Java match/exceed performance of readline

Java match/exceed performance of readline - java

For my application, I had to write a custom "readline" method since I wanted to detect and preserve the newline endings in an ASCII text file. The Java readLine() method does not tell which newline sequence (\r, \n, \r\n) or EOF was encountered, so I cannot put the exact same newline sequence when writing to the modified file.
Here is the SSCE of my test example.
public class TestLineIO {
public static java.util.ArrayList<String> readLineArrayFromFile1(java.io.File file) {
java.util.ArrayList<String> lineArray = new java.util.ArrayList<String>();
try {
java.io.BufferedReader br = new java.io.BufferedReader(new java.io.FileReader(file));
String strLine;
while ((strLine = br.readLine()) != null) {
lineArray.add(strLine);
}
br.close();
} catch (java.io.IOException e) {
System.err.println("Could not read file");
System.err.println(e);
}
lineArray.trimToSize();
return lineArray;
}
public static boolean writeLineArrayToFile1(java.util.ArrayList<String> lineArray, java.io.File file) {
try {
java.io.BufferedWriter out = new java.io.BufferedWriter(new java.io.FileWriter(file));
int size = lineArray.size();
for (int i = 0; i < size; i++) {
out.write(lineArray.get(i));
out.newLine();
}
out.close();
} catch (java.io.IOException e) {
System.err.println("Could not write file");
System.err.println(e);
return false;
}
return true;
}
public static java.util.ArrayList<String> readLineArrayFromFile2(java.io.File file) {
java.util.ArrayList<String> lineArray = new java.util.ArrayList<String>();
try {
java.io.FileInputStream stream = new java.io.FileInputStream(file);
try {
java.nio.channels.FileChannel fc = stream.getChannel();
java.nio.MappedByteBuffer bb = fc.map(java.nio.channels.FileChannel.MapMode.READ_ONLY, 0, fc.size());
char[] fileArray = java.nio.charset.Charset.defaultCharset().decode(bb).array();
if (fileArray == null || fileArray.length == 0) {
return lineArray;
}
int length = fileArray.length;
int start = 0;
int index = 0;
while (index < length) {
if (fileArray[index] == '\n') {
lineArray.add(new String(fileArray, start, index - start + 1));
start = index + 1;
} else if (fileArray[index] == '\r') {
if (index == length - 1) { //last character in the file
lineArray.add(new String(fileArray, start, length - start));
start = length;
break;
} else {
if (fileArray[index + 1] == '\n') {
lineArray.add(new String(fileArray, start, index - start + 2));
start = index + 2;
index++;
} else {
lineArray.add(new String(fileArray, start, index - start + 1));
start = index + 1;
}
}
}
index++;
}
if (start < length) {
lineArray.add(new String(fileArray, start, length - start));
}
} finally {
stream.close();
}
} catch (java.io.IOException e) {
System.err.println("Could not read file");
System.err.println(e);
e.printStackTrace();
return lineArray;
}
lineArray.trimToSize();
return lineArray;
}
public static boolean writeLineArrayToFile2(java.util.ArrayList<String> lineArray, java.io.File file) {
try {
java.io.BufferedWriter out = new java.io.BufferedWriter(new java.io.FileWriter(file));
int size = lineArray.size();
for (int i = 0; i < size; i++) {
out.write(lineArray.get(i));
}
out.close();
} catch (java.io.IOException e) {
System.err.println("Could not write file");
System.err.println(e);
return false;
}
return true;
}
public static void main(String[] args) {
System.out.println("Begin");
String fileName = "test.txt";
long start = 0;
long stop = 0;
start = java.util.Calendar.getInstance().getTimeInMillis();
java.io.File f = new java.io.File(fileName);
java.util.ArrayList<String> javaLineArray = readLineArrayFromFile1(f);
stop = java.util.Calendar.getInstance().getTimeInMillis();
System.out.println("Total time = " + (stop - start) + " ms");
java.io.File oj = new java.io.File(fileName + "_readline.txt");
writeLineArrayToFile1(javaLineArray, oj);
start = java.util.Calendar.getInstance().getTimeInMillis();
java.util.ArrayList<String> myLineArray = readLineArrayFromFile2(f);
stop = java.util.Calendar.getInstance().getTimeInMillis();
System.out.println("Total time = " + (stop - start) + " ms");
java.io.File om = new java.io.File(fileName + "_custom.txt");
writeLineArrayToFile2(myLineArray, om);
System.out.println("End");
}
}
Version 1 uses readLine(), whereas version 2 is my version, which preserves newline characters.
On a text file with about 500K lines, version1 takes about 380 ms, whereas version2 takes 1074 ms.
How can I speed-up the performance of version2?
I checked Google guava and apache-commons libraries but cannot find a suitable replacement for "readLine()" that will tell which newline character was encountered when reading a text file.

Whenever the issue regards a program's speed, the main thing you should keep in mind is that, for any continuous process within that program, the speed is nearly always limited by one of two things: CPU (processing power) or IO (memory allocation and transfer speed).
Usually either your CPU is faster than your IO, or the contrary. Because of this, your program's speed-limit is almost always dictated by one of them, and it's usually easy to know which:
A program that does a lot of calculations but makes only a few, small operations with files, is almost certainly CPU-bound.
A program that reads a lot of data from files, or writes a lot of data to them, but is not very demanding towards processing, is almost certainly IO-bound.
Things are kinda straightforward when trying to improve an CPU-bounded program's speed. It mostly comes down to achieving the same goal or effect while making less operations.
This, on the other hand, does not make the process any easier. In fact, it's usually much harder to optimize CPU-bounded programs than to optimize IO-bounded ones, because each CPU-related operation is usually unique, and has to be revised individually.
Although generally easier once you have the experience, things are not so straightforward with IO-bound programs. There are a lot more stuff to consider when dealing with IO-bound processes.
I'll be using Hard-Disk Drives (HDDs) as the basis, since the characteristics I'll mention affect HDDs the strongest (because they are mechanical), but you should keep in mind that many of the same concepts apply, to some extent, to almost every memory-storage hardware, including Solid-State Drives (SSDs) and even RAM!
These are the main performance characteristics of most memory-storage hardware:
Access time: Also known as response time, it is the time it takes before the hardware can actually transfer data.
For mechanical hardware such as HDDs, this is mostly related to the mechanical nature of the drive, in other words, it's rotating disk and moving "heads". As such, access time of mechanical drives can vary significantly between each-other.
For circuital hardware such as SSDs and RAM, this time is not dependent on moving parts, but rather electrical connections, so the access time is very quick and consistent, and you shouldn't worry about it.
Seek time: The time it takes for the hardware to seek (reach) the correct position within it's internal subdivisions, in order to read from or write to addresses in that section.
For mechanical drives, mainly rotary ones, the seek time measures the time it takes the head assembly on the actuator arm to travel to the track of the disk where the data will be read from or written to.
Average seek time ranges from 3 ms (~) for high-end server drives, to 15 ms (~) for mobile drives, with the most common desktop drives typically having a seek time around 9 ms (~).
With RAM and SSDs, there are no moving parts, so a measurement of the seek time is only testing the electronic circuits, and preparing a particular location on the memory in the device for the operation.
Typical SSDs will have a seek time between 0.08 to 0.16 ms (~), with RAM being even faster.
Command-Processing time: Also known as command overhead, it is the time it takes for the drive's electronics to set up the necessary communication between the various internal components, so it can read or write the data.
This is in the range of 0.003 ms (~) for both, mechanical and circuital devices, and is usually ignored in benchmarks.
Settle time: It is the time it takes for the heads to settle on the target track and stop vibrating, so that they do not read or write off-track.
This amount is usually very small (typically less than 0.1 ms), and typically included in benchmarks as part of the seek time.
Data-Transfer rate: Also called throughput, it covers both: The internal rate, which is the time it takes to move data between the disk surface and the controller on the drive. And the external rate, which is the time to move data between the controller on the drive and an external component in the host system. It has a few sub-factors within:
Media rate: Speed at which the drive can read bits from the media. In other words, the actual read/write speed.
Sector overhead: Additional time (bytes) needed for control structures and other information necessary to manage the drive, locate and validate data and perform other support functions.
Allocation speed: Similar to sector overhead, it's the time taken for the drive to determine the slots that will be written to, and to register them on it's address dictionary. Only needed for write operations.
Head-Switch time: Time required to electrically switch from one head to another; Only applies to multi-head drives and is about 1 to 2 ms.
Cylinder-switch time: Time required to move to an adjacent track; The name cylinder is used because typically all the tracks of a drive with more than one head or data surface are read before moving the actuator, implying the image of a circle or cylinder rather than a track. This time is exclusive to rotary mechanical drives, and is typically about about 2 to 3 ms.
This means that the main performance issues regarding IO are caused by going back-and-forth between IO and processing. An issue that can be enormously diminished by using buffers, and processing and reading/writhing in bigger chunks of data, rather than every byte.
As you can also see, although many of the speed characteristics are still present, RAM and SSDs do not have the same internal limits of HDDs, so their internal and external transfer rates often reach the maximum capabilities of the drive-to-host interface.
Chunk approach example:
This example will create a Test folder on the desktop, and generate a Test.txt file within.
The file is generated with an specified number of lines, each line containing the word "Test" repeated for an specific number of times (for file-size purposes). Each line is ended by "\r", "\n" or "\r\n", sequentially.
It's meaningless to save the results of each chunk in-memory cumulatively, as doing so would lead the whole file end up in-memory eventually, which is nearly the same problem of not using chunks to begin with.
As such, an output file is created in the same Test folder, to which the result of every chunk is stored at, once that chunk is finished.
The base file is read using buffers, and those buffers are additionally used as the chunks.
The process here is simply printing a textual version of the line-separator ("\\r", "\\n" or "\\r\\n"), followed by ": ", followed by the line contents; But for the last line, "EOF" is used instead.
To actually operate with chunks, it's probably easier to manage with a class-based approach, rather than a purely function-based one.
Anyways, here goes the code:
public static void main(String[] args) throws FileNotFoundException, IOException {
File file = new File(TEST_FOLDER, "Test.txt");
//These settings create a 122 MB file.
generateTestFile(file, 500000, 50);
long clock = System.nanoTime();
processChunks(file, 8 * (int) Math.pow(1024, 2));
clock = System.nanoTime() - clock;
float millis = clock / 1000000f;
float seconds = millis / 1000f;
System.out.printf(""
+ "%12d nanos\n"
+ "%12.3f millis\n"
+ "%12.3f seconds\n",
clock, millis, seconds);
}
public static File prepareResultFile(File source) {
String ofn = source.getName(); //Original File Name.
int extPos = ofn.lastIndexOf('.'); //Extension index.
String ext = ofn.substring(extPos); //Get extension.
ofn = ofn.substring(0, extPos); //Get name without extension reusing 'ofn'.
return new File(source.getParentFile(), ofn + "_Result" + ext);
}
public static void processChunks(File file, int buffSize)
throws FileNotFoundException, IOException {
//No need for buffers bigger than the file itself.
if (file.length() < buffSize) {
buffSize = (int)file.length();
}
byte[] buffer = new byte[buffSize];
BufferedInputStream bis = new BufferedInputStream(new FileInputStream(file), buffSize);
BufferedOutputStream bos = new BufferedOutputStream(new FileOutputStream(
prepareResultFile(file)), buffSize);
StringBuilder sb = new StringBuilder();
while (bis.read(buffer) > (-1)) {
//Check if a "\r\n" was split between chunks.
boolean skipFirst = false;
if (sb.length() > 0 && sb.charAt(sb.length() - 1) == '\r') {
if (buffer[0] == '\n') {
bos.write(("\\r\\n: " + sb.toString() + System.lineSeparator()).getBytes());
sb = new StringBuilder();
skipFirst = true;
}
}
for (int i = skipFirst ? 1 : 0; i < buffer.length; i++) {
if (buffer[i] == '\r') {
if (i + 1 < buffer.length) {
if (buffer[i + 1] == '\n') {
bos.write(("\\r\\n: " + sb.toString() + System.lineSeparator()).getBytes());
i++; //Skip '\n'.
} else {
bos.write(("\\r: " + sb.toString() + System.lineSeparator()).getBytes());
}
sb = new StringBuilder(); //Reset accumulator.
} else {
//A "\r\n" might be split between two chunks.
}
} else if (buffer[i] == '\n') {
bos.write(("\\n: " + sb.toString() + System.lineSeparator()).getBytes());
sb = new StringBuilder(); //Reset accumulator.
} else {
sb.append((char) buffer[i]);
}
}
}
bos.write(("EOF: " + sb.toString()).getBytes());
bos.flush();
bos.close();
bis.close();
System.out.println("Finished!");
}
public static boolean generateTestFile(File file, int lines, int elements)
throws IOException {
String[] lineBreakers = {"\r", "\n", "\r\n"};
BufferedOutputStream bos = null;
try {
bos = new BufferedOutputStream(new FileOutputStream(file));
for (int i = 0; i < lines; i++) {
for (int ii = 1; ii < elements; ii++) {
bos.write("test ".getBytes());
}
bos.write("test".getBytes());
bos.write(lineBreakers[i % 3].getBytes());
}
bos.flush();
System.out.printf("LOG: Test file \"%s\" created.\n", file.getName());
return true;
} catch (IOException ex) {
System.err.println("ERR: Could not write file.");
throw ex;
} finally {
try {
bos.close();
} catch (IOException ex) {
System.err.println("WRN: Could not close stream.");
Logger.getLogger(Q_13458142_v2.class.getName()).log(Level.SEVERE, null, ex);
}
}
}
I don't know what IDE you are using, but if it's NetBeans, make a memory-profile of your code and compare to a profile of this one. You should notice a big difference in the amount of memory needed during processing.
Here, the chunk approach's memory usage, which includes not only the chunk itself but also the program's own variables and structures, does not go over 40 MB even tough we are dealing with a file bigger than 100 MB. As you can see:
It also spends very little time in GB, mostly less than 5% at any given point:

The second version doesn't seem to use BufferedReader or another form of buffer. It might be the cause of slow down.
Since you seem to read the whole file in memory, you can perhaps read it as a big string (with a buffer) then parse it in memory to analyze the line endings.

Your are doubling the out statements(one for line and one for newline):
Can you try below(use lineSeparator() to get the line separator and append before writing):
out.write(lineArray.get(i)+System.lineSeparator());

Don't reinvent the wheel.
Check the BufferedReader#readLine() code
Copy, paste, and make the changes you need to keep the line separator inside the line

Related

Split mp3 file into chuncks using multiple threads

I have to write a program which can split and merge files with various extensions. While splitting and merging it should use multiple threads. My code can do only a half of the task - if I don't use multithreading, it splits the file perfectly. If I do use multithreading, it splits the file, but saves only the first part several times.
What should I fix to make it work?
A method of Splitter.class
public void splitFile(CustomFile customFile, int dataSize) {
for (int i = 1; i <= partsNumber; i++) {
FileSplitterThread thread = new FileSplitterThread(customFile, i, dataSize);
thread.start();
}
}
Run method of my thread:
#Override
public void run() {
try {
fileInputStream = new FileInputStream(initialFile.getData());
byte[] b = new byte[dataSize];
String fileName = initialFile.getName() + "_part_" + index + "." + initialFile.getExtension();
fileOutputStream = new FileOutputStream(fileName);
int i = fileInputStream.read(b);
fileOutputStream.write(b, 0, i);
fileOutputStream.close();
fileOutputStream = null;
} catch (IOException e) {
e.printStackTrace();
}
}

The reason is you cannot achieve multi-threaded file splitting with just InputStream. And you are reading the file from the beginning always, you are getting the same bytes
For a simple file splitting mechanism, the following could be the general steps:
Get the size of the file (data size)
Chunk it into offsets for each thread to read. Example, if you have 2 threads and the data is 1000 bytes, the offsets will be 0,1000/2, where the read length is 500. the first thread will read position from 0 to 499, the next thread will start at 500 and read till 999
Get two InputStreams and position them using Channel (here is a good post, Java how to read part of file from specified position of bytes?)
Encapsulate the above info: InputStream, offset, length to read, output file name etc. and provide it to each of the threads

Java: How to efficiently create multiple nested zip files?

I am trying to create several zip files in a multi-threaded environment (actually I tried to write about 400 zip files using an FixedThreadPool ExecutorService serving 16 threads). Each of these zip files may contain thousands of other zip files.
Unfortunately after about two minutes my java process (jdk1.8.0_60_x64 on Windows 64bit) seems to end up in a memory leak. While the heap (according to Java Mission Control) only uses about 1 GB (actually between 500 MB and 1 GB), the java process in total uses about 40 GB of machine memory (seems to be a lot of native memory used). This number keeps increasing and after another while the process/my system practically stops working (I do not have that much memory).
After some research I found out it is possible to simulate the behavior using a rather small main method:
public static void main(String[] args) throws Throwable {
for (int k = 0; k < 16; k++) {
new Thread(Integer.toString(k)) {
#Override
public void run() {
try {
long bytes = 0;
ZipOutputStream zos = new ZipOutputStream(new BufferedOutputStream(new FileOutputStream(new File(getName() + ".tmp"))));
zos.setLevel(Deflater.NO_COMPRESSION);
Random rand = new SecureRandom();
for (int i = 0; i < 65535; i++) {
zos.putNextEntry(new ZipEntry("" + i));
ZipOutputStream inner = new ZipOutputStream(zos);
for (int j = 0; j < 10; j++) {
byte[] b = new byte[512];
bytes += b.length;
rand.nextBytes(b);
inner.putNextEntry(new ZipEntry("" + j));
inner.write(b);
inner.closeEntry();
}
inner.finish();
inner.flush();
zos.closeEntry();
zos.flush();
if (i % 1000 == 0) {
System.err.println(getName() + ": " + i + " (" + bytes + ") bytes");
}
}
zos.flush();
zos.close();
}
catch (Exception e) {
e.printStackTrace();
}
}
}.start();
}
}
Is there anything wrong with my code? Probably.
Is it a bad idea to use I/O operations in these many threads? I'm really not sure about it (actually I would like to gain performance, not loose performance). But on the other side, if I leave out all the zip stuff and just write on the FileOutputStream in even more threads no such problems occur. Do the zip entries overhead increase the size that much?
Is there anything wrong with the usage of my inner ZipOutputStream? As far as I understand I must not call close() for this class as it would close the outer stream named zos as well. Instead I am calling finish().

