usaid-gov/feed-the-future-malawi-baseline-household-survey-xi32-ju8k
Icon for Socrata external plugin

Query the Data Delivery Network

Query the DDN

The 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_malawi_baseline_household_survey table in this repository, by referencing it like:

"usaid-gov/feed-the-future-malawi-baseline-household-survey-xi32-ju8k:latest"."feed_the_future_malawi_baseline_household_survey"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "zih_women_age_range", -- ZIH Women age range
    "zic_school_ever", -- ZIC School ever
    "d02", -- ZID Floor tp
    "f06", -- ZIF Whl day no eat freq
    "h20", -- ZIH Women diet div liver
    "d04", -- ZID Rooms num
    "h02_month", -- ZIH Women month
    "d06", -- ZID Drink water src
    "modf_missing", -- Missing all elements from F
    "h23", -- ZIH Women diet div fish
    "d03", -- ZID Ext wall tp
    "h26", -- ZIH Women diet div oil
    "h25", -- ZIH Women diet div cheese
    "urbrur", -- Urban Rural 1 urban 2 rural
    "h24", -- ZIH Women diet div beans
    "a21", -- Interview outcome derived by module C data
    "h30", -- ZIH Women diet div palm
    "f02", -- ZIF No food freq
    "d07", -- ZID Electr yn
    "d01", -- ZID Roof tp
    "d08", -- ZID Fuel src
    "c02", -- ZIC Sex
    "h22", -- ZIH Women diet div eggs
    "h28", -- ZIH Women diet div spice
    "h18", -- ZIH Women diet div mango
    "beansgrp", -- Legumes and nuts
    "f03", -- ZIF Sleep hungry yn
    "h08", -- ZIH Height
    "lfygrngrp", -- Vitamin A dark green leafy vegetables
    "c03", -- ZIC Prm resp rel
    "a02", -- ZIA Cluster cd
    "modd_missing", -- Missing all elements from D
    "pbs_id", -- PBS ID
    "zih_age_check_yn", -- ZIH Age check yn
    "f04", -- ZIF Sleep hungry freq
    "a09", -- Household type derived by module C data
    "h03", -- ZIH Women age
    "c04", -- ZIC Age
    "a06", -- Household type derived by module C data
    "f05", -- ZIF Whl day no eat yn
    "zic_edu_lvl", -- ZIC Edu lvl
    "wmwght", -- Women weight
    "h14", -- ZIH Women diet div grain
    "zic_literacy", -- ZIC Literacy
    "id_code", -- Respondent ID
    "h15", -- ZIH Women diet div pumpkin
    "h24x", -- ZIH Women diet div dry lf
    "h06", -- ZIH Cur preg
    "f01", -- ZIF No food yn
    "country", -- ZIA Country
    "grainsgrp", -- Grains roots and tubers
    "d05", -- ZID Toilet tp
    "h07", -- ZIH Weight
    "milkgrp", -- Dairy products milk yogurt cheese
    "fleshgrp", -- Flesh foods and other misc small animal protein
    "othfrtgrp", -- Other fruits and vegetables
    "organgrp", -- Organ meat
    "zic_school_cur", -- ZIC School cur
    "h19", -- ZIH Women diet div fruit
    "foodsum", -- Number of Food Groups Consumed 0 9
    "othvitagrp", -- Other Vitamin A rich vegetables and fruits
    "eggsgrp", -- Eggs
    "hhwght", -- Household weight
    "h29", -- ZIH Women diet div insect
    "h27", -- ZIH Women diet div sweets
    "a05", -- ZIG1 Sex g1
    "h17", -- ZIH Women diet div leafy
    "h21", -- ZIH Women diet div meat
    "h02_year", -- ZIH Women year
    "h16" -- ZIH Women diet div potato
FROM
    "usaid-gov/feed-the-future-malawi-baseline-household-survey-xi32-ju8k:latest"."feed_the_future_malawi_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-malawi-baseline-household-survey-xi32-ju8k 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-malawi-baseline-household-survey-xi32-ju8k: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

Install Splitgraph Locally
bash -c "$(curl -sL https://github.com/splitgraph/splitgraph/releases/latest/download/install.sh)"
 

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-malawi-baseline-household-survey-xi32-ju8k" \
  --handler-options '{
    "domain": "data.usaid.gov",
    "tables": {
        "feed_the_future_malawi_baseline_household_survey": "xi32-ju8k"
    }
}'

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-malawi-baseline-household-survey-xi32-ju8k is just another Postgres schema.

Related Documentation: