The document discusses loose-schema databases and heterogeneous data. It proposes that loose-schema databases that allow array and object fields without predefined schemas may be better suited to handling heterogeneous data from different sources and communities that conceptualize data differently. CouchDB is provided as an example of a loose-schema database that stores JSON documents and uses map-reduce functions for queries, which could integrate data from two separate task systems.
range of BP values not same as range of blood glucose, systolic must be greater than diastolic
Designed to store and report on large amounts of “semi-structured” data “shared-nothing" clustering written in Erlang for robust concurrent systems; no shared state threading and all data is immutable no fixed schema, no declarative schema, update function can check consistency and permissions incremental replication, partial replicas possible; also runs on handhelds
Simple map func. Can extract subset of documents map+reduce can collect related documents (e.g. blog post & comments)
Your company uses a traditional Project Planning system, which works in terms of man-hours Blue system has project with two subprojects Your group uses an online task-tracking system like Basecamp Yellow system has three tasks, one of which has a subtask There is also software associated with the CouchDB database, which allows you to specify that yellow tasks are components of blue subprojects From this, we assign a path to each item.
Goal: Calculate # completed tasks for each item [left] documents in CouchDB (blanks are not null, but fields not present) Map function written in JavaScript, emits 0 or more values, to ANY bin (key) [go through map function for each record]
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