What is a common strategy for resizing a hash table?

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Question: What is a common strategy for resizing a hash table?

Options:

Correct Answer: Doubling the size

Solution:

A common strategy for resizing a hash table is to double its size when the load factor exceeds a certain threshold to maintain performance.

What is a common strategy for resizing a hash table?

What is a common strategy for resizing a hash table?

Step 1: Understand what a hash table is. A hash table is a data structure that stores key-value pairs for fast data retrieval.
Step 2: Learn about the load factor. The load factor is a measure of how full the hash table is, calculated as the number of entries divided by the total number of slots.
Step 3: Identify the threshold. A common threshold for the load factor is 0.7, meaning the table is considered too full when 70% of its slots are occupied.
Step 4: Monitor the load factor. Keep track of the load factor as you add items to the hash table.
Step 5: Decide when to resize. If the load factor exceeds the threshold (e.g., goes above 0.7), it's time to resize the hash table.
Step 6: Double the size of the hash table. Increase the number of slots in the hash table to twice its current size.
Step 7: Rehash the existing entries. After resizing, go through all the existing entries and place them into the new larger hash table using the hash function.

Hash Table Resizing – The process of increasing or decreasing the size of a hash table to maintain efficient performance based on the load factor.
Load Factor – A measure of how full the hash table is, typically defined as the number of entries divided by the number of buckets.
Threshold – A predefined limit that, when exceeded by the load factor, triggers the resizing of the hash table.