It is optimized to provide much better performance than be achieved using MusicBrainz or Discogs directly. This combines data between the two datasets, includes all metadata that could be used for tagging. July 2014 We create the first combined MusicBrainz/Discogs database server called Albunack. May 2012 SongKong adds a database based Undo facility that allows metadata changes to be reverted even after a reboot, this feature is unique to SongKong. SongKong is the first application to use Acoustid for acoustic fingerprinting. Nov 2011 SongKong released, the only totally automated tag editor with no options for manual editing. Nov 2008 Jaikoz adds tools for submitting collection to MusicBrainz and seeding MusicBrainz releases.įeb 2010 Jaikoz takes spreadsheet support further by allowing metadata to be exported to a spreadsheet, edited and then imported back into Jaikoz and hence the files. Sep 2008 Jaikoz is the first tagger to add support for Discogs matching when they opened up their metadata without restrictions. Jaudiotagger has been very popular and as well as being popular on Pc, Macs and Linux is now the No 1 tagging library for Android devices. June 2007 JThink open source our tagging library for reading and writing metadata to files for different audioformats called jaudiotagger. From the start we always stored the MusicBrainz Ids as well as the song metadata to allow users libraries to be fully MusicBrainz enabled. June 2005 Jaikoz approach MusicBrainz to become the first commercial tagger to use MusicBrainz for tag matching and help setup the Tagger affiliate program. Jan 200 5 Jaikoz is released with full spreadsheet interface, this meant instead of having to edit tracks one by one changes could be made rapidly. So at the risk of being self-indulgent here is a chronological list of some of these. I have always tried to have original ideas rather than take other people ideas and I realized that actually there are quite a few features of Jaikoz and SongKong where I got their first. It got me thinking where has the time gone, and what have we achieved ? The solution (for now) is to modify my script so that it gets an older version of the AWS-CLI tool that is still compatible with Python 2.7, the problem was my script was just getting the current version and when Amazon changed it to require 3.6 that broke my script.Jaikoz was originally released back in 2005, over ten years ago. I tried using a newer Linux virtual machine but that had newer version of Tomcat and Java that was not compatible with the code base. I didn’t understand the error message at first because I don’t have the script with the name shown, but the name shown was a virtual taskname within another script. But the linux virtual machine that jthinksearch uses only supports Python 2.7 so the script failed and deployment stopped. But yesterday AWS updated the AWS-CLI tool so that it requires Python 3.6, before that Python 2.7 was only required. Then because it failed AWS tried to redeploy the application, as part of this redeployment I have written a number of scripts (ebextensions) and one of these uses and installs the AWS-CLI tool which is required to run another script. Apologies for that, in fact I was rebuild the indexes from the latest MusicBrainz/Discogs data ready for deployment when the problem occurred. The application is periodically redeployed with a new MusicBrainz/Discogs index, this is meant to occur every month but actually it is 5 months since the last redeployment which is why we haven’t had this memory leak issue before. This application failed yesterday, my suspicion being that there was a small memory leak that over time had more effect until the application ran out of memory. Jthinksearch as used by SongKong, Jaikoz and Albunack runs on Amazon Web Services (AWS) using ElasticBeanstalk, the application is installed on an Amazon Linux virtual machine that runs Java and Apache Tomcat.
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