mirror of https://github.com/mongodb/mongo
53 lines
1.8 KiB
JavaScript
53 lines
1.8 KiB
JavaScript
/**
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* Tests that the continuous median accumulator semantics matches the percentile semantics with the
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* field 'p':[0.5].
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* @tags: [
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* requires_fcv_81,
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* featureFlagAccuratePercentiles
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* ]
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*/
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import {testWithMultipleGroupsMedian, testWithSingleGroupMedian} from "jstests/aggregation/libs/percentiles_util.js";
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const coll = db[jsTestName()];
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/**
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* Tests for correctness without grouping. Confirms that $median computes the expected value and
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* also checks that $percentile for p=0.5 computes the same value, because $median is supposed
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* to be completely equivalent to the latter (e.g. we should not optimize $median independently
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* of $percentile).
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*/
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testWithSingleGroupMedian({
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coll: coll,
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docs: [{x: 0}, {x: 2}],
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medianSpec: {$median: {input: "$x", method: "continuous"}},
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expectedResult: 1,
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msg: "Continuous interpolation should allow result not in original dataset",
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});
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testWithSingleGroupMedian({
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coll: coll,
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docs: [{x: 0}, {x: "non-numeric"}, {x: 1}, {no_x: 0}, {x: 2}],
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medianSpec: {$median: {input: "$x", method: "continuous"}},
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expectedResult: 1,
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msg: "Non-numeric data should be ignored",
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});
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testWithSingleGroupMedian({
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coll: coll,
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docs: [{x: "non-numeric"}, {non_x: 1}],
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medianSpec: {$median: {input: "$x", method: "continuous"}},
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expectedResult: null,
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msg: "Median of completely non-numeric data.",
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});
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/**
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* Tests for correctness with grouping on $k and computing the percentile on $x.
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*/
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testWithMultipleGroupsMedian({
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coll: coll,
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docs: [{k: 0, x: 2}, {k: 0, x: 1}, {k: 1, x: 2}, {k: 2}, {k: 0, x: "str"}, {k: 1, x: 0}],
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medianSpec: {$median: {input: "$x", method: "continuous"}},
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expectedResult: [/* k:0 */ 1.5, /* k:1 */ 1, /* k:2 */ null],
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msg: "Median of multiple groups",
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});
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