PHPMem v2.0.1
Version
1.6.45
Uptime
15 days 14 hours 9 minutes 27 seconds
Memory
Total
512MB
Used
9,38MB (1.83%)
Free
502,62MB
Keys
Current
11 436
Total (since start)
35 066
Evictions
0
Reclaimed
738
Expired Unfetched
0
Evicted Unfetched
0
Connections
Current
14 / 1 024 max
Total
174 806
Rejected
0
llm:dc42e23021279aa1b7a0a14c82c0522e7023d85720a72fec67d707a91d8630b4
Edit
The dataset has one identifier, six categorical dimensions, eleven numeric metrics and one real timestamp. The catalog tags its columns with a semantic role, and I adjusted a few of those tags where they misread the data.
**Identifier**
- `user_id` is a text ID running USR-00001 to USR-08500, with no nulls. The grain is one row per user.
- The catalog's distinct count is only approximate (~7,297 against 8,500 rows), so I haven't confirmed that every ID is unique.
**Categorical dimensions**
- `gender` has about 3 values.
- `occupation_type` has about 5 values, such as Corporate 9-to-5 and Student.
- `chronotype` has about 3 values, such as Intermediate and Night Owl.
- `primary_bedtime_app` has about 6 values, such as Instagram / Reddit and YouTube.
- `sleep_debt_category` has about 4 values, from Mild Deficit to Severe Sleep Debt. It is derived from `total_sleep_hours`, so it is an outcome label rather than an independent input.
- `blue_light_filter_active` is a 0/1 flag stored as BIGINT. Treat it as a binary category and don't average it as a measure.
**Numeric metrics**
- Demographic and behavioral inputs:
- `age` (18–65)
- `bedtime_phone_minutes` (1–180)
- `screen_brightness_pct` (10–100)
- `caffeine_post_5pm_mg` (0–250)
- `physical_activity_min` (0–112)
- Sleep and next-day 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)
- `morning_alarm_snoozes` (0–7)
- `next_day_fatigue_score` (1.0–10.0)
The catalog tags `bedtime_phone_minutes` as temporal, but it is a duration in minutes, not a date or time, so it belongs with the metrics. It is also flagged as person-identifying, so aggregate it and don't quote individual values.
**Dates / times**
- `_ingestion_timestamp` is the only true timestamp. It holds a single value (2026-10-01 03:08:19), so it records when the data was loaded and cannot support trend analysis.
- The dataset has no event dates, so there is no time dimension for the sleep behaviour itself.
**Pipeline metadata (not analytical)**
- `_batch_id`, `_source_file` and `_source_system` each hold one constant value. They are lineage fields and carry no analytical signal.