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 weekly_united_states_hospitalization_metrics_by table in this repository, by referencing it like:
"cdc-gov/weekly-united-states-hospitalization-metrics-by-aemt-mg7g:latest"."weekly_united_states_hospitalization_metrics_by"or in a full query, like:
SELECT
":id", -- Socrata column ID
"percent_hospitals_staff_icu_patients_covid_confirmed", -- Percent of total hospitals that reported data for total adult patients hospitalized with COVID-19 in the ICU OR total pediatric patients hospitalized with COVID-19 in the ICU at least one day in the specified week
"percent_hospitals_total_patients_hospitalized_covid_confirmed", -- Percent of total hospitals that reported data for total adult patients hospitalized with COVID-19 OR total pediatric patients hospitalized with COVID-19 at least one day in the specified week
"percent_hospitals_admissions_all_covid_confirmed", -- Percent of total hospitals that reported data for previous day admissions of adult patients with confirmed COVID-19 OR previous day admissions of pediatric patients with confirmed COVID-19 at least one day in the specified week
"percent_hospitals_percent_icu_beds_influenza", -- Percent of total hospitals that reported data for total patients hospitalized with confirmed influenza in the ICU AND total ICU beds at least one day in the specified week
"percent_hospitals_percent_inpatient_beds_influenza", -- Percent of total hospitals that reported data for total patients hospitalized with confirmed influenza AND total inpatient beds at least one day in the specified week
"percent_hospitals_percent_staff_icu_beds_occupied", -- Percent of total hospitals that reported data for ICU beds used and total ICU beds at least one day in the specified week
"percent_hospitals_percent_inpatient_beds_occupied", -- Percent of total hospitals that reported data for inpatient beds used and total inpatient beds at least one day in the specified week
"percent_hospitals_icu_beds_used", -- Percent of total hospitals that reported data for ICU beds used at least one day in the specified week
"percent_hospitals_total_icu_beds", -- Percent of total hospitals that reported data for total ICU beds at least one day in the specified week
"percent_hospitals_inpatient_beds", -- Percent of total hospitals that reported data for total inpatient beds at least one day in the specified week
"percent_hospitals_icu_patients_confirmed_influenza", -- Percent of total hospitals that reported data for total patients hospitalized with confirmed influenza in the ICU at least one day in the specified week
"percent_hospitals_total_patients_hospitalized_confirmed_influen", -- Percent of total hospitals that reported data for total patients hospitalized with confirmed influenza at least one day in the specified week
"percent_hospitals_previous_day_admission_influenza_confirmed", -- Percent of total hospitals that reported data for previous day admissions of patients with confirmed influenza at least one day in the specified week
"percent_pediatric_covid_admissions", -- Percent of the weekly total number of new hospital admissions of patients with confirmed COVID-19 that were pediatric admissions
"percent_adult_covid_admissions", -- Percent of the weekly total number of new hospital admissions of patients with confirmed COVID-19 that were adult admissions
"avg_percent_icu_beds_influenza", -- Weekly average percent of ICU beds occupied by influenza patients
"avg_percent_staff_icu_beds_covid", -- Weekly average percent of ICU beds occupied by COVID-19 patients
"avg_percent_staff_icu_beds_occupied", -- Weekly average percent of ICU beds occupied by any patient
"avg_percent_inpatient_beds_occupied", -- Weekly average percent of inpatient beds occupied by any patient
"avg_total_icu_beds", -- Weekly average number of ICU beds reported
"avg_inpatient_beds", -- Weekly average number of inpatient beds reported
"avg_total_patients_hospitalized_influenza_confirmed", -- Weekly average number of patients hospitalized with confirmed influenza
"avg_admissions_all_influenza_confirmed", -- Weekly average number of new hospital admissions of patients with confirmed influenza
"total_admissions_all_covid_confirmed", -- Weekly total number of new hospital admissions of patients with confirmed COVID-19
"avg_admissions_all_covid_confirmed", -- Weekly average number of new hospital admissions of patients with confirmed COVID-19
"avg_admissions_pediatric_covid_confirmed", -- Weekly average number of new hospital admissions of pediatric patients with confirmed COVID-19
"avg_admissions_adult_covid_confirmed", -- Weekly average number of new hospital admissions of adult patients with confirmed COVID-19
"num_hospitals_staff_icu_patients_covid_confirmed", -- Weekly total number of hospitals that reported data for total adult patients hospitalized with COVID-19 in the ICU OR total pediatric patients hospitalized with COVID-19 in the ICU at least one day in the specified week
"num_hospitals_total_patients_hospitalized_covid_confirmed", -- Weekly total number of hospitals that reported data for total adult patients hospitalized with COVID-19 OR total pediatric patients hospitalized with COVID-19 at least one day in the specified week
"num_hospitals_admissions_all_covid_confirmed", -- Weekly total number of hospitals that reported data for previous day admissions of adult patients with confirmed COVID-19 OR previous day admissions of pediatric patients with confirmed COVID-19 at least one day in the specified week
"num_hospitals_percent_icu_beds_influenza", -- "Weekly total number of hospitals that reported data for total patients hospitalized with confirmed influenza in the ICU AND total ICU beds at least one day in the specified week "
"num_hospitals_percent_staff_icu_beds_covid", -- Weekly total number of hospitals that reported data for (total adult patients hospitalized with COVID-19 in the ICU OR total pediatric patients hospitalized with COVID-19 in the ICU) AND total ICU beds at least one day in the specified week
"num_hospitals_percent_inpatient_beds_influenza", -- "Weekly total number of hospitals that reported data for total patients hospitalized with confirmed influenza AND total inpatient beds at least one day in the specified week "
