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binary partition an array using java

I am a beginner(first year uni student) programmer trying to solve this problem which i'm finding somewhat difficult. If you are to answer this question, don't provide me with a complex daunting algorithm that will leave me scratching my head. I'll really appreciate it if you explain it step my step (both logically/conceptually then through code)
The problem is as follows:image
I have tried to attempt it and my code only works for a certain case that i tested.
package com.company;
import java.lang.Math;
public class Main {
public static int[][] binary_partition(int array[], int k){
int x = (int) Math.pow(2,k);
int[][] partition = new int[((array.length/x)*2)][array.length/x];
int divisor = array.length/x;
if ((array.length % 2) != 0){
return partition;
}
if (divisor >= array.length-1){
return partition;
}
if (k==1){
return partition;
}
int p = 0;
for(int i=0;i<((array.length/x)*2);i++)
{
for (int j = 0; j<array.length/x;j++)
{
partition[i][j] = array[p];
p += 1;
}
}
return partition;
}
public static void main(String[] args){
int[] array = {3, 2, 4, 7, 8, 9, 2, 3};
int[][] result = binary_partition(array,2);
for (int[] x : result){
for (int y : x)
{
System.out.print(y + " ");
}
System.out.println();
}
}
}

Your question is unclear, but this solution creates a function that partitions an array with the right length into 2^k sets.
First, an interesting fact: using the bitshift operator << on an integer increases its value by a power of two. So to find out the size of your partition, you could write
int numPartitions = 1 << k; // Equivalent to getting the integer value of 2^k
With this fact, the function becomes
public static int[][] partition(int[] set, int k) {
if (set == null)
return null; // Don't try to partition a null reference
// If k = 0, the partition of the set is just the set
if (k == 0) {
int[][] partition = new int[1][set.length];
// Copy the original set into the partition
System.arraycopy(set, 0, partition[0], 0, set.length);
return partition;
}
int numPartitions = 1 << k; // The number of sets to partition the array into
int numElements = set.length / numPartitions; // The number of elements per partition
/* Check if the set has enough elements to create a partition and make sure
that the partitions are even */
if (numElements == 0 || set.length % numElements != 0)
return null; // Replace with an error/exception of your choice
int[][] partition = new int[numPartitions][numElements];
int index = 0;
for (int r = 0; r < numPartitions; r++) {
for (int c = 0; c < numElements; c++) {
partition[r][c] = set[index++]; // Assign an element to the partition
}
}
return partition;
}

There are a few lines of your code where the intention is not clear. For example, it is not clear why you are validating divisor >= array.length-1. Checking k==1 is also incorrect because k=1 is a valid input to the method. In fact, all your validation checks are not needed. All you need to validate is that array.length is divisible by x.
The main problem that you have seems to be that you mixed up the lengths of the resulting array.
The resulting array should have a length of array.length / x, and each of the subarrays should have a length of x, hence:
int[][] partition = new int[array.length/x][x];
If you also fix your bounds on the for loops, your code should work.
Your nested for loop can be rewritten as a single for loop:
for(int i = 0 ; i < array.length ; i++)
{
int index = i / x;
int subArrayIndex = i % x;
partition[index][subArrayIndex] = array[i];
}
You just need to figure out which indices a an element array[i] belongs by dividing and getting the remainder.

What is the best way to check if ALL values in a range exist in an array? (java)

I have the task of determining whether each value from 1, 2, 3... n is in an unordered int array. I'm not sure if this is the most efficient way to go about this, but I created an int[] called range that just has all the numbers from 1-n in order at range[i] (range[0]=1, range[1]=2, ect). Then I tried to use the containsAll method to check if my array of given numbers contains all of the numbers in the range array. However, when I test this it returns false. What's wrong with my code, and what would be a more efficient way to solve this problem?
public static boolean hasRange(int [] givenNums, int[] range) {
boolean result = true;
int n = range.length;
for (int i = 1; i <= n; i++) {
if (Arrays.asList(givenNums).containsAll(Arrays.asList(range)) == false) {
result = false;
}
}
return result;
}
(I'm pretty sure I'm supposed to do this manually rather than using the containsAll method, so if anyone knows how to solve it that way it would be especially helpful!)
Here's where this method is implicated for anyone who is curious:
public static void checkMatrix(int[][] intMatrix) {
File numberFile = new File("valid3x3") ;
intMatrix= readMatrix(numberFile);
int nSquared = sideLength * sideLength;
int[] values = new int[nSquared];
int[] range = new int[nSquared];
int valCount = 0;
for (int i = 0; i<sideLength; i++) {
for (int j=0; j<sideLength; j++) {
values[valCount] = intMatrix[i][j];
valCount++;
}
}
for (int i=0; i<range.length; i++) {
range[i] = i+1;
}
Boolean valuesThere = hasRange(values, range);
valuesThere is false when printed.

