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 dohmh_menustat_historical table in this repository, by referencing it like:
"cityofnewyork-us/dohmh-menustat-historical-qgc5-ecnb:latest"."dohmh_menustat_historical"or in a full query, like:
SELECT
":id", -- Socrata column ID
"cholesterol",
"limited_time_offer", -- Coded as ‘1’ if the restaurant describes the item as a limited time offer or seasonal.
"serving_size", -- Serving size in grams or ounces when reported by restaurants
"total_fat_100g", -- Nutrient density is calculated by standardizing the serving size to 100 g when serving size and nutrient information is reported by the restaurant.
"food_category", -- Each menu item is coded into a mutually exclusive food category
"dietary_fiber_text", -- Nutrient reported in a non-specific value
"kids_meal", -- Coded as ‘1’ if the restaurant describes the item as being for kids. Items described as for kids and adults (e.g. kids fries = small fries) says ‘Kids and Adults Menu’ in the Item Description.
"sodium_text", -- Nutrient reported in a non-specific value
"trans_fat_text", -- Nutrient reported in a non-specific value
"carbohydrates_100g", -- Nutrient density is calculated by standardizing the serving size to 100 g when serving size and nutrient information is reported by the restaurant.
"sodium",
"sugar_text", -- Nutrient reported in a non-specific value
"saturated_fat_100g", -- Nutrient density is calculated by standardizing the serving size to 100 g when serving size and nutrient information is reported by the restaurant.
"restaurant", -- Restaurant name
"dietary_fiber",
"potassium_100g", -- Nutrient density is calculated by standardizing the serving size to 100 g when serving size and nutrient information is reported by the restaurant.
"menu_item_id", -- A unique identifier for each item. When the same item is served by a restaurant over multiple years it has an identical Menu Item ID to allow for tracking.
"calories",
"protein_text", -- Nutrient reported in a non-specific value
"shareable", -- Coded as ‘1’ if the restaurant describes the item as shareable and the nutrition cannot be divided in to a single serving (e.g. carafes, whole pies, quarts of ice cream, 2 liter drinks).
"serving_size_unit", -- Serving size in grams or ounces when reported by restaurants. For a limited number of items, serving size was converted to grams for foods and to ounces for beverages; these cases are marked by an asterisk.
"sugar",
"trans_fat_100g", -- Nutrient density is calculated by standardizing the serving size to 100 g when serving size and nutrient information is reported by the restaurant.
"saturated_fat",
"total_fat_text", -- Nutrient reported in a non-specific value
"protein",
"serving_size_text", -- Serving size reported in a non-specific value
"potassium",
"sugar_100g", -- Nutrient density is calculated by standardizing the serving size to 100 g when serving size and nutrient information is reported by the restaurant.
"carbohydrates",
"cholesterol_text", -- Nutrient reported in a non-specific value
"protein_100g", -- Nutrient density is calculated by standardizing the serving size to 100 g when serving size and nutrient information is reported by the restaurant.
"calories_100g", -- Nutrient density is calculated by standardizing the serving size to 100 g when serving size and nutrient information is reported by the restaurant.
"potassium_text", -- Nutrient reported in a non-specific value
"trans_fat",
"serving_size_household", -- Household metric reported to describe serving size
"cholesterol_100g", -- Nutrient density is calculated by standardizing the serving size to 100 g when serving size and nutrient information is reported by the restaurant.
"saturated_fat_text", -- Nutrient reported in a non-specific value
"item_description", -- Menu item name with additional menu information (e.g. menu item components)
"restaurant_item_name", -- Concatenated variable of Restaurant and Item Name
"restaurant_id", -- Unique Identifier for Restaurant
"calories_text", -- Nutrient reported in a non-specific value
"sodium_100g", -- Nutrient density is calculated by standardizing the serving size to 100 g when serving size and nutrient information is reported by the restaurant.
"regional", -- Coded as ‘1’ if the restaurant describes the item as regional (e.g. Midwest states only or at participating locations only).
"total_fat",
"year", -- MenuStat data are collected annually in January.
"carbohydrates_text", -- Nutrient reported in a non-specific value
"item_name", -- Menu item name
"dietary_fiber_100g" -- Nutrient density is calculated by standardizing the serving size to 100 g when serving size and nutrient information is reported by the restaurant.
FROM
"cityofnewyork-us/dohmh-menustat-historical-qgc5-ecnb:latest"."dohmh_menustat_historical"
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 cityofnewyork-us/dohmh-menustat-historical-qgc5-ecnb with SQL in under 60 seconds.
This repository is an "external" repository. That means it's hosted elsewhere, in this case at data.cityofnewyork.us. When you querycityofnewyork-us/dohmh-menustat-historical-qgc5-ecnb: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
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.cityofnewyork.us, 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 \
"cityofnewyork-us/dohmh-menustat-historical-qgc5-ecnb" \
--handler-options '{
"domain": "data.cityofnewyork.us",
"tables": {
"dohmh_menustat_historical": "qgc5-ecnb"
}
}'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, cityofnewyork-us/dohmh-menustat-historical-qgc5-ecnb is just another Postgres schema.