noaa-fisheries-afsc-data-socrata/afscracesapshavey-dna-extraction-from-archived-px7a-nf6c

  • alaska
  • bering sea
  • biota
  • blood smear
  • canada
  • + 7

Query the Data Delivery Network

Query the DDN

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 procotol. 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 afscracesapshavey_dna_extraction_from_archived table in this repository, by referencing it like:

"noaa-fisheries-afsc-data-socrata/afscracesapshavey-dna-extraction-from-archived-px7a-nf6c:latest"."afscracesapshavey_dna_extraction_from_archived"

or in a full query, like:

SELECT 
    ":id", -- Socrata column ID
    "_16s_primer", -- Primer (0 = Did not use primer set on this sample, 1 = Used primer set on this sample)
    "smear_result", -- Smear result (0 = Hematodinium parasite absent on smear, 1 = Hematodinium parasite present on smear)
    "coi_primer", -- Primer (0 = Did not use primer set on this sample, 1 = Used primer set on this sample)
    "id", -- A sequence of unique integers that identifies each blood smear
    "species_name", -- The scientific name of the organism
    "size", -- Carapace size (mm). Null = not reported for this specimen
    "sex", -- Crab sex (1 = male, 2 = female, 3 = unknown)
    "its_amplification", -- Amplification (0 = No DNA amplification using this primer set, 1 = DNA was amplified using primer set, 9 = no amplification to report due to primer set not used in sample)
    "its_primer", -- Primer (0 = Did not use primer set on this sample, 1 = Used primer set on this sample)
    "collection_location", -- General location of collected 
    "smear_coverslipped", -- Treatment of blood smears (0 = no cover slip, 1 = cover slip attached using mounting media).
    "smear_stained", -- Smear staining treatment
    "_16s_amplification", -- Amplification (0 = No DNA amplification using this primer set, 1 = DNA was amplified using primer set, 9 = no amplification to report due to primer set not used in sample)
    "_18s_primer", -- Primer (0 = Did not use primer set on this sample, 1 = Used primer set on this sample)
    "coi_amplification", -- Amplification (0 = No DNA amplification using this primer set, 1 = DNA was amplified using primer set, 9 = no amplification to report due to primer set not used in sample)
    "_18s_amplification", -- Amplification (0 = No DNA amplification using this primer set, 1 = DNA was amplified using primer set, 9 = no amplification to report due to primer set not used in sample)
    "statistical", -- Analyzed using two-sample t-test (0 = smear was not used in statistical analysis, 1 = smear was used in statistical analysis)
    "smear_rating", -- Hematodinium parasite presence on smear was identified as T-rating. See metadata for key
    "spno", -- Specimen number
    "shell_cond", -- Chionoecetes carapace shell condition  (0 = premolt, 1 = soft, 2 = new hardshell, 3 = oldshell, 4 = oldshell, 9 = no shell condition information reported for crab specimen or does not apply)
    "year" -- Year specimen was collected
FROM
    "noaa-fisheries-afsc-data-socrata/afscracesapshavey-dna-extraction-from-archived-px7a-nf6c:latest"."afscracesapshavey_dna_extraction_from_archived"
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 noaa-fisheries-afsc-data-socrata/afscracesapshavey-dna-extraction-from-archived-px7a-nf6c with SQL in under 60 seconds.

This repository is an "external" repository. That means it's hosted elsewhere, in this case at noaa-fisheries-afsc.data.socrata.com. When you querynoaa-fisheries-afsc-data-socrata/afscracesapshavey-dna-extraction-from-archived-px7a-nf6c: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

Install Splitgraph Locally

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 noaa-fisheries-afsc.data.socrata.com, 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 \
  "noaa-fisheries-afsc-data-socrata/afscracesapshavey-dna-extraction-from-archived-px7a-nf6c" \
  --handler-options '{
    "domain": "noaa-fisheries-afsc.data.socrata.com",
    "tables": {
        "afscracesapshavey_dna_extraction_from_archived": "px7a-nf6c"
    }
}'

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, noaa-fisheries-afsc-data-socrata/afscracesapshavey-dna-extraction-from-archived-px7a-nf6c is just another Postgres schema.

Related Documentation: