datahub-usaid-gov/feed-the-future-malawi-interim-survey-in-the-zone-keue-3ma6
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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_interim_survey_in_the_zone table in this repository, by referencing it like:

"datahub-usaid-gov/feed-the-future-malawi-interim-survey-in-the-zone-keue-3ma6:latest"."feed_the_future_malawi_interim_survey_in_the_zone"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "s_hh_wt3", -- Household weights, adjusted for non-response, subgroup 3
    "cluster", -- Cluster number
    "idcode", -- Woman s ID code
    "c06_unit", -- How long has it been since NAME spent the night in this household? Unit
    "c03", -- What is the NAME s relationship to the primary male decisionmaker? If not primary male decisionmaker, what is the NAME s relationship to the female decisionmaker?
    "sex", -- HH members sex, corrected for ineligibilities discovered in modules G, H, and I.
    "strata3", -- Stratification for subgroup 3
    "primedec", -- This variable identifies the primary male and female decisionmaker. 1 indicates that the individual is a primary decisionmaker.
    "c07", -- Woman aged 15-49
    "project", -- Identifies whether the record is used to report on Feed the Future (FTF), Food for Peace (FFP), Catholic Relief Services (CRS), or Project Concern International (PCI) programming. Due to coordinated survey collection, the same record may be used to evalu
    "ghht", -- Derived gendered household type
    "achieveprimary", -- This measure is an indicator that a person has achieved a primary level of education or higher.
    "literate", -- This variable is a recode of C12 where a 1 indicates that a person can read and write (C12 code 4). All other non-null values are coded as 0. Null values in C12 are missing on this measure.
    "c02", -- What is NAME s sex?
    "subgroup3", -- The 7-district FTF FEEDBACK ZOI which will include district level data from rural areas only of Michinji, Lilongwe, Dedza, Mangochi, Ntcheu, Balaka, Machinga.
    "c08", -- Child aged 0-5
    "urbrur", -- Location type (urban rural)
    "c05", -- Did NAME stay here last night?
    "survey", -- Two surveys were administered. This variable identifies whether the survey was the Interim Feed the Future survey or the Baseline Food for Peace survey.
    "c04", -- What is the NAME s age, in years?
    "pbs_id", -- Administrative variable for identifying households
    "notmember", -- Is this member considered part of the household
    "agecat", -- This variable is a recode of the AGE variable into five year age categories.
    "country", -- These data were collected in Malawi
    "today", -- The day of interview as a string variable, MM-DD-YYYY
    "c06_time", -- How long has it been since NAME spent the night in this household? Length of time
    "attendschool", -- This measure is a recode of C10. A value of 1 indicates that the individual is currently attending school. A value of 0 indicates that a person is not currently attending school. Those who have never attended school, as indicated in C09, are also coded a
    "educat", -- This variable is a recode of C11, i.e. the highest level of education attained. C11 is condensed into four categories, and the cut offs may differ across countries.
    "c01a", -- Who would you say is the primary male decisionmaker in this household? This person should be 18 years old or older. This variable is coded such that 1 indicates there is a primary male adult decisionmaker in the household, and 2 if there is not a primary
    "c11", -- What is the highest grade of education completed by NAME ?
    "c09", -- Has NAME ever attended school?
    "age", -- HH members age, corrected for ineligibilities discovered in modules G, H, and I
    "c01b", -- Who would you say is the primary female decisionmaker in this household? This person should be 18 years old or older. This variable is coded such that 1 indicates there is a primary female adult decisionmaker in the household, and 2 if there is not a pri
    "c12", -- Can NAME read and write?
    "zoi", -- Was the data collected by Westat or ICF?
    "c10" -- Is NAME currently attending school?
FROM
    "datahub-usaid-gov/feed-the-future-malawi-interim-survey-in-the-zone-keue-3ma6:latest"."feed_the_future_malawi_interim_survey_in_the_zone"
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 datahub-usaid-gov/feed-the-future-malawi-interim-survey-in-the-zone-keue-3ma6 with SQL in under 60 seconds.

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, 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 datahub-usaid-gov/feed-the-future-malawi-interim-survey-in-the-zone-keue-3ma6: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 datahub-usaid-gov/feed-the-future-malawi-interim-survey-in-the-zone-keue-3ma6

Checkout 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 datahub-usaid-gov/feed-the-future-malawi-interim-survey-in-the-zone-keue-3ma6:latest

This will download all the objects for the latest tag of datahub-usaid-gov/feed-the-future-malawi-interim-survey-in-the-zone-keue-3ma6 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 datahub-usaid-gov/feed-the-future-malawi-interim-survey-in-the-zone-keue-3ma6: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 datahub-usaid-gov/feed-the-future-malawi-interim-survey-in-the-zone-keue-3ma6:latest

This 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, datahub-usaid-gov/feed-the-future-malawi-interim-survey-in-the-zone-keue-3ma6 is just another Postgres schema.

Related Documentation:

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