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 2018_social_vulnerability_index table in this repository, by referencing it like:
"brla-gov/2018-social-vulnerability-index-q7v5-ijjg:latest"."2018_social_vulnerability_index"or in a full query, like:
SELECT
":id", -- Socrata column ID
"ep_uninsur", -- 2014-2018 American Community Survey (ACS) estimated adjunct variable - percentage uninsured in the total civilian noninstitutionalized population
"rpl_themes", -- Overall percentile ranking for all themes
"spl_themes", -- Sum of series themes
"spl_theme4", -- Sum of series for Housing Type/ Transportation theme
"ep_noveh", -- Estimated percentage of households with no vehicle available
"ep_crowd", -- Estimated percentage of occupied housing units with more people than rooms
"e_crowd", -- 2014-2018 American Community Survey (ACS) estimated at household level (occupied housing units), more people than rooms
"e_mobile", -- 2014-2018 American Community Survey (ACS) mobile homes
"e_munit", -- 2014-2018 American Community Survey (ACS) estimated housing in structures with 10 or more units
"ep_limeng", -- 2014-2018 American Community Survey (ACS) estimated percentage of persons (age 5+) who speak English "less than well"
"e_minrty", -- 2014-2018 American Community Survey (ACS) estimated minority (all persons except white, non-Hispanic)
"ep_sngpnt", -- 2014-2018 American Community Survey (ACS) estimated percentage of single parent households with children under 18
"e_sngpnt", -- 2014-2018 American Community Survey (ACS) estimated single parent household with children under 18
"ep_disabl", -- 2014-2018 American Community Survey (ACS) estimated percentage of civilian non-institutionalized population with a disability
"ep_age17", -- 2014-2018 American Community Survey (ACS) estimated percentage of persons aged 17 and younger
"e_age17", -- 2014-2018 American Community Survey (ACS) estimated persons aged 17 and younger
"ep_age65", -- 2014-2018 American Community Survey (ACS) estimated percentage of persons aged 65 and older
"e_nohsdp", -- 2014-2018 American Community Survey (ACS) estimated persons (age 25+) with no high school diploma
"e_pci", -- 2014-2018 American Community Survey (ACS) estimated per capita income
"ep_unemp", -- Estimated unemployment rate
"ep_pov", -- Estimated percentage of persons below poverty
"e_pov", -- 2014-2018 American Community Survey (ACS) estimated persons below poverty
"e_hh", -- 2014-2018 American Community Survey (ACS) estimated households
"e_hu", -- 2014-2018 American Community Survey (ACS) estimated housing units
"e_totpop", -- 2014-2018 American Community Survey (ACS) estimated population
"area_sqmi", -- Area in square miles
"fips", -- Unique identifier for each Census tract based on the Federal Information Processing Standards (FIPS) code
"e_limeng", -- 2014-2018 American Community Survey (ACS) estimated persons (age 5+) who speak English "less than well"
"e_noveh", -- 2014-2018 American Community Survey (ACS) estimated households with no vehicle available
"e_unemp", -- 2014-2018 American Community Survey (ACS) civilian (age 16+) estimated unemployed
"shape", -- Polygon geometry displaying the Census tracts
"e_uninsur", -- 2014-2018 American Community Survey (ACS) estimated adjunct variable - uninsured in the total civilian noninstitutionalized population
"spl_theme3", -- Sum of series for Minority Status/Language theme
"spl_theme2", -- Sum of series for Household Composition theme
"spl_theme1", -- Sum of series for Socioeconomic theme
"ep_groupq", -- 2014-2018 American Community Survey (ACS) estimated percentage of persons in institutionalized group quarters
"e_groupq", -- 2014-2018 American Community Survey (ACS) estimated persons in institutionalized group quarters
"ep_mobile", -- Estimated percentage of mobile homes
"ep_munit", -- Estimated percentage of housing in structures with 10 or more units
"ep_minrty", -- 2014-2018 American Community Survey (ACS) estimated percentage minority (all persons except white, non-Hispanic)
"e_disabl", -- 2014-2018 American Community Survey (ACS) estimated civilian non-institutionalized population with a disability
"e_age65", -- 2014-2018 American Community Survey (ACS) estimated persons aged 65 and older
"ep_nohsdp", -- Estimated percentage of persons with no high school diploma (age 25+)
"e_daypop", -- LandScan 2018 adjunct variable - estimated daytime population
"st_abbr", -- State abbreviation
"county" -- Parish name
FROM
"brla-gov/2018-social-vulnerability-index-q7v5-ijjg:latest"."2018_social_vulnerability_index"
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 brla-gov/2018-social-vulnerability-index-q7v5-ijjg with SQL in under 60 seconds.
This repository is an "external" repository. That means it's hosted elsewhere, in this case at data.brla.gov. When you querybrla-gov/2018-social-vulnerability-index-q7v5-ijjg: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.brla.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 \
"brla-gov/2018-social-vulnerability-index-q7v5-ijjg" \
--handler-options '{
"domain": "data.brla.gov",
"tables": {
"2018_social_vulnerability_index": "q7v5-ijjg"
}
}'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, brla-gov/2018-social-vulnerability-index-q7v5-ijjg is just another Postgres schema.