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 roadway_markings_contractor_work_orders table in this repository, by referencing it like:
"datahub-austintexas-gov/roadway-markings-contractor-work-orders-5dex-63ir:latest"."roadway_markings_contractor_work_orders"or in a full query, like:
SELECT
":id", -- Socrata column ID
"from_street", -- The intersecting from street location.
"road_class", -- The road class ID of the work order associated to the street segment IDs
"contractor_submitted_date", -- The datetime the work order status was submitted by contractor
"street_display_name", -- The main street of the work order.
"gis_id", -- The GIS ID.
"work_authorization_number", -- The work authorization number.
"modified_date", -- The datetime the work order record was last modified.
"created_date", -- The datetime the work order record was created.
"work_groups", -- The list of work groups associated to this work order.
"street_segment_ids", -- The list of geospatial segment IDs associated to this work order.
"atd_issued_date", -- The datetime the work order was issued.
"assigned_to", -- The work assigned to.
"sum_segment_miles", -- The total linear centerline miles calculated by the sum of the street segments in this work order.
"work_status", -- The status of work as in-progress or complete.
"count_inspections", -- Numerical count of inspections associated to the work order
"count_comments", -- Numerical count of comments associated to the work order
"parent_wo", -- The parent work order.
"to_street", -- The intersecting to street location.
"assigned_contractor", -- The contractor group assigned to the work order.
"parent_wo_field", -- The parent work order.
"work_order_id", -- The work order ID
"primary_parent_wo", -- The primary parent work order this may be associated to.
"instruction_comments", -- The instructions and comments in the work order.
"area", -- The work area of the work order.
"follow_up_instructions", -- The follow-up instructions in the work order after inspection.
"count_attachments", -- Numerical count of attachments associated to the work order
"gis_qa", -- Whether GIS QA has been done on this work order record.
"recordid", -- The unique record ID.
"work_order_status", -- The status of the work order.
"contractor_submitted_by", -- The group the work order status was submitted by
"count_work_log" -- Numerical count of work log records associated to the work order
FROM
"datahub-austintexas-gov/roadway-markings-contractor-work-orders-5dex-63ir:latest"."roadway_markings_contractor_work_orders"
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-austintexas-gov/roadway-markings-contractor-work-orders-5dex-63ir 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-austintexas-gov/roadway-markings-contractor-work-orders-5dex-63ir: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-austintexas-gov/roadway-markings-contractor-work-orders-5dex-63irCheckout 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-austintexas-gov/roadway-markings-contractor-work-orders-5dex-63ir:latestThis will download all the objects for the latest tag of datahub-austintexas-gov/roadway-markings-contractor-work-orders-5dex-63ir 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-austintexas-gov/roadway-markings-contractor-work-orders-5dex-63ir: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-austintexas-gov/roadway-markings-contractor-work-orders-5dex-63ir: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-austintexas-gov/roadway-markings-contractor-work-orders-5dex-63ir is just another Postgres schema.