Examples: query, "exact match", wildcard*, wild?ard, wild*rd
Fuzzy search: cake~ (finds cakes, bake)
Term boost: "red velvet"^4, chocolate^2
Field grouping: tags:(+work -"fun-stuff")
Escaping: Escape characters +-&|!(){}[]^"~*?:\ with \, e.g. \+
Range search: properties.timestamp:[1587729413488 TO *] (inclusive), properties.title:{A TO Z}(excluding A and Z)
Combinations: chocolate AND vanilla, chocolate OR vanilla, (chocolate OR vanilla) NOT "vanilla pudding"
Field search: properties.title:"The Title" AND text
Unanswered
How Come


We try to break up every thing into independent tasks and group them using a pipeline. The dependency on an agnet caused an unnecessary overhead since we just want to execute locally. It became a burden once new data scientists join the project and instead of just telling them "yeah, just execute this script" you have to now teach them about clearml, the role of agents, how to launch them, how they behave, how to remove them and stuff like that... things you want to avoid with data scientists

  
  
Posted 2 years ago
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2 years ago
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