Hash Tables Chapter 11 discusses several ways of storing information in an array, and later searching for the information. Hash tables are a common approach.

Slides:



Advertisements
Similar presentations
Chapter 5 introduces the often- used data structure of linked lists. This presentation shows how to implement the most common operations on linked lists.
Advertisements

Chapter 12 discusses several ways of storing information in an array, and later searching for the information. Hash tables are a common approach to the.
Chapter 8 introduces the technique of recursive programming. As you have seen, recursive programming involves spotting smaller occurrences of a problem.
Container Classes A container class is a data type that is capable of holding a collection of items. In C++, container classes can be implemented as.
L l One of the tree applications in Chapter 9 is binary search trees. l l In Chapter 9, binary search trees are used to implement bags and sets. l l This.
 One of the tree applications in Chapter 10 is binary search trees.  In Chapter 10, binary search trees are used to implement bags and sets.  This presentation.
CSC212 Data Structure Lecture 14 Binary Search Trees Instructor: Prof. George Wolberg Department of Computer Science City College of New York.
Searching “It is better to search, than to be searched” --anonymous.
 Chapter 11 has several programming projects, including a project that uses heaps.  This presentation shows you what a heap is, and demonstrates two.
CSC212 Data Structure - Section AB Lecture 20 Hashing Instructor: Edgardo Molina Department of Computer Science City College of New York.
 Chapter 7 introduces the stack data type.  Several example applications of stacks are given in that chapter.  This presentation shows another use called.
P Chapter 6 introduces the stack data type. p Several example applications of stacks are given in that chapter. p This presentation shows another use called.
  Chapter 12 presents several common algorithms for sorting an array of integers.   Two slow but simple algorithms are Selectionsort and Insertionsort.
Searching Kruse and Ryba Ch and 9.6. Problem: Search We are given a list of records. Each record has an associated key. Give efficient algorithm.
P p Chapter 10 has several programming projects, including a project that uses heaps. p p This presentation shows you what a heap is, and demonstrates.
CSC212 Data Structure - Section FG Lecture 21 Quadratic Sorting Instructor: Zhigang Zhu Department of Computer Science City College of New York.
 Chapter 10 introduces trees.  This presentation illustrates the simplest kind of trees: Complete Binary Trees. Complete Binary Trees Data Structures.
hashing1 Hashing It’s not just for breakfast anymore!
hashing1 Hashing It’s not just for breakfast anymore!
Copyright © 1999, Carnegie Mellon. All Rights Reserved. Chapter 12 presents several common algorithms for sorting an array of integers. Two slow but simple.
L l Chapter 11 discusses several ways of storing information in an array, and later searching for the information. l l Hash tables are a common approach.
L l Chapter 4 introduces the often- used linked list data structures l l This presentation shows how to implement the most common operations on linked.
CSC212 Data Structure - Section FG Lecture 12 Stacks and Queues Instructor: Zhigang Zhu Department of Computer Science City College of New York.
 Chapter 8 introduces the queue data type.  Several example applications of queues are given in that chapter.  This presentation describes the queue.
 A Collection class is a data type that is capable of holding a group of items.  In Java, Collection classes can be implemented as a class, along with.
CSC211 Data Structures Lecture 20 Hashing Instructor: Prof. Xiaoyan Li Department of Computer Science Mount Holyoke College.
P p Chapter 11 discusses several ways of storing information in an array, and later searching for the information. p p Hash tables are a common approach.
P p Chapter 11 discusses several ways of storing information in an array, and later searching for the information. p p Hash tables are a common approach.
 An important topic: preconditions and postconditions.  They are a method of specifying what a method accomplishes. Preconditions and Postconditions.
CSC211 Data Structures Lecture 21 Quadratic Sorting Instructor: Prof. Xiaoyan Li Department of Computer Science Mount Holyoke College.
CS201: Data Structures and Discrete Mathematics I Hash Table.
CSC211 Data Structures Lecture 18 Heaps and Priority Queues Instructor: Prof. Xiaoyan Li Department of Computer Science Mount Holyoke College.
COSC 2007 Data Structures II Chapter 13 Advanced Implementation of Tables IV.
P p Chapter 10 introduces trees. p p This presentation illustrates the simplest kind of trees: Complete Binary Trees. Complete Binary Trees Data Structures.
Container Classes  A container class is a data type that is capable of holding a collection of items.  In C++, container classes can be implemented as.
CSC212 Data Structure Lecture 16 Heaps and Priority Queues Instructor: George Wolberg Department of Computer Science City College of New York.
Department of Computer Engineering Faculty of Engineering, Prince of Songkla University 1 9 – Hash Tables Presentation copyright 2010 Addison Wesley Longman,
Hashtables.
Using a Stack Chapter 6 introduces the stack data type.
Linked Lists in Action Chapter 5 introduces the often-used data public classure of linked lists. This presentation shows how to implement the most common.
CSC212 Data Structure - Section AB
Collection Classes A Collection class is a data type that is capable of holding a group of items. In Java, Collection classes can be implemented as a class,
Search by Hashing.
Using a Stack Chapter 6 introduces the stack data type.
Hash Tables Chapter 11 discusses several ways of storing information in an array, and later searching for the information. Hash tables are a common approach.
Using a Stack Chapter 6 introduces the stack data type.
Quadratic Sorting Chapter 12 presents several common algorithms for sorting an array of integers. Two slow but simple algorithms are Selectionsort and.
CSC212 Data Structure - Section AB
Heaps Chapter 10 has several programming projects, including a project that uses heaps. This presentation shows you what a heap is, and demonstrates two.
Heaps Chapter 10 has several programming projects, including a project that uses heaps. This presentation shows you what a heap is, and demonstrates two.
Heaps Chapter 11 has several programming projects, including a project that uses heaps. This presentation shows you what a heap is, and demonstrates.
Hash Tables Chapter 12 discusses several ways of storing information in an array, and later searching for the information. Hash tables are a common.
Using a Stack Chapter 6 introduces the stack data type.
Binary Search Trees One of the tree applications in Chapter 9 is binary search trees. In Chapter 9, binary search trees are used to implement bags and.
Heaps Chapter 11 has several programming projects, including a project that uses heaps. This presentation shows you what a heap is, and demonstrates.
Using a Stack Chapter 6 introduces the stack data type.
Hash Tables Chapter 12 discusses several ways of storing information in an array, and later searching for the information. Hash tables are a common.
Hash Tables Chapter 11 discusses several ways of storing information in an array, and later searching for the information. Hash tables are a common approach.
Hash Tables Chapter 12 discusses several ways of storing information in an array, and later searching for the information. Hash tables are a common.
CSC212 Data Structure - Section KL
Binary Search Trees One of the tree applications in Chapter 9 is binary search trees. In Chapter 9, binary search trees are used to implement bags and.
Using a Queue Chapter 8 introduces the queue data type.
Linked Lists in Action Chapter 5 introduces the often- used data structure of linked lists. This presentation shows how to implement the most common.
Using a Queue Chapter 8 introduces the queue data type.
Heaps Chapter 10 has several programming projects, including a project that uses heaps. This presentation shows you what a heap is, and demonstrates two.
Complete Binary Trees Chapter 9 introduces trees.
Hash Tables Chapter 11 discusses several ways of storing information in an array, and later searching for the information. Hash tables are a common approach.
Presentation transcript:

