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 hospital_inpatient_discharges_sparcs_deidentified table in this repository, by referencing it like:
"health-data-ny-gov/hospital-inpatient-discharges-sparcs-deidentified-rmwa-zns4:latest"."hospital_inpatient_discharges_sparcs_deidentified"or in a full query, like:
SELECT
":id", -- Socrata column ID
"total_charges", -- Total charges for the discharge.
"emergency_department_indicator", -- The Emergency Department Indicator is set based on the submitted revenue codes. If the record contained an Emergency Department revenue code of 045X, the indicator is set to "Y", otherwise it will be “N”.
"source_of_payment_3", -- A description of the type of payment for this occurrence.
"apr_risk_of_mortality", -- All Patient Refined Risk of Mortality (APR ROM). Minor (1), Moderate (2), Major (3) , Extreme (4).
"apr_severity_of_illness_description", -- All Patient Refined Severity of Illness (APR SOI) Description. Minor (1), Moderate (2), Major (3) , Extreme (4).
"ccs_procedure_description", -- AHRQ Clinical Classification Software (CCS) ICD-9 Procedure Category Description. More information on the CCS system may be found at the direct link: http://www.hcup-us.ahrq.gov/toolssoftware/ccs/ccs.jsp
"ccs_diagnosis_code", -- AHRQ Clinical Classification Software (CCS) Diagnosis Category Code. More information on the CCS system may be found at the direct link: http://www.hcup-us.ahrq.gov/toolssoftware/ccs/ccs.jsp
"type_of_admission", -- A description of the manner in which the patient was admitted to the health care facility: Elective, Emergency, Newborn, Not Available, Trauma, Urgent.
"operating_certificate_number", -- The facility Operating Certificate Number as assigned by NYS Department of Health. Blank for abortion records.
"abortion_edit_indicator", -- A flag to indicate if the discharge record contains any indication of abortion ("N" = No; "Y" = Yes).
"birth_weight", -- The neonate birth weight in grams; rounded to nearest 100g.
"ccs_diagnosis_description", -- AHRQ Clinical Classification Software (CCS) Diagnosis Category Description. More information on the CCS system may be found at the direct link: http://www.hcup-us.ahrq.gov/toolssoftware/ccs/ccs.jsp
"ethnicity", -- Patient ethnicity. The ethnicity of the patient: Spanish/Hispanic Origin, Not of Spanish/Hispanic Origin, Multi, Unknown.
"facility_name", -- The name of the facility where services were performed based on the Permanent Facility Identifier (PFI), as maintained by the NYSDOH Division of Health Facility Planning. For abortion records ‘Abortion Record – Facility Name Redacted’ appears.
"facility_id", -- Permanent Facility Identifier. Blank for abortion records.
"source_of_payment_2", -- A description of the type of payment for this occurrence.
"health_service_area", -- A description of the Health Service Area (HSA) in which the hospital is located. Blank for abortion records. Capital/Adirondack, Central NY, Finger Lakes, Hudson Valley, Long Island, New York City, Southern Tier, Western NY.
"age_group", -- Age in years at time of discharge. Grouped into the following age groups: 0 to 17, 18 to 29, 30 to 49, 50 to 69, and 70 or Older.
"zip_code_3_digits", -- The first three digits of the patient's zip code. Blank for: - population size less than 20,000 - abortion records, or - cell size less than 10 on population classification strata. “OOS” are Out of State zip codes.
"length_of_stay", -- The total number of patient days at an acute level and/or other than acute care level (excluding leave of absence days) (Discharge Date - Admission Date) + 1. Length of Stay greater than or equal to 120 days has been aggregated to 120+ days.
"discharge_year", -- The year (CCYY) of discharge.
"patient_disposition", -- The patient's destination or status upon discharge.
"ccs_procedure_code", -- AHRQ Clinical Classification Software (CCS) ICD-9 Procedure Category Code. More information on the CCS system may be found at the direct link: http://www.hcup-us.ahrq.gov/toolssoftware/ccs/ccs.jsp
"apr_mdc_description", -- All Patient Refined Major Diagnostic Category (APR MDC) Description.
"apr_severity_of_illness_code", -- The APR-DRG Severity of Illness Code: 1, 2, 3, 4
"apr_drg_description", -- The APR-DRG Classification Code Description In Calendar Year 2011, Version 28 of the APR-DRG Grouper. http://www.health.ny.gov/statistics/sparcs/sysdoc/appy.htm
"apr_mdc_code", -- All Patient Refined Major Diagnostic Category (APR MDC) Code. APR-DRG Codes 001-006 and 950-956 may group to more than one MDC Code. All other APR DRGs group to one MDC category.
"apr_medical_surgical_description", -- The APR-DRG specific classification of Medical, Surgical or Not Applicable.
"total_costs", -- Total estimated costs for the discharge.
"source_of_payment_1", -- A description of the type of payment for this occurrence.
"race", -- Black/African American, Multi, Other Race, Unknown, White. Other Race includes Native Americans and Asian/Pacific Islander.
"hospital_county", -- A description of the county in which the hospital is located. Blank for abortion records.
"apr_drg_code", -- The APR-DRG Classification Code
"gender" -- Patient gender: (M) Male, (F) Female, (U) Unknown.
FROM
"health-data-ny-gov/hospital-inpatient-discharges-sparcs-deidentified-rmwa-zns4:latest"."hospital_inpatient_discharges_sparcs_deidentified"
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 health-data-ny-gov/hospital-inpatient-discharges-sparcs-deidentified-rmwa-zns4 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 health-data-ny-gov/hospital-inpatient-discharges-sparcs-deidentified-rmwa-zns4: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 health-data-ny-gov/hospital-inpatient-discharges-sparcs-deidentified-rmwa-zns4Checkout 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 health-data-ny-gov/hospital-inpatient-discharges-sparcs-deidentified-rmwa-zns4:latestThis will download all the objects for the latest tag of health-data-ny-gov/hospital-inpatient-discharges-sparcs-deidentified-rmwa-zns4 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 health-data-ny-gov/hospital-inpatient-discharges-sparcs-deidentified-rmwa-zns4: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 health-data-ny-gov/hospital-inpatient-discharges-sparcs-deidentified-rmwa-zns4: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, health-data-ny-gov/hospital-inpatient-discharges-sparcs-deidentified-rmwa-zns4 is just another Postgres schema.