Tim Cook steps down as Apple CEO

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This week’s coding challenge was asked by Amazon 34 times in the last 3 months. Are you ready for it?

Today we will cover:

• Group Anagrams problem

• Change Data Capture

Read time: under 4 minutes

CODING CHALLENGE

Group Anagrams

Given an array of strings strs, group the anagrams together. You can return the answer in any order.

Example 1:

Input: strs = ["eat","tea","tan","ate","nat","bat"]

Output: [["bat"],["nat","tan"],["ate","eat","tea"]]

Explanation:

- There is no string in strs that can be rearranged to form "bat".
- The strings "nat" and "tan" are anagrams as they can be rearranged to form each other.
- The strings "ate", "eat", and "tea" are anagrams as they can be rearranged to form each other.

Example 2:

Input: strs = [""]

Output: [[""]]

Example 3:

Input: strs = ["a"]

Output: [["a"]]

Solve the problem here before reading the solution.

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SOLUTION

To solve this problem, we'll use a dictionary to group anagrams together. Two words are anagrams if they have the same characters with the same frequencies.

For each string, we'll sort its characters. This sorted string will be our key in the dictionary. All anagrams will have the same sorted string.

For example, "eat" and "tea" both become "aet" when sorted. We'll use this sorted string as the key and store the original strings in a list as the value.

This approach has a time complexity of O(n*k*log k), where:

• n is the number of strings in the input array

• k is the maximum length of a string

• k * log k comes from sorting each string

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SYSTEM DESIGN

Change Data Capture (CDC)

Imagine you’re designing the architecture of Instagram. When users visit a profile, they need to instantly see who this person follows. This requires querying a database table containing follower-followed relationships. To make this lookup fast, we need an index on the follower column.

But here’s the problem. To generate a user's newsfeed, we need to quickly find all the people who follow a particular user. To make this query fast, we need an index on the followed column.

Running both these queries efficiently at the same time can be challenging. We could maintain two separate databases - one indexed by follower and another indexed by followed. But this creates unnecessary write overhead. When a user follows someone, we'd need to update both databases simultaneously. This synchronous update significantly slows down the follow action and introduces potential consistency issues if one update fails while the other succeeds.

Change Data Capture (CDC) solves this problem elegantly. Instead of updating both databases synchronously, we only write to the primary database indexed on follower. CDC monitors the database's transaction logs and captures every change made to the follower table. These changes are then pushed to Apache Kafka as events.

A stream processor like Apache Flink continuously processes these events from the Kafka queue and updates the secondary database indexed by followed. This asynchronous process ensures that the follow action remains fast since it only needs to write to one database. The second database eventually catches up through the CDC pipeline.

NEWS

This Week in the Tech World

Tim Cook Steps Down as Apple CEO: After 15 years, Cook will become executive chairman. Hardware chief John Ternus takes over as CEO on September 1, tasked with fixing Apple's lagging AI strategy.

GitHub Copilot Pauses New Signups: Microsoft halted Pro and Pro+ signups as Copilot's weekly costs doubled since January. Token-based billing and tighter rate limits are on the way.

Amazon Pours $5B More Into Anthropic: Amazon's total commitment to Anthropic could reach $33B. In return, Anthropic will spend over $100B on AWS infrastructure over the next decade.

Google Unveils Ironwood TPU: Google launched its 7th-gen TPU at Cloud Next, purpose-built for inference. It also partnered with Marvell to develop new inference-optimized chips.

Windows Defender Zero-Days Exploited: Three leaked Defender flaws are being actively exploited in the wild. Microsoft patched BlueHammer, but RedSun and UnDefend remain unpatched.

Tesla AI5 Chip Hits Milestone: Musk revealed the AI5 chip is nearing production, sending Tesla stock up 8%. Two new "Terafab" facilities are planned in Austin, Texas.

Agentic AI Set to Reshape Chip Demand: Morgan Stanley forecasts agentic AI will add $32-60B in data-center CPU demand by 2030, boosting AMD, Intel, Arm, and memory makers.

Google Cloud Next 2026 Kicks Off: The conference opened in Las Vegas featuring Gemini updates, agentic AI tools, and enterprise security upgrades alongside the Ironwood TPU launch.

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