"num_hospitals_percent_inpatient_beds_covid", -- Weekly total number of hospitals that reported data for (total adult patients hospitalized with COVID-19 OR total pediatric patients hospitalized with COVID-19) AND total inpatient beds at least one day in the specified week
"num_hospitals_icu_beds_used", -- Weekly total number of hospitals that reported data for ICU beds used at least one day in the specified week
"num_hospitals_inpatient_beds_used", -- Weekly total number of hospitals that reported data for inpatient beds used at least one day in the specified week
"num_hospitals_total_icu_beds", -- Weekly total number of hospitals that reported data for total ICU beds at least one day in the specified week
"num_hospitals_inpatient_beds", -- Weekly total number of hospitals that reported data for total inpatient beds at least one day in the specified week
"num_hospitals_icu_patients_confirmed_influenza", -- Weekly total number of hospitals that reported data for total patients hospitalized with confirmed influenza in the ICU at least one day in the specified week
"num_hospitals_total_patients_hospitalized_confirmed_influenza", -- Weekly total number of hospitals that reported data for total patients hospitalized with confirmed influenza at least one day in the specified week
"num_hospitals_previous_day_admission_pediatric_covid_confirmed", -- Weekly total number of hospitals that reported data for previous day admissions of pediatric patients with confirmed COVID-19 at least one day in the specified week
"num_hospitals_previous_day_admission_adult_covid_confirmed", -- Weekly total number of hospitals that reported data for previous day admissions of adult patients with confirmed COVID-19 at least one day in the specified week
"weekly_percent_days_reporting_any_data", -- Percent of expected hospital reporting days that were actually reported for a given week
"week_end_date", -- MMWR week end date
"percent_hospitals_previous_day_admission_adult_covid_confirmed", -- Percent of total hospitals that reported data for previous day admissions of adult patients with confirmed COVID-19 at least one day in the specified week
"total_admissions_all_influenza_confirmed", -- Weekly total number of new hospital admissions of patients with confirmed influenza
"num_hospitals_previous_day_admission_influenza_confirmed", -- Weekly total number of hospitals that reported data for previous day admissions of patients with confirmed influenza at least one day in the specified week
"percent_hospitals_percent_inpatient_beds_covid", -- Percent of total hospitals that reported data for (total adult patients hospitalized with COVID-19 OR total pediatric patients hospitalized with COVID-19) AND total inpatient beds at least one day in the specified week
"percent_hospitals_inpatient_beds_used", -- Percent of total hospitals that reported data for inpatient beds used at least one day in the specified week
"percent_hospitals_previous_day_admission_pediatric_covid_confir", -- Percent of total hospitals that reported data for previous day admissions of pediatric patients with confirmed COVID-19 at least one day in the specified week
"avg_percent_inpatient_beds_influenza", -- Weekly average percent of inpatient beds occupied by influenza patients
"avg_percent_inpatient_beds_covid", -- Weekly average percent of inpatient beds occupied by COVID-19 patients
"avg_icu_beds_used", -- Weekly average number of ICU beds used reported
"avg_inpatient_beds_used", -- Weekly average number of inpatient beds used reported
"avg_icu_patients_influenza_confirmed", -- Weekly average number of patients hospitalized with confirmed influenza in the ICU
"avg_staff_icu_patients_covid_confirmed", -- Weekly average number of patients hospitalized with confirmed COVID-19 in the ICU
"avg_total_patients_hospitalized_covid_confirmed", -- Weekly average number of patients hospitalized with confirmed COVID-19
"total_admissions_pediatric_covid_confirmed", -- Weekly total number of new hospital admissions of pediatric patients with confirmed COVID-19
"total_admissions_adult_covid_confirmed", -- Weekly total number of new hospital admissions of adult patients with confirmed COVID-19
"num_hospitals_percent_staff_icu_beds_occupied", -- Weekly total number of hospitals that reported data for ICU beds used and total ICU beds at least one day in the specified week
"num_hospitals_percent_inpatient_beds_occupied", -- Weekly total number of hospitals that reported data for inpatient beds used and total inpatient beds at least one day in the specified week
"weekly_actual_days_reporting_any_data", -- Total number of actual hospital reporting days for a given week
"percent_hospitals_percent_staff_icu_beds_covid", -- Percent of total hospitals that reported data for (total adult patients hospitalized with COVID-19 in the ICU OR total pediatric patients hospitalized with COVID-19 in the ICU) AND total ICU beds at least one day in the specified week
"jurisdiction" -- Name of country or state
FROM
"cdc-gov/weekly-united-states-hospitalization-metrics-by-aemt-mg7g:latest"."weekly_united_states_hospitalization_metrics_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 cdc-gov/weekly-united-states-hospitalization-metrics-by-aemt-mg7g 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/weekly-united-states-hospitalization-metrics-by-aemt-mg7g: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/weekly-united-states-hospitalization-metrics-by-aemt-mg7gCheckout 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/weekly-united-states-hospitalization-metrics-by-aemt-mg7g:latestThis will download all the objects for the latest tag of cdc-gov/weekly-united-states-hospitalization-metrics-by-aemt-mg7g 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/weekly-united-states-hospitalization-metrics-by-aemt-mg7g: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/weekly-united-states-hospitalization-metrics-by-aemt-mg7g: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/weekly-united-states-hospitalization-metrics-by-aemt-mg7g is just another Postgres schema.