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

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-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.