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 ct_dcf_abuseneglect_reports_and_allegations_by table in this repository, by referencing it like:
"ct-gov/ct-dcf-abuseneglect-reports-and-allegations-by-337d-73fs:latest"."ct_dcf_abuseneglect_reports_and_allegations_by"or in a full query, like:
SELECT
":id", -- Socrata column ID
"rate_phys_neglect_m", -- Physical Neglect Substantiation Rate
"subs_emot_neglect_m", -- Total Number of Emotional Neglect Allegations Substantiated
"subs_educ_neglect_m", -- Total Number of Educational Neglect Allegations Substantiated
"subs_phys_abuse_m", -- Total Number of Physical Abuse Allegations Substantiated
"ttl_moral_neglect_m", -- Total Number of Moral Neglect Allegations
"ttl_sex_abuse_m", -- Total Number of Sexual Abuse Allegations
"ttl_cps_subs_m", -- Total Number of CPS Reports Substantiated
"rate_moral_neglect_m", -- Moral Neglect Substantiation Rate
"rate_em_ab_m", -- Emotional Abuse Substantiation Rate
"rate_hmntr_m", -- Human Trafficking Substantiation Rate
"rate_sex_abuse_m", -- Sexual Abuse Substantiation Rate
"children_subs", -- Number of unique Children with at least one Substantiated Allegation during the reporting period
"sub_em_ab_m", -- Total Number of Emotional Abuse Allegations Substantiated
"subs_sex_abuse_m", -- Total Number of Sexual Abuse Allegations Substantiated
"subs_phys_neglect_m", -- Total Number of Physical Neglect Allegations Substantiated
"subs_medi_neglect_m", -- Total Number of Medical Neglect Allegations Substantiated
"ttl_phys_neglect_m", -- Total Number of Physical Neglect Allegations
"ttl_emot_neglect_m", -- Total Number of Emotional Neglect Allegations
"ttl_educ_neglect_m", -- Total Number of Educational Neglect Allegations
"ttl_phys_abuse_m", -- Total Number of Physical Abuse Allegations
"ttl_allegat_m", -- Total Number of Allegations
"ttl_cps_acept_m", -- Total Number of CPS Reports Accepted
"town", -- Town
"region", -- DCF Region responsible for responding to the Reports. A single Region is comprised of 2 – 3 Offices.
"fisc_period", -- Reporting Period
"rate_at_risk_m", -- At Risk Substantiation Rate
"rate_medi_neglect_m", -- Medical Neglect Substantiation Rate
"rate_educ_neglect_m", -- Educational Neglect Substantiation Rate
"ttl_em_ab_m", -- Total Number of Emotional Abuse Allegations
"ttl_medi_neglect_m", -- Total Number of Medical Neglect Allegations
"office", -- DCF Office responsible for responding to the Reports. With one exception, a single Office is responsible for covering many Towns. Our New Haven Office is responsible solely for the town of New Haven.
"fisc_year", -- Reporting State Fiscal Year
"rate_emot_neglect_m", -- Emotional Neglect Substantiation Rate
"rate_phys_abuse_m", -- Physical Abuse Substantiation Rate
"sub_moral_neglect_m", -- Total Number of Moral Neglect Allegations Substantiated
"ttl_hmntr_m", -- Total Number of Human Trafficking Allegations
"ttl_allegat_subs_m", -- Total Number of Allegations Substantiated
"sub_hmntr_m", -- Total Number of Human Trafficking Allegations Substantiated
"ttl_high_risk_m", -- Total Number of High Risk Newborn Allegations
"ttl_at_risk_m", -- Total Number of At Risk Allegations
"subs_high_risk_m", -- Total Number of High Risk Newborn Allegations Substantiated
"subs_at_risk_m", -- Total Number of At Risk Allegations Substantiated
"rate_high_risk_m" -- High Risk Newborn Substantiation Rate
FROM
"ct-gov/ct-dcf-abuseneglect-reports-and-allegations-by-337d-73fs:latest"."ct_dcf_abuseneglect_reports_and_allegations_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 ct-gov/ct-dcf-abuseneglect-reports-and-allegations-by-337d-73fs 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/ct-dcf-abuseneglect-reports-and-allegations-by-337d-73fs: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/ct-dcf-abuseneglect-reports-and-allegations-by-337d-73fsCheckout 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/ct-dcf-abuseneglect-reports-and-allegations-by-337d-73fs:latestThis will download all the objects for the latest tag of ct-gov/ct-dcf-abuseneglect-reports-and-allegations-by-337d-73fs 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/ct-dcf-abuseneglect-reports-and-allegations-by-337d-73fs: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/ct-dcf-abuseneglect-reports-and-allegations-by-337d-73fs: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/ct-dcf-abuseneglect-reports-and-allegations-by-337d-73fs is just another Postgres schema.