Limit Android Filesize

Background
I'm keeping a relatively large text file in android storage, and appending to it periodically- while limiting the file's size to some arbitrary size (say 2MB)
Hopefully I'm missing a function somewhere, or hopefully there is a better way to do this process.
Currently, when the file a goes over that arbitrary size, I create a temporary file b, copy the relevant portion of the file a (more or less the substring of the file a starting at byte xxx where xxx is the number of bytes too large the file a would be if I wrote the next bit of data to the log) plus the current data, then overwrite the file a with the second file b.
This is obviously terribly inefficient...
Another solution that I'm not terribly fond of is to keep two files, and toggle between the two of them, clearing the next when the current is full, and switching to that file for output.
However, it would be suuuuuper handy if I could just do something like this
File A = new File("output");
A.chip(500);
or maybe
A.subfile(500,A.length()-500);
TLDR;
Is there a function or perhaps library available for Android that can remove a portion of a file?

Did you already take a look at RandomAccessFile? Though you cannot remove portions of a file you can seek any position within the file and even set the length. So if you detect your file grows too large, just grab the relevant portion and jump to the beginning. Set length to 0 and write the new data.
EDIT:
I wrote a small demo. It shows if the file size is limeted to 10 bytes. If you pass in the values 10 to 15 as strings and separate them with commas, after 10,11,12, the file is written from the beginning, so after 15 it reads 13,14,15
public class MainActivity extends Activity {
private static final String TAG = MainActivity.class.getSimpleName();
private static final long MAX = 10;
private static final String FILE_TXT = "file.txt";
#Override
protected void onCreate(Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
for (int i = 10; i <= 15; i++) {
if (i > 10) {
writeToFile(",");
}
writeToFile(Integer.toString(i));
}
}
private void writeToFile(String text) {
try {
File f = new File(getFilesDir(), FILE_TXT);
RandomAccessFile file = new RandomAccessFile(f, "rw");
long currentLength = file.length();
if (currentLength + text.length() > MAX) {
file.setLength(0);
}
file.seek(file.length());
file.write(text.getBytes());
file.close();
} catch (IOException e) {
Log.e(TAG, "writeToFile()", e);
}
printFileContents();
}
private void printFileContents() {
StringBuilder sb = new StringBuilder();
try {
FileInputStream fin = openFileInput(FILE_TXT);
int ch;
while ((ch = fin.read()) != -1) {
sb.append((char) ch);
}
fin.close();
} catch (IOException e) {
Log.e(TAG, "printFileContents()", e);
}
Log.d(TAG, "current content: " + sb.toString());
}
}

