LeetCode #937 — MEDIUM

Reorder Data in Log Files

Move from brute-force thinking to an efficient approach using array strategy.

Solve on LeetCode
The Problem

Problem Statement

You are given an array of logs. Each log is a space-delimited string of words, where the first word is the identifier.

There are two types of logs:

  • Letter-logs: All words (except the identifier) consist of lowercase English letters.
  • Digit-logs: All words (except the identifier) consist of digits.

Reorder these logs so that:

  1. The letter-logs come before all digit-logs.
  2. The letter-logs are sorted lexicographically by their contents. If their contents are the same, then sort them lexicographically by their identifiers.
  3. The digit-logs maintain their relative ordering.

Return the final order of the logs.

Example 1:

Input: logs = ["dig1 8 1 5 1","let1 art can","dig2 3 6","let2 own kit dig","let3 art zero"]
Output: ["let1 art can","let3 art zero","let2 own kit dig","dig1 8 1 5 1","dig2 3 6"]
Explanation:
The letter-log contents are all different, so their ordering is "art can", "art zero", "own kit dig".
The digit-logs have a relative order of "dig1 8 1 5 1", "dig2 3 6".

Example 2:

Input: logs = ["a1 9 2 3 1","g1 act car","zo4 4 7","ab1 off key dog","a8 act zoo"]
Output: ["g1 act car","a8 act zoo","ab1 off key dog","a1 9 2 3 1","zo4 4 7"]

Constraints:

  • 1 <= logs.length <= 100
  • 3 <= logs[i].length <= 100
  • All the tokens of logs[i] are separated by a single space.
  • logs[i] is guaranteed to have an identifier and at least one word after the identifier.

Roadmap

  1. Brute Force Baseline
  2. Core Insight
  3. Algorithm Walkthrough
  4. Edge Cases
  5. Full Annotated Code
  6. Interactive Study Demo
  7. Complexity Analysis
Step 01

Brute Force Baseline

Problem summary: You are given an array of logs. Each log is a space-delimited string of words, where the first word is the identifier. There are two types of logs: Letter-logs: All words (except the identifier) consist of lowercase English letters. Digit-logs: All words (except the identifier) consist of digits. Reorder these logs so that: The letter-logs come before all digit-logs. The letter-logs are sorted lexicographically by their contents. If their contents are the same, then sort them lexicographically by their identifiers. The digit-logs maintain their relative ordering. Return the final order of the logs.

Baseline thinking

Start with the most direct exhaustive search. That gives a correctness anchor before optimizing.

Pattern signal: Array

Example 1

["dig1 8 1 5 1","let1 art can","dig2 3 6","let2 own kit dig","let3 art zero"]

Example 2

["a1 9 2 3 1","g1 act car","zo4 4 7","ab1 off key dog","a8 act zoo"]
Step 02

Core Insight

What unlocks the optimal approach

  • No official hints in dataset. Start from constraints and look for a monotonic or reusable state.
Interview move: turn each hint into an invariant you can check after every iteration/recursion step.
Step 03

Algorithm Walkthrough

Iteration Checklist

  1. Define state (indices, window, stack, map, DP cell, or recursion frame).
  2. Apply one transition step and update the invariant.
  3. Record answer candidate when condition is met.
  4. Continue until all input is consumed.
Use the first example testcase as your mental trace to verify each transition.
Step 04

Edge Cases

Minimum Input
Single element / shortest valid input
Validate boundary behavior before entering the main loop or recursion.
Duplicates & Repeats
Repeated values / repeated states
Decide whether duplicates should be merged, skipped, or counted explicitly.
Extreme Constraints
Upper-end input sizes
Re-check complexity target against constraints to avoid time-limit issues.
Invalid / Corner Shape
Empty collections, zeros, or disconnected structures
Handle special-case structure before the core algorithm path.
Step 05

Full Annotated Code

Source-backed implementations are provided below for direct study and interview prep.

// Accepted solution for LeetCode #937: Reorder Data in Log Files
class Solution {
    public String[] reorderLogFiles(String[] logs) {
        Arrays.sort(logs, (log1, log2) -> {
            String[] split1 = log1.split(" ", 2);
            String[] split2 = log2.split(" ", 2);

            boolean isLetter1 = Character.isLetter(split1[1].charAt(0));
            boolean isLetter2 = Character.isLetter(split2[1].charAt(0));

            if (isLetter1 && isLetter2) {
                int cmp = split1[1].compareTo(split2[1]);
                if (cmp != 0) {
                    return cmp;
                }
                return split1[0].compareTo(split2[0]);
            }

            return isLetter1 ? -1 : (isLetter2 ? 1 : 0);
        });

        return logs;
    }
}
Step 06

Interactive Study Demo

Use this to step through a reusable interview workflow for this problem.

Press Step or Run All to begin.
Step 07

Complexity Analysis

Time
O(n × log n)
Space
O(n)

Approach Breakdown

BRUTE FORCE
O(n²) time
O(1) space

Two nested loops check every pair or subarray. The outer loop fixes a starting point, the inner loop extends or searches. For n elements this gives up to n²/2 operations. No extra space, but the quadratic time is prohibitive for large inputs.

OPTIMIZED
O(n) time
O(1) space

Most array problems have an O(n²) brute force (nested loops) and an O(n) optimal (single pass with clever state tracking). The key is identifying what information to maintain as you scan: a running max, a prefix sum, a hash map of seen values, or two pointers.

Shortcut: If you are using nested loops on an array, there is almost always an O(n) solution. Look for the right auxiliary state.
Coach Notes

Common Mistakes

Review these before coding to avoid predictable interview regressions.

Off-by-one on range boundaries

Wrong move: Loop endpoints miss first/last candidate.

Usually fails on: Fails on minimal arrays and exact-boundary answers.

Fix: Re-derive loops from inclusive/exclusive ranges before coding.