What is the efficient algorithm to implement Stack? - algorithm

I have come across a problem. I need to implement stack with push and pop operations.
Input
The first line of the input file contains a single integer number N (1 <= N <= 10^6) – the number of test cases.
Next N lines tells about operations. + means push. - means pop. I need to print popped element.
Example
Input Output
6
+ 1 10
+ 10 1234
-
+ 2
+ 1234
-
I have written following code
public class Main {
public static void main(String[] args) throws FileNotFoundException {
Scanner sc = new Scanner(new File("stack.in"));
PrintWriter pw = new PrintWriter(new File("stack.out"));
int n=sc.nextInt();
int[] stack = new int[n]; int i=0;
while(n-->0) {
String s = sc.next();
if(s.equals("+")) {
stack[i++]=sc.nextInt();
} else {
pw.println(stack[--i]);
}
}
sc.close(); pw.close();
}
}
This program is giving me Time Limit Exceeded.
Please suggest me an efficient algorithm to solve this.
For each input file:
Time limit: 2 seconds
Memory limit: 256 megabytes

A rule of thumb: if you're solving a competitive programming style problem and the input is large (say, 10^5 numbers or more), the Scanner is too slow.
You can use a StringTokenizer on top of a BufferedReader to speed up the input.
It can look like this:
class FastScanner {
private StringTokenizer tokenizer;
private BufferedReader reader;
public FastScanner(InputStream inputStream) {
reader = new BufferedReader(new InputStreamReader(inputStream));
}
public String next() {
while (tokenizer == null || !tokenizer.hasMoreTokens()) {
String line;
try {
line = reader.readLine();
} catch (IOException e) {
throw new RuntimeException(e);
}
if (line == null)
return null;
tokenizer = new StringTokenizer(line);
}
return tokenizer.nextToken();
}
public int nextInt() {
return Integer.parseInt(next());
}
}

Related

Update Vaadin Progressbar with push asynchronously

I have a question when calculating the hash of files eg: md5, sha1, sha256 setting the progress in the progressBar through the asynchronous process
Thanks to Alejandro Duarte who shows a very practical example
https://github.com/newUserRepo/testbar/blob/issueBar/vaadin-upload/src/main/java/com/example/vaadinupload/ProcessingService.java#L44
the only way I can get it to work is that in method line 75, I put 4 milliseconds to process the task and the bar is updated, but it is too slow.
Yes, I do not sleep the Thread the application does not do the push correctly, and the changes are not reflected correctly to the client.
Another way that actually worked was with the Runnable interface and execute the heavy task in the run() method
#Override
public void run() {
calcularHash();
}
public void calcularHash() {
System.out.println("Path tmp archivo: " +
tmpPath.toFile().getAbsolutePath());
for(int f=0; f<hashType.size(); f++) {
try (InputStream bis = new
BufferedInputStream(Files.newInputStream(tmpPath))) {
t.initTime();
byte[] buffer = new byte[1024];
MessageDigest messageDigest =
MessageDigest.getInstance(hashType.get(f));
int dataRead = 0;
long largo = tmpPath.toFile().length();
Long acum = 0L;
while ((dataRead = bis.read(buffer)) != -1) {
messageDigest.update(buffer, 0, dataRead);
acum += dataRead;
Float per = ((float) acum / largo);
bar.setValue(per);
System.out.println(per * 100);
//textFieldPercent.setValue(Types.formatPercentaje(per *
100));
}
final byte[] bytesDigest = messageDigest.digest();
final StringBuilder sb = new StringBuilder();
for (int c = 0; c < bytesDigest.length; c++) {
sb.append(Integer.toString((bytesDigest[c] & 0xFF) + 0x100,
16).substring(1));
}
final String hashObtenido = sb.toString();
t.finishTime();
final String totalTime = t.getFinalTimeSec() + "seg " +
t.getFinalTimeMs() + "ms";
final String large = Types.getLargeFileFormat(largo);
System.out.println(hashObtenido);
ui.access(() -> {
checksumTransactions.initData(messageDigest.getAlgorithm(),
sb.toString(),large, totalTime);
});
//Files.delete(tmpPath); //fixme borrar desde el grid o UI
} catch (IOException e) {
e.printStackTrace();
} catch (NoSuchAlgorithmException e) {
e.printStackTrace();
}
}
In the present picture I use a simple public void run () and the Progressbar is updated well
but we know that the application may have memory leaks and is not a good practice, the ideal would be to know how to execute that Background thread
I still do not know the best way to achieve this :$

Why in this program BufferedReader taking infinite input

Why is in this program BufferedReader taking infinite input?
Below is the code which is taking input infinitely. To avoid this I have added condition
while((!(s1=br.readLine().trim()).equals(null))&&(!s1.isEmpty())){
but it didn't work out.
import java.io.*;
import java.util.*;
public class skylerStudent {
public static void main(String []args)throws IOException{
BufferedReader br=new BufferedReader(new InputStreamReader(System.in));
String s1="";String s="";
while((!(s1=br.readLine().trim()).equals(null))&&(!s1.isEmpty())){
s+=s1.trim()+" ";
}
StringTokenizer st=new StringTokenizer(s.trim());
int i=0,n=0,q=0;
while(st.hasMoreTokens()){
if(i==0)n=Integer.parseInt(st.nextToken());
if(i==1)q=Integer.parseInt(st.nextToken());
i++;
}
int ar[]=new int[n];i=0;
while(st.hasMoreTokens()){
if(i<n)ar[i]=Integer.parseInt(st.nextToken());
i++;
}
i=0;
while(st.hasMoreTokens()){
StringTokenizer st1=new StringTokenizer(st.nextToken());
while(st.hasMoreTokens()){
if(i<q){
int a=Integer.parseInt(st1.nextToken());
int b=Integer.parseInt(st1.nextToken());
System.out.println(a);System.out.println(b);}
i++;
}
}
}
}
The condition !(s1 = br.readLine().trim()).equals(null) is not correct. If you can call .trim on string then it can never be null. You can check
(s1 = br.readLine()) != null
Also the infinite loop is not in the reading the input, its in the one of the later loops of the code.
while (st.hasMoreTokens()) {
if (i == 0)
n = Integer.parseInt(st.nextToken());
if (i == 1)
q = Integer.parseInt(st.nextToken());
i++;
}
You are not moving forward to nextToken() if the i is not in (0,1). That's why it would never exit the loop.

