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 baseline_study_of_food_for_peace_title_ii table in this repository, by referencing it like:
"datahub-usaid-gov/baseline-study-of-food-for-peace-title-ii-hbgf-57ng:latest"."baseline_study_of_food_for_peace_title_ii"or in a full query, like:
SELECT
":id", -- Socrata column ID
"pvo", -- PVO
"reg", -- A05 REGION
"g65_6", -- G65 What advice extension services on agriculture or production did you have during the last season
"trade", -- Have you exchanged or sold your product in bulk retailing or exporting
"g65_10", -- G65 What advice extension services on agriculture or production did you have during the last season
"cluster", -- Cluster
"vn", -- A02 VILLAGE NUMBER
"g66_5", -- G66 During the last season who provided you with advice extension services about agriculture or production
"strata", -- Strata
"member_id", -- Household member ID for merging with other modules
"fmwt", -- Sampling weight for farmers
"sustainable_livestock_cat", -- Farmers who used at least 2 sustainable livestock practices and or technologies in the past 12 months
"sustainable_agriculture_cat", -- Farmers who used at least 3 sustainable agriculture practices in the past 12 months
"sustainable_nrm_cat", -- Farmers who used at least 2 sustainable NRM practices and or technologies in the past 12 months
"improved_storage", -- Used improved storage practices past 12 months
"g65_9", -- G65 What advice extension services on agriculture or production did you have during the last season
"g69", -- G69 Did you have agricultural insurance in the PAST 12 MONTHS
"records", -- Do you keep records of your production
"sort_crops", -- Before selling your products do you sort them out
"b04", -- B04 Sex
"g65_8", -- G65 What advice extension services on agriculture or production did you have during the last season
"sustainable_crops_cat_alt",
"g65_5", -- G65 What advice extension services on agriculture or production did you have during the last season
"g65_3", -- G65 What advice extension services on agriculture or production did you have during the last season
"id",
"value_chain_any", -- Farmers who practiced any of the value chain activities promoted by the project in the past 12 months
"g66_2", -- G66 During the last season who provided you with advice extension services about agriculture or production
"g65_1", -- G65 What advice extension services on agriculture or production did you have during the last season
"g66_9", -- G66 During the last season who provided you with advice extension services about agriculture or production
"g66_7", -- G66 During the last season who provided you with advice extension services about agriculture or production
"g68", -- G68 Did you save any cash money saved for later use in the PAST 12 MONTHS
"sustainable_crops_alt",
"coop", -- Do you participate in an association or informal producers cooperative
"g66_10", -- G66 During the last season who provided you with advice extension services about agriculture or production
"g66_6", -- G66 During the last season who provided you with advice extension services about agriculture or production
"calculation", -- Do you calculate the costs of production for the market
"improved_macro", -- Used at least one improved variety of macro nutrient dense foods in the most recent season
"g64", -- G64 Have you received advice extension services on agricultural questions during the last season
"sustainable_crops_cat", -- Farmers who used at least 2 sustainable agriculture crop practices and or technologies in the past 12 months
"g66_1", -- G66 During the last season who provided you with advice extension services about agriculture or production
"g66_4", -- G66 During the last season who provided you with advice extension services about agriculture or production
"g66_8", -- G66 During the last season who provided you with advice extension services about agriculture or production
"g66_3", -- G66 During the last season who provided you with advice extension services about agriculture or production
"valuechain_none", -- No activities
"wholesale_transport", -- Before selling your products do you transport them in bulk
"rank_crops", -- Before selling your products do you rank them
"sustainable_agriculture", -- Number of sustainable agriculture practices in the past 12 months
"g63_10", -- G63 Where do you sell your products
"g65_7", -- G65 What advice extension services on agriculture or production did you have during the last season
"g65_4", -- G65 What advice extension services on agriculture or production did you have during the last season
"g67", -- G67 Did you receive agricultural credit in cash or in kind in the PAST 12 MONTHS
"g65_2", -- G65 What advice extension services on agriculture or production did you have during the last season
"plans", -- Do you have a plan to produce and sell your products
"financial_services", -- Farmers who used any financial services in the past 12 months
"savings", -- Saved money in the last 12 months
"hh", -- A01 HOUSEHOLD NUMBER
"credit", -- Obtained an agricultural credit in the last 12 months
"insurance" -- Had agricultural insurance in the last 12 months
FROM
"datahub-usaid-gov/baseline-study-of-food-for-peace-title-ii-hbgf-57ng:latest"."baseline_study_of_food_for_peace_title_ii"
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/baseline-study-of-food-for-peace-title-ii-hbgf-57ng 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 datahub-usaid-gov/baseline-study-of-food-for-peace-title-ii-hbgf-57ng: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/baseline-study-of-food-for-peace-title-ii-hbgf-57ngCheckout 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/baseline-study-of-food-for-peace-title-ii-hbgf-57ng:latestThis will download all the objects for the latest tag of datahub-usaid-gov/baseline-study-of-food-for-peace-title-ii-hbgf-57ng 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/baseline-study-of-food-for-peace-title-ii-hbgf-57ng: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/baseline-study-of-food-for-peace-title-ii-hbgf-57ng: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, datahub-usaid-gov/baseline-study-of-food-for-peace-title-ii-hbgf-57ng is just another Postgres schema.