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 mta_daily_ridership_data_beginning_2020
table in this repository, by referencing it like:
"ny-gov/mta-daily-ridership-data-beginning-2020-vxuj-8kew:latest"."mta_daily_ridership_data_beginning_2020"
or in a full query, like:
SELECT
":id", -- Socrata column ID
"buses_total_estimated_ridersip", -- The daily total estimated bus ridership.
"staten_island_railway_total_estimated_ridership", -- The daily total estimated SIR ridership.
"lirr_total_estimated_ridership", -- The daily total estimated LIRR ridership. Blank value indicates that the ridership data was not or is not currently available or applicable.
"access_a_ride_of_comparable_pre_pandemic_day", -- The daily total scheduled trips as a percentage of total scheduled trips on an equivalent day prior to the COVID-19 pandemic. Blank value indicates that the ridership data was not or is not currently available or applicable.
"bridges_and_tunnels_of_comparable_pre_pandemic_day", -- The daily total traffic as a percentage of total traffic on an equivalent day prior to the COVID-19 pandemic. Blank value indicates that the ridership data was not or is not currently available or applicable.
"date", -- The date of travel (MM/DD/YYYY).
"subways_total_estimated_ridership", -- The daily total estimated subway ridership.
"subways_of_comparable_pre_pandemic_day", -- The daily ridership estimate as a percentage of subway ridership on an equivalent day prior to the COVID-19 pandemic.
"buses_of_comparable_pre_pandemic_day", -- The daily ridership estimate as a percentage of bus ridership on an equivalent day prior to the COVID-19 pandemic.
"metro_north_total_estimated_ridership", -- The daily total estimated Metro-North ridership. Blank value indicates that the ridership data was not or is not currently available or applicable.
"access_a_ride_total_scheduled_trips", -- The daily total scheduled Access-A-Ride trips. Blank value indicates that the ridership data was not or is not currently available or applicable.
"bridges_and_tunnels_total_traffic", -- The daily total Bridges and Tunnels traffic. Blank value indicates that the ridership data was not or is not currently available or applicable.
"staten_island_railway_of_comparable_pre_pandemic_day", -- The daily ridership estimate as a percentage of SIR ridership on an equivalent day prior to the COVID-19 pandemic.
"lirr_of_comparable_pre_pandemic_day", -- The daily ridership estimate as a percentage of LIRR ridership on an equivalent day prior to the COVID-19 pandemic.
"metro_north_of_comparable_pre_pandemic_day" -- The daily ridership estimate as a percentage of Metro-North ridership on an equivalent day prior to the COVID-19 pandemic.
FROM
"ny-gov/mta-daily-ridership-data-beginning-2020-vxuj-8kew:latest"."mta_daily_ridership_data_beginning_2020"
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 ny-gov/mta-daily-ridership-data-beginning-2020-vxuj-8kew
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; sgr
can 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 clone
and sgr checkout
.
Cloning Data
Because ny-gov/mta-daily-ridership-data-beginning-2020-vxuj-8kew: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 ny-gov/mta-daily-ridership-data-beginning-2020-vxuj-8kew
Checkout 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 ny-gov/mta-daily-ridership-data-beginning-2020-vxuj-8kew:latest
This will download all the objects for the latest
tag of ny-gov/mta-daily-ridership-data-beginning-2020-vxuj-8kew
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 ny-gov/mta-daily-ridership-data-beginning-2020-vxuj-8kew: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 ny-gov/mta-daily-ridership-data-beginning-2020-vxuj-8kew:latest
This 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, ny-gov/mta-daily-ridership-data-beginning-2020-vxuj-8kew
is just another Postgres schema.