Running Multiple threads in queue using BlockingCollections

My program has 3 functions. Each function takes a list of Items and fill certain information.
For example
class Item {
String sku,upc,competitorName;
double price;
}
function F1 takes a List and fills upc
function F2 takes List (output of F1) and fills price.
function F3 takes List (output of F2) and fills competitorName
F1 can process 5 items at a time,
F2 can process 20 items at a time,
F3 also 20.
Right now I am running F1 -> F2 -> F3 in serial because F2 needs info(UPC code) from F1. F3 needs price from F2.
I would like to make this process efficient by running F1 run continuously instead of waiting for F2 and F3 to be completed. F1 executes and output into queue then F2 takes 20 items at a time and process them. and then follows F3.
How can i achieve this by using BlockingCollection and Queue?
This is a typical use case of Apache Storm in case you've continuous items coming in to F1. You can implement this in Storm in matter of minutes and you'll have fast and perfectly parallel system in place. Your F1, F2 and F3 will become bolts and your Items producer will become spout.
Since you asked how to do it using BlockingCollections here is an implementation. You'll need 3 threads in total.
ItemsProducer: It is producing 5 items at a time and feeding it to F1.
F2ExecutorThread: It is consuming 20 items at a time and feeding it to F2.
F3ExecutorThread: It is consuming 20 items at a time and feeding it to F3.
You also have 2 blocking queues one is used to transfer data from F1->F2 and one from F2->F3. You can also have a queue to feed data to F1 in similar fashion if required. It depends upon how you are getting the items. I've used Thread.sleep to simulate the time required to execute the function.
Each function will keep looking for items in their assigned queue, irrespective of what other functions are doing and wait until the queue has items. Once they've processed the item they'll put it in another queue for another function. They'll wait until the other queue has space if it is full.
Since all your functions are running in different threads, F1 won't be waiting for F2 or F3 to finish. If your F2 and F3 are significantly faster then F1 you can assign more threads to F1 and keep pushing to same f2Queue.
public class App {
final BlockingQueue<Item> f2Queue = new ArrayBlockingQueue<>(100);
final BlockingQueue<Item> f3Queue = new ArrayBlockingQueue<>(100);
public static void main(String[] args) throws InterruptedException {
App app = new App();
app.start();
}
public void start() throws InterruptedException {
Thread t1 = new ItemsProducer(f2Queue);
Thread t2 = new F2ExecutorThread(f2Queue, f3Queue);
Thread t3 = new F3ExecutorThread(f3Queue);
t1.start();
t2.start();
t3.start();
t1.join();
t2.join();
t3.join();
}
}
/**
* Thread producing 5 items at a time and feeding it to f1()
*/
class ItemsProducer extends Thread {
private BlockingQueue<Item> f2Queue;
private static final int F1_BATCH_SIZE = 5;
public ItemsProducer(BlockingQueue<Item> f2Queue) {
this.f2Queue = f2Queue;
}
public void run() {
Random random = new Random();
while (true) {
try {
List<Item> items = new ArrayList<>();
for (int i = 0; i < F1_BATCH_SIZE; i++) {
Item item = new Item(String.valueOf(random.nextInt(100)));
Thread.sleep(20);
items.add(item);
System.out.println("Item produced: " + item);
}
// Feed items to f1
f1(items);
} catch (InterruptedException e) {
e.printStackTrace();
}
}
}
void f1(List<Item> items) throws InterruptedException {
Random random = new Random();
for (Item item : items) {
Thread.sleep(100);
item.upc = String.valueOf(random.nextInt(100));
f2Queue.put(item);
}
}
}
/**
* Thread consuming items produced by f1(). It takes 20 items at a time, but if they are not
* available it waits and starts processesing as soon as one gets available
*/
class F2ExecutorThread extends Thread {
static final int F2_BATCH_SIZE = 20;
private BlockingQueue<Item> f2Queue;
private BlockingQueue<Item> f3Queue;
public F2ExecutorThread(BlockingQueue<Item> f2Queue, BlockingQueue<Item> f3Queue) {
this.f2Queue = f2Queue;
this.f3Queue = f3Queue;
}
public void run() {
try {
List<Item> items = new ArrayList<>();
while (true) {
items.clear();
if (f2Queue.drainTo(items, F2_BATCH_SIZE) == 0) {
items.add(f2Queue.take());
}
f2(items);
}
} catch (InterruptedException e) {
e.printStackTrace();
}
}
void f2(List<Item> items) throws InterruptedException {
Random random = new Random();
for (Item item : items) {
Thread.sleep(100);
item.price = random.nextInt(100);
f3Queue.put(item);
}
}
}
/**
* Thread consuming items produced by f2(). It takes 20 items at a time, but if they are not
* available it waits and starts processesing as soon as one gets available.
*/
class F3ExecutorThread extends Thread {
static final int F3_BATCH_SIZE = 20;
private BlockingQueue<Item> f3Queue;
public F3ExecutorThread(BlockingQueue<Item> f3Queue) {
this.f3Queue = f3Queue;
}
public void run() {
try {
List<Item> items = new ArrayList<>();
while (true) {
items.clear();
if (f3Queue.drainTo(items, F3_BATCH_SIZE) == 0) {
items.add(f3Queue.take());
}
f3(items);
}
} catch (InterruptedException e) {
e.printStackTrace();
}
}
private void f3(List<Item> items) throws InterruptedException {
Random random = new Random();
for (Item item : items) {
Thread.sleep(100);
item.competitorName = String.valueOf(random.nextInt(100));
System.out.println("Item done: " + item);
}
}
}
class Item {
String sku, upc, competitorName;
double price;
public Item(String sku) {
this.sku = sku;
}
public String toString() {
return "sku: " + sku + " upc: " + upc + " price: " + price + " compName: " + competitorName;
}
}
I guess you can follow the exact same approach in .Net as well. For better understanding I suggest you to go through basic architecture of http://storm.apache.org/releases/current/Tutorial.html
I tried to do same thing in .NET and i think it is working.
using System;
using System.Collections.Concurrent;
using System.Collections.Generic;
using System.Threading;
using System.Threading.Tasks;
namespace BlockingCollectionExample
{
class Program
{
static void Main(string[] args)
{
BlockingCollection<Listing> needUPCJobs = new BlockingCollection<Listing>();
BlockingCollection<Listing> needPricingJobs = new BlockingCollection<Listing>();
// This will have final output
List<Listing> output = new List<Listing>();
// start executor 1 which waits for data until available
var executor1 = Task.Factory.StartNew(() =>
{
int maxSimutenousLimit = 5;
int gg = 0;
while (true)
{
while (needUPCJobs.Count >= maxSimutenousLimit)
{
List<Listing> tempListings = new List<Listing>();
for (int i = 0; i < maxSimutenousLimit; i++)
{
Listing listing = new Listing();
if (needUPCJobs.TryTake(out listing))
tempListings.Add(listing);
}
// Simulating some delay for first executor
Thread.Sleep(1000);
foreach (var eachId in tempListings)
{
eachId.UPC = gg.ToString();
gg++;
needPricingJobs.Add(eachId);
}
}
if (needUPCJobs.IsAddingCompleted)
{
if (needUPCJobs.Count == 0)
break;
else
maxSimutenousLimit = needUPCJobs.Count;
}
}
needPricingJobs.CompleteAdding();
});
// start executor 2 which waits for data until available
var executor2 = Task.Factory.StartNew(() =>
{
int maxSimutenousLimit = 10;
int gg = 10;
while (true)
{
while (needPricingJobs.Count >= maxSimutenousLimit)
{
List<Listing> tempListings = new List<Listing>();
for (int i = 0; i < maxSimutenousLimit; i++)
{
Listing listing = new Listing();
if (needPricingJobs.TryTake(out listing))
tempListings.Add(listing);
}
// Simulating more delay for second executor
Thread.Sleep(10000);
foreach (var eachId in tempListings)
{
eachId.Price = gg;
gg++;
output.Add(eachId);
}
}
if (needPricingJobs.IsAddingCompleted)
{
if(needPricingJobs.Count==0)
break;
else
maxSimutenousLimit = needPricingJobs.Count;
}
}
});
// producer thread
var producer = Task.Factory.StartNew(() =>
{
for (int i = 0; i < 100; i++)
{
needUPCJobs.Add(new Listing() { ID = i });
}
needUPCJobs.CompleteAdding();
});
// wait for producer to finish producing
producer.Wait();
// wait for all executors to finish executing
Task.WaitAll(executor1, executor2);
Console.WriteLine();
Console.WriteLine();
}
}
public class Listing
{
public int ID;
public string UPC;
public double Price;
public Listing() { }
}
}

What is the fastest way to read from standard input in Scala? [duplicate]

I am reading bunch of integers separated by space or newlines from the standard in using Scanner(System.in).
Is there any faster way of doing this in Java?
Is there any faster way of doing this in Java?
Yes. Scanner is fairly slow (at least according to my experience).
If you don't need to validate the input, I suggest you just wrap the stream in a BufferedInputStream and use something like String.split / Integer.parseInt.
A small comparison:
Reading 17 megabytes (4233600 numbers) using this code
Scanner scanner = new Scanner(System.in);
while (scanner.hasNext())
sum += scanner.nextInt();
took on my machine 3.3 seconds. while this snippet
BufferedReader bi = new BufferedReader(new InputStreamReader(System.in));
String line;
while ((line = bi.readLine()) != null)
for (String numStr: line.split("\\s"))
sum += Integer.parseInt(numStr);
took 0.7 seconds.
By messing up the code further (iterating over line with String.indexOf / String.substring) you can get it down to about 0.1 seconds quite easily, but I think I've answered your question and I don't want to turn this into some code golf.
I created a small InputReader class which works just like Java's Scanner but outperforms it in speed by many magnitudes, in fact, it outperforms the BufferedReader as well. Here is a bar graph which shows the performance of the InputReader class I have created reading different types of data from standard input:
Here are two different ways of finding the sum of all the numbers coming from System.in using the InputReader class:
int sum = 0;
InputReader in = new InputReader(System.in);
// Approach #1
try {
// Read all strings and then parse them to integers (this is much slower than the next method).
String strNum = null;
while( (strNum = in.nextString()) != null )
sum += Integer.parseInt(strNum);
} catch (IOException e) { }
// Approach #2
try {
// Read all the integers in the stream and stop once an IOException is thrown
while( true ) sum += in.nextInt();
} catch (IOException e) { }
If you asking from competitive programming point of view, where if the submission is not fast enough, it will be TLE.
Then you can check the following method to retrieve String from System.in.
I have taken from one of the best coder in java(competitive sites)
private String ns()
{
int b = skip();
StringBuilder sb = new StringBuilder();
while(!(isSpaceChar(b))){ // when nextLine, (isSpaceChar(b) && b != ' ')
sb.appendCodePoint(b);
b = readByte();
}
return sb.toString();
}`
You can read from System.in in a digit by digit way. Look at this answer: https://stackoverflow.com/a/2698772/3307066.
I copy the code here (barely modified). Basically, it reads integers, separated by anything that is not a digit. (Credits to the original author.)
private static int readInt() throws IOException {
int ret = 0;
boolean dig = false;
for (int c = 0; (c = System.in.read()) != -1; ) {
if (c >= '0' && c <= '9') {
dig = true;
ret = ret * 10 + c - '0';
} else if (dig) break;
}
return ret;
}
In my problem, this code was approx. 2 times faster than using StringTokenizer, which was already faster than String.split(" ").
(The problem involved reading 1 million integers of up to 1 million each.)
StringTokenizer is a much faster way of reading string input separated by tokens.
Check below example to read a string of integers separated by space and store in arraylist,
String str = input.readLine(); //read string of integers using BufferedReader e.g. "1 2 3 4"
List<Integer> list = new ArrayList<>();
StringTokenizer st = new StringTokenizer(str, " ");
while (st.hasMoreTokens()) {
list.add(Integer.parseInt(st.nextToken()));
}
In programming perspective this customized Scan and Print class is way better than Java inbuilt Scanner and BufferedReader classes.
import java.io.InputStream;
import java.util.InputMismatchException;
import java.io.IOException;
public class Scan
{
private byte[] buf = new byte[1024];
private int total;
private int index;
private InputStream in;
public Scan()
{
in = System.in;
}
public int scan() throws IOException
{
if(total < 0)
throw new InputMismatchException();
if(index >= total)
{
index = 0;
total = in.read(buf);
if(total <= 0)
return -1;
}
return buf[index++];
}
public int scanInt() throws IOException
{
int integer = 0;
int n = scan();
while(isWhiteSpace(n)) /* remove starting white spaces */
n = scan();
int neg = 1;
if(n == '-')
{
neg = -1;
n = scan();
}
while(!isWhiteSpace(n))
{
if(n >= '0' && n <= '9')
{
integer *= 10;
integer += n-'0';
n = scan();
}
else
throw new InputMismatchException();
}
return neg*integer;
}
public String scanString()throws IOException
{
StringBuilder sb = new StringBuilder();
int n = scan();
while(isWhiteSpace(n))
n = scan();
while(!isWhiteSpace(n))
{
sb.append((char)n);
n = scan();
}
return sb.toString();
}
public double scanDouble()throws IOException
{
double doub=0;
int n=scan();
while(isWhiteSpace(n))
n=scan();
int neg=1;
if(n=='-')
{
neg=-1;
n=scan();
}
while(!isWhiteSpace(n)&& n != '.')
{
if(n>='0'&&n<='9')
{
doub*=10;
doub+=n-'0';
n=scan();
}
else throw new InputMismatchException();
}
if(n=='.')
{
n=scan();
double temp=1;
while(!isWhiteSpace(n))
{
if(n>='0'&&n<='9')
{
temp/=10;
doub+=(n-'0')*temp;
n=scan();
}
else throw new InputMismatchException();
}
}
return doub*neg;
}
public boolean isWhiteSpace(int n)
{
if(n == ' ' || n == '\n' || n == '\r' || n == '\t' || n == -1)
return true;
return false;
}
public void close()throws IOException
{
in.close();
}
}
And the customized Print class can be as follows
import java.io.BufferedWriter;
import java.io.IOException;
import java.io.OutputStreamWriter;
public class Print
{
private BufferedWriter bw;
public Print()
{
this.bw = new BufferedWriter(new OutputStreamWriter(System.out));
}
public void print(Object object)throws IOException
{
bw.append("" + object);
}
public void println(Object object)throws IOException
{
print(object);
bw.append("\n");
}
public void close()throws IOException
{
bw.close();
}
}
You can use BufferedReader for reading data
BufferedReader inp = new BufferedReader(new InputStreamReader(System.in));
int t = Integer.parseInt(inp.readLine());
while(t-->0){
int n = Integer.parseInt(inp.readLine());
int[] arr = new int[n];
String line = inp.readLine();
String[] str = line.trim().split("\\s+");
for(int i=0;i<n;i++){
arr[i] = Integer.parseInt(str[i]);
}
And for printing use StringBuffer
StringBuffer sb = new StringBuffer();
for(int i=0;i<n;i++){
sb.append(arr[i]+" ");
}
System.out.println(sb);
Here is the full version fast reader and writer. I also used Buffering.
import java.io.*;
import java.util.*;
public class FastReader {
private static StringTokenizer st;
private static BufferedReader in;
private static PrintWriter pw;
public static void main(String[] args) throws IOException {
in = new BufferedReader(new InputStreamReader(System.in));
pw = new PrintWriter(new BufferedWriter(new OutputStreamWriter(System.out)));
st = new StringTokenizer("");
pw.close();
}
private static int nextInt() throws IOException {
return Integer.parseInt(next());
}
private static long nextLong() throws IOException {
return Long.parseLong(next());
}
private static double nextDouble() throws IOException {
return Double.parseDouble(next());
}
private static String next() throws IOException {
while(!st.hasMoreElements() || st == null){
st = new StringTokenizer(in.readLine());
}
return st.nextToken();
}
}
Reading from disk, again and again, makes the Scanner slow. I like to use the combination of BufferedReader and Scanner to get the best of both worlds. i.e. speed of BufferredReader and rich and easy API of the scanner.
Scanner scanner = new Scanner(new BufferedReader(new InputStreamReader(System.in)));

C3P0 Statement.close deadlock

Google returns lots of people with deadlock issues in C3P0, but none of the solutions appear to apply (most people suggest setting maxStatements = 0 and maxStatementsPerConnection = 0, both of which we have).
I am using a ComboPooledDataSource from C3P0, initialised as;
cpds = new ComboPooledDataSource();
cpds.setDriverClass("org.postgresql.Driver");
cpds.setJdbcUrl("jdbc:postgresql://" + host + ":5432/" + database);
cpds.setUser(user);
cpds.setPassword(pass);
My query function looks like;
public static List<Map<String, Object>> query(String q) {
Connection c = null;
Statement s = null;
ResultSet r = null;
try {
c = cpds.getConnection();
s = c.createStatement();
s.executeQuery(q);
r = s.getResultSet();
/* parse result set into results List<Map> */
return results;
}
catch(Exception e) { MyUtils.logException(e); }
finally {
closeQuietly(r);
closeQuietly(s);
closeQuietly(c);
}
return null;
}
No queries are returning, despite the query() method reaching the return results; line. The issue is that the finally block is hanging. I have determined that the closeQuietly(s); is the line that is hanging indefinitely.
The closeQuietly() method in question is as you would expect;
public static void closeQuietly(Statement s) {
try { if(s != null) s.close(); }
catch(Exception e) { MyUtils.logException(e); }
}
Why would this method hang on s.close()? I guess it is something to do with the way I am using C3P0.
My complete C3P0 configuration (almost entirely defaults) can be viewed here -> http://pastebin.com/K8XDdiBg
MyUtils.logException(); looks something like;
public static void logException(Exception e) {
StackTraceElement ste[] = e.getStackTrace();
String message = " !ERROR!: ";
for(int i = 0; i < ste.length; i++) {
if(ste[i].getClassName().contains("packagename")) {
message += String.format("%s at %s:%d", e.toString(), ste[i].getFileName(), ste[i].getLineNumber());
break;
}
}
System.err.println(message);
}
Everything runs smoothly if I remove the closeQuietly(s); line. Both closing the ResultSet and Connection object work without problem - apart from Connection starvation of course.

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