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HardPrep Room Coding #4661

Hot partition in time-series data

On-callDistributed systemsAlgorithms & data structuresSenior–Staff~35 min

Cassandra cluster storing IoT sensor readings, partition key = `(sensorType, day)`, clustering by timestamp. As fleet grew, write p99 climbed and some nodes show high load while others idle. `nodetool` shows a few partitions are enormous (tens of GB) and tombstone/compaction warnings on them; reads of 'latest readings' for popular sensor types time out. Only a handful of `sensorType` values are common. Triage and redesign the data model so this doesn't recur.

What a strong answer looks like

Stop the bleeding first (mitigate), then form hypotheses from real signals. Separate root cause from symptom, communicate status as you go, and close with what prevents a repeat.

0:00 of about 35 min
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