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 linknyc_new_site_permit_applications table in this repository, by referencing it like:
"cityofnewyork-us/linknyc-new-site-permit-applications-xp25-gxux:latest"."linknyc_new_site_permit_applications"or in a full query, like:
SELECT
":id", -- Socrata column ID
"legacy_id", -- The ID number for the LinkNYC kiosk
"bbl", -- Every real estate property is identified by a set of 3 numbers for taxes, zoning, construction, and other purposes.
"bin", -- Every real estate property has an assigned 7-digit number issued by the Department of City Planning.
"neighborhood_tabulation_area_nta", -- Neighborhood identifiers to differentiate NYC's five boroughs
"bid", -- Is the LinkNYC Kiosk located in a Business Improvement District (BID)?
"latitude", -- Points that fall North or South of the Equator, expressed in degrees.
"gf_cb_comment_period_ends_a", -- Community Board Comment Period Ends on this date
"postcode", -- Five (5) digit postal code assigned by the United States Postal Service.
"longitude", -- Points that fall East or West of the Prime Meridian, expressed in degrees.
"site_id", -- The unique ID for each LinkNYC kiosk site in the format: Borough-Community Board-Payphone ID (e.g., mn-03-123265)
"street_address", -- The name of the street that a site is located on.
"installation_status_", -- Indicates the current status, including planning for utility connections, DOT permitting, and construction.
"council_district", -- Council District is the lawmaking body of the City of New York. There are 51 districts throughout NYC's five boroughs.
"cross_street_1", -- One of the closest streets to a potential LinkNYC site.
"final_submission_a_", -- Submission Date from vendor for review.
":@computed_region_efsh_h5xi", -- This column was automatically created in order to record in what polygon from the dataset 'Zip Codes' (efsh-h5xi) the point in column 'location2' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
":@computed_region_f5dn_yrer", -- This column was automatically created in order to record in what polygon from the dataset 'Community Districts' (f5dn-yrer) the point in column 'location2' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
":@computed_region_yeji_bk3q", -- This column was automatically created in order to record in what polygon from the dataset 'Borough Boundaries' (yeji-bk3q) the point in column 'location2' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
":@computed_region_92fq_4b7q", -- This column was automatically created in order to record in what polygon from the dataset 'City Council Districts' (92fq-4b7q) the point in column 'location2' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
":@computed_region_sbqj_enih", -- This column was automatically created in order to record in what polygon from the dataset 'Police Precincts' (sbqj-enih) the point in column 'location2' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
"gf_permit_appl_id", -- The new site permit application number.
"planned_kiosk_type", -- Indicates style of kiosk (LINK1.0, LINK5G, and LINK5G_NoAd) or public pay phone.
"ixn_code", -- The direction the Kiosk is facing.
"greenfield_in_bid_location", -- Is the LinkNYC Kiosk located in a Business Improvement District (BID)?
"location2",
"gf_doitt_submitted_to_cb_a", -- Information Submitted to Community Board on this date
"ppt_id", -- An 6-digit ID generated by the database - a unique number for each LINK and Pay Public Telephone (PPT)
"zoningnumb", -- The type of zoning a kiosk is located in, displayed by its first letter followed by its zone.
"historic_district", -- Is the LinkNYC Kiosk located in a historic district?
"historic_district_name", -- Name of historic district determined by the Landmarks Preservation Commission (LPC).
"census_tract", -- Census Tract (CT) - Permanent statistical subdivisions to provide a stable set of geographic units for the presentation of statistical data
"borough", -- The New York City borough where the hotspots are located.
"cb", -- Community Board: An appointed advisory group from a variety of districts throughout NYC's five boroughs. They deal with issues such as zoning, land usage, and any other matter related to the quality of life of their residents.
"cross_street_2" -- One of the closest streets to a potential LinkNYC site.
FROM
"cityofnewyork-us/linknyc-new-site-permit-applications-xp25-gxux:latest"."linknyc_new_site_permit_applications"
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/linknyc-new-site-permit-applications-xp25-gxux 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/linknyc-new-site-permit-applications-xp25-gxux: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/linknyc-new-site-permit-applications-xp25-gxuxCheckout 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/linknyc-new-site-permit-applications-xp25-gxux:latestThis will download all the objects for the latest tag of cityofnewyork-us/linknyc-new-site-permit-applications-xp25-gxux 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/linknyc-new-site-permit-applications-xp25-gxux: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/linknyc-new-site-permit-applications-xp25-gxux: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/linknyc-new-site-permit-applications-xp25-gxux is just another Postgres schema.