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 mc311_service_requests table in this repository, by referencing it like:
"montgomerycountymd-gov/mc311-service-requests-xtyh-brr2:latest"."mc311_service_requests"or in a full query, like:
SELECT
":id", -- Socrata column ID
"x_cong_memb", -- U. S. Congress Member for the location, where location is available
"sr_subtype_cd", -- Source for receiving the Service Request (examples: Web, Phone)
"x_city", -- City location for the Service Request (where available)
"sr_area", -- Area in the County Department assigned to resolve the Service Request
"created", -- Date & Time the MC311 Service Request was opened
"last_upd", -- Date & Time the MC311 Service Request record was last updated in the system
"sr_sub_area", -- Sub-Area in the County Department/Area assigned to resolve the Service Request
"closed", -- Date & Time the MC311 Service Request was closed
"number_of_days_open", -- Number of County Business days the Service Request has been opened.
"x_councilmbr", -- Montgomery County Council Member for the location, where location is available
"x_councildist", -- Montgomery County Council District, where location is available
"x_electiondist", -- Election District, where location is available
"x_zipcode", -- 5 digit postal Zip Code for the Service Request (where available)
"x_sla", -- Service Level Agreement (SLA) for the number of days expected for the attached solution to resolve the Service Request
"department", -- Code for the County Department assigned to resolve the Service Request
"sr_num", -- Service Request ID Number (unique identifier) assigned by the MC311 Call Center
"x_mdstatedist", -- Maryland State Election District number, where location is available
"sla_yes", -- Number of days to fulfill the service request is under the SLA window.
"x_state", -- State location for the Service Request
"x_congdist", -- U. S. Congressional District, where location is available
"faq_ques_text", -- Describes the solution selected to resolve the Service Request
"sla_no", -- Number of days to fulfill the service request is over the SLA window.
"sr_type", -- Type of Request - General Information or Service Request Fulfillment
"within_sla_window", -- To indicate the number of days a service request is over or under SLA as is currently measured by CountyStat.
"sr_stat_id" -- Current status (since the last daily update) of the MC311 Service Request (Closed, In Progress)
FROM
"montgomerycountymd-gov/mc311-service-requests-xtyh-brr2:latest"."mc311_service_requests"
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 montgomerycountymd-gov/mc311-service-requests-xtyh-brr2 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 montgomerycountymd-gov/mc311-service-requests-xtyh-brr2: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 montgomerycountymd-gov/mc311-service-requests-xtyh-brr2Checkout 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 montgomerycountymd-gov/mc311-service-requests-xtyh-brr2:latestThis will download all the objects for the latest tag of montgomerycountymd-gov/mc311-service-requests-xtyh-brr2 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 montgomerycountymd-gov/mc311-service-requests-xtyh-brr2: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 montgomerycountymd-gov/mc311-service-requests-xtyh-brr2: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, montgomerycountymd-gov/mc311-service-requests-xtyh-brr2 is just another Postgres schema.