creating large csv files in Java getting really slow

i have a performance problem when trying to create a csv file starting from another csv file.
this is how the original file looks:
country,state,co,olt,olu,splitter,ont,cpe,cpe.latitude,cpe.longitude,cpe.customer_class,cpe.phone,cpe.ip,cpe.subscriber_id
COUNTRY-0001,STATE-0001,CO-0001,OLT-0001,OLU0001,SPLITTER-0001,ONT-0001,CPE-0001,28.21487,77.451775,ALL,SIP:+674100002743#IMS.COMCAST.NET,SIP:E28EDADA06B2#IMS.COMCAST.NET,CPE_SUBSCRIBER_ID-QHLHW4
COUNTRY-0001,STATE-0002,CO-0002,OLT-0002,OLU0002,SPLITTER-0002,ONT-0002,CPE-0002,28.294018,77.068924,ALL,SIP:+796107443092#IMS.COMCAST.NET,SIP:58DD999D6466#IMS.COMCAST.NET,CPE_SUBSCRIBER_ID-AH8NJQ
potentially it could be millions of lines like this, i have detected the problem with 1.280.000 lines.
this is the algorithm:
File csvInputFile = new File(csv_path);
int blockSize = 409600;
brCsvInputFile = new BufferedReader(frCsvInputFile, blockSize);
String line = null;
StringBuilder sbIntermediate = new StringBuilder();
skipFirstLine(brCsvInputFile);
while ((line = brCsvInputFile.readLine()) != null) {
createIntermediateStringBuffer(sbIntermediate, line.split(REGEX_COMMA));
}
private static void skipFirstLine(BufferedReader br) throws IOException {
String line = br.readLine();
String[] splitLine = line.split(REGEX_COMMA);
LOGGER.debug("First line detected! ");
createIndex(splitLine);
createIntermediateIndex(splitLine);
}
private static void createIndex(String[] splitLine) {
LOGGER.debug("START method createIndex.");
for (int i = 0; i < splitLine.length; i++)
headerIndex.put(splitLine[i], i);
printMap(headerIndex);
LOGGER.debug("COMPLETED method createIndex.");
}
private static void createIntermediateIndex(String[] splitLine) {
LOGGER.debug("START method createIntermediateIndex.");
com.tekcomms.c2d.xml.model.v2.Metadata_element[] metadata_element = null;
String[] servicePath = newTopology.getElement().getEntity().getService_path().getLevel();
if (newTopology.getElement().getMetadata() != null)
metadata_element = newTopology.getElement().getMetadata().getMetadata_element();
LOGGER.debug(servicePath.toString());
LOGGER.debug(metadata_element.toString());
headerIntermediateIndex.clear();
int indexIntermediateId = 0;
for (int i = 0; i < servicePath.length; i++) {
String level = servicePath[i];
LOGGER.debug("level is: " + level);
headerIntermediateIndex.put(level, indexIntermediateId);
indexIntermediateId++;
// its identificator is going to be located to the next one
headerIntermediateIndex.put(level + "ID", indexIntermediateId);
indexIntermediateId++;
}
// adding cpe.latitude,cpe.longitude,cpe.customer_class, it could be
// better if it would be metadata as well.
String labelLatitude = newTopology.getElement().getEntity().getLatitude();
// indexIntermediateId++;
headerIntermediateIndex.put(labelLatitude, indexIntermediateId);
String labelLongitude = newTopology.getElement().getEntity().getLongitude();
indexIntermediateId++;
headerIntermediateIndex.put(labelLongitude, indexIntermediateId);
String labelCustomerClass = newTopology.getElement().getCustomer_class();
indexIntermediateId++;
headerIntermediateIndex.put(labelCustomerClass, indexIntermediateId);
// adding metadata
// cpe.phone,cpe.ip,cpe.subscriber_id,cpe.vendor,cpe.model,cpe.customer_status,cpe.contact_telephone,cpe.address,
// cpe.city,cpe.state,cpe.zip,cpe.bootfile,cpe.software_version,cpe.hardware_version
// now i need to iterate over each Metadata_element belonging to
// topology.element.metadata
// are there any metadata?
if (metadata_element != null && metadata_element.length != 0)
for (int j = 0; j < metadata_element.length; j++) {
String label = metadata_element[j].getLabel();
label = label.toLowerCase();
LOGGER.debug(" ==label: " + label + " index_pos: " + j);
indexIntermediateId++;
headerIntermediateIndex.put(label, indexIntermediateId);
}
printMap(headerIntermediateIndex);
LOGGER.debug("COMPLETED method createIntermediateIndex.");
}
Reading the entire dataset, 1.280.000 lines take 800 ms! so the problem is in this method
private static void createIntermediateStringBuffer(StringBuilder sbIntermediate, String[] splitLine) throws ClassCastException,
NullPointerException {
LOGGER.debug("START method createIntermediateStringBuffer.");
long start, end;
start = System.currentTimeMillis();
ArrayList<String> hashes = new ArrayList<String>();
com.tekcomms.c2d.xml.model.v2.Metadata_element[] metadata_element = null;
String[] servicePath = newTopology.getElement().getEntity().getService_path().getLevel();
LOGGER.debug(servicePath.toString());
if (newTopology.getElement().getMetadata() != null) {
metadata_element = newTopology.getElement().getMetadata().getMetadata_element();
