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This repository has been archived by the owner on Apr 3, 2018. It is now read-only.
The ideal implementation will give folks the ability to use ApplyTimestampAndDuration as it is written (it already does some defense to avoid putting bad timestamps in). Those who use this are likely looking for the "duration" query, and are willing to have some inaccuracy in exchange for backfilling timestamp and duration from applications who don't report it (yet).
In its most basic form, all this is is a conditional wrapper of ApplyTimestampAndDuration which is tripped by a property like "zipkin.sparkstreaming.adjuster.apply-timestamp-and-duration.enabled=true"
Since this is of high re-use (per the existing issue tracking it), and requires no dependencies, such an adjuster could be added to the default "sparkstreaming" and "sparkstreaming-job" modules. This means that there would be no new scaffolding required, except autoconfiguration and a wrapper.
Later, other properties could be added, but in all likelihood, we'd not need to.
The text was updated successfully, but these errors were encountered:
The motivation of this change is openzipkin/openzipkin.github.io#49 which tracks many, but not all libraries with regards to their ability to properly implement timestamp and duration as noted in our web site. http://zipkin.io/pages/instrumenting.html
The ideal implementation will give folks the ability to use ApplyTimestampAndDuration as it is written (it already does some defense to avoid putting bad timestamps in). Those who use this are likely looking for the "duration" query, and are willing to have some inaccuracy in exchange for backfilling timestamp and duration from applications who don't report it (yet).
In its most basic form, all this is is a conditional wrapper of ApplyTimestampAndDuration which is tripped by a property like "zipkin.sparkstreaming.adjuster.apply-timestamp-and-duration.enabled=true"
Since this is of high re-use (per the existing issue tracking it), and requires no dependencies, such an adjuster could be added to the default "sparkstreaming" and "sparkstreaming-job" modules. This means that there would be no new scaffolding required, except autoconfiguration and a wrapper.
Later, other properties could be added, but in all likelihood, we'd not need to.
The text was updated successfully, but these errors were encountered: