3. Using Go language, try to explain how to implement a direct addressing table. The keywords of each element in the table do not have to be different, and each element can have satellite data. All three dictionary operations (INSERT, DELETE and SEARCH) should run in O(1) time (don’t forget that DELETE deals with the pointer variable of the deleted object, not the keyword.)
Wenxin said, the code runs normally:
In Go language, we can use map data structure to implement direct addressing table. This is because the bottom layer of Go’s map is a hash table, and the time complexity of its search, insertion and deletion operations is O(1).
Here is an implementation:
package main
import "fmt"
//Define satellite data type
type satelliteData struct {<!-- -->
data int
}
//Define direct addressing table structure
type directAddressTable struct {<!-- -->
table map[int]*satelliteData
}
//Create a new direct addressing table
func NewDirectAddressTable() *directAddressTable {<!-- -->
return & amp;directAddressTable{<!-- -->table: make(map[int]*satelliteData)}
}
//Insert element
func (d *directAddressTable) Insert(key int, satelliteData *satelliteData) {<!-- -->
d.table[key] = satelliteData
}
// delete element
func (d *directAddressTable) Delete(key int) {<!-- -->
delete(d.table, key)
}
// Find element
func (d *directAddressTable) Search(key int) *satelliteData {<!-- -->
return d.table[key]
}
func main() {<!-- -->
//Create a new direct addressing table
dart := NewDirectAddressTable()
//Create satellite data
satellite1 := & amp;satelliteData{<!-- -->data: 100}
satellite2 := & amp;satelliteData{<!-- -->data: 200}
//Insert satellite data into direct addressing table
dart.Insert(1, satellite1)
dart.Insert(2, satellite2)
//Search element
fmt.Println(dart.Search(1).data) // Output: 100
fmt.Println(dart.Search(2).data) // Output: 200
// delete element
dart.Delete(1)
fmt.Println(dart.Search(1)) // Output: <nil> because the element has been removed
}
In this implementation, satellite data is stored in a map of directly addressed tables. Satellite data is a simple structure containing a field of type int. The direct addressing table contains a map of pointers to satellite data. In this way, we can store and manipulate satellite data, and the key is the key to the satellite data.
Iflytek Spark, the code runs normally:
To implement a directly addressed table, we can use a hash table as the underlying data structure. The advantage of a hash table is that the time complexity of search, insertion and deletion operations is O(1). The following is a direct addressing table implemented in Go language:
package main
import (
"fmt"
)
type Entry struct {<!-- -->
Key int
Value interface{<!-- -->}
}
type HashTable struct {<!-- -->
table[]*Entry
size int
}
func NewHashTable(size int) *HashTable {<!-- -->
return & amp;HashTable{<!-- -->
table: make([]*Entry, size),
size: size,
}
}
func (h *HashTable) hash(key int) int {<!-- -->
return key % h.size
}
func (h *HashTable) Insert(key int, value interface{<!-- -->}) {<!-- -->
index := h.hash(key)
entry := & amp;Entry{<!-- -->Key: key, Value: value}
h.table[index] = entry
}
func (h *HashTable) Search(key int) (interface{<!-- -->}, bool) {<!-- -->
index := h.hash(key)
entry := h.table[index]
if entry == nil || entry.Key != key {<!-- -->
return nil, false
}
return entry.Value, true
}
func (h *HashTable) Delete(key int) {<!-- -->
index := h.hash(key)
entry := h.table[index]
if entry == nil || entry.Key != key {<!-- -->
return
}
h.table[index] = nil
}
func main() {<!-- -->
hashTable := NewHashTable(10)
hashTable.Insert(1, "one")
hashTable.Insert(11, "eleven")
hashTable.Insert(21, "twenty one")
value, ok := hashTable.Search(1)
fmt.Println("Search key 1:", value, ok)
value, ok = hashTable.Search(11)
fmt.Println("Search key 11:", value, ok)
value, ok = hashTable.Search(21)
fmt.Println("Search key 21:", value, ok)
hashTable.Delete(11)
value, ok = hashTable.Search(11)
fmt.Println("Search key 11 after delete:", value, ok)
}
In this implementation, we define an Entry structure to store key-value pairs, and a HashTable structure to represent a hash table. HashTable contains a table slice that stores Entry pointers. We also implemented the Insert, Search and Delete methods for inserting, finding and deleting elements respectively. The time complexity of these methods is O(1).
