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1. Overview

Apache Tika is a toolkit for extracting content and metadata from various types of documents, such as Word, Excel, and PDF or even multimedia files like JPEG and MP4.

All text-based and multimedia files can be parsed using a common interface, making Tika a powerful and versatile library for content analysis.

In this article, we’ll give an introduction to Apache Tika, including its parsing API and how it automatically detects the content type of a document. Working examples will also be provided to illustrate operations of this library.

2. Getting Started

In order to parse documents using Apache Tika, we need only one Maven dependency:

<dependency>
    <groupId>org.apache.tika</groupId>
    <artifactId>tika-parsers</artifactId>
    <version>1.17</version>
</dependency>

The latest version of this artifact can be found here.

3. The Parser API

The Parser API is the heart of Apache Tika, abstracting away the complexity of the parsing operations. This API relies on a single method:

void parse(
  InputStream stream, 
  ContentHandler handler, 
  Metadata metadata, 
  ParseContext context) 
  throws IOException, SAXException, TikaException

The meanings of this method’s parameters are:

  • stream an InputStream instance created from the document to be parsed
  • handler a ContentHandler object receiving a sequence of XHTML SAX events parsed from the input document; this handler will then process events and export the result in a particular form
  • metadata a Metadata object conveying metadata properties in and out of the parser
  • context a ParseContext instance carrying context-specific information, used to customize the parsing process

The parse method throws an IOException if it fails to read from the input stream, a TikaException if the document taken from the stream cannot be parsed and a SAXException if the handler is unable to process an event.

When parsing a document, Tika attempts to reuse existing parser libraries such as Apache POI or PDFBox as much as possible. As a result, most of the Parser implementation classes are just adapters to such external libraries.

In section 5, we’ll see how the handler and metadata parameters can be used to extract content and metadata of a document.

For convenience, we can use the facade class Tika to access the functionality of the Parser API.

4. Auto-Detection

Apache Tika can automatically detect the type of a document and its language based on the document itself rather than on additional information.

4.1. Document Type Detection

The detection of document types can be done using an implementation class of the Detector interface, which has a single method:

MediaType detect(java.io.InputStream input, Metadata metadata) 
  throws IOException

This method takes a document, and its associated metadata – then returns a MediaType object describing the best guess regarding the type of the document.

Metadata isn’t the only source of information on which a detector relies. The detector can also make use of magic bytes, which are a special pattern near the beginning of a file or delegate the detection process to a more suitable detector.

In fact, the algorithm used by the detector is implementation dependent.

For instance, the default detector works with magic bytes first, then metadata properties. If the content type hasn’t been found at this point, it will use the service loader to discover all available detectors and try them in turn.

4.2. Language Detection

In addition to the type of a document, Tika can also identify its language even without help from metadata information.

In previous releases of Tika, the language of the document is detected using a LanguageIdentifier instance.

However, LanguageIdentifier has been deprecated in favor of web services, which is not made clear in the Getting Started docs.

Language detection services are now provided via subtypes of the abstract class LanguageDetector. Using web services, you can also access fully-fledged online translation services, such as Google Translate or Microsoft Translator.

For the sake of brevity, we won’t go over those services in detail.

5. Tika in Action

This section illustrates Apache Tika features using working examples.

The illustration methods will be wrapped in a class:

public class TikaAnalysis {
    // illustration methods
}

5.1. Detecting Document Types

Here’s the code we can use to detect the type of a document read from an InputStream:

public static String detectDocTypeUsingDetector(InputStream stream) 
  throws IOException {
    Detector detector = new DefaultDetector();
    Metadata metadata = new Metadata();

    MediaType mediaType = detector.detect(stream, metadata);
    return mediaType.toString();
}

Assume we have a PDF file named tika.txt in the classpath. The extension of this file has been changed to try to trick our analysis tool. The real type of the document can still be found and confirmed by a test:

@Test
public void whenUsingDetector_thenDocumentTypeIsReturned() 
  throws IOException {
    InputStream stream = this.getClass().getClassLoader()
      .getResourceAsStream("tika.txt");
    String mediaType = TikaAnalysis.detectDocTypeUsingDetector(stream);

    assertEquals("application/pdf", mediaType);

    stream.close();
}

It’s clear that a wrong file extension can’t keep Tika from finding the correct media type, thanks to the magic bytes %PDF at the start of the file.

For convenience, we can re-write the detection code using the Tika facade class with the same result:

public static String detectDocTypeUsingFacade(InputStream stream) 
  throws IOException {
 
    Tika tika = new Tika();
    String mediaType = tika.detect(stream);
    return mediaType;
}

5.2. Extracting Content

Let’s now extract the content of a file and return the result as a String – using the Parser API:

public static String extractContentUsingParser(InputStream stream) 
  throws IOException, TikaException, SAXException {
 
    Parser parser = new AutoDetectParser();
    ContentHandler handler = new BodyContentHandler();
    Metadata metadata = new Metadata();
    ParseContext context = new ParseContext();

    parser.parse(stream, handler, metadata, context);
    return handler.toString();
}

Given a Microsoft Word file in the classpath with this content:

Apache Tika - a content analysis toolkit
The Apache Tika™ toolkit detects and extracts metadata and text ...

The content can be extracted and verified:

@Test
public void whenUsingParser_thenContentIsReturned() 
  throws IOException, TikaException, SAXException {
    InputStream stream = this.getClass().getClassLoader()
      .getResourceAsStream("tika.docx");
    String content = TikaAnalysis.extractContentUsingParser(stream);

    assertThat(content, 
      containsString("Apache Tika - a content analysis toolkit"));
    assertThat(content, 
      containsString("detects and extracts metadata and text"));

    stream.close();
}

Again, the Tika class can be used to write the code more conveniently:

public static String extractContentUsingFacade(InputStream stream) 
  throws IOException, TikaException {
 
    Tika tika = new Tika();
    String content = tika.parseToString(stream);
    return content;
}

5.3. Extracting Metadata

In addition to the content of a document, the Parser API can also extract metadata:

public static Metadata extractMetadatatUsingParser(InputStream stream) 
  throws IOException, SAXException, TikaException {
 
    Parser parser = new AutoDetectParser();
    ContentHandler handler = new BodyContentHandler();
    Metadata metadata = new Metadata();
    ParseContext context = new ParseContext();

    parser.parse(stream, handler, metadata, context);
    return metadata;
}

When a Microsoft Excel file exists in the classpath, this test case confirms that the extracted metadata is correct:

@Test
public void whenUsingParser_thenMetadataIsReturned() 
  throws IOException, TikaException, SAXException {
    InputStream stream = this.getClass().getClassLoader()
      .getResourceAsStream("tika.xlsx");
    Metadata metadata = TikaAnalysis.extractMetadatatUsingParser(stream);

    assertEquals("org.apache.tika.parser.DefaultParser", 
      metadata.get("X-Parsed-By"));
    assertEquals("Microsoft Office User", metadata.get("Author"));

    stream.close();
}

Finally, here’s another version of the extraction method using the Tika facade class:

public static Metadata extractMetadatatUsingFacade(InputStream stream) 
  throws IOException, TikaException {
    Tika tika = new Tika();
    Metadata metadata = new Metadata();

    tika.parse(stream, metadata);
    return metadata;
}

6. Conclusion

This tutorial focused on content analysis with Apache Tika. Using the Parser and Detector APIs, we can automatically detect the type of a document, as well as extract its content and metadata.

For advanced use cases, we can create custom Parser and Detector classes to have more control over the parsing process.

The complete source code for this tutorial can be found over on GitHub.

I just announced the new Spring Boot 2 material, coming in REST With Spring:

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