LessThan / Operator Layer

Compare if values in a column are less than a constant or another column's values. Similar to pandas df['A'] < df['B'] or df['A'] < 5, numpy.less(), or R's < operator. Returns a boolean column.

Mathematical form:

Common applications:

  • Safety limits (pressure < max_safe)
  • Budget constraints (cost < budget)
  • Deadline checking (time < due_date)
  • Capacity monitoring (usage < limit)
  • Performance alerts (speed < minimum)
  • Error margins (deviation < tolerance)

Note: Comparison follows standard numeric ordering rules.

Table
0
0
Table

The primary column for comparison. Forms the left side of the less-than check (e.g., current value, measurement, actual reading).

Integer
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64-bit signed integer upper bound. Range: -2^63 to 2^63-1. Use cases:

  • Time constraints (delay < 1000ms)
  • Error limits (failures < 3)
  • Resource bounds (threads < 100)
  • Age restrictions (age < 65)
0

64-bit unsigned integer upper bound. Range: 0 to 2^64-1. Examples:

  • Memory limits (usage < max_memory)
  • Queue lengths (waiting < capacity)
  • Batch boundaries (size < chunk_size)
  • Counter thresholds (attempts < max_tries)
0

64-bit floating-point upper bound. Common scenarios:

  • Error rates (failure_rate < 0.01)
  • Statistical tests (p_value < 0.05)
  • Physical limits (temperature < 100.0)
  • Performance targets (latency < 0.5)

Other

column

The comparison column for less-than check. Common pairs:

  • usage < capacity (resource monitoring)
  • actual < budget (cost control)
  • current < threshold (limit checking)
  • measured < reference (compliance testing)

Controls null value handling:

  • true: propagates nulls (null < value returns null)
  • false: treats nulls as false

Default is true for standard SQL-like null behavior

Name for the new column. If not provided, the system generates a unique name. If AsColumn matches an existing column, the existing column is replaced. The name should follow valid column naming conventions.