I have to write huge data in text[csv] file. I used BufferedWriter to write the data and it took around 40 secs to write 174 mb of data. Is this the fastest speed java can offer?
bufferedWriter = new BufferedWriter ( new FileWriter ( "fileName.csv" ) ); Note: These 40 secs include the time of iterating and fetching the records from resultset as well. :) . 174 mb is for 400000 rows in resultset.
You might try removing the BufferedWriter and just using the FileWriter directly. On a modern system there's a good chance you're just writing to the drive's cache memory anyway.
It takes me in the range of 4-5 seconds to write 175MB (4 million strings) -- this is on a dual-core 2.4GHz Dell running Windows XP with an 80GB, 7200-RPM Hitachi disk.
Can you isolate how much of the time is record retrieval and how much is file writing?
import java.io.BufferedWriter; import java.io.File; import java.io.FileWriter; import java.io.IOException; import java.io.Writer; import java.util.ArrayList; import java.util.List; public class FileWritingPerfTest { private static final int ITERATIONS = 5; private static final double MEG = (Math.pow(1024, 2)); private static final int RECORD_COUNT = 4000000; private static final String RECORD = "Help I am trapped in a fortune cookie factory\n"; private static final int RECSIZE = RECORD.getBytes().length; public static void main(String[] args) throws Exception { List<String> records = new ArrayList<String>(RECORD_COUNT); int size = 0; for (int i = 0; i < RECORD_COUNT; i++) { records.add(RECORD); size += RECSIZE; } System.out.println(records.size() + " 'records'"); System.out.println(size / MEG + " MB"); for (int i = 0; i < ITERATIONS; i++) { System.out.println("\nIteration " + i); writeRaw(records); writeBuffered(records, 8192); writeBuffered(records, (int) MEG); writeBuffered(records, 4 * (int) MEG); } } private static void writeRaw(List<String> records) throws IOException { File file = File.createTempFile("foo", ".txt"); try { FileWriter writer = new FileWriter(file); System.out.print("Writing raw... "); write(records, writer); } finally { // comment this out if you want to inspect the files afterward file.delete(); } } private static void writeBuffered(List<String> records, int bufSize) throws IOException { File file = File.createTempFile("foo", ".txt"); try { FileWriter writer = new FileWriter(file); BufferedWriter bufferedWriter = new BufferedWriter(writer, bufSize); System.out.print("Writing buffered (buffer size: " + bufSize + ")... "); write(records, bufferedWriter); } finally { // comment this out if you want to inspect the files afterward file.delete(); } } private static void write(List<String> records, Writer writer) throws IOException { long start = System.currentTimeMillis(); for (String record: records) { writer.write(record); } // writer.flush(); // close() should take care of this writer.close(); long end = System.currentTimeMillis(); System.out.println((end - start) / 1000f + " seconds"); } } 
writer.flush() is not necessary in this case because writer.close() flushes memory implicity. BTW: best practices recommend using try resource close instead explicitly calling close().
Writer.flush() and it says “Close the stream, flushing it first.”. So calling flush() before close() was never needed. By the way, one of the reasons why BufferedWriter might be useless, is that FileWriter, a specialization of the OutputStreamWriter, has to have its own buffering anyway, when it does the conversion from char sequences to byte sequences in the target encoding. Having more buffers at the front-end doesn’t help when the charset encoder has to flush its smaller byte buffer at a higher rate anyway.Buffered… counterpart for the channel types at all.try memory mapped files (takes 300 m/s to write 174MB in my m/c, core 2 duo, 2.5GB RAM) :
byte[] buffer = "Help I am trapped in a fortune cookie factory\n".getBytes(); int number_of_lines = 400000; FileChannel rwChannel = new RandomAccessFile("textfile.txt", "rw").getChannel(); ByteBuffer wrBuf = rwChannel.map(FileChannel.MapMode.READ_WRITE, 0, buffer.length * number_of_lines); for (int i = 0; i < number_of_lines; i++) { wrBuf.put(buffer); } rwChannel.close(); 
Only for the sake of statistics:
The machine is old Dell with new SSD
CPU: Intel Pentium D 2,8 Ghz
SSD: Patriot Inferno 120GB SSD
4000000 'records' 175.47607421875 MB Iteration 0 Writing raw... 3.547 seconds Writing buffered (buffer size: 8192)... 2.625 seconds Writing buffered (buffer size: 1048576)... 2.203 seconds Writing buffered (buffer size: 4194304)... 2.312 seconds Iteration 1 Writing raw... 2.922 seconds Writing buffered (buffer size: 8192)... 2.406 seconds Writing buffered (buffer size: 1048576)... 2.015 seconds Writing buffered (buffer size: 4194304)... 2.282 seconds Iteration 2 Writing raw... 2.828 seconds Writing buffered (buffer size: 8192)... 2.109 seconds Writing buffered (buffer size: 1048576)... 2.078 seconds Writing buffered (buffer size: 4194304)... 2.015 seconds Iteration 3 Writing raw... 3.187 seconds Writing buffered (buffer size: 8192)... 2.109 seconds Writing buffered (buffer size: 1048576)... 2.094 seconds Writing buffered (buffer size: 4194304)... 2.031 seconds Iteration 4 Writing raw... 3.093 seconds Writing buffered (buffer size: 8192)... 2.141 seconds Writing buffered (buffer size: 1048576)... 2.063 seconds Writing buffered (buffer size: 4194304)... 2.016 seconds As we can see the raw method is slower the buffered.