360 Intelligent Brain, the code cannot be run:
A direct-addressed table is a key-based linear data structure in which each element has a unique key. In a directly addressed table, elements can be quickly accessed via keywords. In order to perform INSERT, DELETE and SEARCH operations in O(1) time complexity, we can use the Go language to implement the following code:
package main
import (
"fmt"
)
type Data struct {<!-- -->
key int
}
type DirectAddress struct {<!-- -->
table [100]map[int]*Data
}
func NewDirectAddress() *DirectAddress {<!-- -->
return &DirectAddress{<!-- -->}
}
func (da *DirectAddress) Insert(x *Data) {<!-- -->
if len(*da.table) >= 100 {<!-- -->
fmt.Println("Table is full.")
return
}
table := (*da.table)[:100]
for k, d := range x.key {<!-- -->
table = table[k : k + 100]
}
table = make(map[int]*Data)
for i, key := range table {<!-- -->
if key == x.key {<!-- -->
*da.table[i] = x
return
}
}
table[x.key] = x
}
func (da *DirectAddress) Delete(x *Data) {<!-- -->
if len(*da.table) == 0 {<!-- -->
fmt.Println("Table is empty.")
return
}
table := (*da.table)[:100]
for k, d := range x.key {<!-- -->
table = table[k : k + 100]
}
for i, key := range table {<!-- -->
if key == x.key {<!-- -->
delete(table,i)
return
}
}
fmt.Println("No element found with the key:", x.key)
}
func (da *DirectAddress) Search(x *Data) *Data {<!-- -->
if len(*da.table) == 0 || (*da.table)[0][x.key] == nil {<!-- -->
fmt.Println("Table is empty or first entry has no satellite data.")
return nil
}
table := (*da.table)[:100]
for k, d := range x.key {<!-- -->
table = table[k : k + 100]
}
return (*da.table)[0][x.key]
}
func main() {<!-- -->
da := NewDirectAddress()
da.Insert( & amp;Data{<!-- -->key: 1})
da.Insert( & amp;Data{<!-- -->key: 2})
da.Insert( & amp;Data{<!-- -->key: 3})
da.Delete( & amp;Data{<!-- -->key: 1})
da.Search( & amp;Data{<!-- -->key: 1})
}
In the above code, we use the map data structure of the Go language to store elements and their keywords. During insertion, deletion and search operations, we iterate over the entire key-value pair to complete the operation in O(1) time. Additionally, we used pointers to access satellite data for better performance.
The wisdom spectrum is clear, the code cannot be run:
In Go language, you can use hash tables to implement direct addressing tables. In order to achieve O(1) time complexity, we need to perform certain optimizations on the hash table. The following is an implementation of a directly addressed table, including INSERT, DELETE, and SEARCH operations:
package main
import (
"container/hash"
"fmt"
)
type Node struct {<!-- -->
Key string
Value interface{<!-- -->}
Next *Node
}
type DirectAddressTable struct {<!-- -->
Size int
HashCode int
Root*Node
}
func NewDirectAddressTable(size int) *DirectAddressTable {<!-- -->
return & amp;DirectAddressTable{<!-- -->
Size: size,
HashCode: -1,
Root: nil,
}
}
func (d *DirectAddressTable) INSERT(key string, value interface{<!-- -->}) {<!-- -->
if d.HashCode == -1 {<!-- -->
d.HashCode = calculateHashCode(key)
}
node := & amp;Node{<!-- -->Key: key, Value: value}
insertNode(d.Root, node)
d.Size++
}
func insertNode(node *Node, newNode *Node) {<!-- -->
if node == nil {<!-- -->
return
}
if newNode.Key < node.Key {<!-- -->
node.Next = insertNode(node.Next, newNode)
} else {<!-- -->
newNode.Next = node
}
}
func (d *DirectAddressTable) SEARCH(key string) (interface{<!-- -->}, bool) {<!-- -->
node := d.searchNode(d.Root, key)
if node != nil {<!-- -->
return node.Value, true
}
return nil, false
}
func searchNode(node *Node, key string) *Node {<!-- -->
if node == nil {<!-- -->
return nil
}
if node.Key == key {<!-- -->
return node
}
if key < node.Key {<!-- -->
return searchNode(node.Next, key)
}
return searchNode(node.Next, key)
}
func (d *DirectAddressTable) DELETE(key string) {<!-- -->
d.Root = d.deleteNode(d.Root, key)
d.Size--
}
func deleteNode(node *Node, key string) *Node {<!-- -->
if node == nil {<!-- -->
return nil
}
if key < node.Key {<!-- -->
node.Next = deleteNode(node.Next, key)
} else if key == node.Key {<!-- -->
if node.Next == nil {<!-- -->
return nil
}
nextNode := node.Next
node.Next = nil
return nextNode
}
return deleteNode(node.Next, key)
}
func calculateHashCode(key string) int {<!-- -->
hashCode := 0
for _, char := range key {<!-- -->
hashCode = hash.String(char) + hashCode
}
return hashCode
}
func main() {<!-- -->
table := NewDirectAddressTable(10)
table.INSERT("apple", "fruit")
table.INSERT("banana", "fruit")
table.INSERT("orange", "fruit")
value, found := table.SEARCH("apple")
if found {<!-- -->
fmt.Println("Found:", value)
} else {<!-- -->
fmt.Println("Not found")
}
table.DELETE("apple")
value, found = table.SEARCH("apple")
if found {<!-- -->
fmt.Println("Found:", value)
} else {<!-- -->
fmt.Println("Not found")
}
}
In this implementation, we use a pointer to the next node for satellite data. INSERT, DELETE, and SEARCH operations all run in O(1) time. However, this implementation uses a simple string hash function, which may not guarantee O(1) time complexity in practical applications. To achieve O(1) time complexity, a more efficient hash function or an improved lookup algorithm can be used.
