsylvania the codes start with 42 and are completed with the three-digit county code. The state code is the first two digits of the five digit FIPS code.
"county_name", -- The name of the county in Pennsylvania or "Statewide" for all of Pennsylvania.
"month", -- Calendar Month Number
"state_name", -- PA is the Pennsylvania abbreviation and the indicator for the State
":@computed_region_rayf_jjgk",
":@computed_region_r6rf_p9et",
":@computed_region_amqz_jbr4",
":@computed_region_d3gw_znnf",
":@computed_region_nmsq_hqvv"
FROM
"pa-gov/supplemental-nutrition-assistance-program-kd9x-cq7y:latest"."supplemental_nutrition_assistance_program"
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 pa-gov/supplemental-nutrition-assistance-program-kd9x-cq7y 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 pa-gov/supplemental-nutrition-assistance-program-kd9x-cq7y: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 pa-gov/supplemental-nutrition-assistance-program-kd9x-cq7yCheckout 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 pa-gov/supplemental-nutrition-assistance-program-kd9x-cq7y:latestThis will download all the objects for the latest tag of pa-gov/supplemental-nutrition-assistance-program-kd9x-cq7y 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 pa-gov/supplemental-nutrition-assistance-program-kd9x-cq7y: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 pa-gov/supplemental-nutrition-assistance-program-kd9x-cq7y: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, pa-gov/supplemental-nutrition-assistance-program-kd9x-cq7y is just another Postgres schema.