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 wdfwcreel_analysis_interview table in this repository, by referencing it like:
"wa-gov/wdfwcreel-analysis-interview-rpax-ahqm:latest"."wdfwcreel_analysis_interview"or in a full query, like:
SELECT
":id", -- Socrata column ID
"survey_type", -- Defines if the location is used as an index or census
"p_census_bank", -- The asssumed proportion of bank anglers in a particular section that are surveyed during a census effort count
"p_census_boat", -- The asssumed proportion of bank anglers in a particular section that are surveyed during a census effort count
"trip_guided", -- Indicator if the angling trip was guided
"water_body", -- Waterbody where angling party fished
"indirect_census_bank", -- The assumed spatial expansion of bank anglers in a particular section used when census count data are unavailable
"location_season_name", -- Optional name for location specific to the fishery
"fishing_end_time", -- Time the angling group stopped fishing
"direct_census_bank", -- The assumed spatial expansion of boat anglers in a particular section used when census count data are unavailable
"pole_count", -- Count of poles used simultaneously by interview party
"previously_interviewed", -- Flag to indicate if the angling party was previously interviewed that day
"interview_location", -- Location where the interview occurred
"event_date", -- Date interview was conducted
"fishing_start_time", -- Time the angling group began fishing
"modified_datetime", -- Date record was modified
"created_datetime", -- Date record was created
"creel_event_id", -- Primary key id value for record in creel_event table
"project_name", -- Data collection project name
"crc_area", -- Catch record card area
"fishery_name", -- Name of fishery being monitored
"state_residence", -- Primary residence state of angling party
"vehicle_count", -- Count of vehicles associated with angling party
"angler_type", -- Categorical classification of angler to bank or boat used by some projects
"interview_id", -- Primary key id value for record in interview table
"total_group_count", -- Total count of people in the interview party
"boat_type", -- Type of boat used if applicable
"interview_number", -- Interview number
"boat_used", -- Indicator if the party used a boat or other watercraft
"trip_status", -- Defines if the angling trip was complete or still in progress when the party was interviewed
"angler_count", -- Count of people angling in the interview party
"location_type", -- Defines if the location is a discrete site or a broader section
"fishing_location", -- Location where the angling party primarily fished
"zip_code", -- Zip code(s) of angling party members
"fish_from_boat", -- Indicator if the party primarily fished out of a boat or watercraft
"trailer_count", -- Count of trailers associated with angling party
"location_id", -- Primary key id value for the fishing location if present, otherwise the id value for the interview location
"comment_txt", -- Comments pertaining to the interview
"target_species", -- Species the angling group was targeting
"section_num", -- Section number assigned to survey location
"interview_time", -- Time the angling group was interviewed
"surveyor_num" -- Survey number assigned to each creel survey location
FROM
"wa-gov/wdfwcreel-analysis-interview-rpax-ahqm:latest"."wdfwcreel_analysis_interview"
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 wa-gov/wdfwcreel-analysis-interview-rpax-ahqm 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 wa-gov/wdfwcreel-analysis-interview-rpax-ahqm: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 wa-gov/wdfwcreel-analysis-interview-rpax-ahqmCheckout 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 wa-gov/wdfwcreel-analysis-interview-rpax-ahqm:latestThis will download all the objects for the latest tag of wa-gov/wdfwcreel-analysis-interview-rpax-ahqm 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 wa-gov/wdfwcreel-analysis-interview-rpax-ahqm: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 wa-gov/wdfwcreel-analysis-interview-rpax-ahqm: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, wa-gov/wdfwcreel-analysis-interview-rpax-ahqm is just another Postgres schema.