Query the Data Delivery Network

The 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 checkbook_la_data table in this repository, by referencing it like:

"controllerdata-lacity/checkbook-la-data-pggv-e4fn:latest"."checkbook_la_data"

or in a full query, like:

SELECT
    ":id", -- Socrata column ID
    "item_code", -- Purchased Item Code
    "account_name", -- Account Name
    "vendor_name", -- Vendor Name
    "expenditure_type", -- Expenditure Type
    "dollar_amount", -- Dollar Amount
    "data_source", -- Data Sourced From
    "payment_method", -- How payment was made
    "po_date", -- Purchase Order Date
    "authority",
    "receiver_id",
    "sales_tax", -- Sales Tax Amount
    "authority_name", -- Authory Name
    "calendar_month", -- Calendar Month
    "fund", -- Fund #
    "discount", -- Discount on purchased item
    "supplier_country", -- Vendor Country
    "buyer_name", -- City Buyer ID
    "detailed_item_description", -- Detailed description of purchase
    "description", -- Description of purchased item
    "transaction_id", -- Accounting System Transaction (FMS) ID
    "po_num", -- Purchase Order Number
    "inv_dist_line", -- System line associated with Vendor's Invoice Line Number
    "supplier_city", -- Vendor City
    "inv_line", -- Vendor's Invoice Line Number
    "site_location", -- Purchased Item Site Location
    "inv_date", -- Invoice Receipt Date
    "invoice_discount_due_date", -- Invoice discount due date
    "invoice_due_date", -- Invoice due date
    "fund_name", -- Fund Name
    "inv_num", -- Invoice #
    "po_line_number", -- Purchase Order Line Number
    "government_activity", -- Government Activity Category
    "procurement_organization",
    "fund_type", -- Fund Type
    "bu_name", -- City Business Unit Name
    "settlement_judgment", -- Relates to Settlement/Judgment
    "sales_tax_percent", -- Sales Tax %
    "unit_of_measure",
    "quantity", -- Number of items purchased
    "account_code", -- Account # Code
    "unit_price", -- Unit Price of purchased item
    "authority_link", -- Authority Link (if applicable)
    "calendar_month_number", -- Calendar Month #
    "fiscal_year_month", -- Fiscal Year & Month
    "btrc", -- Business Tax Registration Certificate
    "fiscal_year_quarter", -- Fiscal Year Quarter
    "fiscal_year", -- Fiscal Year
    "calendar_month_year", -- Calendar Month & Year
    "fund_group_name", -- Fund Group Name
    "department_number", -- Department #
    "program", -- Expense based on Program Activity 
    "fiscal_month_number", -- Fiscal Month #
    "vendor_id", -- Vendor ID
    "zip", -- Vendor Zip Code
    "transaction_date", -- Transaction Date
    "payment_status", -- Status of payment
    "department_name", -- Department Name
    "currency", -- Type of currency used in transaction
    "vendor_num", -- Vendor ID + Vendor Name
    "value_of_spend", -- Calculation of Unit Price * Quanity
    "item_code_name" -- Purchased Item Code Name
FROM
    "controllerdata-lacity/checkbook-la-data-pggv-e4fn:latest"."checkbook_la_data"
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 controllerdata-lacity/checkbook-la-data-pggv-e4fn with SQL in under 60 seconds.

This repository is an "external" repository. That means it's hosted elsewhere, in this case at controllerdata.lacity.org. When you querycontrollerdata-lacity/checkbook-la-data-pggv-e4fn:latest on the DDN, we "mount" the repository using the socrata mount handler. The mount handler proxies your SQL query to the upstream data source, translating it from SQL to the relevant language (in this case SoQL).

We also cache query responses on the DDN, but we run the DDN on multiple nodes so a CACHE_HIT is only guaranteed for subsequent queries that land on the same node.

Query Your Local Engine

bash -c "$(curl -sL https://github.com/splitgraph/splitgraph/releases/latest/download/install.sh)"

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 (like this repository), 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, where the author has pushed Splitgraph Images to the repository, you can "clone" and/or "checkout" the data using sgr cloneand sgr checkout.

Mounting Data

This repository is an external repository. It's not hosted by Splitgraph. It is hosted by controllerdata.lacity.org, and Splitgraph indexes it. This means it is not an actual Splitgraph image, so you cannot use sgr clone to get the data. Instead, you can use the socrata adapter with the sgr mount command. Then, if you want, you can import the data and turn it into a Splitgraph image that others can clone.

First, install Splitgraph if you haven't already.

Mount the table with sgr mount

sgr mount socrata \
  "controllerdata-lacity/checkbook-la-data-pggv-e4fn" \
  --handler-options '{
    "domain": "controllerdata.lacity.org",
    "tables": {
        "checkbook_la_data": "pggv-e4fn"
    }
}'

That's it! Now you can query the data in the mounted table like any other Postgres table.

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, controllerdata-lacity/checkbook-la-data-pggv-e4fn is just another Postgres schema.