First style:
if (condition == false) // Works, but at the end you have if (true == false) or such
if (!condition) // Better: not condition
// Do proper usage, if you have a parameter, do not read it in the method.
File numberFile = new File("valid3x3") ;
intMatrix = readMatrix(numberFile);
checkMatrix(intMatrix);
public static void checkMatrix(int[][] intMatrix) {
int nSquared = sideLength * sideLength;
int[] values = new int[nSquared];
Then the problem. It is laudable to see that a List or even better a Set approach is the exact abstraction level: going into detail not sensible. Here however just that is wanted.
To know whether every element in a range [1, ..., n] is present.
You could walk through the given numbers,
and for every number look whether it new in the range, mark it as no longer new,
and if n new numbers are reached: return true.
int newRangeNumbers = 0;
boolean[] foundRangeNumbers = new boolean[n]; // Automatically false
Think of better names.

You say you have a one dimensional array right?
Good. Then I think you are thinking to complicated.
I try to explain you another way to check if all numbers in an array are in number order.
For instance you have the array with following values:
int[] array = {9,4,6,7,8,1,2,3,5,8};
First of all you can order the Array simpel with
Arrays.sort(array);
After you've done this you can loop through the array and compare with the index like (in a method):
for(int i = array[0];i < array.length; i++){
if(array[i] != i) return false;

One way to solve this is to first sort the unsorted int array like you said then run a binary search to look for all values from 1...n. Sorry I'm not familiar with Java so I wrote in pseudocode. Instead of a linear search which takes O(N), binary search runs in O(logN) so is much quicker. But precondition is the array you are searching through must be sorted.
//pseudocode
int range[N] = {1...n};
cnt = 0;
while(i<-inputStream)
int unsortedArray[cnt]=i
cnt++;
sort(unsortedArray);
for(i from 0 to N-1)
{
bool res = binarySearch(unsortedArray, range[i]);
if(!res)
return false;
}
return true;

What I comprehended from your description is that the array is not necessarily sorted (in order). So, we can try using linear search method.
public static void main(String[] args){
boolean result = true;
int[] range <- Contains all the numbers
int[] givenNums <- Contains the numbers to check
for(int i=0; i<givenNums.length; i++){
if(!has(range, givenNums[i])){
result = false;
break;
}
}
System.out.println(result==false?"All elements do not exist":"All elements exist");
}
private static boolean has(int[] range, int n){
//we do linear search here
for(int i:range){
if(i == n)
return true;
}
return false;
}
This code displays whether all the elements in array givenNums exist in the array range.

Arrays.asList(givenNums).
This does not do what you think. It returns a List<int[]> with a single element, it does not box the values in givenNums to Integer and return a List<Integer>. This explains why your approach does not work.
Using Java 8 streams, assuming you don't want to permanently sort givens. Eliminate the copyOf() if you don't care:
int[] sorted = Arrays.copyOf(givens,givens.length);
Arrays.sort(sorted);
boolean result = Arrays.stream(range).allMatch(t -> Arrays.binarySearch(sorted, t) >= 0);

public static boolean hasRange(int [] givenNums, int[] range) {
Set result = new HashSet();
for (int givenNum : givenNums) {
result.add(givenNum);
}
for (int num : range) {
result.add(num);
}
return result.size() == givenNums.length;
}

The problem with your code is that the function hasRange takes two primitive int array and when you pass primitive int array to Arrays.asList it will return a List containing a single element of type int[]. In this containsAll will not check actual elements rather it will compare primitive array object references.
Solution is either you create an Integer[] and then use Arrays.asList or if that's not possible then convert the int[] to Integer[].
public static boolean hasRange(Integer[] givenNums, Integer[] range) {
return Arrays.asList(givenNums).containsAll(Arrays.asList(range));
}
Check here for sample code and output.
If you are using ApacheCommonsLang library you can directly convert int[] to Integer[].
Integer[] newRangeArray = ArrayUtils.toObject(range);

A mathematical approach: if you know the max value (or search the max value) check the sum. Because the sum for the numbers 1,2,3,...,n is always equal to n*(n+1)/2. So if the sum is equal to that expression all values are in your array and if not some values are missing. Example
public class NewClass12 {
static int [] arr = {1,5,2,3,4,7,9,8};
public static void main(String [] args){
System.out.println(containsAllValues(arr, highestValue(arr)));
}
public static boolean containsAllValues(int[] arr, int n){
int sum = 0;
for(int k = 0; k<arr.length;k++){
sum +=arr[k];
}
return (sum == n*(n+1)/2);
}
public static int highestValue(int[]arr){
int highest = arr[0];
for(int i = 0; i < arr.length; i++) {
if(highest<arr[i]) highest = arr[i];
}
return highest;
}
}
according to this your method could look like this
public static boolen hasRange (int [] arr){
int highest = arr[0];
int sum = 0;
for(int i = 0; i < arr.length; i++) {
if(highest<arr[i]) highest = arr[i];
}
for(int k = 0; k<arr.length;k++){
sum +=arr[k];
}
return (sum == highest *(highest +1)/2);
}

Complexity and Efficiency in Algorithm for: a[j]-a[i] i>=j

I'm looking to make this much quicker. I've contemplated using a tree, but I'm not sure if that would actually help much.
I feel like the problem is for most cases you don't need to calculate all the possible maximums only a hand full, but I'm not sure where to draw the line
Thanks so much for the input,
Jasper
public class SpecialMax {
//initialized to the lowest possible value of j;
public static int jdex = 0;
//initialized to the highest possible value of i;
public static int idex;
//will hold possible maximums
public static Stack<Integer> possibleMaxs = new Stack<Integer> ();
public static int calculate (int[] a){
if (isPositive(a)){
int size = a.length;
int counterJ;
counterJ = size-1;
//find and return an ordered version of a
int [] ordered = orderBySize (a);
while (counterJ>0){
/* The first time this function is called, the Jvalue will be
* the largest it can be, similarly, the Ivalue that is found
* is the smallest
*/
int jVal = ordered[counterJ];
int iVal = test (a, jVal);
possibleMaxs.push(jVal-iVal);
counterJ--;
}
int answer = possibleMaxs.pop();
while (!possibleMaxs.empty()){
if (answer<possibleMaxs.peek()){
answer = possibleMaxs.pop();
} else {
possibleMaxs.pop();
}
}
System.out.println("The maximum of a[j]-a[i] with j>=i is: ");
return answer;
} else {
System.out.println ("Invalid input, array must be positive");
return 0; //error
}
}
//Check to make sure the array contains positive numbers
public static boolean isPositive(int[] a){
boolean positive = true;
int size = a.length;
for (int i=0; i<size; i++){
if (a[i]<0){
positive = false;
break;
}
}
return positive;
}
public static int[] orderBySize (int[] a){
//orders the array into ascending order
int [] answer = a.clone();
Arrays.sort(answer);
return answer;
}
/*Test returns an Ival to match the input Jval it accounts for
* the fact that jdex<idex.
*/
public static int test (int[] a, int jVal){
int size = a.length;
//initialized to highest possible value
int tempMin = jVal;
//keeps a running tally
Stack<Integer> mIndices = new Stack<Integer> ();
//finds the index of the jVal being tested
for (int i=0; i<size; i++) {
if (jVal==a[i]){
//finds the highest index for instance
if (jdex<i){
jdex = i;
}
}
}
//look for the optimal minimal below jdex;
for (int i=0; i<jdex; i++){
if (a[i]<tempMin){
tempMin = a[i];
mIndices.push(i);
}
}
//returns the index of the last min
if (!mIndices.empty()){
idex = mIndices.pop();
}
return tempMin;
}
}

It can be done in linear time and linear memory. The idea is: find the minimum over each suffix of the array and maximum over each prefix, then find the point where the difference between the two is the highest. You'll also have to store the index on which the maximum/minimum for each prefix is reached if you need the indices, rather than just the difference value.

