Detect Stream Data Anomalies | Dataford Interview Questions

Given a series of event logs from a broadcast stream, detect missing frames or data anomalies and output a corrected time-series sequence.

Implement def correct_stream(logs):. Each log is [timestamp, value], timestamps are integers, and values are numeric or null. Return [timestamp, value] entries for every integer timestamp from the earliest to latest log. Sort out-of-order logs, keep the last entry for duplicate timestamps, and linearly interpolate missing or null values. The first and last unique timestamps always have numeric values.

Constraints

1 <= len(logs) <= 100000
Each log has the form [timestamp, value]
timestamps are integers
Values are integers, floating-point numbers, or null
The first and last unique timestamps have numeric values
The earliest timestamp is less than or equal to the latest timestamp
Return values created by interpolation as floating-point numbers when necessary

Function Signature

def correct_stream(logs):

Your question is Detect Stream Data Anomalies. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.

Problem

Given a series of event logs from a broadcast stream, detect missing frames or data anomalies and output a corrected time-series sequence.

Constraints

1 <= len(logs) <= 100000
Each log has the form [timestamp, value]
timestamps are integers
Values are integers, floating-point numbers, or null
The first and last unique timestamps have numeric values
The earliest timestamp is less than or equal to the latest timestamp
Return values created by interpolation as floating-point numbers when necessary

Function Signature

def correct_stream(logs):

Your question is Detect Stream Data Anomalies. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.