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 feed_the_future_uganda_populationbased_survey table in this repository, by referencing it like:
"usaid-gov/feed-the-future-uganda-populationbased-survey-q2cb-s4jg:latest"."feed_the_future_uganda_populationbased_survey"or in a full query, like:
SELECT
":id", -- Socrata column ID
"i04_mm", -- ZII Child birth month
"i11", -- ZII Height
"i13_consent", -- ZII Anemia consent
"i16", -- ZII Ever breastfed
"i21", -- ZII Water
"i26", -- ZII Juice
"i30", -- ZII Porridge
"bmiz",
"chwght", -- Children weight
"whz2", -- Weight for Height 2sd
"i03", -- ZII Child sex
"f06", -- ZIF Whl day no eat freq
"f02", -- ZIF No food freq
"f03", -- ZIF Sleep hungry yn
"f01", -- ZIF No food yn
"d03", -- ZID Ext wall tp
"pbs_id", -- PBS ID
"i46", -- ZII Sugary foods
"i34", -- ZII Orange veg
"i15", -- ZII Under 2
"zii_avail_wght_hght", -- ZII Avail wght hght
"i09", -- ZII Edema
"i05", -- ZII Child age years
"i42", -- ZII Fish
"i33", -- ZII Grains
"i29", -- ZII Yogurt freq
"i35", -- ZII Root crop
"i38", -- ZII Oth fruit veg
"i48", -- ZII Insects
"i40", -- ZII Meat
"f04", -- ZIF Sleep hungry freq
"i27", -- ZII Broth
"i37", -- ZII Vit a fruit
"d02", -- ZID Floor tp
"i13_a", -- ZII Under 6 months
"haz2", -- Height for Age 2sd
"d07", -- ZID Electr yn
"i25", -- ZII Milk freq
"i12", -- ZII BMI
"a21", -- Interview outcome derived by module C data
"i44", -- ZII Milk prod
"i49", -- ZII Red palm
"a06", -- Household type derived by module C data
"i18", -- ZII Other breast milk
"i45", -- ZII Oils fats
"i50", -- ZII Eat yesterday
"i14", -- ZII Anemia test result
"i51", -- ZII Eat yesterday freq
"d05", -- ZID Toilet tp
"i23", -- ZII Formula freq
"i08", -- ZII Under 60 months
"i31", -- ZII Other water based
"i22", -- ZII Formula
"waz", -- Underweight Z score
"i41", -- ZII Eggs
"i36", -- ZII Green leafy
"i32", -- ZII Other liquids
"f05", -- ZIF Whl day no eat yn
"a02", -- ZIA Cluster cd
"d08", -- ZID Fuel src
"i07_yr", -- ZII Consistent age year
"country", -- ZIG1 Country
"i39", -- ZII Organ meats
"a09", -- Household type derived by module C data
"urbrur", -- Urban Rural 1 urban 2 rural
"hhwght", -- Household weight
"i47", -- ZII Condiments
"whz", -- Wasting Z score
"haz", -- Stunting Z score
"i19", -- ZII Vit med drops
"i20", -- ZII Rehyd solution
"i24", -- ZII Milk
"i28", -- ZII Yogurt
"i43", -- ZII Beans nuts
"id_code", -- Respondent ID
"waz2", -- Weight for Age 2sd
"i04_yy", -- ZII Child birth year
"i06", -- ZII Child age months
"i07_mo", -- ZII Consistent age month
"i10", -- ZII Weight
"i17", -- ZII Breastfed yesterday
"a05", -- ZIG1 Sex g1
"d01", -- ZID Roof tp
"d04", -- ZID Rooms num
"d06", -- ZID Drink water src
"modd_missing", -- Missing all elements from D
"modf_missing", -- Missing all elements from F
"i01", -- ZII Caregiver id
"i04_dd" -- ZII Child birth day
FROM
"usaid-gov/feed-the-future-uganda-populationbased-survey-q2cb-s4jg:latest"."feed_the_future_uganda_populationbased_survey"
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 usaid-gov/feed-the-future-uganda-populationbased-survey-q2cb-s4jg with SQL in under 60 seconds.
This repository is an "external" repository. That means it's hosted elsewhere, in this case at data.usaid.gov. When you queryusaid-gov/feed-the-future-uganda-populationbased-survey-q2cb-s4jg: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.usaid.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 \
"usaid-gov/feed-the-future-uganda-populationbased-survey-q2cb-s4jg" \
--handler-options '{
"domain": "data.usaid.gov",
"tables": {
"feed_the_future_uganda_populationbased_survey": "q2cb-s4jg"
}
}'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, usaid-gov/feed-the-future-uganda-populationbased-survey-q2cb-s4jg is just another Postgres schema.