Working AtlasAnalytics aggregation

Click Counter Flush

Group click counts and compare fewer database writes with a longer wait before they are saved.

TrySet a 7-second flush and compare grouped writes with clicks still waiting to persist.

Watch forLonger flushes reduce writes but leave more synthetic clicks waiting to persist.

Project capability model

Synthetic model of this capability; it does not recreate production.

Interactive model

A constructed counter stream shows the persistence trade-off. It is an independent teaching model, not a trace of ClickTrail’s production Redis setup.

Tune the synthetic analytics stream

Click events per second4

Flush interval (seconds)4

Hot-campaign share70%

24-SECOND MODEL

From clicks to durable counters

Each column is one second. Green marks clicks persisted by a flush; amber marks the counter buffer left at that moment; coral marks buffered clicks cleared at restart. At second 12, the loss switch clears amber work before that second’s arrivals.

Second 11
Second 22
Second 33
Second 44
Second 55
Second 66
Second 77
Second 88
Second 99
Second 1010
Second 1111
Second 1212
Second 1313
Second 1414
Second 1515
Second 1616
Second 1717
Second 1818
Second 1919
Second 2020
Second 2121
Second 2222
Second 2323
Second 2424

Shared scale: 0–16 clicks

Persisted this secondPending counter bufferLost at restart

96 of 96 clicks reached the durable counter table. Peak buffered work was 16 clicks.

Clicks received

Synthetic events in the 24-second run

Grouped database writes

One write per non-empty campaign counter at each flush

Writes avoided

Compared with one database write per persisted click

Not saved

0 buffered · 0 lost at restart

BUFFER → STORE

Counter by campaign

Persisted and pending synthetic clicks for each campaign
Campaign	Stored	Buffer
launch	67	0
always-on	7	0
partner	6	0
community	8	0
other	8	0

All clicks in this run reached the durable counter table.

Preparing the interactive experiment…

Skill practicedTrade fewer writes for a longer wait before counts are saved

Connection to my workClickTrail documents Redis-backed counter aggregation; this model explores the write savings and unsaved-count risk of batching.

Related project:ClickTrail →

Understand the result

A deterministic stream groups synthetic clicks into per-campaign counters, then flushes non-empty counters at a selected interval. Compare the number of database writes with a per-click baseline, and inspect how much work remains buffered. The counters, timing, and simulated volatile-buffer loss are a teaching model, not production ClickTrail telemetry or an implementation replica.

Controls

Click events per second: Sets the number of synthetic click events added during each second of the 24-second run.
Flush interval (seconds): Sets how often each non-empty campaign counter is written as one grouped database record.
Hot-campaign share: Sets the share of events assigned to one hot campaign; remaining events rotate through four other campaigns.
Simulate lost clicks: At second 12, discard synthetic clicks still waiting to be saved.
Reset experiment: Restores the starting traffic, flush interval, campaign share, and healthy-buffer scenario.

What to watch for

Lengthen the flush interval. A single grouped record can persist more clicks, while the end-of-run buffer and peak waiting count grow.
Turn on Simulate lost clicks. Only synthetic clicks still in the buffer at second 12 are dropped; clicks flushed earlier remain stored. Real Redis recovery depends on persistence settings.
Set Hot-campaign share to 100%. Every write window then has at most one campaign record, making the per-click write reduction easy to inspect.

Why it happens

The model stores counts by campaign in a volatile buffer and flushes each non-empty counter as one record. Grouping amortizes writes, but delays persistence; this experiment deliberately discards the portion that has not yet been flushed. Whether a real Redis restart loses pending data depends on persistence, replication, retry behavior, idempotency, and transactional boundaries, none of which this compact model simulates.

How this project capability informs the model

This synthetic exercise makes the trade-off between write efficiency and persistence delay visible. It does not describe ClickTrail’s production topology, exact flush policy, or telemetry.

See the broader engineering brief