Apache Tika

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Revision as of 15:13, 19 October 2021 by Tallison (talk | contribs) (Added info on 2.x and tika-eval)
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Java based tool for identifying file formats using signatures and extracting metadata and text content from documents.
Homepage:http://tika.apache.org/
License:Apache License, Version 2.0
Platforms:Java
Function:Metadata Extraction,File Format Identification


Release Feed

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Issues Feed

2022-07-02 08:14:24
Márton Balassi closed Lim Qing Wei created ASF GitHub Bot updated a link from ASF GitHub Bot updated a link from ASF GitHub Bot updated a link from Description

Java based tool for identifying file formats using signatures and extracting metadata and text content from documents.

Functional notes

Apache Tika  is able to detect many different file formats. The following list names only the file formats which are supported by the parsers in the current Apache Tika version 1.9 and from which Tika is able to extract metadata and/or textual content:

  • HTML,
  • XML and derived formats,
  • MS Office document formats,
  • ODF,
  • iWorks document formats,
  • PDF,
  • EPUB,
  • RTF,
  • compression and packaging formats,
  • text formats,
  • feed and syndication formats,
  • CHM,
  • audio formats,
  • image formats,
  • video formats,
  • Java class files and archives,
  • source code,
  • mail formats,
  • DWG CAD format,
  • font formats,
  • scientific formats,
  • executable programs and libraries,
  • crypto formats.

For detailed information see Apache Tika 2.1.0 .

Apache Tika also processes embedded files and returns text and metadata from embedded files. The best way to see information on embedded files is to run tika-app with the -J option (e.g. java -jar tika-app-2.1.0.jar -J -t myfile.pdf), or if you're running tika-server, use the /rmeta endpoint.

tika-eval

In addition to extracting text and metadata from files, Tika also offers a tika-eval module that can be used for profiling content or comparing the results of two different text extractors. This module can be used to identify PDFs, for example, that may require Optical Character Recognition for reasonably reliable text.

See tika-eval wiki

User Experiences

Development Activity

The Tika team released the 2.x over 2021. Please see Migrating to Tika 2.0.0 for notes on upgrading to the 2.x branch.