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 utility_energy_registry_monthly_community_energy table in this repository, by referencing it like:
"ny-gov/utility-energy-registry-monthly-community-energy-4txm-py4p:latest"."utility_energy_registry_monthly_community_energy"or in a full query, like:
SELECT
":id", -- Socrata column ID
"data_field", -- Name of UER energy metric pursuant to Public Service Commission CASE 17-M-0315 found at http://documents.dps.ny.gov/public/MatterManagement/CaseMaster.aspx?MatterCaseNo=17-M-0315 A detailed description of these data fields can be found at https://utilityregistry.org/app/#/about
"uer_id", -- Unique ID used for a utility in the UER data schema. 2 is Central Hudson, 3 is Consolidated Edison, 4 is National Fuel, 5 is National Grid, 6 is New York State Gas and Electric (NYSEG), 7 is Orange and Rockland, 8 is Public Service Enterprise Group (PSEG) Long Island, and 9 is Rochester Gas and Electric (RG&E). CCA-Admin-1 is MEGA, CCA-Admin-2 is Westchester Power, CCA-Admin-3 is Joule Community Power, and CCA-Admin-4 is Good Energy.
"county_name", -- Name of county or counties associated with municipality. Field is blank for Villages
"full_fips", -- US Census Full FIPS Code for incorporated municipality as a concatenation of State FIPS (2 digits), County FIPS (3 digits), and Place FIPS (5 digits). Villages do not have County FIPS included
"data_field_display_name", -- Name of UER energy metric defined per the “PSC Order Adopting the Utility Energy Registry” CASE 17-M-0315. For more details see http://documents.dps.ny.gov/public/MatterManagement/CaseMaster.aspx?MatterCaseNo=17-M-0315 A detailed description of these data fields can be found at https://utilityregistry.org/app/#/about
"com_name", -- Name of municipality. Municipalities served by more than one electric or gas utility will have multiple entries.
"value", -- Value of “data_field”. Data are geospatially aggregated data in the municipality across the associated calendar month. Blank cells mean that it was not reported by the utility, -999 means the data was withheld for privacy concerns, all other values are the reported value of the “data_field”. UER data are prepared by utility companies and Community Choice Aggregation administrators and submitted to NYSERDA. Utilities and CCA Administrators are solely responsible for the accuracy and quality of UER data, and NYSERDA does not warrant or guarantee the accuracy of data submitted to the UER.
"year", -- Four-digit integer describing calendar year
"number_of_accounts", -- Number of utility accounts in the aggregation reported in the “value” field.
"utility_display_name", -- The reporting utility or CCA administrator name in text form
"data_stream", -- The geospatial layer and reporting frequency associate with the data. “community” means incorporated municipality, and county and ZIP code are as stated
"month", -- Integer 1-12 describing calendar month, 1 = Jan, and so on
"data_class", -- Describes energy type; either electricity or natural_gas
"state_2", -- Standard 2-digit abbreviation for US State
"unit", -- Unit of measurement associated with “data_field”; either Integer, MW, MWh, or Therms
"com_type" -- Type of incorporated municipality; either City, Town, or Village. City and town aggregations exclude data from villages located within that city or town.
FROM
"ny-gov/utility-energy-registry-monthly-community-energy-4txm-py4p:latest"."utility_energy_registry_monthly_community_energy"
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/utility-energy-registry-monthly-community-energy-4txm-py4p 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/utility-energy-registry-monthly-community-energy-4txm-py4p: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/utility-energy-registry-monthly-community-energy-4txm-py4pCheckout 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/utility-energy-registry-monthly-community-energy-4txm-py4p:latestThis will download all the objects for the latest tag of ny-gov/utility-energy-registry-monthly-community-energy-4txm-py4p 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/utility-energy-registry-monthly-community-energy-4txm-py4p: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/utility-energy-registry-monthly-community-energy-4txm-py4p: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/utility-energy-registry-monthly-community-energy-4txm-py4p is just another Postgres schema.