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 dcf_children_in_placement_annual_pointintime_trend table in this repository, by referencing it like:
"ct-gov/dcf-children-in-placement-annual-pointintime-trend-agib-7xfs:latest"."dcf_children_in_placement_annual_pointintime_trend"or in a full query, like:
SELECT
":id", -- Socrata column ID
"medical", -- Number of children where placement setting is in a Hospital setting for either medical or psychiatric reasons
"residential", -- Number of children where placement setting is a Residential Treatment Center
"group_home", -- Number of children where placement setting is some form of Group Home, which includes Maternity, Preparing Adolescents for Self-Sufficiency (PASS), Specialized or Therapeutic Group Home settings
"pdc_safe_home", -- Number of children where placement setting is either a Permanency Diagnostic Center (not utilized since 2011), or a Safe Home (a temporary congregate care service that is a homelike setting providing immediate, 24-hour care for children ages 6-13, with some exceptions to age made to keep sibling groups together)
"therapeutic_foster_care", -- Number of children where placement setting is some form of Therapeutic foster home (recruited, trained, and supported by a Child-Placing Agency on contract with DCF)
"relative_care", -- Number of children where placement setting is a Relative Foster home (provider is a member of the child's extended family; in most cases providers are recruited, trained, licensed and supported by DCF directly, though some provide Therapeutic Foster Care but for reporting purposes are included in the Relative Care category)
"foster_care", -- Number of children where placement setting is some form of DCF "Core" foster home (recruited, trained, licensed and supported by DCF directly)
"total_cip", -- Total number of children in placement on the Month In Care date
"region", -- DCF Region responsible for child's case
"data_as_of", -- Date the data was pulled from the database
"dcf_cjts", -- Number of children where placement setting is the CT Juvenile Training School
"independent_living", -- Number of children where placement setting is some form of supervised but independent living setting, including Supportive Work, Education and Transition Programs (SWET), or Community Housing Apartment Programs (CHAP)
"dcf_solnit", -- Number of children where placement setting is either the Solnit Center North Campus (formerly CT Children's Place) or Solnit Center South Campus (formerly Riverview Psychiatric Hospital)
"shelter", -- Number of children where placement setting is some form of Shelter (a temporary congregate care program that provides short-term care, assessment and a range of clinical and nursing services)
"special_study", -- Number of children where placement setting is a Special Study foster home (provider is connected to the child in some fashion, but is not a member of the child's extended family; in most cases providers are recruited, trained, licensed and supported by DCF directly, though some provide Therapeutic Foster Care but for reporting purposes are included in the Special Study category)
"month_in_care", -- Observation Date; date the child was residing in an open DCF placement
"demographic", -- Child's Gender (M/F)
"dcf_highmeadows", -- Number of children where placement setting is the High Meadows facility (previously run by DCF and closed in 2009)
"out_of_state", -- Are placement settings outside CT? (Y/N)
"office_name" -- DCF Office responsible for child's case
FROM
"ct-gov/dcf-children-in-placement-annual-pointintime-trend-agib-7xfs:latest"."dcf_children_in_placement_annual_pointintime_trend"
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 ct-gov/dcf-children-in-placement-annual-pointintime-trend-agib-7xfs 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 ct-gov/dcf-children-in-placement-annual-pointintime-trend-agib-7xfs: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 ct-gov/dcf-children-in-placement-annual-pointintime-trend-agib-7xfsCheckout 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 ct-gov/dcf-children-in-placement-annual-pointintime-trend-agib-7xfs:latestThis will download all the objects for the latest tag of ct-gov/dcf-children-in-placement-annual-pointintime-trend-agib-7xfs 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 ct-gov/dcf-children-in-placement-annual-pointintime-trend-agib-7xfs: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 ct-gov/dcf-children-in-placement-annual-pointintime-trend-agib-7xfs: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, ct-gov/dcf-children-in-placement-annual-pointintime-trend-agib-7xfs is just another Postgres schema.