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Questions and Answers
What is the primary purpose of a hash table in the dictionary problem?
What is the primary purpose of a hash table in the dictionary problem?
What does each key in an associative array or dictionary represent?
What does each key in an associative array or dictionary represent?
Which of the following is NOT a standard solution to the dictionary problem?
Which of the following is NOT a standard solution to the dictionary problem?
What is a defining characteristic of keys in a hashmap?
What is a defining characteristic of keys in a hashmap?
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In what way can the values in a hashmap be structured?
In what way can the values in a hashmap be structured?
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What is the main advantage of using a lookup table?
What is the main advantage of using a lookup table?
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Which example demonstrates a portmanteau word?
Which example demonstrates a portmanteau word?
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What role do keys play in the functionality of a dictionary or hashmap?
What role do keys play in the functionality of a dictionary or hashmap?
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What is the primary purpose of a hash table?
What is the primary purpose of a hash table?
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What can occur when a hash function generates the same index for different keys?
What can occur when a hash function generates the same index for different keys?
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In a well-dimensioned hash table, the average cost for each lookup is:
In a well-dimensioned hash table, the average cost for each lookup is:
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Which feature makes hash tables particularly efficient compared to search trees?
Which feature makes hash tables particularly efficient compared to search trees?
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What type of objects do iterators in maps essentially reference?
What type of objects do iterators in maps essentially reference?
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What is one common application of hash tables?
What is one common application of hash tables?
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How does a hash table compute an index for a key?
How does a hash table compute an index for a key?
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What happens when a hash table has a poorly designed hash function?
What happens when a hash table has a poorly designed hash function?
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Study Notes
Hashing and Maps
- Hashing and maps are fundamental data structures in computer science
- They provide efficient ways to store and retrieve data
- A dictionary problem involves designing a data structure to maintain a set of data during search, delete, and insert operations
- Hash tables are a standard solution often used to implement a dictionary
Dictionary Problem
- The dictionary problem is a classic computer science problem
- It concerns designing a data structure to hold a set of data, supporting search, delete, and insert operations
- A dictionary structure enables efficient retrieval of information based on a given entry
Portmanteaus
- A portmanteau is a blend of words where parts of multiple words are combined into one word
- Smog (smoke + fog), motel (motor + hotel), are examples
- In linguistics, a portmanteau is a single morph analyzed as comprising multiple morphemes
- Hashmaps facilitate quick access from a key to a value
Hash Tables
- Hash tables are data structures implemented using arrays of buckets
- A hash function maps keys to indices in the array of buckets
- The desired value can be found by accessing the corresponding bucket
- Ideally, different keys map to different buckets without collisions
Hash Collisions
- Collisions occur when different keys produce the same hash code (index in the array)
- Hash table designs often employ imperfect hash functions, leading to collisions
- Collisions need to be resolved to access the correct key-value pair
Perfect Hash Function
- A perfect hash function maps distinct keys to distinct buckets
- This function avoids collisions, simplifying the process of retrieving or modifying values
- Perfect hash functions have applications similar to other hash functions; no collision resolution is required
Hash Map Example
- A HashMap allows for quick access to data based on a key
- It jumps directly to the relevant data associated with the key
Hash Function
- A hash function takes a key (input) and returns an index (output)
- This index is used to locate the value associated with the key in the hash table
Example Simplified Hash Function
- The function
hashCodetakes a string key and an integer size as input - It then calculates a hash value for the key
- The hash value is then used to ensure a value is stored at the correct position in the array
- This allows the function to calculate the position in the array
Hash Collisions
- Collisions happen when keys map to the same hash code
- This leads to inefficiency as multiple elements need checking when a value is retrieved
List Operations
- In a hash table, each bucket can be a linked list of entries
- This approach allows handling collisions
Separate Chaining
- Separate chaining handles collisions by using linked lists at each bucket
- The time for operations depends on finding the bucket in constant time plus the time for traversing the linked list
- It handles collisions by creating a linked list in that bucket that holds all records with the same hash code
Open Addressing
- In open addressing, all entries are stored directly in the bucket array
- When a collision occurs, the program searches for an alternative location within the array
- Probe sequences (searching) are used to handle potential collisions by providing secondary locations
Probe Sequences
- Well-known probe techniques such as linear, quadratic, and double hashing aim for uniform distribution
- They help to disperse elements across buckets when collisions occur
Hashmap Load Factor (α)
- The load factor is the ratio of entries to the number of buckets defining the map
- A higher load factor results in a higher memory usage and a larger chance of collisions
- A lower load factor uses more memory, but reduces the likelihood of collisions
HashMap Resizing
- When entries exceed the load factor multiplied by the capacity, a hashmap may resize to a larger number of buckets
- Rehashes existing pairs into the new larger array, maintaining performance
- Resizing reduces collisions and spreads the entries more evenly
Key Features of HashMap
- Key-Value Pairs: Each entry is a pair
- Unique Keys: A HashMap only accepts one value for each key
- Null Values: HashMap can hold null keys and null values
- Efficient Retrieval: Lookups are often fast
- Unordered: The order of elements may change
Java HashMap
- Java HashMap uses separate chaining for collision resolution
- For large buckets, it employs a tree-based structure
Hashmap and Trees
- When the number of entries within a single bucket exceeds a threshold, the linked list is replaced by a red-black tree
Hashmap Resizing Example
- If a HashMap has a capacity of 16 and a load factor of 0.75, resizing occurs when the entries exceed 12
Operations Associated with HashMap
- Addition of pairs
- Removal of pairs
- Modification of existing pairs
- Lookup of values linked to a key
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Description
Test your knowledge on hashing, maps, and the dictionary problem in computer science. This quiz covers fundamental concepts such as hash tables, efficient data retrieval, and the use of portmanteaus in linguistics. Evaluate your understanding of these essential data structures and their applications.
