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• While a TermTagger instance is tagging terms, it does not respond to any other requests. Each new request is waiting for the TermTagger until it responds.
  • This led to several TermTagger DOWN messages in the past, now the timeouts are adjusted and a timeouted termtagger is not considered as DOWN anymore.
• One TermTagger instance is using one CPU core when tagging, so the count of the parallel running TermTagger instances should be oriented along to the available CPU cores
• Since for the GUI tagger only the one saved segment is processed by the tagger, it responds fast and the latency is low, so one tagger for the GUI should be enough for most setups
• The word count of the segment is increasing the duration in an exponential way. Tags are not considered as words.
• Depending on how much imports are running and how big the imported tasks are, multiple import taggers can improve the throughput. Recommendation: 2-3 import term taggers.

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Configure translate5 to use 2 termTaggers for imports and one for the GUI by executing the following SQL on your translate5 database

UPDATE `Zf_configuration` SET` value` =translate5.sh config runtimeOptions.termTagger.url.default '["http://localhost:9001", "http://localhost:9002"]' WHERE `Zf_configuration`.`name` = '
translate5.sh config runtimeOptions.termTagger.url.default';
UPDATE `Zf_configuration` SET` value` =import '["http://localhost:9001", "http://localhost:9002"]' WHERE `Zf_configuration`.`name` = '
translate5.sh config runtimeOptions.termTagger.url.import';
UPDATE `Zf_configuration` SET` value` =gui '["http://localhost:9003"]' WHERE `Zf_configuration`.`name` = 'runtimeOptions.termTagger.url.gui';

Restart your termTagger, if you run termTagger as a service. With supervisord this would look like:

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