Tongyi Qianwen, the code runs normally, plus package main:
In the Go language, you can use map to implement direct addressing tables. map is an alias for an associative array or hash table that associates unique keys with corresponding values. The time complexity of its insertion, deletion and search operations is O(1), which meets the requirements of the question.
Here’s a simple example:
type SatelliteData struct {<!-- -->
//Define the structure of satellite data
}
func main() {<!-- -->
directAddressingTable := make(map[string]*SatelliteData)
//Insert element
satelliteData := & amp;SatelliteData{<!-- -->}
directAddressingTable["key"] = satelliteData
// Find element
if value, ok := directAddressingTable["key"]; ok {<!-- -->
fmt.Println("Found:", value)
} else {<!-- -->
fmt.Println("Not found")
}
// delete element
delete(directAddressingTable, "key")
// Verify if the element has been deleted
if _, ok := directAddressingTable["key"]; !ok {<!-- -->
fmt.Println("Deleted")
}
}
In this example, we define a structure named SatelliteData as satellite data. We then created an empty map and set its type to a map of strings to SatelliteData pointers. We can insert, find and delete elements by given key.
Note that when we delete an element, we are passing the key, not the value or satellite data. This is because a map accesses its elements by key. Once we associate a specific key with a value, we cannot change the key or we will lose the reference to that value. So if we want to delete an element, we need to know its key.
Tiangong, the code runs normally:
In the Go language, we can use a hash table to implement a direct addressing table, that is, a data structure that directly accesses elements in the table through keywords. Here is a simple example code:
package main
import "fmt"
type Node struct {<!-- -->
Key int
Data string
Deleted bool
}
type DirectAddressTable struct {<!-- -->
Table[]*Node
}
func NewDirectAddressTable(size int) *DirectAddressTable {<!-- -->
return & amp;DirectAddressTable{<!-- -->
Table: make([]*Node, size),
}
}
func (dat *DirectAddressTable) Insert(key int, data string) {<!-- -->
node := & amp;Node{<!-- -->
Key: key,
Data: data,
}
dat.Table[key] = node
}
func (dat *DirectAddressTable) Delete(key int) {<!-- -->
if dat.Table[key] != nil {<!-- -->
dat.Table[key].Deleted = true
}
}
func (dat *DirectAddressTable) Search(key int) *Node {<!-- -->
if dat.Table[key] != nil & amp; & amp; !dat.Table[key].Deleted {<!-- -->
return dat.Table[key]
}
return nil
}
func main() {<!-- -->
dat := NewDirectAddressTable(100)
dat.Insert(10, "Data for key 10")
dat.Insert(20, "Data for key 20")
dat.Insert(30, "Data for key 30")
dat.Insert(40, "Data for key 40")
fmt.Println(dat.Search(10))
fmt.Println(dat.Search(20))
fmt.Println(dat.Search(30))
fmt.Println(dat.Search(40))
dat.Delete(20)
fmt.Println(dat.Search(20))
}
In this example, we define a Node structure to represent the elements in the direct addressing table. Each element contains a keyword Key and satellite data Data. The DirectAddressTable structure represents the entire direct addressing table, where Table is a slice pointing to Node. In the Insert operation, we use the Key as the index and insert the Node into the corresponding position in the Table; in the Delete operation, we set the Deleted field to true means that the element has been deleted; in the Search operation, we find and return the corresponding Node based on the Key. If the Node exists and has not been deleted, the Node is returned, otherwise nil is returned.
In this way, for Insert, Delete and Search operations, they can all be completed with O(1) time complexity, because we directly access and operate the corresponding elements through Key. It should be noted that the Delete operation deals with the pointer variable of the deleted object, not the keyword itself.
The above is a simple implementation example of a direct addressing table. You can further expand and optimize the code according to your own needs.
Ling Xiaozhi, the code runs normally:
In the Go language, a hash table can be used to implement a direct addressing table, which meets the requirements that the keywords of each element do not have to be different, and each element can have satellite data. A hash table is a data structure for fast lookup based on the hash value of a key.
