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 business_services_purchases table in this repository, by referencing it like:
"citydata-mesaaz-gov/business-services-purchases-u5x3-dvhs:latest"."business_services_purchases"or in a full query, like:
SELECT
":id", -- Socrata column ID
"dept_ytd_purchase_mesa", -- Field used for PM calculation that shows the department's monthly purchase in Mesa total for the fiscal year to date
"dept_ytd_small_purchase_total", -- Field used for PM calculation that shows the department's monthly small purchase total for the fiscal year to date
"award_document_code", -- Code that identifies the type of purchasing award document (i.e. PO, DO, CT)
"concatenated_award_document", -- Concatenated field that includes the Document Code, Department Code and Document ID number of the Purchasing award document from the document header
"award_department_code", -- Code that identifies the department code of the purchasing award document
"award_department_name", -- Code that identifies the department name of the purchasing award document
"award_document_id", -- Document ID number of the Purchasing award document from the document header
"award_document_version_number", -- Version number of the purchasing award document from the document header (we only look at version 1 so the document isn’t included multiple times)
"award_document_procurement", -- Code for the procurement type used on the award document (we only look at Purchasing Procurement Types 1, 2, 3, 4, 5, 6, and 7)
"award_document_procurement_1", -- Name for the procurement type used on the award document
"award_header_reporting_code", -- Field on the header of the purchasing award document that indicates type of purchase (we exclude code 800 and 810 as those are Warehouse inventory adjustments)
"award_header_reporting_code_1", -- Field on the header of the purchasing award document that indicates the name of the type of purchase
"award_header_fiscal_year", -- Fiscal year on the header of the purchasing award document
"award_header_accounting_period", -- Accounting period on the header of the purchasing award document
"award_header_accounting_12", -- Accounting period on the header of the purchasing award document, with Period 13 listed as Period 12
"accounting_period_date_format", -- Date format of the Award Header Fiscal Year and Accounting Period
"award_document_name", -- Name of the purchasing award document as shown on the header
"dept_ytd_small_purchase_total_100k", -- Dept YTD Small Purchase Total 100K
"dept_ytd_small_purchase_mesa_100k", -- Dept YTD Small Purchase Mesa 100K
"award_header_citied_authority", -- Code indicating how the award was authorized (Council, administratively, etc.)
"vendor_city", -- Field from vendor address record that indicated the city the vendor is in (for the vendor of record on the purchasing document)
"dept_ytd_purchase_az_100k", -- Dept YTD Purchase AZ 100K
"dept_ytd_purchase_mesa_100k", -- Dept YTD Purchase Mesa 100K
"dept_ytd_purchase_az", -- Field used for PM calculation that shows the department's monthly purchase in Arizona total for the fiscal year to date
"dept_ytd_purchase_total", -- Field used for PM calculation that shows the department's monthly purchase total for the fiscal year to date
"vendor_state", -- Field from the vendor address record that indicates the state the vendor is in (for the vendor of record on the Purchasing document)
"dept_ytd_small_purchase_az_100k", -- Dept YTD Small Purchase AZ 100K
"purchase_under_100000_flag", -- Purchase Under 100000 Flag
"dept_ytd_purchase_total_100k", -- Dept YTD Purchase Total 100K
"dept_ytd_small_purchase_mesa", -- Field used for PM calculation that shows the department's monthly small purchase in Mesa total for the fiscal year to date
"purchase_under_25000_flag", -- Field which indicates if the header of the purchasing award document was greater than or equal to $25,000
"dept_ytd_small_purchase_az", -- Field used for PM calculation that shows the department's monthly small purchase in Arizona total for the fiscal year to date
"row_number", -- Field used for PM calculation to indicate the row number of the purchase over department and accounting period
"award_header_actual_amount" -- Amount of the award as shown on the header of the purchasing award document
FROM
"citydata-mesaaz-gov/business-services-purchases-u5x3-dvhs:latest"."business_services_purchases"
LIMIT 100;Connecting to the DDN is easy. All you need is an existing SQL client that can connect to Postgres. As long as you have a SQL client ready, you'll be able to query citydata-mesaaz-gov/business-services-purchases-u5x3-dvhs with SQL in under 60 seconds.
Query Your Local Engine
bash -c "$(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 citydata-mesaaz-gov/business-services-purchases-u5x3-dvhs: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 citydata-mesaaz-gov/business-services-purchases-u5x3-dvhsCheckout 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 citydata-mesaaz-gov/business-services-purchases-u5x3-dvhs:latestThis will download all the objects for the latest tag of citydata-mesaaz-gov/business-services-purchases-u5x3-dvhs 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 citydata-mesaaz-gov/business-services-purchases-u5x3-dvhs: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 citydata-mesaaz-gov/business-services-purchases-u5x3-dvhs: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, citydata-mesaaz-gov/business-services-purchases-u5x3-dvhs is just another Postgres schema.