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Good morning and a great start of the week! Fresh project Data Processing Guidelines (eg Data Import

Denis Turkov
Denis Turkov VP Architecture Sprykee Posts: 39 🏛 - Council (mod)

Good morning and a great start of the week!
Fresh project Data Processing Guidelines (eg Data Import, Export, P&S) were recently published: https://documentation.spryker.com/docs/data-processing-guidelines
You are familiar with most of the content, so consider it as an additional conceptual refresh. 😉
If you would like to see any additional section there or faced pitfalls that should be addressed, please let me know ✏


  • Alberto Reyer
    Alberto Reyer Lead Spryker Solution Architect / Technical Director Posts: 690 🪐 - Explorer
    edited July 2020

    In the https://documentation.spryker.com/docs/data-processing-guidelines#common-table-expressions part there are CTE for insert and update which is suboptimal performance wise, because CTE’s will be written to the filesystem at least in Postgres (https://medium.com/@hakibenita/be-careful-with-cte-in-postgresql-fca5e24d2119).
    I assume this is done to generate the id for inserted rows.

    The same can be achieved using COALESCE and upsert.
    We reduced the runtime of a few heavy importers a lot by this change, sorry that I don’t have concrete numbers, but give it a try for your own plain SQL based importers 😉


    WITH records AS (
            COALESCE(t.id_<table>, nextval('<table>_pk_seq')) AS id_<table>,
            input."<field>" AS "<field>",
        FROM (
                     unnest(? :: VARCHAR []) AS "<field>"
             ) input
                 LEFT JOIN <table> AS t ON (t."<field>" = input."field")
    INSERT INTO <table> (
    ) SELECT
    FROM records
      "<field>" = EXCLUDED."<field>"
    RETURNING id_<table>;