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_women_on_medical_assistance_ma_diagnosed table in this repository, by referencing it like:
"pa-gov/rate-of-women-on-medical-assistance-ma-diagnosed-mmps-kc6p:latest"."rate_of_women_on_medical_assistance_ma_diagnosed"or in a full query, like:
SELECT
":id", -- Socrata column ID
"year", -- Calendar year for measurement (January 1–December 31).
"geographic_area", -- Region for measure, either total for Commonwealth or individual county.
"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.
":@computed_region_r6rf_p9et",
":@computed_region_rayf_jjgk",
":@computed_region_d3gw_znnf",
":@computed_region_nmsq_hqvv",
"total_number_of_deliveries_2", -- Describes number of women with a delivery.
"type_of_rate", -- Description of deliveries with OUD diagnosis rate.
"number_of_women_with_a_2", -- Describes number of women with a delivery and OUD diagnosis.
"geographic_name", -- Name of geographic area.
"gender", -- Gender of women with deliveries (all female in this dataset).
"total_number_of_deliveries_1", -- Indicates if the number of deliveries has been suppressed to protect confidentiality. Counts less than 11 are not provided.
":@computed_region_amqz_jbr4",
"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).
"total_number_of_deliveries", -- Count of deliveries, including live births and stillbirths. This count is provided by the Pennsylvania Department of Human Services (DHS).
"number_of_women_with_a_1", -- 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", -- Count of women with a delivery and an OUD diagnosis. This count is provided by the Pennsylvania Department of Human Services (DHS).
"deliveries_with_oud_diagnosis", -- Rate of women with a delivery that were diagnosed with Opioid Use Disorder (OUD) per 1000 deliveries.
"time_period_dates", -- Start and end dates of time period.
"time_period", -- Period for measurement (annual, federal fiscal year, or quarterly, if available).
"age" -- Age of women with deliveries.
FROM
"pa-gov/rate-of-women-on-medical-assistance-ma-diagnosed-mmps-kc6p:latest"."rate_of_women_on_medical_assistance_ma_diagnosed"
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-women-on-medical-assistance-ma-diagnosed-mmps-kc6p with SQL in under 60 seconds.
This repository is an "external" repository. That means it's hosted elsewhere, in this case at data.pa.gov. When you querypa-gov/rate-of-women-on-medical-assistance-ma-diagnosed-mmps-kc6p:latest on the DDN, we "mount" the repository using the socrata mount handler. The mount handler proxies your SQL query to the upstream data source, translating it from SQL to the relevant language (in this case SoQL).
We also cache query responses on the DDN, but we run the DDN on multiple nodes so a CACHE_HIT is only guaranteed for subsequent queries that land on the same node.
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 (like this repository), 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, where the author has pushed Splitgraph Images to the repository, you can "clone" and/or "checkout" the data using sgr cloneand sgr checkout.
Mounting Data
This repository is an external repository. It's not hosted by Splitgraph. It is hosted by data.pa.gov, and Splitgraph indexes it. This means it is not an actual Splitgraph image, so you cannot use sgr clone to get the data. Instead, you can use the socrata adapter with the sgr mount command. Then, if you want, you can import the data and turn it into a Splitgraph image that others can clone.
First, install Splitgraph if you haven't already.
Mount the table with sgr mount
sgr mount socrata \
"pa-gov/rate-of-women-on-medical-assistance-ma-diagnosed-mmps-kc6p" \
--handler-options '{
"domain": "data.pa.gov",
"tables": {
"rate_of_women_on_medical_assistance_ma_diagnosed": "mmps-kc6p"
}
}'That's it! Now you can query the data in the mounted table like any other Postgres table.
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-women-on-medical-assistance-ma-diagnosed-mmps-kc6p is just another Postgres schema.