Labs
Each lab takes under an hour on a laptop and turns a claim from this mechanism into a number you measured yourself.
- 1
Find your own break-even point
Time a full rebuild against an incremental merge as the changed fraction grows, and find where they cross.
MeasurePython with DuckDB - 2
Trigger overhead
Time single-row and bulk inserts with and without a shadow-table trigger that records every change.
Real systemDocker, Python - 3
Watch the log retention problem happen
Create a logical replication slot, never read it, and watch the database keep its write-ahead log until the slot is dropped.
Real systemDocker, Python - 4
Aliasing in a polling pipeline
Poll a fast-changing row every few seconds and count how many of its changes, and its delete, the poller ever sees.
Break itPython - 5
What query-based CDC misses
A poller on updated_at against three changes it cannot see: intermediate updates, a delete, and a slow commit.
Real system · Break itDocker, Python - 6
Sum versus max under deletes
Maintain SUM and MAX per group under inserts and deletes, and count the rescans and memory each needs.
SimulatePython - 7
Inject loss, then catch it
Drop 0.1% of the changes in a toy CDC pipeline, catch it with a count + checksum, and crash it under three cursor-commit orders.
Break itPython