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 annual_examination_schedule_of_each_fiscal_year table in this repository, by referencing it like:
"cityofnewyork-us/annual-examination-schedule-of-each-fiscal-year-4ptz-hmtc:latest"."annual_examination_schedule_of_each_fiscal_year"or in a full query, like:
SELECT
":id", -- Socrata column ID
"open_competitive_promotion", -- Open Competitive exams are open to any person who meets the minimum qualifications listed in the Notice of Examination. Promotion exams are only open to current permanent and 55-a employees in an eligible title and who meet minimum qualification requirements listed in the Notice of Examination. Qualified Incumbent Exams are open only to employees serving in the exam title and meet the eligibility requirements for the exam listed in the Notice of Examination
"application_period_start", -- The date on which candidates can begin to submit applications to take an exam. Applications are only accepted when an application period has begun.
"exam_title", -- Civil Service title of the exam being offered
"application_period_end_date", -- The date on which the application period for an exam will end. Applications for exams are not accepted after the Application Period End Date
"exam_number", -- Four-digit number assigned to each exam offered by DCAS in each Fiscal Year. Exam numbers are recycled every 10 years.
"data_current_as_of" -- This date the data are current as of
FROM
"cityofnewyork-us/annual-examination-schedule-of-each-fiscal-year-4ptz-hmtc:latest"."annual_examination_schedule_of_each_fiscal_year"
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/annual-examination-schedule-of-each-fiscal-year-4ptz-hmtc 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 cityofnewyork-us/annual-examination-schedule-of-each-fiscal-year-4ptz-hmtc: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 cityofnewyork-us/annual-examination-schedule-of-each-fiscal-year-4ptz-hmtcCheckout 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 cityofnewyork-us/annual-examination-schedule-of-each-fiscal-year-4ptz-hmtc:latestThis will download all the objects for the latest tag of cityofnewyork-us/annual-examination-schedule-of-each-fiscal-year-4ptz-hmtc 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 cityofnewyork-us/annual-examination-schedule-of-each-fiscal-year-4ptz-hmtc: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 cityofnewyork-us/annual-examination-schedule-of-each-fiscal-year-4ptz-hmtc: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, cityofnewyork-us/annual-examination-schedule-of-each-fiscal-year-4ptz-hmtc is just another Postgres schema.