1. IntroductionWhen working with large files in Java, developers may encounter memory restrictions while reading from an input stream. In particular, the challenge of converting an InputStream to a DataHandler while maintaining memory efficiency is a common problem.In this tutorial, we’ll cover how to convert an InputStream to a DataHandler. First, we’ll understand why memory inefficiency occurs when extracting the content from large files using InputStream. Next, we’ll cover the getBinaryStream function and its limitations. After that, we’ll elaborate on the working of a DataHandler. Lastly, we’ll implement the DataSource and its implementation.2. Understanding the InputStream ProblemWhen working with files, a common technique is to extract the entire file content as a byte array using the getBytes() method on a ResultSet object when retrieving the data from the databases. Moreover, this byte array gets converted into a DataHandler using the constructor that accepts a byte array and a MIME type specification.Let’s look at the sample code:byte[] bytes = resultSet.getBytes(1); DataHandler dh = new DataHandler(bytes, "application/octet-stream");While this approach works for small files, it becomes problematic when dealing with larger files. To elaborate, the entire file content must reside in memory simultaneously. As a result, applications may experience OutOfMemoryError exceptions or severe performance degradation as heap space becomes exhausted.3. Using getBinaryStreamThe first solution to overcome the problem we described uses getBinaryStream to retrieve data as an InputStream. Through this approach, we have access to the content without loading everything into memory at once. However, the DataHandler class doesn’t provide a direct constructor that accepts an InputStream. This creates a barrier to implementation.Furthermore, attempts to create an empty DataHandler that provides access to an OutputStream prove unsuccessful because the DataHandler method getOutputStream typically returns null unless the underlying data source explicitly supports output operations.4. Working of a DataHandlerThe Java Activation Framework doesn’t provide a constructor that accepts an InputStream directly when creating a DataHandler. That’s where DataSource comes in. DataHandler works with DataSource objects and serves as an abstraction layer that encapsulates data and provides methods for accessing both input and output streams.It is important to note that since Java 11, the Java Activation Framework, javax.activation is no longer included in the JDK. Therefore, we must explicitly add the required dependency to our project.4.1. Implementing the DataSourceFor this example, we create a custom class that implements the DataSource interface. This class provides four essential methods:getInputStream()getOutputStream()getContentType()getName()Let’s look at the code of InputStreamDataSource.java:public class InputStreamDataSource implements DataSource { private InputStream inputStream; public InputStreamDataSource(InputStream inputStream) { this.inputStream = inputStream; } @Override public InputStream getInputStream() throws IOException { return inputStream; } @Override public OutputStream getOutputStream() throws IOException { throw new UnsupportedOperationException("Not implemented"); } @Override public String getContentType() { return "*/*"; } @Override public String getName() { return "InputStreamDataSource"; }}In this case, we only implemented getInputStream to demonstrate the function. The getOutputStream method throws an UnsupportedOperationException because the use case we present only requires reading data, not writing it.4.2. DataSource UsageNow we use the reusable InputStreamDataSource to create a DataHandler. The following example simulates retrieving data from a database. We simulate retrieving data from a database and creating a DataHandler in DataSourceDemo.java:public class DataSourceDemo { public static void main(String[] args) { try { String sampleData = "Hello from the database! This could be a large file."; InputStream inputStream = new ByteArrayInputStream(sampleData.getBytes()); System.out.println("Step 1: Retrieved InputStream from database"); System.out.println("Data size: " + sampleData.length() + " bytes\n"); DataHandler dataHandler = new DataHandler( new InputStreamDataSource(inputStream) ); System.out.println("Step 2: Created DataHandler successfully!"); System.out.println("Content type: " + dataHandler.getContentType()); System.out.println("Data source name: " + dataHandler.getName() + "\n"); InputStream resultStream = dataHandler.getInputStream(); String retrievedData = new String(resultStream.readAllBytes()); System.out.println("Step 3: Retrieved data from DataHandler:"); System.out.println("\"" + retrievedData + "\""); System.out.println("\n✓ Success! Data streamed without loading entirely into memory first."); } catch (Exception e) { System.err.println("Error: " + e.getMessage()); e.printStackTrace(); } }}In the above example, we wrap the InputStream in our InputStreamDataSource and then create a DataHandler. Although readAllBytes() simplifies the example, it loads the entire content into memory. This defeats the purpose of streaming for large files. In real-world applications, we process the InputStream incrementally using buffered reads to preserve memory efficiency.Next, we compile the file:javac DataSourceDemo.javajava DataSourceDemoThe output now displays the streamed data:Step 1: Retrieved InputStream from databaseData size: 52 bytesStep 2: Created DataHandler successfully!Content type: */*Data source name: InputStreamDataSourceStep 3: Retrieved data from DataHandler:"Hello from the database! This could be a large file."✓ Success! Data streamed without loading entirely into memory first.Critically, we replace the simulation code with the real database code in the actual environment.The key advantage of this approach is that the data remains in the database and streams through the application as needed. The memory footprint stays constant regardless of file size, which enables the application to handle files that would previously cause memory exhaustion.4.3. Using Content TypeWhile the basic implementation works well for read-only scenarios, some situations may require additional functionality. For instance, if the content type needs to be specified dynamically rather than using a wildcard, the InputStreamDataSource constructor can be enhanced to accept a MIME type parameter:public class EnhancedDataSourceDemo { public static void main(String[] args) { try { ... InputStream pdfStream = new ByteArrayInputStream("PDF content here".getBytes()); DataHandler pdfHandler = new DataHandler( new InputStreamDataSource(pdfStream, "application/pdf") ); System.out.println("Content type: " + pdfHandler.getContentType()); System.out.println(); }... }}Through this modification, we enable precise content type specification modification. This is useful specifically where the MIME type affects behavior, such as email attachments or HTTP responses.5. ConclusionIn this article, we covered how to convert an InputStream to a DataHandler. First, we explained the memory efficiency problem in Java. After that, we covered the inefficiency of using getBytes alone. Lastly, we discussed converting an InputStream to a DataHandler using the DataSource abstraction.The source code is available over on GitHub.The post Convert an InputStream to a DataHandler in Java first appeared on Baeldung.