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72 lines
3.5 KiB
SQL
72 lines
3.5 KiB
SQL
-- The input is table(test text, query text, run UInt32, version UInt8, metrics Array(float)).
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-- Run like this:
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-- clickhouse-local --queries-file eqmed.sql -S 'test text, query text, run UInt32, version UInt8, metrics Array(float)' --file analyze/tmp/modulo_0.tsv
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select
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arrayMap(x -> floor(x, 4), original_medians_array.medians_by_version[1] as l) l_rounded,
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arrayMap(x -> floor(x, 4), original_medians_array.medians_by_version[2] as r) r_rounded,
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arrayMap(x, y -> floor((y - x) / x, 3), l, r) diff_percent,
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arrayMap(x, y -> floor(x / y, 3), threshold, l) threshold_percent,
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test, query
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from
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(
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-- quantiles of randomization distributions
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-- note that for small number of runs, the exact quantile might not make
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-- sense, because the last possible value of randomization distribution
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-- might take a larger percentage of distribution (i.e. the distribution
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-- actually has discrete values, and the last step can be large).
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select quantileExactForEach(0.99)(
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arrayMap(x, y -> abs(x - y), metrics_by_label[1], metrics_by_label[2]) as d
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) threshold
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---- Uncomment to see what the distribution is really like. This debug
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---- code only works for single (the first) metric.
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--, uniqExact(d[1]) u
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--, arraySort(x->x.1,
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-- arrayZip(
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-- (sumMap([d[1]], [1]) as f).1,
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-- f.2)) full_histogram
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from
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(
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-- make array 'random label' -> '[median metric]'
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select virtual_run, groupArrayInsertAt(median_metrics, random_label) metrics_by_label
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from (
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-- get [median metric] arrays among virtual runs, grouping by random label
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select medianExactForEach(metrics) median_metrics, virtual_run, random_label
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from (
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-- randomly relabel measurements
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select *, toUInt32(rowNumberInAllBlocks() % 2) random_label
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from (
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select metrics, number virtual_run
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from
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-- strip the query away before the join -- it might be several kB long;
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(select metrics, run, version from table) no_query,
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-- duplicate input measurements into many virtual runs
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numbers(1, 10000) nn
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-- for each virtual run, randomly reorder measurements
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order by virtual_run, rand()
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) virtual_runs
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) relabeled
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group by virtual_run, random_label
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) virtual_medians
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group by virtual_run -- aggregate by random_label
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) virtual_medians_array
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-- this select aggregates by virtual_run
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) rd,
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(
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select groupArrayInsertAt(median_metrics, version) medians_by_version
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from
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(
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select medianExactForEach(metrics) median_metrics, version
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from table
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group by version
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) original_medians
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) original_medians_array,
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(
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select any(test) test, any(query) query from table
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) any_query,
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(
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select throwIf(uniq((test, query)) != 1) from table
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) check_single_query -- this subselect checks that there is only one query in the input table;
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-- written this way so that it is not optimized away (#10523)
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SETTINGS allow_experimental_analyzer = 0
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;
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