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 2020_final_assisted_reproductive_technology_art table in this repository, by referencing it like:
"cdc-gov/2020-final-assisted-reproductive-technology-art-3x54-3thk:latest"."2020_final_assisted_reproductive_technology_art"or in a full query, like:
SELECT
":id", -- Socrata column ID
"geolocation", -- Location code for ART clinic location to be used for geocoding
"breakoutid", -- Stratification value identifier
"filterid", -- Filter identifier
"questionid", -- Question identifier
"typeid", -- Type identifier
"cycle_count", -- Total number of ART cycles
"data_value_footnote", -- Footnote description, if applicable
"data_value_num", -- Data numeric values only, e.g. number, percentage within the breakout, question or subtopic
"data_value", -- Data value, e.g. number, percentage, or fraction within the breakout, question or subtopic
"breakout", -- Stratification value, e.g. fresh embryos fresh eggs, <35 years
"filter", -- Filter description, e.g. infertility diagnosis
"topic", -- Topic description, e.g. clinic services and profile, patient and cycle characteristics, success rates: patients using donor eggs, success rates: patients using own eggs, or summary
"type", -- Type description, e.g. patients using their own eggs, patients with no prior ART using their own eggs
"phone", -- Phone number for ART clinic
"zipcode", -- Zip code for ART clinic location
"city", -- City for ART clinic location
"address", -- Address for ART clinic location
"medicaldirector", -- Name of medical director verifying data
"facilityname", -- ART clinic name or national data indicator
"locationdesc", -- State for ART clinic location
"breakoutcategoryid", -- Stratification grouping identifier
"topicid", -- Topic identifier
"clinicid", -- ART clinic identifier
"data_value_footnote_symbol", -- Symbol used to flag footnotes, if applicable
"breakout_category", -- Stratification grouping, e.g. egg/embryo type, age group of patient
"question", -- Question description, e.g. specific patient and cycle characteristic or specific success factor
"clinic_status", -- Operating status for ART clinic, e.g. open, closed, reorganized
"locationabbr", -- Abbreviated state for ART clinic location
"year" -- Reporting year
FROM
"cdc-gov/2020-final-assisted-reproductive-technology-art-3x54-3thk:latest"."2020_final_assisted_reproductive_technology_art"
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 cdc-gov/2020-final-assisted-reproductive-technology-art-3x54-3thk 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 cdc-gov/2020-final-assisted-reproductive-technology-art-3x54-3thk: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 cdc-gov/2020-final-assisted-reproductive-technology-art-3x54-3thkCheckout 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 cdc-gov/2020-final-assisted-reproductive-technology-art-3x54-3thk:latestThis will download all the objects for the latest tag of cdc-gov/2020-final-assisted-reproductive-technology-art-3x54-3thk 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 cdc-gov/2020-final-assisted-reproductive-technology-art-3x54-3thk: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 cdc-gov/2020-final-assisted-reproductive-technology-art-3x54-3thk: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, cdc-gov/2020-final-assisted-reproductive-technology-art-3x54-3thk is just another Postgres schema.