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commit f8df8d9fc433bdc172b04363e5ab2897edfc0944 Author: Andrew Lim <[email protected]> AuthorDate: Mon Jan 27 20:07:21 2020 -0500 NIFI-7066 Update nifi.analytics.query.interval documented default value in Admin Guide to match nifi.properties value (#4022) --- nifi-docs/src/main/asciidoc/administration-guide.adoc | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/nifi-docs/src/main/asciidoc/administration-guide.adoc b/nifi-docs/src/main/asciidoc/administration-guide.adoc index e1338e9..54f0d1c 100644 --- a/nifi-docs/src/main/asciidoc/administration-guide.adoc +++ b/nifi-docs/src/main/asciidoc/administration-guide.adoc @@ -2405,9 +2405,9 @@ NiFi has an internal analytics framework which can be enabled to predict back pr image:back_pressure_prediction_model_example.png["Back pressure prediction based on Queue/Object Count"] -In order to generate predictions, local status snapshot history is queried to obtain enough data to generate a model. By default component status snapshots are captured every minute. Internal models need at least 2 or more observations to generate a prediction, therefore it may take up to 2 or more minutes for predictions to be available by default. If predictions are needed sooner than what is provided by default, the timing of snapshots can be adjusted using the `nifi.components.stat [...] +In order to generate predictions, local status snapshot history is queried to obtain enough data to generate a model. By default, component status snapshots are captured every minute. Internal models need at least 2 or more observations to generate a prediction, therefore it may take up to 2 or more minutes for predictions to be available by default. If predictions are needed sooner than what is provided by default, the timing of snapshots can be adjusted using the `nifi.components.sta [...] -NiFi evaluates the model's effectiveness before sending prediction information by using the model's R-Squared score by default. One important note: R-Square is a measure of how close the regression line fits the observation data vs. how accurate the prediction will be; therefore there may be some measure of error. If the R-Squared score for the calculated model meets the configured threshold (as defined by `nifi.analytics.connection.model.score.threshold`) then the model will be used for [...] +NiFi evaluates the model's effectiveness before sending prediction information by using the model's R-Squared score by default. One important note: R-Square is a measure of how close the regression line fits the observation data vs. how accurate the prediction will be; therefore there may be some measure of error. If the R-Squared score for the calculated model meets the configured threshold (as defined by `nifi.analytics.connection.model.score.threshold`) then the model will be used for [...] The prediction interval `nifi.analytics.predict.interval` can be configured to project out further when back pressure will occur. The prediction query interval `nifi.analytics.query.interval` can also be configured to determine how far back in time past observations should be queried in order to generate the model. Adjustments to these settings may require tuning of the model's scoring threshold value to select a score that can offer reasonable predictions. @@ -3399,11 +3399,11 @@ These properties determine the behavior of the internal NiFi predictive analytic |==== |*Property*|*Description* |`nifi.analytics.predict.enabled`|This indicates whether prediction should be enabled for the cluster. The default is `false`. -|`nifi.analytics.predict.interval`|This indicates a time interval for which analytical predictions (queue saturation, e.g.) should be made. The default value is `3 mins`. -|`nifi.analytics.query.interval`|This indicates a time interval to query for past observations (e.g. the last 3 minutes of snapshots). The default value is `3 mins`. NOTE: This value should be at least 3 times greater than `nifi.components.status.snapshot.frequency` to ensure enough observations are retrieved for predictions. -|`nifi.analytics.connection.model.implementation`|This is the implementation class for the status analytics model used to make connection predictions. The default value is `org.apache.nifi.controller.status.analytics.models.OrdinaryLeastSquares`. -|`nifi.analytics.connection.model.score.name`|This is the name of the scoring type that should be used to evaluate model. The default value is `rSquared`. -|`nifi.analytics.connection.model.score.threshold`|This is the threshold for the scoring value (where model score should be above given threshold). The default value is `.9`. +|`nifi.analytics.predict.interval`|The time interval for which analytical predictions (e.g. queue saturation) should be made. The default value is `3 mins`. +|`nifi.analytics.query.interval`|The time interval to query for past observations (e.g. the last 3 minutes of snapshots). The default value is `5 mins`. NOTE: This value should be at least 3 times greater than `nifi.components.status.snapshot.frequency` to ensure enough observations are retrieved for predictions. +|`nifi.analytics.connection.model.implementation`|The implementation class for the status analytics model used to make connection predictions. The default value is `org.apache.nifi.controller.status.analytics.models.OrdinaryLeastSquares`. +|`nifi.analytics.connection.model.score.name`|The name of the scoring type that should be used to evaluate the model. The default value is `rSquared`. +|`nifi.analytics.connection.model.score.threshold`|The threshold for the scoring value (where model score should be above given threshold). The default value is `.90`. |====
