FileSensor for file arrival detection in Apache Airflow - Time & Space Complexity

Time Complexity: FileSensor for file arrival detection

O(n)

Understanding Time Complexity

When using Airflow's FileSensor, it's important to understand how the time it takes to detect a file grows as the number of checks increases.

We want to know how the sensor's repeated checking affects execution time as it waits for a file.

Scenario Under Consideration

Analyze the time complexity of the following Airflow FileSensor code snippet.

from airflow.sensors.filesystem import FileSensor

file_sensor = FileSensor(
    task_id='wait_for_file',
    filepath='/path/to/file.txt',
    poke_interval=10,  # seconds
    timeout=600       # seconds
)

This code waits for a specific file to appear by checking every 10 seconds, timing out after 600 seconds if the file does not arrive.

Identify Repeating Operations

The FileSensor repeatedly checks if the file exists.

• Primary operation: Checking file existence on disk.
• How many times: Approximately timeout divided by poke_interval times (e.g., 600/10 = 60 checks).

How Execution Grows With Input

As the timeout or the number of checks increases, the total number of file existence checks grows linearly.

Input Size (number of checks)	Approx. Operations (file checks)
10	10
100	100
1000	1000

Pattern observation: The number of file checks grows directly with the number of allowed checks, so doubling checks doubles operations.

Final Time Complexity

Time Complexity: O(n)

This means the time to detect the file grows linearly with the number of checks performed.

Common Mistake

[X] Wrong: "The FileSensor checks the file only once and waits internally without repeated checks."

[OK] Correct: The sensor actually performs repeated checks at intervals, so the total time depends on how many times it checks, not just one instant check.

Interview Connect

Understanding how sensors like FileSensor scale with input helps you design efficient workflows and shows you can reason about waiting and polling mechanisms in real systems.

Self-Check

What if we changed the poke_interval to a smaller value? How would the time complexity change?