Pre-sorting a[] makes the procedure complicated and impairs performance. It is not necessary, so we leave a[] unsorted.
Then (EDITED, because I had read j>=i in the body of your code, rather than i>=j in the problem description/title, which I now assume is what is required (I didn't go over your coding details); The two varieties can easily be derived from each other anyway.)
// initialize result(indices)
int iFound = 0;
int jFound = 0;
// initialize a candidate that MAY replace jFound
int jAlternative = -1; // -1 signals: no candidate currently available
// process the (remaining) elements of the array - skip #0: we've already handled that one at the initialization
for (int i=1; i<size; i++)
{
// if we have an alternative, see if that combines with the current element to a higher "max".
if ((jAlternative != -1) && (a[jAlternative]-a[i] > a[jFound]-a[iFound]))
{
jFound = jAlternative;
iFound = i;
jAlternative = -1;
}
else if (a[i] < a[iFound]) // then we can set a[iFound] lower, thereby increasing "max"
{
iFound = i;
}
else if (a[i] > a[jFound])
{ // we cannot directly replace jFound, because of the condition iFound>=jFound,
// but when we later may find a lower a[i], then it can jump in:
// set it as a waiting candidate (replacing an existing one if the new one is more promising).
if ((jAlternative = -1) || (a[i] > a[jAlternative]))
{
jAlternative = i;
}
}
}
double result = a[jFound] - a[iFound];

Determine if array contains two elements which equal a certain sum?

// Checks whether the array contains two elements whose sum is s.
// Input: A list of numbers and an integer s
// Output: return True if the answer is yes, else return False
public static boolean calvalue (int[] numbers, int s){
for (int i=0; i< numbers.length; i++){
for (int j=i+1; j<numbers.length;j++){
if (numbers[i] < s){
if (numbers[i]+numbers[j] == s){
return true;
}
}
}
}
return false;
}

This can be achieved in O(n).
Create a hash-backed set out of your list, such that it contains all elements of the list. This takes O(n).
Walk through each element n of your list, calculate s-n = d, and check for the presence of d in the set. If d is present, then n+d = s, so return true. If you pass through the list without finding an appropriate d, return false. This is achieved in a single pass through your list, with each lookup taking O(1), so this step also takes O(n).

Both the solutions mentioned in other answers to this post, and a few other answers as well (eg using a bitmap instead of a hash-table), appear in the following duplicates and slight variations of the question:
• Find two elements in an array that sum to k,
• Find a pair of elements from an array whose sum equals a given number,
• Determine whether or not there exist two elements in set s whose sum is exactly,
• Checking if 2 numbers of array add up to i,
• Find pair of numbers in array that add to given sum,
• Design an algorithm to find all pairs of integers within an array which sum to a,
• Given an unsorted array find any two elements in the array whose sum is equal t,
• A recursive algorithm to find two integers in an array that sums to a given inte,
• Find 2 numbers in an unsorted array equal to a given sum,
• Find two elements so sum is equal to given value,
• and, per google, many more.

You can solve this by sorting the array, then keep 2 pointers to the start and the end of the array and find the 2 numbers by moving both pointers. The sorting step takes O(nlog n) and the 2nd step takes O(n).
As #Adam has pointed out, it is also good to remove duplicate elements from the array, so that you may reduce the time from the second step if the array contains many duplicated numbers.
As for how to do the second step:
Move the pointer at the end backward if sum of the current 2 numbers is larger than n.
Move the pointer at the start forward if sum of the current 2 numbers is smaller than n.
Stop and reject when both pointers point to the same element. Accept if sum is equal to n.
Why is this correct (I use right end to denote larger end and left end to denote smaller end):
If sum is larger than n, there is no point in using the right end, since all numbers larger than current left end will make it worse.
If sum is smaller than n, there is no point in using the left end, since all numbers smaller than current right end will make it worse.
At each step, we will have gone through all possible combinations (logically) between the removed numbers and the numbers which remain. At the end, we will exhaust all possible combinations possible between all pairs of numbers.

