SShortSingh.
Back to feed

Migrating Lotus Notes Documents to SQL Server: Mapping Fields to Tables

0
·3 views

A migration from a twenty-year-old Lotus Notes application to SQL Server requires deciding how bag-of-items documents map onto relational tables. The article recommends building the schema from a census of every item name across all documents, since form designs don't reflect what existing data actually contains. Multi-valued fields such as approver lists should become child tables that preserve position, because workflow order matters. Response hierarchies map to a parent_id foreign key, with the original UNID retained. Notes hierarchical user names also need a dedicated name-resolution table, since they don't correspond to logins in the new system.

Read the full story at DEV Community

This is an AI-generated summary. ShortSingh links to the original source for the complete article.

Discussion (0)

Log in to join the discussion and vote.

Log in

Related stories

0
ProgrammingDEV Community ·

CogniPrep adds three hub pages explaining assessment tests to new users

CogniPrep recently launched three hub pages aimed at people unfamiliar with assessment vendors. Two cover the same subject for different markets: a British English page on psychometric tests for UK graduate schemes, and a US English page on pre-employment tests organised by role type. A third page covers game-based assessments across vendors and is market-neutral. The author notes the two regional pages differ in substance, not just in a find-and-replace of spelling. Some shared components, such as footer labels, URL slugs and schema.org markup, still carry mixed spelling because regional pages cannot override them.

0
ProgrammingDEV Community ·

Munchable adds an eighth condition, exposing how hardcoded counts drifted out of sync

Munchable, a tool that checks packaged food against digestive-condition rule sets, expanded from seven conditions to eight. A single commit touched 63 files, and a dozen of the changes were one-line edits replacing the spelled-out word "seven" in copy across the app, docs, and shared packages. The author notes the number had been scattered through the codebase as literal text rather than derived from the data. A test checking the phrase also hardcoded "seven", so it kept passing despite the copy becoming wrong. The fix was to compute the count from the condition registry and have the tests import the same constant the pages render.

0
ProgrammingDEV Community ·

Header Normalization Can Create Column Collisions in Order CSV Files

An order file containing both 'Order ID' and 'order_id' can become ambiguous if header names are trimmed and normalized before lookup construction. When two columns map to the same key, the value used for an order reference may depend on which column overwrote the other. The proposed remedy is to validate the full header set before mapping rows, rejecting ambiguous normalized names outright. The author, of YX Fulfillment, presents a JavaScript example that applies NFKC normalization, trimming, lowercasing, and whitespace-to-underscore replacement, and throws on duplicate keys or missing required fields. The example is described as an independent file-adapter check rather than a production connector.

0
ProgrammingDEV Community ·

Developer builds Bakeoff on Switch to pick one of several competing pull requests

A developer ran the Switch agent platform headless on a small cloud server to help a team choose among several AI-generated pull requests for the same issue. Switch's maintainer had said only one PR would be selected per issue, after a hackathon left its repository with nearly 400 open PRs. The developer's tool, Bakeoff, opens a Switch chat room whenever two or more PRs reference the same issue, where two agents from different vendors review each diff against the issue's checklist. A maintainer then picks a winner, a person approves the merge through an approval card, and the other PRs receive notes listing the checklist items they missed. The post walks first-time users through Switch's setup, including Docker Compose configuration, agent enrollment, and agent roles, and describes several snags encountered along the way.