Hash Tables Chapter 11 discusses several ways of storing information in an array, and later searching for the information. Hash tables are a common approach to the storing/searching problem. This presentation introduces hash tables. This lecture illustrates hash tables, using open addressing. Before this lecture, students should have seen other forms of a Dictionary, where a collection of data is stored, and each data item has a key associated with it. Data Structures and Other Objects Using Java

What is a Hash Table ? The simplest kind of hash table is an array of records. This example has 701 records. [ 0 ] [ 1 ] [ 2 ] [ 3 ] [ 4 ] [ 5 ] [ 700] This lecture introduces hash tables, which are an array-based method for implementing a Dictionary. You should recall that we have seen dictionaries implemented in other ways, for example with a binary search tree. The abstract properties of a dictionary remain the same: We can insert items in the dictionary, and each item has a key associated with it. When we want to retrieve an item, we specify only the key, and the retrieval process finds the associated data. What we do now is use an array to implement the dictionary. The array is an array of records. In this example, we could store up to 701 records in the array. . . . An array of records

What is a Hash Table ? [ 4 ] Number 506643548 Each record has a special field, called its key. In this example, the key is a long integer field called Number. [ 0 ] [ 1 ] [ 2 ] [ 3 ] [ 4 ] [ 5 ] [ 700] Each record in the array contains two parts. The first part is a number that we'll use for the key of the item. We could use something else for the keys, such as a string. But for a hash table, numbers make the most convenient keys. . . .