Here is a solution witch takes into account duplicate entries. It is written in javascript and assumes array is sorted.
var count_pairs = function(_arr,x) {
if(!x) x = 0;
var pairs = 0;
var i = 0;
var k = _arr.length-1;
if((k+1)<2) return pairs;
var halfX = x/2;
while(i<k) {
var curK = _arr[k];
var curI = _arr[i];
var pairsThisLoop = 0;
if(curK+curI==x) {
// if midpoint and equal find combinations
if(curK==curI) {
var comb = 1;
while(--k>=i) pairs+=(comb++);
break;
}
// count pair and k duplicates
pairsThisLoop++;
while(_arr[--k]==curK) pairsThisLoop++;
// add k side pairs to running total for every i side pair found
pairs+=pairsThisLoop;
while(_arr[++i]==curI) pairs+=pairsThisLoop;
} else {
// if we are at a mid point
if(curK==curI) break;
var distK = Math.abs(halfX-curK);
var distI = Math.abs(halfX-curI);
if(distI > distK) while(_arr[++i]==curI);
else while(_arr[--k]==curK);
}
}
return pairs;
}
Enjoy!

In Java
private static boolean find(int[] nums, long k, int[] ids) {
// walk from both sides towards center.
// index[0] keep left side index, index[1] keep right side index,
// runtime O(N)
int l = ids[0];
int r = ids[1];
if (l == r) {
ids[0] = -1;
ids[1] = -1;
return false;
}
if (nums[l] + nums[r] == k) {
ids[0]++;
ids[1]++;
return true;
}
if (nums[l] + nums[r] < k) {
ids[0]++;
} else {
ids[1]--;
}
return find(nums, k, ids);
}
public static boolean twoSum(final int[] nums, int target) {
// Arrays.sort(nums); //if the nums is not sorted, then sorted it firstly, thus the running time will be O(NlogN)
int[] ids = new int[2];
ids[0] = 0;
ids[1] = nums.length - 1;
return find(nums, target, ids);
}
Test
#Test(timeout = 10L, expected = Test.None.class)
public void test() {
Assert.assertEquals( twoSum(new int[]{3, 2, 4}, 6), true);
Assert.assertEquals( twoSum(new int[]{3, 2, 4}, 8), false);
}
IF only answer is not enough, and want to know which one is i and j that the A[i]+A[j]=target
with the idea of #cheeken as following, if there are duplicated number, take the the one appears firstly.
public static int[] twoSum2(final int[] nums, int target) {
int[] r = new int[2];
r[0] = -1;
r[1] = -1;
Set<Integer> set = new HashSet<>(nums.length);
Map<Integer, List<Integer>> map = new HashMap<>(nums.length);
for (int i = 0; i < nums.length; i++) {
int v = nums[i];
if (set.contains(target - v)) {
r[0] = map.get(target - v).get(0);
r[1] = i;
return r;
}
set.add(v);
List ids = map.get(v);
if (ids == null) {
ids = new LinkedList<>();
ids.add(i);
map.put(v, ids);
} else {
ids.add(i);
map.put(v, ids);
}
}
return r;
}
Test
int[] r = twoSum2(new int[]{3, 2, 4}, 6);
Assert.assertEquals(r[0], 1);
Assert.assertEquals(r[1], 2);
r = twoSum2(new int[]{3, 2, 4}, 8);
Assert.assertEquals(r[0], r[1]);
Assert.assertEquals(r[1], -1);

Finding prime numbers with the Sieve of Eratosthenes (Originally: Is there a better way to prepare this array?)

