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 rate_of_dependent_children_removed_from_their_home table in this repository, by referencing it like:
"pa-gov/rate-of-dependent-children-removed-from-their-home-ekf9-na9n:latest"."rate_of_dependent_children_removed_from_their_home"or in a full query, like:
SELECT
":id", -- Socrata column ID
":@computed_region_d3gw_znnf",
":@computed_region_amqz_jbr4",
":@computed_region_r6rf_p9et",
":@computed_region_rayf_jjgk",
"time_period_dates", -- Start and end dates of time period.
"year", -- Federal fiscal year for measurement (October 1–September 30).
"age", -- Age of children.
"time_period", -- Period for measurement (annual, federal fiscal year, or quarterly, if available).
"removal_rate", -- Rate of dependent children removed from home due to parental drug use per 1,000 children or rate of dependent children in kinship care because of parental drug use per 1,000 children.
"type_of_rate", -- Description of removal rate.
"number_of_removals", -- Count of dependent children removed from home due to parental drug use or count of dependent children in kinship care because of parental drug use. This count is provided by the Office of Children, Youth and Families (OCYF) of the Pennsylvania Department of Human Services (DHS).
"number_of_removals_description", -- Specifies if the removals are in kinship care or not.
"total_number_of_children", -- Estimated number of children, 0-18 years of age. This count is the 5-year estimate from the United States Census Bureau’s American Community Survey (ACS).
"county_code_number", -- Pennsylvania county code provided as a number (1-67 for counties, 0 for Commonwealth).
"state_fips_code", -- First 2 digits of the 5-digit Federal Information Processing Standard (FIPS) code that designate the state association. Each state has its own 2-digit number and each county within the state has its own 3-digit number which are combined into a 5-digit number to uniquely identify every US county.
"geocoded_column", -- Georeferenced column for the latitude and longitude for use in mapping visuals.
"county_fips_code", -- Last 3 digits of the 5-digit Federal Information Processing Standard (FIPS) code that designate the county association. Each state has its own 2-digit number and each county within the state has its own 3-digit number which are combined into a 5-digit number to uniquely identify every US county.
"geographic_name", -- Name of geographic area.
"county_code_text", -- Pennsylvania county code provided as text (1-67 for counties sorted alphabetically, 0 for Commonwealth).
"number_of_removals_notes", -- Indicates if the number of removals count has been suppressed to protect confidentiality. Counts less than 11 are not provided.
"total_number_of_children_2", -- Description provided for the Total Number of Children count column.
"geographic_area", -- Region for measure, either total for Commonwealth or individual county.
"gender", -- Gender of children.
"total_number_of_children_1", -- Indicates if the estimated number of children is not available.
"latitude_longitude", -- Latitude and longitude coordinates in degrees for a centroid point for geographic area.
":@computed_region_nmsq_hqvv"
FROM
"pa-gov/rate-of-dependent-children-removed-from-their-home-ekf9-na9n:latest"."rate_of_dependent_children_removed_from_their_home"
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/rate-of-dependent-children-removed-from-their-home-ekf9-na9n 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/rate-of-dependent-children-removed-from-their-home-ekf9-na9n: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/rate-of-dependent-children-removed-from-their-home-ekf9-na9nCheckout 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/rate-of-dependent-children-removed-from-their-home-ekf9-na9n:latestThis will download all the objects for the latest tag of pa-gov/rate-of-dependent-children-removed-from-their-home-ekf9-na9n 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/rate-of-dependent-children-removed-from-their-home-ekf9-na9n: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/rate-of-dependent-children-removed-from-their-home-ekf9-na9n: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/rate-of-dependent-children-removed-from-their-home-ekf9-na9n is just another Postgres schema.