What is a Hash Table ? [ 4 ] Number 506643548 The number might be a person's identification number, and the rest of the record has information about the person. [ 0 ] [ 1 ] [ 2 ] [ 3 ] [ 4 ] [ 5 ] [ 700] The numbers might be identification numbers of some sort, and the rest of the record contains information about a person. So the pattern that you see here is the same pattern that you've seen in other dictionaries: Each entry in the dictionary has a key (in this case an identifying number) and some associated data. . . .

What is a Hash Table ? When a hash table is in use, some spots contain valid records, and other spots are "empty". . . . When a hash table is being used as a dictionary, some of the array locations are in use, and other spots are "empty", waiting for a new entry to come along. Oftentimes, the empty spots are identified by a special key. For example, if all our identification numbers are positive, then we could use 0 as the Number that indicates an empty spot. With this drawing, locations [0], [4], [6], and maybe some others would all have Number=0. [ 0 ] [ 1 ] [ 2 ] [ 3 ] [ 4 ] [ 5 ] [ 700] Number 281942902 Number 233667136 Number 506643548 Number 155778322

Inserting a New Record Number 580625685 In order to insert a new record, the key must somehow be converted to an array index. The index is called the hash value of the key. . . . In order to insert a new entry, the key of the entry must somehow be converted to an index in the array. For our example, we must convert the key number into an index between 0 and 700. The conversion process is called hashing and the index is called the hash value of the key. [ 0 ] [ 1 ] [ 2 ] [ 3 ] [ 4 ] [ 5 ] [ 700] Number 281942902 Number 233667136 Number 506643548 Number 155778322

Inserting a New Record Typical way create a hash value: Number 580625685 Typical way create a hash value: (Number mod 701) What is (580625685 mod 701) ? . . . There are many ways to create hash values. Here is a typical approach. a. Take the key mod 701 (which could be anywhere from 0 to 700). So, quick, what is (580,625,685 mod 701) ? [ 0 ] [ 1 ] [ 2 ] [ 3 ] [ 4 ] [ 5 ] [ 700] Number 281942902 Number 233667136 Number 506643548 Number 155778322

Inserting a New Record 3 Typical way to create a hash value: Number 580625685 Typical way to create a hash value: (Number mod 701) 3 What is (580625685 mod 701) ? . . . Three. [ 0 ] [ 1 ] [ 2 ] [ 3 ] [ 4 ] [ 5 ] [ 700] Number 281942902 Number 233667136 Number 506643548 Number 155778322

Inserting a New Record [3] Number 580625685 The hash value is used for the location of the new record. [3] . . . So, this new item will be placed at location [3] of the array. [ 0 ] [ 1 ] [ 2 ] [ 3 ] [ 4 ] [ 5 ] [ 700] Number 281942902 Number 233667136 Number 506643548 Number 155778322

Inserting a New Record The hash value is used for the location of the new record. . . . The hash value is always used to find the location for the record. [ 0 ] [ 1 ] [ 2 ] [ 3 ] [ 4 ] [ 5 ] [ 700] Number 281942902 Number 233667136 Number 580625685 Number 506643548 Number 155778322

Collisions Number 701466868 Here is another new record to insert, with a hash value of 2. My hash value is [2]. . . . Sometimes, two different records might end up with the same hash value. [ 0 ] [ 1 ] [ 2 ] [ 3 ] [ 4 ] [ 5 ] [ 700] Number 281942902 Number 233667136 Number 580625685 Number 506643548 Number 155778322

When a collision occurs, Collisions Number 701466868 This is called a collision, because there is already another valid record at [2]. When a collision occurs, move forward until you find an empty spot. . . . This is called a collision. When a collision occurs, the insertion process will move forward through the array until an empty spot is found. Sometimes you will have a second collision... [ 0 ] [ 1 ] [ 2 ] [ 3 ] [ 4 ] [ 5 ] [ 700] Number 281942902 Number 233667136 Number 580625685 Number 506643548 Number 155778322

