bts-gov/trips-by-distance-w96p-f2qv
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Query the Data Delivery Network

Query the DDN

The 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 trips_by_distance table in this repository, by referencing it like:

"bts-gov/trips-by-distance-w96p-f2qv:latest"."trips_by_distance"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "row_id", -- Unique row identifier
    "trips_5_10", -- Number of trips by residents greater than 5 miles and shorter than 10 miles (5 ≤ trip distance < 10 miles)
    "pop_not_stay_at_home", -- Number of residents not staying at home
    "trips_25_50", -- Number of trips by residents greater than 25 miles and shorter than 50 miles (25 ≤ trip distance < 50 miles)
    "county", -- County name
    "trips_1", -- Number of trips by residents shorter than one mile
    "trips_250_500", -- Number of trips by residents greater than 250 miles and shorter than 500 miles (250 ≤ trip distance < 500 miles)
    "date", -- Date
    "trips_10_25", -- Number of trips by residents greater than 10 miles and shorter than 25 miles (10 ≤ trip distance < 25 miles)
    "state_fips", -- Two-digit FIPS state code
    "trips_100_250", -- Number of trips by residents greater than 100 miles and shorter than 250 miles (100 ≤ trip distance < 250 miles)
    "state_code", -- State postal code
    "trips_50_100", -- Number of trips by residents greater than 50 miles and shorter than 100 miles (50 ≤ trip distance < 100 miles)
    "trips_500", -- Number of trips by residents greater than 500 miles (trip distance ≥ 500 miles)
    "county_fips", -- Five-digit FIPS county code
    "week",
    "month",
    "level", -- Indicates National, State, or County level metrics
    "pop_stay_at_home", -- Number of residents staying at home, i.e., persons who make no trips with a trip end more than one mile away from home
    "trips", -- Number of trips made by residents, i.e., movements that include a stay of longer than 10 minutes at an anonymized location away from home.
    "trips_1_3", -- Number of trips by residents greater than one mile and shorter than 3 miles (1 ≤ trip distance < 3 miles)
    "trips_3_5" -- Number of trips by residents greater than 3 miles and shorter than 5 miles (3 ≤ trip distance < 5 miles)
FROM
    "bts-gov/trips-by-distance-w96p-f2qv:latest"."trips_by_distance"
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 bts-gov/trips-by-distance-w96p-f2qv with SQL in under 60 seconds.

Query Your Local Engine

Install Splitgraph Locally
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 bts-gov/trips-by-distance-w96p-f2qv: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 bts-gov/trips-by-distance-w96p-f2qv

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 bts-gov/trips-by-distance-w96p-f2qv:latest

This will download all the objects for the latest tag of bts-gov/trips-by-distance-w96p-f2qv 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 bts-gov/trips-by-distance-w96p-f2qv: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 bts-gov/trips-by-distance-w96p-f2qv: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, bts-gov/trips-by-distance-w96p-f2qv is just another Postgres schema.

Related Documentation:

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