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_rwanda_baseline_household_survey table in this repository, by referencing it like:
"usaid-gov/feed-the-future-rwanda-baseline-household-survey-d44p-5duj:latest"."feed_the_future_rwanda_baseline_household_survey"or in a full query, like:
SELECT
":id", -- Socrata column ID
"h02_year",
"zih_women_age_range",
"h19", -- Any other fruits or vegetables
"h22", -- Eggs
"h02_month",
"h06",
"c02", -- What is NAME s sex
"a04",
"f01", -- In the past 4 weeks 30 days was there ever no food to eat of any kind in your house because of lack of resources to get food
"h27", -- Any sugary foods such as chocolates sweets candies pastries cakes or biscuits
"organgrp",
"h15", -- Pumpkin carrots squash or sweet potatoes that are yellow or orange inside or other local yellow orange foods
"h28", -- Condiments for flavor such as chilies spices herbs or fish powder
"eggsgrp",
"d07", -- Does this household have electricity
"h26", -- Any oil fats or butter or foods made with any of these
"d05", -- What is the main type of toilets your household uses
"a09",
"h29", -- Grubs snails or insects
"h14", -- Food made from grains such as bread rice noodles porridge or other local grain food
"f05", -- In the past 4 weeks 30 days did you or any household member go a whole day and night without eating anything at all because there was not enough food
"h23", -- Fresh or dried fish shellfish or seafood
"d04", -- How many rooms are there in this dwelling
"lfygrngrp",
"f02", -- How often did this happen in the past 4 weeks 30 days
"h25", -- Cheese yogurt or other milk products
"f04", -- How often did this happen in the past 4 weeks 30 days
"othvitagrp",
"foodsum",
"h18", -- Ripe mangoes ripe papayas or other local vitamin A rich fruits
"d02", -- Type of floor
"modd_missing",
"h07",
"zih_age_check_yn",
"a21", -- Final outcome of interview
"h24", -- Any foods made from beans peas lentils nuts or seeds add any local names
"d08", -- What is the main source of cooking fuel for your household
"fleshgrp",
"h24x",
"h08",
"h20", -- Liver kidney heart or other organ meats
"h30", -- Foods made with red palm oil red palm nut
"h16", -- White potatoes white yams manioc cassava other local root crops or any other foods made from roots
"d01", -- Type of roof
"beansgrp",
"h17", -- Any dark green leafy vegetables such as local dark green leafy vegetables
"f06", -- How often did this happen in the past 4 weeks 30 days
"d03", -- Type of walls
"milkgrp",
"id_code",
"grainsgrp",
"modf_missing",
"a02", -- Household listing number
"country",
"d06", -- What is the main source of drinking water for your household
"f03", -- In the past 4 weeks 30 days did you or any household member go to sleep at night hungry because there was not enough food
"a06", -- Province
"h21", -- Any meat such as beef pork lamb goat chicken or duck
"othfrtgrp",
"pbs_id",
"a05", -- District
"c03", -- What is NAME s relationship to the primary respondent
"c04", -- What is NAME s age in years
"h03", -- Please tell me how old you are What was your age at your last birthday
"urbrur",
"wmwght"
FROM
"usaid-gov/feed-the-future-rwanda-baseline-household-survey-d44p-5duj:latest"."feed_the_future_rwanda_baseline_household_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-rwanda-baseline-household-survey-d44p-5duj with SQL in under 60 seconds.
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, 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 (like this repository), where the author has pushed Splitgraph Images to the repository, you can "clone" and/or "checkout" the data using sgr cloneand sgr checkout.
Cloning Data
Because usaid-gov/feed-the-future-rwanda-baseline-household-survey-d44p-5duj:latest is a Splitgraph Image, you can clone the data from Spltgraph Cloud to your local engine, where you can query it like any other Postgres database, using any of your existing tools.
First, install Splitgraph if you haven't already.
Clone the metadata with sgr clone
This will be quick, and does not download the actual data.
sgr clone usaid-gov/feed-the-future-rwanda-baseline-household-survey-d44p-5dujCheckout the data
Once you've cloned the data, you need to "checkout" the tag that you want. For example, to checkout the latest tag:
sgr checkout usaid-gov/feed-the-future-rwanda-baseline-household-survey-d44p-5duj:latestThis will download all the objects for the latest tag of usaid-gov/feed-the-future-rwanda-baseline-household-survey-d44p-5duj and load them into the Splitgraph Engine. Depending on your connection speed and the size of the data, you will need to wait for the checkout to complete. Once it's complete, you will be able to query the data like you would any other Postgres database.
Alternatively, use "layered checkout" to avoid downloading all the data
The data in usaid-gov/feed-the-future-rwanda-baseline-household-survey-d44p-5duj:latest is 0 bytes. If this is too big to download all at once, or perhaps you only need to query a subset of it, you can use a layered checkout.:
sgr checkout --layered usaid-gov/feed-the-future-rwanda-baseline-household-survey-d44p-5duj:latestThis will not download all the data, but it will create a schema comprised of foreign tables, that you can query as you would any other data. Splitgraph will lazily download the required objects as you query the data. In some cases, this might be faster or more efficient than a regular checkout.
Read the layered querying documentation to learn about when and why you might want to use layered queries.
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-rwanda-baseline-household-survey-d44p-5duj is just another Postgres schema.