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 census_demographics table in this repository, by referencing it like:
"brla-gov/census-demographics-xsrb-mxqt:latest"."census_demographics"or in a full query, like:
SELECT
":id", -- Socrata column ID
"vacancy_rates", -- Rate of housing unit vacancy
"median_year_built", -- Median year housing unit was built
"median_house_value_owner_occu", -- Median value of owner occupied housing units
"percent_owner_occupied", -- Percent of owner occupied housing units
"occupied_housing_units", -- Number of occupied housing units
"doctoral_degree_female", -- Number of females with a doctoral degree
"masters_degree_female", -- Number of females with a masters degree
"associates_degree_female", -- Number of females with an associates degree
"college_1yr_more_female", -- Number of females with more than one year of college education
"high_school_female", -- Number of female high school graduates
"bachelors_degree_male", -- Number of males with a bachelors degree
"associates_degree_male", -- Number of males with an associates degree
"median_age", -- Median age of the block group
"population_one_race", -- Total population of people of one race
"population_am_indian", -- Total American Indian population of the block group
"population_black", -- Total black population of the block group
"percent_renter_occupied", -- Percent of renter occupied housing units
"college_1yr_less_female", -- Number of females with less than one year of college education
"high_school_male", -- Number of male high school graduates
"population_white", -- Total white population of the block group
"pct_25yrover_high_school_more", -- Percent of 25 year or older high school graduates
"census_year", -- Year in which census data was reported
"population_asian", -- Total Asian population of the block group
"population_pacf_island", -- Total population of Pacific Islanders
"population_25_older", -- Total population of the block group that is 25 years or older
"fips_id", -- Federal Information Processing Standards which is a combination of the state, county, tract and block group codes
"tract", -- Census tract number
"block_group", -- Census block group number
"unique_id", -- Unique identifier of record comprised of Census Year and FIPS Code
"owner_occupied_housing", -- Number of owner occupied housing units
"doctoral_degree_male", -- Number of males with a doctoral degree
"professional_degree_male", -- Number of males with a professional degree
"total_population", -- Total population of the Census block group
"bachelors_degree_female", -- Number of females with a bachelors degree
"median_household_income", -- Median household income of the block group
"college_1yr_more_male", -- Number of males with more than one year of college education
"high_school_more_female", -- Number of females with more than a high school education
"population_other", -- Total other population of the block group
"population_multi_race", -- Total population of people of multiple races
"masters_degree_male", -- Number of males with a masters degree
"renter_occupied_housing", -- Number of renter occupied housing units
"high_school_more_male", -- Number of males with more than a high school education
"college_1yr_less_male", -- Number of males with less than one year of college education
"professional_degree_female", -- Number of females with a professional degree
"housing_units" -- Number of housing units
FROM
"brla-gov/census-demographics-xsrb-mxqt:latest"."census_demographics"
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 brla-gov/census-demographics-xsrb-mxqt 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 brla-gov/census-demographics-xsrb-mxqt: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 brla-gov/census-demographics-xsrb-mxqtCheckout 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 brla-gov/census-demographics-xsrb-mxqt:latestThis will download all the objects for the latest tag of brla-gov/census-demographics-xsrb-mxqt 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 brla-gov/census-demographics-xsrb-mxqt: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 brla-gov/census-demographics-xsrb-mxqt: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, brla-gov/census-demographics-xsrb-mxqt is just another Postgres schema.