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 highway_data_element_dictionary table in this repository, by referencing it like:
"datahub-transportation-gov/highway-data-element-dictionary-nhvr-exvq:latest"."highway_data_element_dictionary"or in a full query, like:
SELECT
":id", -- Socrata column ID
"data_element_name", -- Unit of data that is considered in context to be indivisible. A Data Element is considered to be a basic unit of data of interest to an organization. It is a unit of data for which the definition, identification, representation, and permissible values are specified by means of a set of attributes. https://data.transportation.gov/resource/3enx-g69f.csv?data_element_name=Data+Element+Name
"preferred_physical_name", -- This is the preferred name for physical models or data definition language (DDL). https://data.transportation.gov/resource/3enx-g69f.csv?data_element_name=Preferred+Physical+Name
"maximum_length", -- This field is the maximum number of units of length, where units of length varies depending on the type that is being derived from. The value of maxLength must be a nonNegativeInteger. https://data.transportation.gov/resource/3enx-g69f.csv?data_element_name=Maximum+Length
"value_domain", -- Value Domain is a class each instance of which models a value domain, a collection of permissible values. A value domain provides representation, but has no implication as to what data element concept the values are associated with, nor what the values mean. Permissible values are designations, bindings of signs (values) to their corresponding value meanings. https://data.transportation.gov/resource/3enx-g69f.csv?data_element_name=Value+Domain
"business_owner_name", -- The organization and contact within the organization that is responsible for the definition and other mandatory attributes by which the metadata item is specified. https://data.transportation.gov/resource/3enx-g69f.csv?data_element_name=Business+Owner+Name
"data_asset_name", -- The name of the data asset or data set. A data asset is collection of data elements or datasets that make sense to group together. A given Data Asset may represent an entire database consisting of multiple distinct entity classes, or may represent a single entity class. https://data.transportation.gov/resource/3enx-g69f.csv?data_element_name=Data+Asset+Name
"system_number", -- This is the number of systems the data element is used. The current systems that have been crosswalked are FMIS, HPMS, TMAS, and LTPP.
"data_type_code", -- The format used for the collection of letters, digits, and/or symbols, to depict values of a data element, determined by the operations that may be performed on a data element. https://data.transportation.gov/resource/3enx-g69f.csv?data_element_name=Data+Type+Code
"precision_number", -- The number of decimal places permitted in any associated data element values. https://data.transportation.gov/resource/3enx-g69f.csv?data_element_name=Precision+Number
"subject_category_code", -- This is the primary high-level taxonomy subject category for the data element. https://data.transportation.gov/resource/3enx-g69f.csv?data_element_name=Subject+Category+Code
"description_text", -- The definition text is a statement hich specifies the meaning of the Data Element. It may additionally record a source for the text. https://data.transportation.gov/resource/3enx-g69f.csv?data_element_name=Description+Text
"data_asset_abbreviation", -- The abbreviation for the data asset or data set. A data asset is collection of data elements or datasets that make sense to group together. A given Data Asset may represent an entire database consisting of multiple distinct entity classes, or may represent a single entity class. https://data.transportation.gov/resource/3enx-g69f.csv?data_element_name=Data+Asset+Abbreviation
"pattern_text", -- Pattern is a constraint on the value space of a datatype which is achieved by constraining the lexical space to literals which match a specific pattern. The value of pattern should be a regular expression. https://data.transportation.gov/resource/3enx-g69f.csv?data_element_name=Pattern+Number
"unit_of_measure" -- Magnitude for some quantity, either physical or immaterial. https://data.transportation.gov/resource/3enx-g69f.csv?data_element_name=Unit+of+Measure
FROM
"datahub-transportation-gov/highway-data-element-dictionary-nhvr-exvq:latest"."highway_data_element_dictionary"
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 datahub-transportation-gov/highway-data-element-dictionary-nhvr-exvq with SQL in under 60 seconds.
This repository is an "external" repository. That means it's hosted elsewhere, in this case at datahub.transportation.gov. When you querydatahub-transportation-gov/highway-data-element-dictionary-nhvr-exvq: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)"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 (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 datahub.transportation.gov, 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 \
"datahub-transportation-gov/highway-data-element-dictionary-nhvr-exvq" \
--handler-options '{
"domain": "datahub.transportation.gov",
"tables": {
"highway_data_element_dictionary": "nhvr-exvq"
}
}'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, datahub-transportation-gov/highway-data-element-dictionary-nhvr-exvq is just another Postgres schema.