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 selected_scholarship_programs_by_metric_type table in this repository, by referencing it like:
"ny-gov/selected-scholarship-programs-by-metric-type-6u2t-cy73:latest"."selected_scholarship_programs_by_metric_type"or in a full query, like:
SELECT
":id", -- Socrata column ID
"federal_school_code", -- Used for Metric Type = “College” only. Institution code used by the US Department of Education. Note that there is not always a 1-for-1 correspondence between TAP Code and Federal Code. In some situations, there may be more than one TAP Code for a single Federal School Code. A typical example would be separate TAP Codes for undergraduate and graduate levels of study at the same Federal School Code institution.
"tap_college_name", -- Used for Metric Type = “College” only. Name of Institution used by the Tuition Assistance Program.
"tap_college_code", -- Used for Metric Type = “College” only. Name of Institution used by the Tuition Assistance Program.
"metric_value", -- For Metric Type = “College”, this field is blank. For Metric Type = “Gender”: Male Female n/a = Not available For Metric Type = “Income”: The recipient’s New York State Net Taxable Income category: $ n/a ( > $80K) = Not available, but known to be greater than $80,000 $ 0 to $10,000 $10,001 to $20,000 $20,001 to $30,000 (Additional categories in $10k increments added as needed) For Metric Type = “Region”: The region, as designated by the NYS Department of Labor, where the applicant resides. Capital District: Albany, Columbia, Greene, Rensselaer, Saratoga, Schenectady, Warren, and Washington; Central New York: Cayuga, Cortland, Madison, Onondaga, and Oswego; Finger Lakes: Genesee, Livingston, Monroe, Ontario, Orleans, Seneca, Wayne, Wyoming, and Yates; Hudson Valley: Dutchess, Orange, Putnam, Rockland, Sullivan, Ulster, and Westchester; Long Island: Nassau and Suffolk; Mohawk Valley: Fulton, Herkimer, Montgomery, Oneida, Otsego, and Schoharie; New York City: Bronx, Kings, New York, Queens, and Richmond; North Country Clinton, Essex, Franklin, Hamilton, Jefferson, Lewis, and St. Lawrence; Southern Tier: Broome, Chemung, Chenango, Delaware, Schuyler, Steuben, Tioga, and Tompkins; Western New York: Allegany, Cattaraugus, Chautauqua, Erie, and Niagara; n/a: Not available--Region was unable to be determined.
"metric_type", -- Valid values for metric type are “College”, “Gender”, “Income”, and “Region”. Note that income data is generally unavailable for applicants during the early stages of processing. Therefore, the "Income" metric is only present for scholarship recipients.
"processing_snapshot_date", -- For scholarship applicants, this is the date of the processing snapshot and data presented will reflect eligibility determinations as of that point in time. For scholarship recipients, this field is blank.
"sector_type", -- Used for Metric Type = “College” only. Name of Institution used by the Tuition Assistance Program.
"year", -- Academic Year is from July 1 through June 30. For scholarship applicants, this is the academic year of first application for the scholarship award. For scholarship recipients, this is the academic year of award.
"scholarship_name", -- The name of the scholarship program administered by HESC.
"tap_sector_group", -- Used for Metric Type = “College” only. Sector Group of Institution: 1-CUNY SR = CUNY Senior Colleges; 2-CUNY CC = CUNY Community Colleges; 3-SUNY SO = SUNY State Operated; 4-SUNY CC = SUNY Community Colleges; 5-INDEPENDENT = Independent Colleges; 6-BUS. DEGREE = Business Degree Granting Institutions; 7-BUS. NON-DEG = Non-Degree Business Schools; 8-OTHER = All Other Institutions; 9-CHAPTER XXII = Chapter XXII TAP Schools; VOCATIONAL – VET SCHOOLS ONLY = Vocational schools approved for Veteran Tuition Award only.
"headcount", -- For Headcount Type = “Eligible Applicant(s)”: The number of applicants determined to be eligible for this scholarship program as of the processing snapshot date. For Headcount Type = “Recipient(s)”: The number of recipients as measured by students receiving at least one term award during the academic year.
"headcount_type", -- Type of headcount is either “Eligible Applicant(s)” or “Recipient(s)”.
"college_region_name" -- Used for Metric Type = “College” only. The region, as designated by the NYS Department of Labor, where the applicant resides. Capital District: Albany, Columbia, Greene, Rensselaer, Saratoga, Schenectady, Warren, and Washington; Central New York: Cayuga, Cortland, Madison, Onondaga, and Oswego; Finger Lakes: Genesee, Livingston, Monroe, Ontario, Orleans, Seneca, Wayne, Wyoming, and Yates; Hudson Valley: Dutchess, Orange, Putnam, Rockland, Sullivan, Ulster, and Westchester; Long Island: Nassau and Suffolk; Mohawk Valley: Fulton, Herkimer, Montgomery, Oneida, Otsego, and Schoharie; New York City: Bronx, Kings, New York, Queens, and Richmond; North Country Clinton, Essex, Franklin, Hamilton, Jefferson, Lewis, and St. Lawrence; Southern Tier: Broome, Chemung, Chenango, Delaware, Schuyler, Steuben, Tioga, and Tompkins; Western New York: Allegany, Cattaraugus, Chautauqua, Erie, and Niagara; n/a: Not available--Region was unable to be determined.
FROM
"ny-gov/selected-scholarship-programs-by-metric-type-6u2t-cy73:latest"."selected_scholarship_programs_by_metric_type"
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/selected-scholarship-programs-by-metric-type-6u2t-cy73 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/selected-scholarship-programs-by-metric-type-6u2t-cy73: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/selected-scholarship-programs-by-metric-type-6u2t-cy73Checkout 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/selected-scholarship-programs-by-metric-type-6u2t-cy73:latestThis will download all the objects for the latest tag of ny-gov/selected-scholarship-programs-by-metric-type-6u2t-cy73 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/selected-scholarship-programs-by-metric-type-6u2t-cy73: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/selected-scholarship-programs-by-metric-type-6u2t-cy73: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/selected-scholarship-programs-by-metric-type-6u2t-cy73 is just another Postgres schema.