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 homeless_dedicated_housing table in this repository, by referencing it like:
"sonomacounty-ca-gov/homeless-dedicated-housing-4svx-khws:latest"."homeless_dedicated_housing"or in a full query, like:
SELECT
":id", -- Socrata column ID
"last_update_on",
"hmis_beds_hh_w_children", -- Beds for Households with Children listed in Homeless Management Information System.
"beds_hh_w_o_children", -- Beds for Households with Children
"beds_hh_w_children", -- Beds for Households with Children
"project_name",
"ch_beds_hh_w_o_children", -- Beds for Chronically Homeless Households without Children (Head of Household is Chronically Homeless).
"target_pop_a", -- SM=Single Males, SF=Single Females, SMF=Single Males & Females, HC=Households with Children, YMF=Youth Male & Female, SMHC/SFHC/SMF+HC=combinations of the foregoing
"year", -- The year of data collection.
"location_1_address",
"location_1_city",
"location_1_state",
":@computed_region_xw9s_pz78",
":@computed_region_dig5_f3vy",
"location_1_zip",
"inventory_type", -- C=Current, N=New (first year active), U=Under development (not yet active)
"veteran_beds_hh_w_o_children", -- Beds for Veteran Households without Children (Head of Household is Veteran).
"th_unit_type",
"bed_type", -- Facility-based beds = all beds in one facility, Other beds = beds in scattered locations.
"target_pop_b", -- DV=Victims of Domestic Violence, HIV=Individuals with HIV, NA=Not Applicable
"mckinney_vento", -- Whether the project receives any HUD McKinney-Vento funding.
"units_hh_w_children", -- Units (rooms) for Households with Children
"veteran_beds_hh_w_children", -- Beds for Veteran Households with Children (Head of Household is Veteran)
"ch_beds_hh_w_children", -- Beds for Chronically Homeless Households with Children (Head of Household is Chronically Homeless).
"year_round_beds", -- Number of year-round beds available.
"hmis_beds_hh_w_only_children", -- Beds for Households with only Children listed in Homeless Management Information System.
"of_hmis_beds_hh_w_only_children", -- Beds for Households with only Children listed in Homeless Management Information System / Beds for Households with only Children.
"seasonal_beds_available_in_hmis", -- Number of seasonal (partial year) beds listed in Homeless Management Information System.
"total_seasonal_beds", -- Number of seasonal (partial year) beds.
"pit_count", -- Count of participants in program at Point In Time Count (January 27, 2017).
"overflow_beds", -- Overflow beds are available on an ad hoc or temporary basis during the year in response to demand that exceeds planned (year-round or seasonal) bed capacity.
"utilization_rate", -- Utilization Rate = Point in Time Count / Total Beds.
"total_beds", -- Total beds in program.
"proj_type", -- ES = Emergency Shelter OPH = Other Perminant Housing PSH = Permanent Supportive Housing RRH = Rapid Re-Housing TH = Transitional Housing
"location_1", -- Location of the center of the Census Tract and not the actual location of the shelter.
"beds_hh_w_only_children", -- Beds for Households with only Children
"youth_beds_hh_w_children", -- Beds for Youth Households with Children (Head of Household is Youth.
"ch_beds_hh_w_only_children", -- Beds for Chronically Homeless Households with only Children (Head of Household is under age 19 and Chronically Homeless).
"other_federal_funding_other", -- What other HUD (non McKinney-Vento) funding is received.
"youth_beds_hh_w_o_children", -- Beds for Youth Households with Children (Head of Household is Youth).
"other_federal_funding", -- Whether the project receives other HUD (non McKinney-Vento) funding.
"hmis_beds_hh_w_o_children", -- Beds for Households without Children listed in Homeless Management Information System.
"of_hmis_beds_hh_with_children", -- Beds for Households with Children listed in Homeless Management Information System / Beds for Households with Children.
"of_hmis_beds_hh_without_children" -- Beds for Households without Children listed in Homeless Management Information System / Beds for Households without Children.
FROM
"sonomacounty-ca-gov/homeless-dedicated-housing-4svx-khws:latest"."homeless_dedicated_housing"
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 sonomacounty-ca-gov/homeless-dedicated-housing-4svx-khws with SQL in under 60 seconds.
This repository is an "external" repository. That means it's hosted elsewhere, in this case at data.sonomacounty.ca.gov. When you querysonomacounty-ca-gov/homeless-dedicated-housing-4svx-khws: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.sonomacounty.ca.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 \
"sonomacounty-ca-gov/homeless-dedicated-housing-4svx-khws" \
--handler-options '{
"domain": "data.sonomacounty.ca.gov",
"tables": {
"homeless_dedicated_housing": "4svx-khws"
}
}'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, sonomacounty-ca-gov/homeless-dedicated-housing-4svx-khws is just another Postgres schema.