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 campaign_finance_disclosure_contributions_data table in this repository, by referencing it like:
"pa-gov/campaign-finance-disclosure-contributions-data-wb79-wsa4:latest"."campaign_finance_disclosure_contributions_data"or in a full query, like:
SELECT
":id", -- Socrata column ID
"employer_location_2_zip",
"employer_location_2_city",
"employer_location_1_zip",
"employer_location_1_address",
"contributor_location_2_address",
"contributor_location_2_city",
"contributor_location_1_state",
"contributor_location_1_city",
"contributor_location_2_state",
"contributor_location_1_address",
"employer_location_2_address",
"employer_location_1_state",
"contributor_location_1_zip",
"contributor_location_2_zip",
"employer_location_1_city",
"employer_location_2_state",
"employer_location_2", -- Employer Location based on Employer Address 2. If Employer Address 2 is blank but the Employer City, State, and Zip are not blank, this is likely a generalized location.
"employer_location_1", -- Employer Location based on Employer Address 1.
"contributor_location_2", -- Contributor Location based on Contributor Address 2. If Contributor Address 2 is blank, this location will likely be a general location for the address. This column includes the latitude and longitude geocoded during the data import.
"contributor_location_1", -- Contributor Location based on Contributor Address 1. This column includes the Latitude and Longitude geocoded during the data import.
"contribution_description", -- A field for the candidate or committee to explain the recorded contribution.
"contribution_date", -- This field represents the date of the contribution being recorded by the candidate or committee. (Formatted as YYYYMMDD)
"employer_zip_code", -- This field represents the zip code of the employer of the contributor if their aggregate contribution(s) surpass $250 in a reporting period.
"employer_city", -- This field denotes the employer city of the contributor if their aggregate contribution(s) surpass $250 in a reporting period.
"employer_state", -- This field denotes the state of the employer of the contributor if their aggregate contribution(s) surpass $250 in a reporting period.
"employer_address_2", -- This field is a secondary address field for the employer of the contributor if their aggregate contribution(s) are equal to or greater than $250 in a reporting period.
"employer_address_1", -- This field denotes the employer address of the contributor if their aggregate contribution(s) are equal to or greater than $250 in a reporting period.
"employer_name", -- This field denotes the employer name of the contributor if their aggregate contribution(s) are equal to or greater than $250 in a reporting period.
"occupation", -- This field denotes the occupation of the contributor if their aggregate contribution(s) are equal to or greater than $250 in a reporting period.
"contributor_zip_code", -- The zip code of the contributor at the time of their contribution.
"contributor_state", -- The state of the contributor at the time of their contribution.
"contributor_city", -- The city of the contributor at the time of their contribution.
"contributor_address_2", -- This is a secondary address field for the individual or entity contributing to the candidate or committee if they meet the reporting requirements.
"contributor_address_1", -- The address of the individual or entity contributing to the candidate or committee if they meet the reporting requirements.
"contributor", -- The name of the individual or entity contributing to the candidate or committee if they meet the reporting requirements.
"cycle", -- This specifies the reporting cycle or timeframe the contributions were accepted by the candidate or committee.
"election_year", -- This denotes the election cycle or year the candidate or committee is filing
"filer_identification_number", -- This is the Filer Identification Number which is unique to each entity reporting campaign finance contributions (i.e. candidates and committees)
"section", -- This denotes the location of the line item on the campaign finance report form.
"contribution_amount" -- The amount of the contribution recorded by the candidate or committee.
FROM
"pa-gov/campaign-finance-disclosure-contributions-data-wb79-wsa4:latest"."campaign_finance_disclosure_contributions_data"
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 pa-gov/campaign-finance-disclosure-contributions-data-wb79-wsa4 with SQL in under 60 seconds.
This repository is an "external" repository. That means it's hosted elsewhere, in this case at data.pa.gov. When you querypa-gov/campaign-finance-disclosure-contributions-data-wb79-wsa4: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.pa.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 \
"pa-gov/campaign-finance-disclosure-contributions-data-wb79-wsa4" \
--handler-options '{
"domain": "data.pa.gov",
"tables": {
"campaign_finance_disclosure_contributions_data": "wb79-wsa4"
}
}'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, pa-gov/campaign-finance-disclosure-contributions-data-wb79-wsa4 is just another Postgres schema.