Your transfer speed is likely not to be limited by Java. Instead I would suspect (in no particular order)
If you read the complete dataset and then write it out to disk, then that will take longer, since the JVM will have to allocate memory, and the db rea/disk write will happen sequentially. Instead I would write out to the buffered writer for every read that you make from the db, and so the operation will be closer to a concurrent one (I don't know if you're doing that or not)
For these bulky reads from DB you may want to tune your Statement's fetch size. It might save a lot of roundtrips to DB.
http://download.oracle.com/javase/1.5.0/docs/api/java/sql/Statement.html#setFetchSize%28int%29
package all.is.well; import java.io.IOException; import java.io.RandomAccessFile; import java.util.concurrent.ExecutorService; import java.util.concurrent.Executors; import junit.framework.TestCase; /** * @author Naresh Bhabat * Following implementation helps to deal with extra large files in java. This program is tested for dealing with 2GB input file. There are some points where extra logic can be added in future. Pleasenote: if we want to deal with binary input file, then instead of reading line,we need to read bytes from read file object. It uses random access file,which is almost like streaming API. * **************************************** Notes regarding executor framework and its readings. Please note :ExecutorService executor = Executors.newFixedThreadPool(10); * for 10 threads:Total time required for reading and writing the text in * :seconds 349.317 * * For 100:Total time required for reading the text and writing : seconds 464.042 * * For 1000 : Total time required for reading and writing text :466.538 * For 10000 Total time required for reading and writing in seconds 479.701 * * */ public class DealWithHugeRecordsinFile extends TestCase { static final String FILEPATH = "C:\\springbatch\\bigfile1.txt.txt"; static final String FILEPATH_WRITE = "C:\\springbatch\\writinghere.txt"; static volatile RandomAccessFile fileToWrite; static volatile RandomAccessFile file; static volatile String fileContentsIter; static volatile int position = 0; public static void main(String[] args) throws IOException, InterruptedException { long currentTimeMillis = System.currentTimeMillis(); try { fileToWrite = new RandomAccessFile(FILEPATH_WRITE, "rw");//for random write,independent of thread obstacles file = new RandomAccessFile(FILEPATH, "r");//for random read,independent of thread obstacles seriouslyReadProcessAndWriteAsynch(); } catch (IOException e) { // TODO Auto-generated catch block e.printStackTrace(); } Thread currentThread = Thread.currentThread(); System.out.println(currentThread.getName()); long currentTimeMillis2 = System.currentTimeMillis(); double time_seconds = (currentTimeMillis2 - currentTimeMillis) / 1000.0; System.out.println("Total time required for reading the text in seconds " + time_seconds); } /** * @throws IOException * Something asynchronously serious */ public static void seriouslyReadProcessAndWriteAsynch() throws IOException { ExecutorService executor = Executors.newFixedThreadPool(10);//pls see for explanation in comments section of the class while (true) { String readLine = file.readLine(); if (readLine == null) { break; } Runnable genuineWorker = new Runnable() { @Override public void run() { // do hard processing here in this thread,i have consumed // some time and eat some exception in write method. writeToFile(FILEPATH_WRITE, readLine); // System.out.println(" :" + // Thread.currentThread().getName()); } }; executor.execute(genuineWorker); } executor.shutdown(); while (!executor.isTerminated()) { } System.out.println("Finished all threads"); file.close(); fileToWrite.close(); } /** * @param filePath * @param data * @param position */ private static void writeToFile(String filePath, String data) { try { // fileToWrite.seek(position); data = "\n" + data; if (!data.contains("Randomization")) { return; } System.out.println("Let us do something time consuming to make this thread busy"+(position++) + " :" + data); System.out.println("Lets consume through this loop"); int i=1000; while(i>0){ i--; } fileToWrite.write(data.getBytes()); throw new Exception(); } catch (Exception exception) { System.out.println("exception was thrown but still we are able to proceeed further" + " \n This can be used for marking failure of the records"); //exception.printStackTrace(); } } }
For those who want to improve the time for retrieval of records and dump into the file (i.e no processing on records), instead of putting them into an ArrayList, append those records into a StringBuffer. Apply toSring() function to get a single String and write it into the file at once.
For me, the retrieval time reduced from 22 seconds to 17 seconds.
StringBuffer would probably be faster. A raw String array (String[]) would also probably be faster.