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This updates log rate analysis to be able to auto-detect whether the selected deviation is a spike or dip compared to the baseline time range. To achieve this, we compare the median bucket size of the two selections. If a dip gets detected, the analysis will then switch the window parameters sent to the API endpoint to run the analysis. An info callout points out the auto-selected analysis type and explains to which time range the analysis results refer to. We need to do this to make it clear that for dip analysis the significant terms and their doc counts refer to the baseline time range and vice versa for spike analysis.
15 lines
606 B
TypeScript
15 lines
606 B
TypeScript
/*
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* Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
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* or more contributor license agreements. Licensed under the Elastic License
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* 2.0; you may not use this file except in compliance with the Elastic License
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* 2.0.
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*/
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export { getLogRateAnalysisType } from './get_log_rate_analysis_type';
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export { LOG_RATE_ANALYSIS_TYPE, type LogRateAnalysisType } from './log_rate_analysis_type';
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export { type LogRateHistogramItem } from './log_rate_histogram_item';
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export {
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getSnappedWindowParameters,
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getWindowParameters,
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type WindowParameters,
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} from './window_parameters';
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