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 percent_of_women_on_medical_assistance_ma table in this repository, by referencing it like:
"pa-gov/percent-of-women-on-medical-assistance-ma-ig6a-8jqi:latest"."percent_of_women_on_medical_assistance_ma"or in a full query, like:
SELECT
":id", -- Socrata column ID
"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.
"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.
"county_code_text", -- Pennsylvania county code provided as text (1-67 for counties sorted alphabetically, 0 for Commonwealth).
"county_code_number", -- Pennsylvania county code provided as a number (1-67 for counties, 0 for Commonwealth).
"number_of_women_with_a_4", -- Indicates if the number of women with a delivery and diagnosis of OUD has been suppressed to protect confidentiality. Counts less than 11 are not provided.
"number_of_women_with_a_2", -- Describes number of women receiving MAT with a delivery and an OUD diagnosis.
"number_of_women_with_a_1", -- Indicates if the number of women receiving MAT with a delivery and an OUD diagnosis has been suppressed to protect confidentiality. Counts less than 11 are not provided.
"number_of_women_with_a", -- Count of women receiving MAT with a delivery and an OUD diagnosis. This count is provided by the Pennsylvania Department of Human Services (DHS).
"type_of_percent", -- Description of percent of pregnant women with OUD diagnosis receiving MAT.
"deliveries_with_oud_diagnosis_receiving_mat_percent", -- Percent of pregnant women with a delivery and Opioid Use Disorder (OUD) diagnosis receiving Medication-Assisted Treatment (MAT).
"deliveries_with_oud_diagnosis", -- Rate of women receiving Medication-Assisted Treatment (MAT) for Opioid Use Disorder (OUD) per 1000 women with OUD diagnosis and delivery.
"time_period_dates", -- Start and end dates of time period.
"age", -- Age of women with deliveries.
"gender", -- Gender of women with deliveries (all female in this dataset).
"geographic_name", -- Name of geographic area.
"geocoded_column", -- A generic georeferenced Latitude & Longitude point within the county. These points can be used to create visualizations such as maps to show the data by county. A point is also provided for outside of the state (on a map it will sit to the southeast of the state). This number represents the total number for the state and this location provides a spot on a map to display the PA number without having it duplicate within a county when using in a mapping visual.
"number_of_women_with_a_5", -- Describes number of women with a delivery and OUD diagnosis.
"number_of_women_with_a_3", -- Count of women with a delivery and an OUD diagnosis. This count is provided by the Pennsylvania Department of Human Services (DHS).
"time_period", -- Period for measurement (annual, federal fiscal year, or quarterly, if available).
"year", -- Calendar year for measurement (January 1–December 31).
"geographic_area", -- Region for measure, either total for Commonwealth or individual county.
"type_of_rate", -- Description of deliveries with OUD diagnosis receiving MAT rate.
":@computed_region_nmsq_hqvv",
":@computed_region_d3gw_znnf",
":@computed_region_rayf_jjgk",
":@computed_region_r6rf_p9et",
":@computed_region_amqz_jbr4"
FROM
"pa-gov/percent-of-women-on-medical-assistance-ma-ig6a-8jqi:latest"."percent_of_women_on_medical_assistance_ma"
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/percent-of-women-on-medical-assistance-ma-ig6a-8jqi 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/percent-of-women-on-medical-assistance-ma-ig6a-8jqi: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/percent-of-women-on-medical-assistance-ma-ig6a-8jqiCheckout 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/percent-of-women-on-medical-assistance-ma-ig6a-8jqi:latestThis will download all the objects for the latest tag of pa-gov/percent-of-women-on-medical-assistance-ma-ig6a-8jqi 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/percent-of-women-on-medical-assistance-ma-ig6a-8jqi: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/percent-of-women-on-medical-assistance-ma-ig6a-8jqi: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/percent-of-women-on-medical-assistance-ma-ig6a-8jqi is just another Postgres schema.