The following is a simple example code that demonstrates how to use a hash table to implement a directly addressed table and guarantee that the running time of INSERT, DELETE and SEARCH operations is O(1):
package main
import (
"fmt"
)
type Element struct {<!-- -->
Key int
Satellite string
Next *Element
}
type Dictionary struct {<!-- -->
Table[]*Element
Size int
}
func NewDictionary(size int) *Dictionary {<!-- -->
return & amp;Dictionary{<!-- -->
Table: make([]*Element, size),
Size: size,
}
}
func (d *Dictionary) hash(key int) int {<!-- -->
return key%d.Size
}
func (d *Dictionary) Insert(key int, satellite string) {<!-- -->
hashKey := d.hash(key)
element := & amp;Element{<!-- -->Key: key, Satellite: satellite}
if d.Table[hashKey] == nil {<!-- -->
d.Table[hashKey] = element
} else {<!-- -->
current := d.Table[hashKey]
for current.Next != nil {<!-- -->
current = current.Next
}
current.Next = element
}
}
func (d *Dictionary) Delete(key int) {<!-- -->
hashKey := d.hash(key)
element := d.Table[hashKey]
if element == nil {<!-- -->
return
}
if element.Key == key {<!-- -->
d.Table[hashKey] = element.Next
} else {<!-- -->
for element.Next != nil {<!-- -->
if element.Next.Key == key {<!-- -->
element.Next = element.Next.Next
break
}
element = element.Next
}
}
}
func (d *Dictionary) Search(key int) *Element {<!-- -->
hashKey := d.hash(key)
element := d.Table[hashKey]
for element != nil {<!-- -->
if element.Key == key {<!-- -->
return element
}
element = element.Next
}
return nil
}
func main() {<!-- -->
dict := NewDictionary(10)
dict.Insert(1, "Satellite 1")
dict.Insert(2, "Satellite 2")
dict.Insert(11, "Satellite 3") // Different keywords used in the example
//Search element
elem := dict.Search(1)
fmt.Printf("Key: %d, Satellite: %s\\
", elem.Key, elem.Satellite)
// delete element
dict.Delete(2)
elem = dict.Search(2)
if elem == nil {<!-- -->
fmt.Println("Element not found.")
} else {<!-- -->
fmt.Printf("Key: %d, Satellite: %s\\
", elem.Key, elem.Satellite)
}
}
In the above example, we create a new direct addressing table through the NewDictionary function and specify its size. The Insert function is used to insert elements into the direct addressing table, the Delete function is used to delete elements with specified keywords, and the Search function is used to search Element that specifies keywords. The hash function uses a simple modulo operation to map the keyword to the index position of the hash table.
It should be noted that the operation time to achieve O(1) is established in the average case. For hash conflicts in extreme cases, the operation time may increase to O(n). The implementation can be further optimized by using better hash functions or methods of resolving collisions.
chatgpt, the code runs normally, plus package main and main functions:
To implement a direct addressing table (Direct Addressing Table), you can use an array in the Go language to represent it. Here is a sample code:
type DirectAddressTable struct {<!-- -->
data []*Element // Array used to store elements
}
type Element struct {<!-- -->
key int // element keyword
satellite interface{<!-- -->} // Satellite data, you can choose the appropriate type according to your needs
}
func NewDirectAddressTable(size int) *DirectAddressTable {<!-- -->
return &DirectAddressTable{<!-- -->
data: make([]*Element, size),
}
}
func (dat *DirectAddressTable) Insert(key int, satellite interface{<!-- -->}) {<!-- -->
element := & amp;Element{<!-- -->
key: key,
satellite: satellite,
}
dat.data[key] = element
}
func (dat *DirectAddressTable) Delete(key int) {<!-- -->
dat.data[key] = nil
}
func (dat *DirectAddressTable) Search(key int) (*Element, bool) {<!-- -->
element := dat.data[key]
if element != nil & amp; & amp; element.key == key {<!-- -->
return element, true
}
return nil, false
}
In the above code, the DirectAddressTable structure represents the direct addressing table, where data is an array of pointers pointing to the Element structure for storing elements. .
In the Insert method, create a new Element object and place it in the correct position (determined by the keyword). This guarantees that the insert operation has O(1) running time.
In the Delete method, set the element at the specified position to nil to delete the element. It should be noted that the pointer variable is operated here, not the keyword itself.
In the Search method, find the element based on the given keyword. If a matching element is found, it returns that element and true; otherwise, nil and false are returned.
It should be noted that integers are used directly as keywords in the above code. In actual applications, the keyword type and the size of the data structure may need to be modified according to specific needs.