Note: Version 2, below, uses the Sieve of Eratosthenes. There are several answers that helped with what I originally asked. I have chosen the Sieve of Eratosthenes method, implemented it, and changed the question title and tags appropriately. Thanks to everyone who helped!
Introduction
I wrote this fancy little method that generates an array of int containing the prime numbers less than the specified upper bound. It works very well, but I have a concern.
The Method
private static int [] generatePrimes(int max) {
int [] temp = new int [max];
temp [0] = 2;
int index = 1;
int prime = 1;
boolean isPrime = false;
while((prime += 2) <= max) {
isPrime = true;
for(int i = 0; i < index; i++) {
if(prime % temp [i] == 0) {
isPrime = false;
break;
}
}
if(isPrime) {
temp [index++] = prime;
}
}
int [] primes = new int [index];
while(--index >= 0) {
primes [index] = temp [index];
}
return primes;
}
My Concern
My concern is that I am creating an array that is far too large for the final number of elements the method will return. The trouble is that I don't know of a good way to correctly guess the number of prime numbers less than a specified number.
Focus
This is how the program uses the arrays. This is what I want to improve upon.
I create a temporary array that is
large enough to hold every number
less than the limit.
I generate the prime numbers, while
keeping count of how many I have
generated.
I make a new array that is the right
dimension to hold just the prime
numbers.
I copy each prime number from the
huge array to the array of the
correct dimension.
I return the array of the correct
dimension that holds just the prime
numbers I generated.
Questions
Can I copy the whole chunk (at once) of
temp[] that has nonzero
elements to primes[]
without having to iterate through
both arrays and copy the elements
one by one?
Are there any data structures that
behave like an array of primitives
that can grow as elements are added,
rather than requiring a dimension
upon instantiation? What is the
performance penalty compared to
using an array of primitives?
Version 2 (thanks to Jon Skeet):
private static int [] generatePrimes(int max) {
int [] temp = new int [max];
temp [0] = 2;
int index = 1;
int prime = 1;
boolean isPrime = false;
while((prime += 2) <= max) {
isPrime = true;
for(int i = 0; i < index; i++) {
if(prime % temp [i] == 0) {
isPrime = false;
break;
}
}
if(isPrime) {
temp [index++] = prime;
}
}
return Arrays.copyOfRange(temp, 0, index);
}
Version 3 (thanks to Paul Tomblin) which uses the Sieve of Erastosthenes:
private static int [] generatePrimes(int max) {
boolean[] isComposite = new boolean[max + 1];
for (int i = 2; i * i <= max; i++) {
if (!isComposite [i]) {
for (int j = i; i * j <= max; j++) {
isComposite [i*j] = true;
}
}
}
int numPrimes = 0;
for (int i = 2; i <= max; i++) {
if (!isComposite [i]) numPrimes++;
}
int [] primes = new int [numPrimes];
int index = 0;
for (int i = 2; i <= max; i++) {
if (!isComposite [i]) primes [index++] = i;
}
return primes;
}

Your method of finding primes, by comparing every single element of the array with every possible factor is hideously inefficient. You can improve it immensely by doing a Sieve of Eratosthenes over the entire array at once. Besides doing far fewer comparisons, it also uses addition rather than division. Division is way slower.

ArrayList<> Sieve of Eratosthenes
// Return primes less than limit
static ArrayList<Integer> generatePrimes(int limit) {
final int numPrimes = countPrimesUpperBound(limit);
ArrayList<Integer> primes = new ArrayList<Integer>(numPrimes);
boolean [] isComposite = new boolean [limit]; // all false
final int sqrtLimit = (int)Math.sqrt(limit); // floor
for (int i = 2; i <= sqrtLimit; i++) {
if (!isComposite [i]) {
primes.add(i);
for (int j = i*i; j < limit; j += i) // `j+=i` can overflow
isComposite [j] = true;
}
}
for (int i = sqrtLimit + 1; i < limit; i++)
if (!isComposite [i])
primes.add(i);
return primes;
}
Formula for upper bound of number of primes less than or equal to max (see wolfram.com):
static int countPrimesUpperBound(int max) {
return max > 1 ? (int)(1.25506 * max / Math.log((double)max)) : 0;
}

Create an ArrayList<Integer> and then convert to an int[] at the end.
There are various 3rd party IntList (etc) classes around, but unless you're really worried about the hit of boxing a few integers, I wouldn't worry about it.
You could use Arrays.copyOf to create the new array though. You might also want to resize by doubling in size each time you need to, and then trim at the end. That would basically be mimicking the ArrayList behaviour.

Algo using Sieve of Eratosthenes
public static List<Integer> findPrimes(int limit) {
List<Integer> list = new ArrayList<>();
boolean [] isComposite = new boolean [limit + 1]; // limit + 1 because we won't use '0'th index of the array
isComposite[1] = true;
// Mark all composite numbers
for (int i = 2; i <= limit; i++) {
if (!isComposite[i]) {
// 'i' is a prime number
list.add(i);
int multiple = 2;
while (i * multiple <= limit) {
isComposite [i * multiple] = true;
multiple++;
}
}
}
return list;
}
Image depicting the above algo (Grey color cells represent prime number. Since we consider all numbers as prime numbers intially, the whole is grid is grey initially.)
Image Source: WikiMedia

The easiest solution would be to return some member of the Collections Framework instead of an array.

Are you using Java 1.5? Why not return List<Integer> and use ArrayList<Integer>? If you do need to return an int[], you can do it by converting List to int[] at the end of processing.