When a collision occurs, Collisions Number 701466868 This is called a collision, because there is already another valid record at [2]. When a collision occurs, move forward until you find an empty spot. . . . ...and a third collision... [ 0 ] [ 1 ] [ 2 ] [ 3 ] [ 4 ] [ 5 ] [ 700] Number 281942902 Number 233667136 Number 580625685 Number 506643548 Number 155778322

When a collision occurs, Collisions Number 701466868 This is called a collision, because there is already another valid record at [2]. When a collision occurs, move forward until you find an empty spot. . . . But if there are any empty spots, eventually you will reach an empty spot, and the new item is inserted here. [ 0 ] [ 1 ] [ 2 ] [ 3 ] [ 4 ] [ 5 ] [ 700] Number 281942902 Number 233667136 Number 580625685 Number 506643548 Number 155778322

Collisions This is called a collision, because there is already another valid record at [2]. The new record goes in the empty spot. . . . The new record is always placed in the first available empty spot, after the hash value. [ 0 ] [ 1 ] [ 2 ] [ 3 ] [ 4 ] [ 5 ] [ 700] Number 281942902 Number 233667136 Number 580625685 Number 506643548 Number 701466868 Number 155778322

A Quiz Where would you be placed in this table, if there is no collision? Use your social security number or some other favorite number. . . . Time for another quiz . . . Did anyone end up with a hash value of 700? Well, I did. My ID number is 155779023, which has a hash value of 700. (No, not really, but I needed to illustrate another kind of collision. There is a collision with the last location of the array. In this case, you would circle back to the start of the array, and try location number 0, then 1, .... until you find an empty spot. In this example, I would be inserted at location 0, since that location is empty. [ 0 ] [ 1 ] [ 2 ] [ 3 ] [ 4 ] [ 5 ] [ 700] Number 281942902 Number 233667136 Number 580625685 Number 506643548 Number 701466868 Number 155778322

Searching for a Key Number 701466868 The data that's attached to a key can be found fairly quickly. . . . It is fairly easy to search for a particular item based on its key. [ 0 ] [ 1 ] [ 2 ] [ 3 ] [ 4 ] [ 5 ] [ 700] Number 281942902 Number 233667136 Number 580625685 Number 506643548 Number 701466868 Number 155778322

Searching for a Key Calculate the hash value. Number 701466868 Calculate the hash value. Check that location of the array for the key. My hash value is [2]. Not me. . . . Start by computing the hash value, which is 2 in this case. Then check location 2. If location 2 has a different key than the one you are looking for, then move forward... [ 0 ] [ 1 ] [ 2 ] [ 3 ] [ 4 ] [ 5 ] [ 700] Number 281942902 Number 233667136 Number 580625685 Number 506643548 Number 701466868 Number 155778322

Searching for a Key Number 701466868 Keep moving forward until you find the key, or you reach an empty spot. My hash value is [2]. Not me. . . . ...if the next location is not the one we are looking for, then keep moving forward... [ 0 ] [ 1 ] [ 2 ] [ 3 ] [ 4 ] [ 5 ] [ 700] Number 281942902 Number 233667136 Number 580625685 Number 506643548 Number 701466868 Number 155778322

Searching for a Key Number 701466868 Keep moving forward until you find the key, or you reach an empty spot. My hash value is [2]. Not me. . . . Keep moving forward until you find the sought-after key... [ 0 ] [ 1 ] [ 2 ] [ 3 ] [ 4 ] [ 5 ] [ 700] Number 281942902 Number 233667136 Number 580625685 Number 506643548 Number 701466868 Number 155778322

Searching for a Key Number 701466868 Keep moving forward until you find the key, or you reach an empty spot. My hash value is [2]. Yes! . . . In this case we find the key at location [5]. [ 0 ] [ 1 ] [ 2 ] [ 3 ] [ 4 ] [ 5 ] [ 700] Number 281942902 Number 233667136 Number 580625685 Number 506643548 Number 701466868 Number 155778322

