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 mayors_management_report_agency_performance
table in this repository, by referencing it like:
"cityofnewyork-us/mayors-management-report-agency-performance-rbed-zzin:latest"."mayors_management_report_agency_performance"
or in a full query, like:
SELECT
":id", -- Socrata column ID
"goal", -- What the agency hopes to achieve related to each service.
"retired", -- Indicates if the indicator is retired. A retired indicator is no longer reported in the DMMR, MMR, PMMR.
"agency_name", -- Full name of the reporting agency
"createdon", -- The date the indicator was created in the database.
"frequency", -- This refers to how frequently the data is reported by the agency to the Mayor's Office of Operations.
"lagtime", -- Lag time, in weeks, is the amount of time after the close of the reporting period that the Mayor's Office of Operations expects to receive the data.
"valuedate", -- Value date indicates for which month this data value is reported.
"agency", -- The acronym of the agency’s name
"acceptedvalueytd", -- The accepted year to date value for the designated month.
"targetmmr", -- The performance target for the reporting fiscal year.
"targetmmr2", -- The performance target for the next reporting fiscal year.
"source", -- The data source as defined by the agency.
"geo", -- This field tags the indicator as a "mapping indicator," or indicator which is disaggregated by specified geographic area.
"description", -- Definition of the indicator.
"id", -- ID number for the individual indicator.
"geotype", -- This specifies which geographic area is used for this mapping indicator.
"geovalue", -- The specific number or name of the geographic area.
"reporting_period", -- Reporting period describes the cadence of the data collection.
"critical", -- An indicator is tagged as critical if it is particularly important to meet the stated goal or is a priority for the agency.
"service", -- The agency’s major areas of responsibility for delivering services to New Yorkers.
"fiscalyear", -- The reporting fiscal year. The New York City fiscal year extends from July 1 - June 30. Ex. Fiscal 2017 is July 1, 2016 - June 30, 2017.
"acceptedvalue", -- The accepted data value for the designated month.
"desireddirection", -- The desired direction of the indicator over time
"parentid", -- Mapping indicators, as indicated by the "geo" tag in this dataset, are sub-indicators of a citywide total. The parent ID represents the parent indicator to which the distinct mapping indicators are related. Non-mapping indicators will have the same ID and parentID.
"indicator", -- Indicators are measures of agency performance.
"measurement_type", -- The unit type of the indicator.
"additive" -- Additive indicators have a cumulative total in the year Accepted Value YTD column.
FROM
"cityofnewyork-us/mayors-management-report-agency-performance-rbed-zzin:latest"."mayors_management_report_agency_performance"
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/mayors-management-report-agency-performance-rbed-zzin
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; sgr
can 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 clone
and sgr checkout
.
Cloning Data
Because cityofnewyork-us/mayors-management-report-agency-performance-rbed-zzin: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/mayors-management-report-agency-performance-rbed-zzin
Checkout 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/mayors-management-report-agency-performance-rbed-zzin:latest
This will download all the objects for the latest
tag of cityofnewyork-us/mayors-management-report-agency-performance-rbed-zzin
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/mayors-management-report-agency-performance-rbed-zzin: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/mayors-management-report-agency-performance-rbed-zzin:latest
This 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/mayors-management-report-agency-performance-rbed-zzin
is just another Postgres schema.