LOGGER.debug(metadata_element.toString());
}
for (int i = 0; i < servicePath.length; i++) {
String level = servicePath[i];
LOGGER.debug("level is: " + level);
if (splitLine.length > getPositionFromIndex(level)) {
String name = splitLine[getPositionFromIndex(level)];
sbIntermediate.append(name);
hashes.add(name);
sbIntermediate.append(REGEX_COMMA).append(HashUtils.calculateHash(hashes)).append(REGEX_COMMA);
LOGGER.debug(" ==sbIntermediate: " + sbIntermediate.toString());
}
}
// end=System.currentTimeMillis();
// LOGGER.info("COMPLETED adding name hash. " + (end - start) + " ms. " + (end - start) / 1000 + " seg.");
// adding cpe.latitude,cpe.longitude,cpe.customer_class, it should be
// better if it would be metadata as well.
String labelLatitude = newTopology.getElement().getEntity().getLatitude();
if (splitLine.length > getPositionFromIndex(labelLatitude)) {
String lat = splitLine[getPositionFromIndex(labelLatitude)];
sbIntermediate.append(lat).append(REGEX_COMMA);
}
String labelLongitude = newTopology.getElement().getEntity().getLongitude();
if (splitLine.length > getPositionFromIndex(labelLongitude)) {
String lon = splitLine[getPositionFromIndex(labelLongitude)];
sbIntermediate.append(lon).append(REGEX_COMMA);
}
String labelCustomerClass = newTopology.getElement().getCustomer_class();
if (splitLine.length > getPositionFromIndex(labelCustomerClass)) {
String customerClass = splitLine[getPositionFromIndex(labelCustomerClass)];
sbIntermediate.append(customerClass).append(REGEX_COMMA);
}
// end=System.currentTimeMillis();
// LOGGER.info("COMPLETED adding lat,lon,customer. " + (end - start) + " ms. " + (end - start) / 1000 + " seg.");
// watch out metadata are optional, it can appear as a void chain!
if (metadata_element != null && metadata_element.length != 0)
for (int j = 0; j < metadata_element.length; j++) {
String label = metadata_element[j].getLabel();
LOGGER.debug(" ==label: " + label + " index_pos: " + j);
if (splitLine.length > getPositionFromIndex(label)) {
String actualValue = splitLine[getPositionFromIndex(label)];
if (!"".equals(actualValue))
sbIntermediate.append(actualValue).append(REGEX_COMMA);
else
sbIntermediate.append("").append(REGEX_COMMA);
} else
sbIntermediate.append("").append(REGEX_COMMA);
LOGGER.debug(" ==sbIntermediate: " + sbIntermediate.toString());
}//for
sbIntermediate.append("\n");
end = System.currentTimeMillis();
LOGGER.info("COMPLETED method createIntermediateStringBuffer. " + (end - start) + " ms. ");
}
As you can see, this method adds a precalculated line to the StringBuffer, reads every line from input csv file, calculate new data from that lines and finally add the generated line to the StringBuffer, so finally i can create the file with that buffer.
I have run jconsole and i can see that there are no memory leaks, i can see the sawtooths representing the creation of objects and the gc recollecting garbaje. It never traspasses the memory heap threshold.
One thing i have noticed is that the time needed for add a new line to the StringBuffer is completed within a very few ms range, (5,6,10), but is raising with time, to (100-200) ms and i suspect more in a near future, so probably this is the battle horse.
I have tried to analyze the code, i know that there are 3 for loops, but they are very shorts, the first loop iterates over 8 elements only:
for (int i = 0; i < servicePath.length; i++) {
String level = servicePath[i];
LOGGER.debug("level is: " + level);
if (splitLine.length > getPositionFromIndex(level)) {
String name = splitLine[getPositionFromIndex(level)];
sbIntermediate.append(name);
hashes.add(name);
sbIntermediate.append(REGEX_COMMA).append(HashUtils.calculateHash(hashes)).append(REGEX_COMMA);
LOGGER.debug(" ==sbIntermediate: " + sbIntermediate.toString());
}
}
I have meassured the time needed to get the name from the splitline and it is worthless, 0 ms, the same to calculateHash method, 0 ms.
the other loop, are practically the same, iterates over 0 to n, where n is a very tiny int, 3 to 10 for example, so i do not understand why it takes more time to finish the method, the only thing i find is that to add a new line to the buffer is getting slow the process.
I am thinking about a producer consumer multi threaded strategy, a reader thread that reads every line and put them into a circular buffer, another threads take it one by one, process them and add a precalculated line to the StringBuffer, which is thread safe, when the file is fully readed, the reader thread sends a message to to the another threads telling them to stop. Finally i have to save this buffer to a file. What do you think? this is a good idea?

