java-read-lines-large-file
How to Read a Large File Efficiently with Java
1. Overview
This article is part of the “Java – Back to Basic” tutorial here on Baeldung.
Further reading:
Java – Write an InputStream to a File
How to write an InputStream to a File – using Java, Guava and the Commons IO library.
Java – Convert File to InputStream
How to open an InputStream from a Java File – using plain Java, Guava and the Apache Commons IO library.
Java – Read from File
Read contents from a file in Java – using any of these: BufferedReader, Scanner, StreamTokenizer, DataInputStream, SequenceInputStream, FileChannel, etc.
2. Reading In Memory
The standard way of reading the lines of the file is in memory – both Guava and Apache Commons IO provide a quick way to do just that:
Files.readLines(new File(path), Charsets.UTF_8);FileUtils.readLines(new File(path));The problem with this approach is that all the file lines are kept in memory – which will quickly lead to OutOfMemoryError if the File is large enough.
For example – reading a ~1Gb file:
@Test
public void givenUsingGuava_whenIteratingAFile_thenWorks() throws IOException {
String path = ...
Files.readLines(new File(path), Charsets.UTF_8);
}This starts off with a small amount of memory being consumed: (~0 Mb consumed)
[main] INFO org.baeldung.java.CoreJavaIoUnitTest - Total Memory: 128 Mb
[main] INFO org.baeldung.java.CoreJavaIoUnitTest - Free Memory: 116 MbHowever, after the full file has been processed, we have at the end: (~2 Gb consumed)
[main] INFO org.baeldung.java.CoreJavaIoUnitTest - Total Memory: 2666 Mb
[main] INFO org.baeldung.java.CoreJavaIoUnitTest - Free Memory: 490 MbWhich means that about 2.1 Gb of memory are consumed by the process – the reason is simple – the lines of the file are all being stored in memory now.
It should be obvious by this point that keeping in memory the contents of the file will quickly exhaust the available memory – regardless of how much that actually is.
What’s more, we usually don’t need all of the lines in the file in memory at once – instead, we just need to be able to iterate through each one, do some processing and throw it away. So, this is exactly what we’re going to do – iterate through the lines without holding the in memory.
3. Streaming Through the File
Let’s now look at a solution – we’re going to use a java.util.Scanner to run through the contents of the file and retrieve lines serially, one by one:
FileInputStream inputStream = null;
Scanner sc = null;
try {
inputStream = new FileInputStream(path);
sc = new Scanner(inputStream, "UTF-8");
while (sc.hasNextLine()) {
String line = sc.nextLine();
// System.out.println(line);
}
// note that Scanner suppresses exceptions
if (sc.ioException() != null) {
throw sc.ioException();
}
} finally {
if (inputStream != null) {
inputStream.close();
}
if (sc != null) {
sc.close();
}
}This solution will iterate through all the lines in the file – allowing for processing of each line – without keeping references to them – and in conclusion, without keeping them in memory: (~150 Mb consumed)
[main] INFO org.baeldung.java.CoreJavaIoUnitTest - Total Memory: 763 Mb
[main] INFO org.baeldung.java.CoreJavaIoUnitTest - Free Memory: 605 Mb4. Streaming with Apache Commons IO
The same can be achieved using the Commons IO library as well, by using the custom LineIterator provided by the library:
LineIterator it = FileUtils.lineIterator(theFile, "UTF-8");
try {
while (it.hasNext()) {
String line = it.nextLine();
// do something with line
}
} finally {
LineIterator.closeQuietly(it);
}Since the entire file is not fully in memory – this will also result in pretty conservative memory consumption numbers: (~150 Mb consumed)
[main] INFO o.b.java.CoreJavaIoIntegrationTest - Total Memory: 752 Mb
[main] INFO o.b.java.CoreJavaIoIntegrationTest - Free Memory: 564 Mb5. Conclusion
This quick article shows how to process lines in a large file without iteratively, without exhausting the available memory – which proves quite useful when working with these large files.
The implementation of all these examples and code snippets can be found in our GitHub project – this is a Maven-based project, so it should be easy to import and run as it is.
