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 solar_electric_programs_reported_by_nyserda table in this repository, by referencing it like:
"ny-gov/solar-electric-programs-reported-by-nyserda-3x8r-34rs:latest"."solar_electric_programs_reported_by_nyserda"or in a full query, like:
SELECT
":id", -- Socrata column ID
"remote_net_metering", -- Indicates if project is Remote Net Metered. Blank cells represent data that were not required or are not currently available
"inverter_manufacturer", -- Name of primary inverter manufacturer for project. Some projects may use more than one type of inverter manufacturer. Only the primary inverter manufacturer is provided. Blank cells represent data that were not required or are not currently available
"primary_inverter_model_number", -- Name of primary inverter model number for project. Some projects may use more than one type of inverter model. Only the primary inverter model number is provided. Blank cells represent data that were not required or are not currently available
"minority_or_women_owned_business_enterprise_mwbe", -- Indicates if the Contractor is a Minority or Women Owned Business Enterprise (MWBE). Blank cells represent data that were not required or are not currently available
"date_install", -- Date NYSERDA recognized the project as interconnected and operational, and closed out the project application. Blank cells represent pipeline data for projects not yet completed.
"date_application_received", -- Date project application was received by the program
"solicitation", -- NYSERDA Program Opportunity Notification (PON) or Request for Proposal (RFP) number.
"sector", -- Name of project sector. The sectors in this dataset are either Residential or Non-Residential
"municipality_type", -- Type of incorporated municipality; either City or Town
"zip_code", -- ZIP code for project location. Where available, standardized ZIP code is provided.
"state", -- Name of US state for project location. Where available, standardized state abbreviation is provided
"city", -- Name of city for project location. Where available, standardized United States Postal Service (USPS) city name is provided
"street_address", -- Street address for project location for projects with a non-residential sector. Where available, standardized address is provided. Blank cells indicate that the project sector is residential, or the address is not available.
"cesir_number", -- Unique number assigned to projects by the electric utility company. Stands for Coordinated Electric System Interconnection Review. Blank cells indicate that a CESIR engineering study was not performed by the electric utility, or that the CESIR number was not reported to NYSERDA by the project developer.
"legacy_project_number", -- Unique identifier for project, assigned using a defunct NYSERDA database. For some projects, the Legacy Project Number was provided as the Project Number in this Open NY dataset prior to August 31, 2020. Blank cells indicate that the project was submitted after NYSERDA discontinued the older database or the Project Number remained the same
"project_number", -- Unique identifier for project
"latitude", -- The approximate latitude coordinate of the project. For Residential projects, the center point of the census tract area is provided, not the exact project location. For Non-Residential projects, the coordinate of the street address is provided.
"community_distributed_generation", -- Indicates if project Community Distributed Generation (Shared Solar or Community Solar)
"totalnameplatekwdc", -- The sum of kilowatt (kW) DC capacity ratings of the installed photovoltaic modules
"affordable_multifamily_housing_incentive", -- Dollars awarded to the project through the Multifamily Affordable Housing Incentive, which provides additional funding to regulated affordable housing
"total_nyserda_incentive", -- Amount of project incentives paid by the program in USD. Blank cells represent data that were not required or are not currently available. Projects that received Green Jobs-Green NY financing but no incentive show an Incentive Amount of $0
"contractor", -- Name of entity responsible for installation of the project. Blank cells represent data that were not required or are not currently available. Contractor data is not provided for Pipeline projects
"electric_utility", -- Name of electric utility for project location
"program_type", -- Name of program type; either Residential/Small Commercial, Commercial/Industrial (Competitive), or Commercial/Industrial (MW Block).
"climate_and_economic_justice_screening_tool_status", -- Indicates if the project is located in a federal disadvantaged community as defined by the White House Council on Environmental Quality
"nys_disadvantaged_community_status", -- Indicates if the project is located in a New York State disadvantaged community (DAC) as defined by the Climate Justice Working Group
"census_tract", -- Census tract identifier; a concatenation of the state FIPS code, county FIPS code, and census tract code. Blank cells represent data that were not required or are not currently available
"incorporated_municipality", -- Name of the incorporated city/town municipality for the project location
"county", -- Name of county for project location. Where available, standardized county name is provided
"project_status", -- Either Complete or Pipeline. Complete indicates projects that are interconnected and operational, and closed out the project application. Pipeline indicates projects with an active application that are not yet complete. Pipeline projects are subject to change
":@computed_region_kjdx_g34t", -- This column was automatically created in order to record in what polygon from the dataset 'Counties' (kjdx-g34t) the point in column 'georeference' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
":@computed_region_wbg7_3whc", -- This column was automatically created in order to record in what polygon from the dataset 'New York Zip Codes' (wbg7-3whc) the point in column 'georeference' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
":@computed_region_yamh_8v7k", -- This column was automatically created in order to record in what polygon from the dataset 'NYS Municipal Boundaries' (yamh-8v7k) the point in column 'georeference' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
":@computed_region_n8jy_tbqr", -- This column was automatically created in order to record in what polygon from the dataset 'NYS Assembly Districts' (n8jy-tbqr) the point in column 'georeference' is located. This enables the creation of region maps (choropleths) in the visualization canvas and data lens.
"green_jobs_green_new_york_participant", -- Indicates if project accessed Green Jobs-Green New York financing.
"expected_kwh_annual_production", -- Expected annual electricity production in kilowatt-hours (kWh) as a result of project
"prevailing_wage_adder", -- Dollars awarded to the project through the Prevailing Wage Adder, which provides additional funding to projects that pay prevailing wage during construction
"project_cost", -- Expected project installation cost in US dollars (USD), as reported by the solar project contractor. Blank cells represent data that were not required or are not currently available
"purchase_type", -- Solar photovoltaic project purchase agreement type. The purchase types are either Lease, Purchase or Power Purchase Agreement. Blank cells represent data that were not required or are not currently available
"reporting_period", -- The time period covered by the data set
"inverter_quantity", -- Quantity of all inverters installed for project. Quantity provided is for all inverters, not just the primary inverter. Blank cells represent data that were not required or are not currently available
"pv_module_manufacturer", -- Name of primary photovoltaic (PV) module manufacturer for project. Some projects may use more than one type of PV module manufacturer. Only the primary PV module manufacturer is provided. Blank cells represent data that were not required or are not currently available
"pv_module_model_number", -- Name of primary photovoltaic (PV) module model number for project. Some projects may use more than one type of PV module model. Only the primary PV module model number is provided. Blank cells represent data that were not required or are not currently available
"pv_module_quantity", -- Quantity of all photovoltaic (PV) modules installed for project. Quantity provided is for all PV modules, not just the primary PV module. Blank cells represent data that were not required or are not currently available
"affordable_solar_residential_adder", -- Dollars awarded to the project through the Affordable Solar Residential Incentive, which provides additional funding to income-eligible single family projects
"community_adder", -- Dollars awarded to the project through the Community Adder, which provides additional funding to community solar projects
"inclusive_community_solar_adder", -- Dollars awarded to the project through the Inclusive Community Solar Adder, which provides additional funding to community solar projects serving offtakers in disadvantaged communities
"expanded_solar_for_all_adder", -- Dollars awarded to the project through the Expanded Solar For All program, which provides additional funding to community solar projects serving eligible offtakers in National Grid territory
"brownfield_landfill_adder", -- Dollars awarded to the project through the Brownfield/Landfill Adder, which provides additional funding to projects sited on brownfield sites or landfills
"canopy_adder", -- Dollars awarded to the project through the Canopy Adder, which provides additional funding to projects sited on rooftop canopies or carports in ConEdison territory
"longitude", -- The approximate longitude coordinate of the project. For Residential projects, the center point of the census tract area is provided, not the exact project location. For Non-Residential projects, the coordinate of the street address is provided.
"georeference" -- Open Data platform-generated geocoding information from supplied address components. Point-type location is the centroid of the address components provided and does not reflect a specific address if the street address component is not provided. Point-type location is supplied in "POINT (<geocoded longitude> <geocoded latitude>)" format.
FROM
"ny-gov/solar-electric-programs-reported-by-nyserda-3x8r-34rs:latest"."solar_electric_programs_reported_by_nyserda"
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/solar-electric-programs-reported-by-nyserda-3x8r-34rs 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 ny-gov/solar-electric-programs-reported-by-nyserda-3x8r-34rs: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/solar-electric-programs-reported-by-nyserda-3x8r-34rsCheckout 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/solar-electric-programs-reported-by-nyserda-3x8r-34rs:latestThis will download all the objects for the latest tag of ny-gov/solar-electric-programs-reported-by-nyserda-3x8r-34rs 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/solar-electric-programs-reported-by-nyserda-3x8r-34rs: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/solar-electric-programs-reported-by-nyserda-3x8r-34rs: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, ny-gov/solar-electric-programs-reported-by-nyserda-3x8r-34rs is just another Postgres schema.