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 american_community_survey_2018_22_estimates_by table in this repository, by referencing it like:
"cambridgema-gov/american-community-survey-2018-22-estimates-by-mayq-xm5d:latest"."american_community_survey_2018_22_estimates_by"or in a full query, like:
SELECT
":id", -- Socrata column ID
"owner_occupied_units", -- A housing unit consists of separate living quarters where the occupants live apart from any other people in the building and that has direct access from the outside of the building or through a common hall. A housing unit may consist of a house, an apartment, a group of rooms, or a single room that is occupied (or if vacant, is intended for occupancy) as separate living quarters.
"other_vacant_units_1", -- Proportion of units in the neighborhood that are unoccupied but are unavailable to new permanent occupants through the rental or sale market.
"other_vacant_units", -- Units categorized as “other vacant” include those unoccupied units categorized by the Census Bureau as “Rented, Not Occupied”, “Sold, Not Occupied”, “For Seasonal, Recreational, or Occasional Use”, "For Migrant Workers” and “Other Vacant”. These units are unavailable to new permanent occupants through the for-rent or for-sale housing markets and are excluded from the market vacancy rate.
"market_vacant_units_1", -- Proportion of units in the neighborhood that are unoccupied and available to new permanent occupants through the rental or sale market.
"market_vacant_units", -- Unoccupied units in neighborhood that are available to new permanent occupants through the rental or sale market.
"vacant_units_1", -- Proportion of vacant housing units in neighborhood.
"vacant_units", -- The Census Bureau treats all unoccupied units as vacant. Vacant units include those set aside for part time occupancy, such as vacation and other second homes, temporary worker housing, homes for rent or for sale, homes rented or sold and awaiting occupancy, and vacant units that are not on the market.
"housing_units_per_acre", -- A housing unit consists of separate living quarters where the occupants live apart from any other people in the building and that has direct access from the outside of the building or through a common hall. A housing unit may consist of a house, an apartment, a group of rooms, or a single room that is occupied (or if vacant, is intended for occupancy) as separate living quarters.
"housing_units", -- A housing unit consists of separate living quarters where the occupants live apart from any other people in the building and that has direct access from the outside of the building or through a common hall. A housing unit may consist of a house, an apartment, a group of rooms, or a single room that is occupied (or if vacant, is intended for occupancy) as separate living quarters.
"land_area_in_acres",
"area",
"neighborhood", -- Cambridge neighborhood
"owner_occupied_as_of_occupied", -- Proportion of all occupied units in the neighborhood that are owner-occupied.
":@computed_region_e4yd_rwk4",
":@computed_region_swkg_bavi",
":@computed_region_rffn_qbt6",
":@computed_region_v7jj_366k",
":@computed_region_guic_hr4a",
"total_occupied_units", -- A housing unit consists of separate living quarters where the occupants live apart from any other people in the building and that has direct access from the outside of the building or through a common hall. A housing unit may consist of a house, an apartment, a group of rooms, or a single room that is occupied (or if vacant, is intended for occupancy) as separate living quarters.
"housing_units_as_of_city", -- Neighborhood housing units as proportion of city total.
"geocoded_column",
"centerpoint_x",
"centerpoint_y",
"renter_occupied_as_of_occupied", -- Proportion of all occupied units in the neighborhood that are renter-occupied.
"renter_occupied_units" -- A housing unit consists of separate living quarters where the occupants live apart from any other people in the building and that has direct access from the outside of the building or through a common hall. A housing unit may consist of a house, an apartment, a group of rooms, or a single room that is occupied (or if vacant, is intended for occupancy) as separate living quarters.
FROM
"cambridgema-gov/american-community-survey-2018-22-estimates-by-mayq-xm5d:latest"."american_community_survey_2018_22_estimates_by"
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 cambridgema-gov/american-community-survey-2018-22-estimates-by-mayq-xm5d 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 cambridgema-gov/american-community-survey-2018-22-estimates-by-mayq-xm5d: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 cambridgema-gov/american-community-survey-2018-22-estimates-by-mayq-xm5dCheckout 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 cambridgema-gov/american-community-survey-2018-22-estimates-by-mayq-xm5d:latestThis will download all the objects for the latest tag of cambridgema-gov/american-community-survey-2018-22-estimates-by-mayq-xm5d 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 cambridgema-gov/american-community-survey-2018-22-estimates-by-mayq-xm5d: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 cambridgema-gov/american-community-survey-2018-22-estimates-by-mayq-xm5d: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, cambridgema-gov/american-community-survey-2018-22-estimates-by-mayq-xm5d is just another Postgres schema.