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NoSQL data workflows with Mathematica and Google // Indexing and Census

Posted 6 years ago
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Who needs SQL in the cloud age?

This and followup tutorials will show how flexible data workflows can be built in Mathematica, relying on Google cloud-based apps (Drive, gsheet..) for storage, sync, and team co-editing.

I'll use examples from a large, time-and-motion study - called Quick- of computer use by doctors at two large institutions.

Here we show how index and perform basic file census in a few lines. The star is keyTrie: a one-liner recursive trie constructor that mirrors the entire filesystem (at the given root) as nested associations.

Suppose your data is stored under a common folder, here "~/Google Drive/VASD/Projects/Quick/Data" . All data here is de-identified (it has been cleaned up from versions that are in secure storage).

quick[index] = Dataset["~/Google Drive/VASD/Projects/Quick/Data"][fileIndex /* AssociationMap[Reverse]][keyTrie]

enter image description here

Preliminary timing studies show linear time complexity (http://mathematica.stackexchange.com/a/84952/80) - attributable to the efficient hash tree implementation of Association. (Be warned if you point keyTrie at a root directory "~/Google Drive" directory will take a while to complete.)

keyTrie =  Query[keyGroupBy[First]] /* Query[All, KeyMap[Rest]] /* Query[All, If[Keys[#] == {{}}, First@Values[#], keyTrie[#]] &];

keyTrie uses the helper keyGroupBy, which is as useful as the built-in GroupBy when processing nested Associations - here is the operator form:

keyGroupBy[f_][expr_] := Association /@ GroupBy[Normal@expr, Keys /* f];

fileIndex is less interesting, but showing for completion: It filters data files, eg CSV, TXT, .gsheet etc and performs a basic filename cleanup (details upon request)

fileIndex[path_]  :=  
  FileNames["*.csv" | "*.txt" | "*.xls" | "*.xlsx" | "*.gsheet", path, Infinity] // 
     AssociationMap[Drop[StringSplit[#, "/"], Length@StringSplit[path, "/"]] &] // 
    Dataset // Query[All,MapAt[First@StringSplit[#, {".", "-", "_"}] &, #, -1] &];

At this point, files comprise data and metadata and are only indexed, not imported.

For example, here's what a portion of the folder under EHR looks like

quick[index]["VisitData", "EHR", preLeafMap[Keys]]

enter image description here

where identifiers Qxxx are units of study (patients, visits) - extracted from filenames by fileIndex above. Each file is typically a CSV or gsheet, eg:

quick[index]["VisitData", "EHR", First, First]

"~/Google Drive/VASD/Projects/Quick/Data/VisitData/EHR/EpicAccessLogs/Q115-18_epicLog.csv"

preLeafMap is a convenience operator form of Map applied at level -2:

preLeafMap[f_][expr_] := Map[f, expr, {-2}];

Note that nesting of files in folders varies by data layer, eg "HumanCodedMouseActivity" contains sub-folders "UCSD", "VASD".

Using associationFlatten a census dashboard can be obtained easily: here scaled up to "VisitData":

quick[index]["VisitData", preLeafMap[KeyDrop["meta"] /* Keys] /* associationFlatten][All, 
 GroupBy[quick[data]["Master", All, "Site"]] /* {"UCSD", "VASD"}, Replace[_Missing -> 0] /* Length]

enter image description here

where:

associationFlatten[as_Association] :=  Map[keyFlatten, as, {0, Infinity}];

and

keyFlatten[as_Association] := 
  as // KeyValueMap[
       List /* Replace[{{a_, b_Association} :> 
           KeyMap[{a, #} &, b], {a_, b_} :> <|a -> b|>}]] // 
     Map[Normal] // Flatten // Association;

keyFlatten[l_List] := l;

keyFlatten[a_ /; AtomQ[a]] := a;

Notes:

The grouping of the Qxxx into sites "UCSD" and "VASD" is based on metadata in the gsheet "Master" - which again is available to anyone in the team in real time for co-editing:

enter image description here

Once Master is imported, the GroupBy can use the derived association of PatientID to Site:

quick[data]["Master",All,"Site"]
3 Replies

Very interesting, @Alan Calvitti, thanks for sharing! Both - the research and the NoSQL workflow. But about the research, isn't it something related to mouse tracking on screen like iographica or am I way off and this is about real mice? DO you use Mathematica in your research for analysis?

The study uses data collected by usability software (TechSmith Morae) which is installed on doctors' computers - as well as video capture and other sensors, during real clinical encounters.

I use Mathematica exclusively for research and analysis and is the centerpiece of our team-based scientific workflow. The V10 functionality released in 2014 accelerated data workflow to the point where a few lines of code have replaced pages of (V9) code.

enter image description here - you earned "Featured Contributor" badge, congratulations !

Dear @Alan Calvitti, this is a great post and it has been selected for the curated Staff Picks group. Your profile is now distinguished by a "Featured Contributor" badge and displayed on the "Featured Contributor" board.

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