I am thinking about a producer consumer multi threaded strategy, a reader thread that reads every line and put them into a circular buffer, another threads take it one by one, process them and add a precalculated line to the StringBuffer, which is thread safe, when the file is fully readed, the reader thread sends a message to to the another threads telling them to stop. Finally i have to save this buffer to a file. What do you think? this is a good idea?
Maybe, but it's quite a lot of work, I'd try something simpler first.
line.split(REGEX_COMMA)
Your REGEX_COMMA is a string which gets compiled into an regex a million times. It's trivial, but I'd try to use a Pattern instead.
You're producing a lot of garbage with your split. Maybe you should avoid it by manually splitting the input into a reused ArrayList<String> (it's just a few lines).
If all you need is writing the result into a file, it might be better to avoid building one huge String. Maybe a List<String> or even a List<StringBuilder> would be better, maybe writing directly to a buffered stream would do.
You seem to be working with ASCII only. Your encoding is platform dependent which may mean you're using UTF-8, which is possibly slow. Switching to a simpler encoding could help.
Working with byte[] instead of String would most probably help. Bytes are half as big as chars and there's no conversion needed when reading a file. All the operations you do can be done with bytes equally easy.
One thing i have noticed is that the time needed for add a new line to the StringBuffer is completed within a very few ms range, (5,6,10), but is raising with time, to (100-200) ms and i suspect more in a near future, so probably this is the battle horse.
That's resizing, which could be sped up by using the suggested ArrayList<String>, as the amount of data to be copied is much lower. Writing the data out when the buffer gets big would do as well.
I have meassured the time needed to get the name from the splitline and it is worthless, 0 ms, the same to calculateHash method, 0 ms.
Never use currentTimeMillis for this as nanoTime is strictly better. Use a profiler. The problem with a profiler is that it changes what it should measure. As a poor man's profiler, you can compute the sum of all the times spend inside of the suspect method and compare it with the total time.
What's the CPU load and what does GC do when running the program?

I used superCSV library in my project to handle large set of lines. it is relatively fast than manually read the lines. Reference

download file in java from wampserver

i create java downloader and download 900MB file from my wampserver , and it works correctly , but when i check the Ram usage , it increase a lot , i dont know why?
i used IDM to download same file form my wampserver and it didnt use a lot of Ram
when i see process and disk usage of my java downloader it take about 50MB and 5% cup but when i look to performance in Performance TAB , my RAM increase alot.
this is performance pic : http://i.stack.imgur.com/zfxNv.png
and this my code that my app create 8 thread to download this file simultaneously:
private void downloadFile() {
try {
this.response = this.con.getInputStream();
this.bis = new BufferedInputStream(this.response, 32 * 1024);
this.responseContentSize = this.con.getContentLength();
if (this.responseContentSize == (this.end_range - this.start_range) + 1) {
int MAX_BUFFER_SIZE = 32*1024;
byte buffer[] = new byte[MAX_BUFFER_SIZE];
makeTmpFile();
out = new FileOutputStream(this.tmpdir + this.tmpFilename);
bos = new BufferedOutputStream(out, 32 * 1024);
while (true) {
int r = this.bis.read(buffer, 0, this.MAX_BUFFER_SIZE);
if (r == -1)
break;
bos.write(buffer, 0, r);
downloadedBytes += r;
}
if (bos != null)
bos.close();
if (out != null)
out.close();
if (bis != null)
bis.close();
if (response != null)
response.close();
}
} catch (IOException e) {
sharedDownloadStatus.setCell(this.threadIndex, STATUS, 0);//error
log.setLog("func : downloadFile =>\n couldnt download file\n" + e.getMessage());
}
}

You allocate data buffer for each chunk. They temporarily occupy a lot of memory befor garbage collector take care of them.
Try holding only one data buffer per thread. (Using ThreadLocal, for example).

You can use the jvisualvm.exe program to look at your memory consumption and see where its being allocated. jvisualvm is located in the bin folder of your jdk installation.
Heres what I would do to change your code:
Get rid of the BufferedInput/BufferedOutput streams. These buffered streams are unnecessary in your program and are just adding in an additional memory allocation (of 32kb per buffered stream) but arent needed.
Dont use 8 threads, I've build file download application to transfer very large files across networks and I have found the optimal amount of threads is 2 or 3. You cant download the file faster than your internet connection therefore adding in extra thread doesnt do anything but waste memory and time.
Use a smaller buffer, a 32kb buffer is quite large, I would test using a smaller buffer like 1kb.
Dont confuse wammp memory/cpu usage with your Java applications memory/cpu usage. Use the 'Processes' tab of the Windows Task Manager instead of the Performance tab.
With that said I dont have your entire program and cant test and debug performance for you but these are the things I would do. Below is your code that I have modified as much as possible.
private void downloadFile() {
try {
this.response = this.con.getInputStream();
this.responseContentSize = this.con.getContentLength();
if (this.responseContentSize == (this.end_range - this.start_range) + 1) {
int MAX_BUFFER_SIZE = 1024;
byte buffer[] = new byte[MAX_BUFFER_SIZE];
makeTmpFile();
out = new FileOutputStream(this.tmpdir + this.tmpFilename);
int r = 0;
while ((r = response.read(buffer)) != -1) {
out.write(buffer, 0, r);
downloadedBytes = r;
}
}
} catch (IOException e) {
sharedDownloadStatus.setCell(this.threadIndex, STATUS, 0);//error
log.setLog("func : downloadFile =>\n couldnt download file\n" + e.getMessage());
} finally {
if (out != null)
out.close();
if (response != null)
response.close();
}
}

Develop Reference

Java is a programming language and computing platform first released by Sun Microsystems in 1995.