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 landlordtenant_monthly_caseload_cy_20232024 table in this repository, by referencing it like:
"texas-gov/landlordtenant-monthly-caseload-cy-20232024-8qme-eqs9:latest"."landlordtenant_monthly_caseload_cy_20232024"or in a full query, like:
SELECT
":id", -- Socrata column ID
"all_other_dispositions", -- Number of dispositions not clearly identifiable as any of the above categories.
"cases_appealed_after_trial", -- Number of cases for which an appeal from the final judgment of the court was filed after trial.
"cases_appealed_without_trial", -- Number of cases for which an appear from the final judgment of the court was filed without trial.
"county",
"cases_pending", -- All cases previously filed in which a judgment had not been entered at the beginning of the month.
"date",
"default_judgments", -- Number of cases in which the judgment was reached by default- the defendant, though served, failed to appear and answer, and judgment by default was granted in favor of the plaintiff.
"inactive_cases_pending", -- Number of cases in which a judgment had not been entered that had been classified as inactive.
"total_cases_disposed", -- Total number of cases disposed during the month.
"new_cases_filed", -- Total number of new cases filed during the month.
"cases_non_suited_or_dismissed", -- Number of cases in which a dismissal was entered at the request of the plaintiff or petitioner or dismissed by agreement of both parties.
"cases_dismissed_for_want", -- Number of cases dismissed because the plaintiff or petitioner did not appear or otherwise made no effort to pursue their case.
"bench_trials", -- Number of cases in which the decision was reached after a trial or hearing by the judge, without a jury.
"agreed_judgments", -- Number of cases in which the court entered a judgment based upon the mutual agreement of the parties involved in the suit.
"all_other_cases_added", -- Number of cases added to the docket in a manner other than the filing of a new, original case.
"court",
"cases_reactivated", -- Number of cases that had previously been placed in an inactive pending status, bus for which further court proceedings and activities can now be resumed so that the case can proceed to disposition.
"active_cases_pending", -- Number of cases in which a judgment had not been entered that were active at the beginning of the month.
"cases_placed_on_inactive", -- Number of cases in which a judgment had not been entered that were place in an inactive pending status because further court proceedings and activities could not continue.
"cases_pending_end_of_month", -- Sum of active and inactive cases at the end of the month.
"active_cases_end_of_month", -- Number of cases in which a judgment had not been entered that were classified as active and awaiting entry of a judgment at the end of the month.
"jury_trials", -- Number of cases in which a judgment was entered after trial based on the verdict of a jury.
"inactive_cases_end_of_month" -- Number of cases in which a judgment had not been entered at the end of the month that had been classified as inactive.
FROM
"texas-gov/landlordtenant-monthly-caseload-cy-20232024-8qme-eqs9:latest"."landlordtenant_monthly_caseload_cy_20232024"
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 texas-gov/landlordtenant-monthly-caseload-cy-20232024-8qme-eqs9 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 texas-gov/landlordtenant-monthly-caseload-cy-20232024-8qme-eqs9: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 texas-gov/landlordtenant-monthly-caseload-cy-20232024-8qme-eqs9Checkout 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 texas-gov/landlordtenant-monthly-caseload-cy-20232024-8qme-eqs9:latestThis will download all the objects for the latest tag of texas-gov/landlordtenant-monthly-caseload-cy-20232024-8qme-eqs9 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 texas-gov/landlordtenant-monthly-caseload-cy-20232024-8qme-eqs9: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 texas-gov/landlordtenant-monthly-caseload-cy-20232024-8qme-eqs9: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, texas-gov/landlordtenant-monthly-caseload-cy-20232024-8qme-eqs9 is just another Postgres schema.