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 lobbying_disclosure_data_2017_state
table in this repository, by referencing it like:
"pa-gov/lobbying-disclosure-data-2017-state-wbm6-mh8t:latest"."lobbying_disclosure_data_2017_state"
or in a full query, like:
SELECT
":id", -- Socrata column ID
"registration_location_city",
"registration_location_address",
"registration_location_zip",
"registration_location_state",
"registration_location", -- Location for the registered group.
"registration_zip", -- The zip code at which the entity is registered.
"registration_state", -- The state at which the entity is registered.
"registration_city", -- The city at which the entity is registered.
"registration_address", -- The address at which the entity is registered.
"total_costs", -- The total cost of direct and indirect expenses.
"total_indirect_cost", -- This is the expense of any effort, whether written, oral or by any other medium, to encourage others, including the general public, to take action to directly influence legislation or administrative action. For example, this would include letter writing campaigns, mailing, telephone banks, print media, etc.
"total_direct_costs", -- This is the expense of any effort, whether written, oral or by any other medium, made by a lobbyist or a principal, directed to a state official or employee. For example, this would include the cost of meetings, letters, phone calls with state officials or legislators.
"quarter_of_expense", -- The quarter in which the expense occurred.
"date_of_expense", -- The date on which the expense report was submitted.
"subject", -- The type of lobbying expense or business being reported.
"registration_type", -- The capacity or role in which the entity will be engaging in lobbying activity.
"registration_name", -- The name of the entity registering with the Dept. of State for lobbying purposes.
"registration_number", -- The number the Dept. of State assigns once the entity registers.
":@computed_region_amqz_jbr4",
":@computed_region_rayf_jjgk",
":@computed_region_d3gw_znnf",
":@computed_region_nmsq_hqvv",
":@computed_region_r6rf_p9et"
FROM
"pa-gov/lobbying-disclosure-data-2017-state-wbm6-mh8t:latest"."lobbying_disclosure_data_2017_state"
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 pa-gov/lobbying-disclosure-data-2017-state-wbm6-mh8t
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 pa-gov/lobbying-disclosure-data-2017-state-wbm6-mh8t: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 pa-gov/lobbying-disclosure-data-2017-state-wbm6-mh8t
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 pa-gov/lobbying-disclosure-data-2017-state-wbm6-mh8t:latest
This will download all the objects for the latest
tag of pa-gov/lobbying-disclosure-data-2017-state-wbm6-mh8t
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 pa-gov/lobbying-disclosure-data-2017-state-wbm6-mh8t: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 pa-gov/lobbying-disclosure-data-2017-state-wbm6-mh8t: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, pa-gov/lobbying-disclosure-data-2017-state-wbm6-mh8t
is just another Postgres schema.