Microsoft's Rust Plan

Welcome back!

This week, we will solve the most popular number puzzle on the planet. Back in the day, many people would buy a newspaper just to solve this puzzle. Are you ready?

Today we will cover:

• Valid Sudoku

• Optimistic vs Pessimistic Locking

Read time: under 4 minutes

CODING CHALLENGE

Valid Sudoku

Determine if a 9 x 9 Sudoku board is valid. Only the filled cells need to be validated according to the following rules:

1. Each row must contain the digits 1-9 without repetition.

2. Each column must contain the digits 1-9 without repetition.

3. Each of the nine 3 x 3 sub-boxes of the grid must contain the digits 1-9 without repetition.

Note:

A Sudoku board (partially filled) could be valid but is not necessarily solvable.

Only the filled cells need to be validated according to the mentioned rules.

Example 1:

Input: board = 
[["5","3",".",".","7",".",".",".","."]
,["6",".",".","1","9","5",".",".","."]
,[".","9","8",".",".",".",".","6","."]
,["8",".",".",".","6",".",".",".","3"]
,["4",".",".","8",".","3",".",".","1"]
,["7",".",".",".","2",".",".",".","6"]
,[".","6",".",".",".",".","2","8","."]
,[".",".",".","4","1","9",".",".","5"]
,[".",".",".",".","8",".",".","7","9"]]
Output: true

Example 2:

Input: board = 
[["8","3",".",".","7",".",".",".","."]
,["6",".",".","1","9","5",".",".","."]
,[".","9","8",".",".",".",".","6","."]
,["8",".",".",".","6",".",".",".","3"]
,["4",".",".","8",".","3",".",".","1"]
,["7",".",".",".","2",".",".",".","6"]
,[".","6",".",".",".",".","2","8","."]
,[".",".",".","4","1","9",".",".","5"]
,[".",".",".",".","8",".",".","7","9"]]
Output: false
Explanation: Same as Example 1, except with the 5 in the top left corner being modified to 8. Since there are two 8's in the top left 3x3 sub-box, it is invalid.

Solve the problem here before reading the solution.

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SOLUTION

To solve this problem, we'll validate the Sudoku board by checking three conditions:

1. No repetition in rows

2. No repetition in columns

3. No repetition in 3x3 sub-boxes

We'll use sets to efficiently track unique digits in each row, column, and sub-box. By checking each condition during a pass through the board, we can determine its validity.

Time complexity is O(1) since the board size is fixed at 9x9. Space complexity is also O(1) as we're using a constant amount of extra space.

SYSTEM DESIGN

Optimistic vs Pessimistic Locking

When multiple users try to update the same data in a database simultaneously, it can lead to data inconsistency. For example, if two bank tellers try to update a customer's balance at the same time, one update might override the other. Database locking helps prevent such conflicts.

There are two main approaches to handle concurrent updates: Optimistic Locking and Pessimistic Locking.

Optimistic Locking assumes conflicts are rare. It lets users make changes freely but checks for conflicts before saving. Each record has a version number that increases with each update. When saving changes, the system verifies if the last version number matches what it was when the user started editing. If someone else made changes in between, the version numbers won't match, and the save fails.

This approach works well for systems where conflicts are uncommon, like social media posts where users typically edit their own content. It's also more efficient since it doesn't block other users from reading or editing.

Pessimistic Locking takes a more cautious approach. When a user starts editing a record, it gets locked immediately. Other users must wait until the first user finishes.

This approach is better for systems where conflicts are likely and data consistency is crucial, like banking transactions. But it can create performance issues if locks are held for too long, as other users are forced to wait.

Here's how they compare:

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NEWS

This Week in the Tech World

Microsoft's Rust Plan: Microsoft plans to eliminate all C/C++ code by 2030, replacing it with Rust using AI-assisted refactoring. The company's goal is "1 engineer, 1 month, 1 million lines of code."

Nvidia Acquires Groq Tech: Nvidia licenses Groq's inference technology for a reported $20 billion and hires founder Jonathan Ross. Groq's LPU chip claims 10x faster inference using one-tenth the energy.

Google Buys Intersect Power: Alphabet acquires data center and energy infrastructure firm Intersect for $4.75 billion plus debt. The deal secures gigawatts of power capacity for Google's AI data centers.

GitHub Copilot Goes Free: GitHub launched a free Copilot tier offering 2,000 code completions and 50 chat messages monthly. Users can access Claude 3.5 Sonnet and choose from multiple AI models.

TikTok Sale Finalized: TikTok signed agreements to sell its U.S. operations to Oracle, Silver Lake, and MGX. ByteDance retains under 20% ownership with the deal closing January 22.

Snowflake Backs AtScale: AtScale announced new equity financing led by Snowflake to deepen integration for enterprise AI and data analytics stacks across cloud platforms.

Nscale Raises $865M: UK-based Nscale secured $865 million in funding to expand its specialized GPU-as-a-Service infrastructure in the U.S. for AI workloads.

Data Center Water Usage: New reports reveal major tech companies' AI data centers are consuming massive water volumes in drought-prone regions, raising sustainability concerns.

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