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The return type from a bulk insertion will be 201 Created, with the content of the returned structure indicating specific success or otherwise messages on a per-document basis.The content and structure of the returned JSON will depend on the transaction semantics being used for the bulk update; see Bulk document operations are non-atomic.Internally, LTREE parses the periods for me, drops the requested number of path levels and removes the extra leading period. In the statement above, the error was caused by the root node in the tree: update tree set path = 'C' where path = 'A. In the event of a crash, some of the documents may have been successfully saved, while others lost.The response structure will indicate whether the document was updated by supplying the new In this case no new revision has been created and you will need to submit the document update, with the correct revision tag, to update the document.
The information is returned as a JSON structure containing meta information about the return structure, including a list of all design documents and basic contents, consisting the ID, revision and key.
Here’s the tree I’ve been working with during the last few blog posts: In my last post, I saved this tree in my database using a series of insert statements: insert into tree (letter, path) values ('A', 'A'); insert into tree (letter, path) values ('B', 'A.
B'); insert into tree (letter, path) values ('C', 'A.
The key is the from the design document’s The bulk document API allows you to create and update multiple documents at the same time within a single request.
The basic operation is similar to creating or updating a single document, except that you batch the document structure and information.
The power of LTREE’s functions is that they seamlessly integrate with SQL, harnessing and extending the power of Postgres.