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 individual_landmark_and_historic_district_building table in this repository, by referencing it like:
"cityofnewyork-us/individual-landmark-and-historic-district-building-gpmc-yuvp:latest"."individual_landmark_and_historic_district_building"or in a full query, like:
SELECT
":id", -- Socrata column ID
"style_prim", -- Primary architectural style as listed in the designation report building description. If this information was not included in the designation report, the field is represented as 'Not determined'.
"notes", -- Notes field used to enter additional or clarifying information about the building or structure's history, design or alterations. When a substantial change has taken place after designation, such as the construction of a new building on a vacant lot, that information is included in the “notes,” but the top level information from the designation report is still included in the fields.
"build_oth", -- Secondary building type if the building's use or purpose has changed over time. For example, If a building was built as a warehouse but was converted to apartments its secondary type would be listed as an apartment building.
"date_combo", -- Combination of both the date low and date high fields, e.g. 1887 - 1880. If construction was completed within one year the Date_Combo field is represented by a single year, e.g. 1887. If the Circa flag field is checked as one, the information in the Date_Combo field will have a "c." preceding it. If the designation report gives vague age information the Date_Combo field may be represented as "early 18th century" or "1960s". If the original dates of construction are not included the designation report, the field is represented as 'Not determined'.
"date_high", -- The high end of the date range for the original date(s) of construction in the designation report. E.g. if the date range is 1887 – 1889 this field would be 1889.
"date_low", -- The low end of the date range for the original date(s) of construction in the designation report. E.g. if the date range is 1887 – 1889 this field would be 1887.
"alt_arch_2", -- Architect or builder responsible for a second (or third) significant alteration represented by field Alt_Date_2
"sc_flag",
"circa", -- This is a yes / no field that represents whether a building’s construction date is identified as being circa. (1 = circa date, 0 = non-circa date )
"bin", -- Department of Buildings “Building Identification Number;” Note: numbers in this field are not auto-updated and so some may be outdated; BINs here are derived using building footprint GIS shapefiles from the NYC Department of Information Technology and Telecommunication (DoITT) (2007-2009); because this file contains both building and non-building landmarks (such as monuments or vacant lots), some records display “dummy” BIN numbers; the following BIN #s serve only as “dummy” BIN #s: 1000000, 2000000, 3000000, 4000000, 5000000
"bbl", -- Concatenation of the borough code (1=MN, 2=BX,3=BK,4=QN,5=SI), the five digit tax map block and four digit tax map lot numbers (ex. Manhattan Tax Map Block 123 Lot 45 would appear as 1001230045); Note: numbers in this field are not auto-updated and so some may be outdated; because this file contains both building and non-building landmarks (such as monuments or vacant lots) as well as some landmarks not located on tax map lots (such as bridges), some records display “dummy” BBLs; the following BBLs serve only as “dummy” BBLs: 1000000000, 2000000000, 3000000000, 4000000000, 5000000000
"des_addres", -- The address of the building or structure as written in the designation report.
"shape_area",
"mat_other", -- Additional field for building material description.
"build_type", -- The original type of building or structure as designed or built. If this information was not included in the designation report, is not known the field is represented as 'Not determined'.
"mat_four", -- Quaternary building material as listed in the designation report building description.
"use_other", -- Secondary use if a change has occurred over time. For example, If a building was built as a carriage house but was converted to a residence its secondary use would be listed as residential.
"lot", -- The four digit tax map lot number, without leading zeros (ex. Lot 0456 appears as 456)
"shape_leng",
"arch_build", -- This field records the original architect or builder listed in the designation report. If only builder information was provided in the designation report the individual's name will be followed by builder in brackets. E.g. (builder). If this information is not included in the designation report, the field is represented as 'Not determined'.
"mat_third", -- Tertiary building material as listed in the designation report building description.
"own_devel", -- This field records the building or structure's original owner or developer from the designation report. If this information is not included in the designation report, the field is represented as 'Not determined'.
"use_orig", -- The original use of the building or structure as designed or built. If this information was not included in the designation report, the field is represented as 'Not determined'.
"bbl_int",
"mat_sec", -- Secondary building material as listed in the designation report description.
"mat_prim", -- Primary building material as listed in the designation report building description.
"style_oth", -- Tertiary architectural style as listed in the designation report building description.
"lm_new", -- A.K.A. name of designated individual landmark
"style_sec", -- Secondary architectural style as listed in the designation report building description.
"borough", -- Borough expressed as a two character abbreviation (MN=Manhattan, BX=Bronx, BK=Brooklyn, QN=Queens, and SI=Staten Island)
"lm_orig", -- Name of designated individual landmark as it appears in the designation report.
"hist_dist", -- Name of designated historic district in which the building or structure is located.
"alt_arch_1", -- Architect or builder responsible for first significant alteration represented by field Alt_Date_1.
"altered",
"alt_date_2", -- This pertains to the date of a second significant alteration. If a third (or fourth) alteration has been done dates will be separated by a semicolon.
"the_geom", -- Geometry column
"block", -- The five digit tax map block number, without leading zeros (ex. tax lot 00123 appears as 123)
"alt_date_1", -- If a significant alteration has been performed its date is represented here. For the purposes of this database only alterations that were noted as significant in the designation report were recorded in this field.
"build_nme" -- Building name, if included in designation report.
FROM
"cityofnewyork-us/individual-landmark-and-historic-district-building-gpmc-yuvp:latest"."individual_landmark_and_historic_district_building"
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/individual-landmark-and-historic-district-building-gpmc-yuvp 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/individual-landmark-and-historic-district-building-gpmc-yuvp: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/individual-landmark-and-historic-district-building-gpmc-yuvpCheckout 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/individual-landmark-and-historic-district-building-gpmc-yuvp:latestThis will download all the objects for the latest tag of cityofnewyork-us/individual-landmark-and-historic-district-building-gpmc-yuvp 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/individual-landmark-and-historic-district-building-gpmc-yuvp: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/individual-landmark-and-historic-district-building-gpmc-yuvp: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/individual-landmark-and-historic-district-building-gpmc-yuvp is just another Postgres schema.