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Spark Join With Fuzzy Condition
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Spark Join With Fuzzy Condition

MediumSQL · PostgreSQL

Problem

How would you join two large datasets when the join condition is not strict, and you need to keep only the relevant rows?

Use the supplied gpu_telemetry and thermal_rules tables. Return only telemetry readings that satisfy the applicable device, validity-period, and temperature conditions.

Output

  1. One row per matching telemetry reading and rule.
  2. Columns: reading_id, device_id, measured_at, temperature_c, rule_id, severity.
  3. Order by measured_at, reading_id, and rule_id ascending.

Schema

gpu_telemetry
ColumnTypeDescription
reading_idPKINTUnique telemetry reading identifier
device_idVARCHAR(20)GPU device identifier
measured_atTIMESTAMPTime when the reading was recorded
temperature_cDECIMAL(5,2)Measured temperature in Celsius
thermal_rules
ColumnTypeDescription
rule_idPKINTUnique thermal rule identifier
device_idVARCHAR(20)GPU device to which the rule applies
valid_fromTIMESTAMPInclusive start of the rule validity period
valid_toTIMESTAMPExclusive end of the rule validity period, null means no end
min_temperature_cDECIMAL(5,2)Minimum temperature accepted by the rule
max_temperature_cDECIMAL(5,2)Maximum temperature accepted by the rule, null means no upper limit
severityVARCHAR(20)Classification assigned by the rule
Tablesgpu_telemetrythermal_rules
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