Amazing work, thank you Sergey!!

++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Chris Mattmann, Ph.D.
Principal Data Scientist, Engineering Administrative Office (3010)
Manager, NSF & Open Source Projects Formulation and Development Offices (8212)
NASA Jet Propulsion Laboratory Pasadena, CA 91109 USA
Office: 180-503E, Mailstop: 180-503
Email: [EMAIL PROTECTED]
WWW:  http://sunset.usc.edu/~mattmann/
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
Director, Information Retrieval and Data Science Group (IRDS)
Adjunct Associate Professor, Computer Science Department
University of Southern California, Los Angeles, CA 90089 USA
WWW: http://irds.usc.edu/
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 

On 9/11/17, 7:33 AM, "Allison, Timothy B." <[EMAIL PROTECTED]> wrote:

    What great news!  Thank you, Sergey!!!
   
    -----Original Message-----
    From: Sergey Beryozkin [mailto:[EMAIL PROTECTED]]
    Sent: Monday, September 11, 2017 9:18 AM
    To: Allison, Timothy B. <[EMAIL PROTECTED]>; [EMAIL PROTECTED]
    Subject: Re: Integrating Tika with Apache Beam
   
    Hi Tim, All
   
    It took it some time, but finally Beam TikaIO component is in its 2.2.0-SNAPSHOT master,
   
    https://github.com/apache/beam/tree/master/sdks/java/io/tika
   
    I've created a basic project which can help with running it quickly:
   
    https://github.com/sberyozkin/beamTikaExample
   
    One can just build it and run as suggested in Readme.md, simply have some PDF files for example, and point to one or all of them.
   
    By default, Beam will output the data to /tmp/tika.
   
    main() can be updated with supporting more options, they can be collected from the command line either with TikaOptions:
   
    https://github.com/apache/beam/blob/master/sdks/java/io/tika/src/main/java/org/apache/beam/sdk/io/tika/TikaOptions.java
   
    (all options but the "--input" are optional)
   
    or directly from the code, some variations are shown in the tests:
   
    https://github.com/apache/beam/blob/master/sdks/java/io/tika/src/test/java/org/apache/beam/sdk/io/tika/TikaIOTest.java
   
    By default TikaReader will use an internal queue to make the SAX events available to the Beam pipeline, this is why you can see the options like "queuePollTime", etc. If it's known that a given parser can really read the whole text in the single op only then the process can be optimized with 'parseSynchronously'...
   
    One can also try to update main() in the example to do more interesting things then just print the data :-).
   
    Give it a try please if you get a chance, help make TikeIO the major part of Beam :-) with PRs, etc
   
    Thanks, Sergey
   
   
   
   
   
    On 25/05/17 17:47, Sergey Beryozkin wrote:
    > Hi Guys
    >
    > The link to the initial code is available in JIRA, at this stage the
    > focus is on preparing a solid initial PR, and then we can all improve
    > Tika related code :-)
    >
    > Cheers, Sergey
    > On 24/05/17 11:41, Sergey Beryozkin wrote:
    >> Hi Tim, All,
    >>
    >> I thought I'd start a dedicated thread.
    >>
    >> I added some initial comments to [1], I'm quite close now to creating
    >> the initial PR.
    >>
    >> Thanks, Sergey
    >>
    >> [1] https://issues.apache.org/jira/browse/BEAM-2328
    >> On 23/05/17 17:42, Allison, Timothy B. wrote:
    >>> Another idea...if you have any interest, it would be great to get
    >>> Apache Beam set up on our Rackspace VM (with Spark?) and use it for
    >>> our regression tests?
    >>>
    >>> -----Original Message-----
    >>> From: Sergey Beryozkin [mailto:[EMAIL PROTECTED]]
    >>> Sent: Friday, May 19, 2017 4:21 PM
    >>> To: [EMAIL PROTECTED]
    >>> Subject: Re: Extracting Text from embedded images in PDF docs
    >>>
    >>> Hi Tim
    >>>
    >>> Sure, once I get an initial PR ready I'll send an update and I'll
    >>> explain what I did for a start and we will discuss it further
    >>>
    >
    >
NEW: Monitor These Apps!
elasticsearch, apache solr, apache hbase, hadoop, redis, casssandra, amazon cloudwatch, mysql, memcached, apache kafka, apache zookeeper, apache storm, ubuntu, centOS, red hat, debian, puppet labs, java, senseiDB