PHPMem v2.0.1
Version
1.6.45
Uptime
15 days 12 hours 52 minutes 8 seconds
Memory
Total
512MB
Used
9,60MB (1.88%)
Free
502,40MB
Keys
Current
11 840
Total (since start)
35 066
Evictions
0
Reclaimed
733
Expired Unfetched
0
Evicted Unfetched
0
Connections
Current
14 / 1 024 max
Total
173 981
Rejected
0
llm:4af05ea522eec4450fda714d1f481c89e76f6a0c37eb18edde4f73a338937d39
Edit
Of the 22 columns, one is an identifier, six are categorical dimensions, thirteen are numeric metrics, and the only true date/time column is a technical ingestion timestamp. The classification below comes from the column profile and the distinct and range checks I ran (steps 0 to 4).
**Identifier (1)**
- `user_id` is a VARCHAR primary key. All 8,500 rows have a distinct value, running from USR-00001 to USR-08500 with no nulls. The profiler's "~7,297 distinct" is only an approximation, and the exact check gave 8,500 distinct values.
**Categorical dimensions (6)**
- `gender` (3 values), `occupation_type` (5), `chronotype` (3), `primary_bedtime_app` (6) and `sleep_debt_category` (4) are text classifiers.
- `blue_light_filter_active` is stored as BIGINT but is a 0/1 flag with 2 values, so treat it as a dimension, not a metric.
- `sleep_debt_category` is derived from `total_sleep_hours`. Keep it out of any model that predicts sleep outcomes from sleep hours.
**Numeric metrics (13)**
- Behaviour and exposure:
- `bedtime_phone_minutes` (1–180)
- `screen_brightness_pct` (10–100)
- `caffeine_post_5pm_mg` (0–250)
- `physical_activity_min` (0–112)
- `age` (18–65)
- Sleep outcomes:
- `sleep_latency_min` (6.0–123.3)
- `total_sleep_hours` (3.2–9.8)
- `deep_sleep_pct` (8.1–28.0)
- `rem_sleep_pct` (9.6–27.0)
- Next-day outcomes:
- `morning_alarm_snoozes` (0–7)
- `next_day_fatigue_score` (1.0–10.0)
- The profiler tags some of these as "categorical" (for example `morning_alarm_snoozes`, `next_day_fatigue_score`, `age`) only because they have few distinct values. They are still numeric measures.
- `age` is a measure by role, though you could bin it into groups for segmentation.
**Dates and times (1 true, 1 look-alike)**
- `_ingestion_timestamp` is the only TIMESTAMP column. It holds a single value, 2026-10-01 03:08:19, so it carries no analytical time dimension.
- `bedtime_phone_minutes` is labelled "temporal" by the profiler, but it is a duration in minutes, not a date or time. Treat it as a numeric metric.
- The dataset has no event date, so there is no real time series to trend.
**Technical lineage columns (3)**
- `_batch_id`, `_source_file` and `_source_system` each have exactly 1 distinct value. They are ingestion metadata and carry no analytical value.