Searching for a Key Number 701466868 When the item is found, the information can be copied to the necessary location. My hash value is [2]. Yes! . . . The data from location [5] can then be copied to to provide the result of the search function. What happens if a search reaches an empty spot? In that case, it can halt and indicate that the key was not in the hash table. [ 0 ] [ 1 ] [ 2 ] [ 3 ] [ 4 ] [ 5 ] [ 700] Number 281942902 Number 233667136 Number 580625685 Number 506643548 Number 701466868 Number 155778322

Deleting a Record Records may also be deleted from a hash table. Please delete me. . . . Records can be deleted from a hash table... [ 0 ] [ 1 ] [ 2 ] [ 3 ] [ 4 ] [ 5 ] [ 700] Number 281942902 Number 233667136 Number 580625685 Number 506643548 Number 701466868 Number 155778322

Deleting a Record Records may also be deleted from a hash table. But the location must not be left as an ordinary "empty spot" since that could interfere with searches. . . . But the spot of the deleted record cannot be left as an ordinary empty spot, since that would interfere with searches. (Remember that a search can stop when it reaches an empty spot.) [ 0 ] [ 1 ] [ 2 ] [ 3 ] [ 4 ] [ 5 ] [ 700] Number 281942902 Number 233667136 Number 580625685 Number 701466868 Number 155778322

Deleting a Record Records may also be deleted from a hash table. But the location must not be left as an ordinary "empty spot" since that could interfere with searches. The location must be marked in some special way so that a search can tell that the spot used to have something in it. . . . Instead we must somehow mark the location as "a location that used to have something here, but no longer does." We might do this by using some other special value for the Number field of the record. In any case, a search can not stop when it reaches "a location that used to have something here". A search can only stop when it reaches a true empty spot. [ 0 ] [ 1 ] [ 2 ] [ 3 ] [ 4 ] [ 5 ] [ 700] Number 281942902 Number 233667136 Number 580625685 Number 701466868 Number 155778322

Summary Hash tables store a collection of records with keys. The location of a record depends on the hash value of the record's key. When a collision occurs, the next available location is used. Searching for a particular key is generally quick. When an item is deleted, the location must be marked in a special way, so that the searches know that the spot used to be used. A quick summary . . .

Took Data Structures in Fall 1993. Grade A. Kathy Martin 817339024 Took Data Structures in Fall 1993. Grade A. Hard worker. Always gets things done on time. Currently working for Hewlett-Packard in Fort Collins. To finish things off, I have hard copies of the next five slides. I tell the students that these are some records of my past students and I want to store them in a small hash table with size 5 (indexes 0 to 4). Of course, this is an unrealistic size, but it makes sure that they know the insertion, searching, and deletion algorithms. I then use five students from the front row to be the hash table locations. I insert the five items, remove Bill Clinton and do three searches (for Will Smith, Bill Clinton, and Elizabeth).

Will Smith 506643973 Took Data Structures in Fall 1995. Grade A. A bit of a goof-off, but he comes through in a pinch. Currently saving the world from alien invasion.

William “Bill” Clinton 330220393 Took Data Structures in Fall 1998. Grade B-. Gets along with most people well. Currently working for federal government.

Elizabeth Windsor 092223340 Took Data Structures in Fall 1997. Grade B-. Prefers to be called “Elizabeth II” or “Her Majesty.” Has some family problems. Currently working in public relations near London.

Al Einstein 699200102 Took CSCI 2270 in Fall 1995. Grade F. In spite of poor grade, I think there is good academic ability in Al. Currently a well-known advocate for peace.

THE END Presentation copyright 1998 Addison Wesley Longman, For use with Data Structures and Other Objects Using Java by Michael Main. Some artwork in the presentation is used with permission from Presentation Task Force (copyright New Vision Technologies Inc) and Corel Gallery Clipart Catalog (copyright Corel Corporation, 3G Graphics Inc, Archive Arts, Cartesia Software, Image Club Graphics Inc, One Mile Up Inc, TechPool Studios, Totem Graphics Inc). Students and instructors who use Data Structures and Other Objects Using Java are welcome to use this presentation however they see fit, so long as this copyright notice remains intact. Feel free to send your ideas to: Michael Main main@colorado.edu THE END