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 fin_provider_scorecards table in this repository, by referencing it like:
"internal-open-piercecountywa-gov/fin-provider-scorecards-spmz-u53a:latest"."fin_provider_scorecards"or in a full query, like:
SELECT
":id", -- Socrata column ID
"ce_connection_num", -- The number of household enrollments with an enrollment in CE within 14 days of the project enrollment
"avg_time_project_den", -- Number of households that exited
"returns_12mos_den", -- Number of households that exited one year prior
"hmis_quality_num", -- The number of data entry fields that are complete and accurate, averaged across all individual records
"project_type", -- The homeless services project type, such as Emergency Shelter or Rapid Re-Housing
"ce_referral_acceptance_num", -- The number of referrals that are accepted by the provider or canceled/denied for an acceptable reason
"avg_time_movein_num", -- Sum of all lengths of time to move in
"prioritize_chronicity_num", -- The number of new household enrollments in Permanent Supportive Housing where the head of household was chronically homeless
"last_updated", -- Date of the export from HMIS
"ce_utilization_num", -- The number of household enrollments that had a referral from CE within 6 months prior or within 14 days after the enrollment entry date
"ce_utilization_den", -- The number of household enrollments
"ce_referral_acceptance", -- The percent of referrals that are accepted by the provider or canceled/denied for an acceptable reason
"exits_ph_num", -- Number of exits to permanent housing destinations
"exits_ph_den", -- Number of exits
"avg_time_movein_den", -- Number of households that moved in
"avg_time_project", -- The average length of time, in days, between the enrollment entry date and the enrollment exit date
"returns_12mos_num", -- The number of household exits to permanent housing that resulted in a return to the homeless housing system within one year of exiting
"income_increase_den", -- Number of project exits where the client was 18+ years old
"income_increase_maintain_1", -- The number of exits for adult clients where the client had an increase in income or maintained their income from enrollment entry to enrollment exit date
"income_increase_maintain_2", -- Number of exits where the client was 18+ years old
"prioritize_chronicity", -- The percent of new household enrollments in Permanent Supportive Housing where the head of household was chronically homeless
"psh_stability", -- The percent of households active in Permanent Supportive Housing projects that had been housed for 12 months or longer, based on daily averages
"bed_utilization", -- The percent of beds that were occupied during the reporting period, calculated as the average of the daily client count divided by the daily bed count
"hmis_quality", -- The percent of data entry fields that are complete and accurate, averaged across all individual records
"hmis_timeliness_num", -- The number of client enrollment records that were entered in HMIS within 5 working days of the enrollment entry date
"hmis_timeliness_den", -- Number of client enrollment records
"provider", -- Homeless services provider
"year", -- Year
"ce_utilization", -- The percent of households with new enrollments that had a referral from CE within 6 months prior or within 14 days after the enrollment entry date
"ce_referral_acceptance_den", -- The number of referrals sent to the provider
"ce_connection", -- The percent of household enrollments with an enrollment in CE within 14 days of the project enrollment
"ce_connection_den", -- The number of household enrollments
"exits_ph", -- The percent of exits to permanent housing destinations
"avg_time_movein", -- The average length of time, in days, between the enrollment entry date and the housing move-in date
"avg_time_project_num", -- Sum of all lengths of time in the project
"returns_12mos", -- The percent of household exits to permanent housing that resulted in a return to the homeless housing system within one year of exiting
"income_increase", -- The percent of exits for adult clients where the client had an increase in income from enrollment entry to enrollment exit date
"income_increase_num", -- The number of exits for adult clients where the client had an increase in income from enrollment entry to enrollment exit date
"income_increase_maintain", -- The percent of exits for adult clients where the client had an increase in income or maintained their income from enrollment entry to enrollment exit date
"prioritize_chronicity_den", -- New household enrollments in Permanent Supportive Housing
"psh_stability_den", -- The average daily count of households that were active in Permanent Supportive Housing projects
"bed_utilization_den", -- The average daily bed count
"hmis_quality_den", -- Number of data entry fields
"hmis_timeliness" -- The percent of client enrollment records that were entered in HMIS within 5 working days of the enrollment entry date
FROM
"internal-open-piercecountywa-gov/fin-provider-scorecards-spmz-u53a:latest"."fin_provider_scorecards"
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 internal-open-piercecountywa-gov/fin-provider-scorecards-spmz-u53a with SQL in under 60 seconds.
This repository is an "external" repository. That means it's hosted elsewhere, in this case at internal.open.piercecountywa.gov. When you queryinternal-open-piercecountywa-gov/fin-provider-scorecards-spmz-u53a: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 internal.open.piercecountywa.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 \
"internal-open-piercecountywa-gov/fin-provider-scorecards-spmz-u53a" \
--handler-options '{
"domain": "internal.open.piercecountywa.gov",
"tables": {
"fin_provider_scorecards": "spmz-u53a"
}
}'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, internal-open-piercecountywa-gov/fin-provider-scorecards-spmz-u53a is just another Postgres schema.