As Paul Tomblin points out, there are better algorithms.
But keeping with what you have, and assuming an object per result is too big:
You are only ever appending to the array. So, use a relatively small int[] array. When it's full use append it to a List and create a replacement. At the end copy it into a correctly sized array.
Alternatively, guess the size of the int[] array. If it is too small, replace by an int[] with a size a fraction larger than the current array size. The performance overhead of this will remain proportional to the size. (This was discussed briefly in a recent stackoverflow podcast.)

Now that you've got a basic sieve in place, note that the inner loop need only continue until temp[i]*temp[i] > prime.

I have a really efficient implementation:
we don't keep the even numbers, therefore halving the memory usage.
we use BitSet, requiring only one bit per number.
we estimate the upper bound for number of primes on the interval, thus we can set the initialCapacity for the Array appropriately.
we don't perform any kind of division in the loops.
Here's the code:
public ArrayList<Integer> sieve(int n) {
int upperBound = (int) (1.25506 * n / Math.log(n));
ArrayList<Integer> result = new ArrayList<Integer>(upperBound);
if (n >= 2)
result.add(2);
int size = (n - 1) / 2;
BitSet bs = new BitSet(size);
int i = 0;
while (i < size) {
int p = 3 + 2 * i;
result.add(p);
for (int j = i + p; j < size; j += p)
bs.set(j);
i = bs.nextClearBit(i + 1);
}
return result;
}

Restructure your code. Throw out the temporary array, and instead write function that just prime-tests an integer. It will be reasonably fast, since you're only using native types. Then you can, for instance, loop and build a list of integers that are prime, before finally converting that to an array to return.

Not sure if this will suite your situation but you can take a look at my approach. I used mine using Sieve of Eratosthenes.
public static List<Integer> sieves(int n) {
Map<Integer,Boolean> numbers = new LinkedHashMap<>();
List<Integer> primes = new ArrayList<>();
//First generate a list of integers from 2 to 30
for(int i=2; i<n;i++){
numbers.put(i,true);
}
for(int i : numbers.keySet()){
/**
* The first number in the list is 2; cross out every 2nd number in the list after 2 by
* counting up from 2 in increments of 2 (these will be all the multiples of 2 in the list):
*
* The next number in the list after 2 is 3; cross out every 3rd number in the list after 3 by
* counting up from 3 in increments of 3 (these will be all the multiples of 3 in the list):
* The next number not yet crossed out in the list after 5 is 7; the next step would be to cross out every
* 7th number in the list after 7, but they are all already crossed out at this point,
* as these numbers (14, 21, 28) are also multiples of smaller primes because 7 × 7 is greater than 30.
* The numbers not crossed out at this point in the list are all the prime numbers below 30:
*/
if(numbers.get(i)){
for(int j = i+i; j<n; j+=i) {
numbers.put(j,false);
}
}
}
for(int i : numbers.keySet()){
for(int j = i+i; j<n && numbers.get(i); j+=i) {
numbers.put(j,false);
}
}
for(int i : numbers.keySet()){
if(numbers.get(i)) {
primes.add(i);
}
}
return primes;
}
Added comment for each steps that has been illustrated in wikipedia

I have done using HashMap and found it very simple
import java.util.HashMap;
import java.util.Map;
/*Using Algorithms such as sieve of Eratosthanas */
public class PrimeNumber {
public static void main(String[] args) {
int prime = 15;
HashMap<Integer, Integer> hashMap = new HashMap<Integer, Integer>();
hashMap.put(0, 0);
hashMap.put(1, 0);
for (int i = 2; i <= prime; i++) {
hashMap.put(i, 1);// Assuming all numbers are prime
}
printPrimeNumberEratoshanas(hashMap, prime);
}
private static void printPrimeNumberEratoshanas(HashMap<Integer, Integer> hashMap, int prime) {
System.out.println("Printing prime numbers upto" + prime + ".....");
for (Map.Entry<Integer, Integer> entry : hashMap.entrySet()) {
if (entry.getValue().equals(1)) {
System.out.println(entry.getKey());
for (int j = entry.getKey(); j < prime; j++) {
for (int k = j; k * j <= prime; k++) {
hashMap.put(j * k, 0);
}
}
}
}
}
}
Think this is effective

public static void primes(int n) {
boolean[] lista = new boolean[n+1];
for (int i=2;i<lista.length;i++) {
if (lista[i]==false) {
System.out.print(i + " ");
}
for (int j=i+i;j<lista.length;j+=i) {
lista[j]=true;
}
}
}