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 household_pulse_survey_hps_covid19_vaccination table in this repository, by referencing it like:
"cdc-gov/household-pulse-survey-hps-covid19-vaccination-u4vw-xsmf:latest"."household_pulse_survey_hps_covid19_vaccination"or in a full query, like:
SELECT
":id", -- Socrata column ID
"coinf_95", -- The 95% confidence interval of the estimate.
"estimate_type", -- Vaccinaton status estimate categorization can display one of “Vaccinated”, “Bivalent Booster" Reasons for not receiving bivalent booster estimate categorization can display one of : "My doctor has not recommended it", "Other", "already had COVID-19", "enough immunity to COVID-19 from prior doses of the vaccine", "experienced side effects from my previous dose(s) of the COVID-19 vaccine", "not required to get a COVID-19 booster (by my work or school)", "not worried about getting COVID-19", "not yet eligible to receive an updated COVID-19 booster dose", "plan to get a booster and am eligible, but haven't yet"
"estimate", -- The numerical estimate of the weighted proportion giving the response.
"suppression_flag", -- Estimates that did not meet the National Center for Health Statistics (NCHS) standards of reliability are suppressed (left missing) and have a value of 1 for this field. If the estimate met the NCHS standards of reliability, the estimate was not suppressed, and this field has a value of 0.
"sample_size", -- The unweighted sample size used to create the estimate for each demographic and disability status grouping.
"status", -- The reported disability status for which estimates are calculated. The two statuses are “With Disability” and “Without Disability.”
"report", -- The report where data is being currently displayed
"disability_type", -- One of the WG-SS four domains of functioning: seeing (even when wearing glasses), hearing (even when using a hearing aid), mobility (walking or climbing stairs), and cognition (remembering or concentrating); or "Any Disability" for respondents with any disability.
"week", -- The date range during which data was collected to produce these estimates. More information about data collection periods can be found at https://www.census.gov/programs-surveys/household-pulse-survey/technical-documentation.html.
"demographic", -- The sociodemographic group for which estimates are calculated.
"category" -- The classification of the sociodemographic category for which estimates are calculated. The two applicable categories are "Age" and "Race and Ethnicity."
FROM
"cdc-gov/household-pulse-survey-hps-covid19-vaccination-u4vw-xsmf:latest"."household_pulse_survey_hps_covid19_vaccination"
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/household-pulse-survey-hps-covid19-vaccination-u4vw-xsmf 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/household-pulse-survey-hps-covid19-vaccination-u4vw-xsmf: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/household-pulse-survey-hps-covid19-vaccination-u4vw-xsmfCheckout 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/household-pulse-survey-hps-covid19-vaccination-u4vw-xsmf:latestThis will download all the objects for the latest tag of cdc-gov/household-pulse-survey-hps-covid19-vaccination-u4vw-xsmf 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/household-pulse-survey-hps-covid19-vaccination-u4vw-xsmf: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/household-pulse-survey-hps-covid19-vaccination-u4vw-xsmf: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/household-pulse-survey-hps-covid19-vaccination-u4vw-xsmf is just another Postgres schema.