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builtins: deflake TestSerialNormalizationWithUniqueUnorderedID #91868

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Nov 22, 2022
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builtins: deflake TestSerialNormalizationWithUniqueUnorderedID #91868

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42 changes: 32 additions & 10 deletions pkg/sql/sem/builtins/builtins_test.go
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Original file line number Diff line number Diff line change
Expand Up @@ -100,8 +100,6 @@ func TestSerialNormalizationWithUniqueUnorderedID(t *testing.T) {
defer leaktest.AfterTest(t)()
ctx := context.Background()

skip.WithIssue(t, 91858) // flaky test

skip.UnderRace(t, "the test is too slow and the goodness of fit test "+
"assumes large N")
params := base.TestServerArgs{}
Expand All @@ -121,24 +119,48 @@ CREATE TABLE t (

numberOfRows := 10000

// Enforce 3 bits worth of range splits in the high order to collect range
// statistics after row insertions.
// Insert rows.
tdb.Exec(t, fmt.Sprintf(`
ALTER TABLE t SPLIT AT SELECT i<<(60) FROM generate_series(1, 7) as t(i);
INSERT INTO t(j) SELECT * FROM generate_series(1, %d);
`, numberOfRows))

// Derive range statistics.
// Build an equi-width histogram over the key range. The below query will
// generate the key bounds for each high-order bit pattern as defined by
// prefixBits. For example, if this were 3, we'd get the following groups:
//
// low | high
// ----------------------+----------------------
// 0 | 2305843009213693952
// 2305843009213693952 | 4611686018427387904
// 4611686018427387904 | 6917529027641081856
// 6917529027641081856 | 9223372036854775807
//
const prefixBits = 4
var keyCounts pq.Int64Array
tdb.QueryRow(t, "SELECT "+
"array_agg((crdb_internal.range_stats(start_key)->>'key_count')::int) AS rows "+
"FROM crdb_internal.ranges_no_leases WHERE table_id"+
"='t'::regclass;").Scan(&keyCounts)
tdb.QueryRow(t, `
WITH boundaries AS (
SELECT i << (64 - $1) AS p FROM ROWS FROM (generate_series(0, (1<<($1-1)) -1)) AS t (i)
UNION ALL SELECT (((1 << 62) - 1) << 1)+1 -- int63 max value
),
groups AS (
SELECT *
FROM (SELECT p AS low, lead(p) OVER () AS high FROM boundaries)
WHERE high IS NOT NULL
),
counts AS (
SELECT count(i) AS c
FROM t, groups
WHERE low <= i AND high > i
GROUP BY (low, high)
)
SELECT array_agg(c)
FROM counts;`, prefixBits).Scan(&keyCounts)

t.Log("Key counts in each split range")
for i, keyCount := range keyCounts {
t.Logf("range %d: %d\n", i, keyCount)
}
require.Len(t, keyCounts, 1<<(prefixBits-1))

// To check that the distribution over ranges is not uniform, we use a
// chi-square goodness of fit statistic. We'll set our null hypothesis as
Expand Down