Concept

Variance — where it appears

How widely a randomised estimator's answers spread around their mean, which is what extra state buys and what a weak hash family fails to bound. It is what extra state buys and what a weak hash family fails to bound, so a structure's accuracy claim rests on the family as much as on the size.

Named by 10 essays across 5 fields — each of them below, with the objects they name alongside it.

0.1bits the register neededrelative errora = 2a = 1.5a = 1.2a = 1.1a = 1.05a = 1.02√((a−1)/2), predicted200 runs per base · n = 20,000 · exact counter needs 15 bits72.6% at 5 bits

Counting past what the register holds

Morris's counter counts ten million events in five bits by incrementing with probability 2 to the minus c. The estimate is exactly unbiased at every n, its relative error is 71%, and the base is a dial that trades one against the other at a rate of the square root of half of a minus one.

streaming · Sketch
01325leading-zero rank keptregister, 0 to 255estimate 7,107truth 7,368error -3.54%0 still empty256 registers × 5 bits = 1,280 bitspredicted ±6.50%

A count read off the leading zeros

Hash every key and watch for the longest run of leading zeros. Seeing k of them is evidence of about two to the k distinct keys — an estimator with a variance so large it is worthless, and the two devices that fix it are the whole of what a cardinality sketch is.

streaming · Cardinality
randomised pivot164 random bits2.96 ±23%median of mediansno random bits7.94 ±2%0.04.38.6comparisons per element — bar is the range over seeds, tick is the mean30 seeds, n = 4,001, median2.68× the mean, 14× the spread

What derandomising costs

Randomised selection finds the median of twenty thousand elements in 3.21 comparisons per element and median-of-medians takes 8.15 — two and a half times as many for the same answer, both linear. The number that decides between them is not either of those. It is that the first varies by 28% from seed to seed and the second by 1.6%.

bounds · Distribution
+1−1keys, most frequent firstΣ s(x)·f(x) = 9,034squared: 81,613,156true F2: 36,931,352121.0% outa polynomial of degree 4 · cash-register model · counts exactone register, 32 bits

The estimate that squares the stream

The length of a stream is a counter and the number of distinct keys is a register bank. The sum of the squared frequencies has nothing obvious to count — and one number, one sign per key, and a squaring get within 4% of it in a fortieth of the space.

streaming · Moment
04812162024283236404448slots from homepale: linear probing · dark: Robin Hoodmean 2.384identical for bothworst 48 → 12var 37 → 7435 keys, 512 slots, seed 20260811displacements, counted exactly

The probe nobody waits for

Robin Hood hashing makes an inserting key steal a slot from a key that has probed less far. The mean number of probes afterwards is 4.817, and before it was 4.817 — identical, and it cannot be otherwise, because the total displacement is fixed by the hash. What changes is the worst case, from 114 slots from home to 19, and a table reported by its average lookup cost shows no difference at all.

structures · Structure
column height = keys in that bucket · line = threshold of 8a well-spread hashlongest 44 → 4worst lookupthe low bits onlylongest 3131 → 5worst lookupevery key collideslongest 192192 → 8worst lookup192 keys, 256 buckets, seed 20260811threshold 8, 64 buckets shown

A bucket that becomes a tree

Java's HashMap converts a chained bucket into a red-black tree once it holds eight entries. The comment in the source computes the probability of that happening under a decent hash at about six in a hundred million, so the mechanism is written never to run. Under a hash that fails, the worst lookup falls from 192 comparisons to 8 — and the whole value of the tree is in a case its author does not control.

structures · Structure
10,0000.1total bits of stateruns outside ±15%1 × 483 × 485 × 487 × 489 × 48240 runs per design · tolerance ±15% · truth 12,00067 → 3 failures

The estimate that is a median of means

An estimator with a 70% spread is not usable and an estimator with a stated failure probability is. The construction that turns the first into the second is two lines long, it is where every delta in this field comes from, and its exponential is measured here by counting failures rather than by evaluating a bound.

randomness · Sketch
1 coefficient13 members2 coefficients169 members3 coefficients2,197 members4 coefficients28,561 members1 key2 keys3 keys4 keys5 keysexact92% gone99% gone100% gone100% goneexactexact92% gone99% gone100% goneexactexactexact92% gone99% goneexactexactexactexact92% goneevery member walked · GF(13) · no tolerance and no seeddegree 1, 2, 3, 4

The independence an estimator spends

Every sketch's analysis begins by assuming a truly random hash, and nobody comes back to that line. Independence has a degree, the degree is enumerable over a small field, and an estimator's mean and its variance spend different amounts of it.

randomness · Moment
0.0000.0100.0200.030150200comparisonsprobability per comparison countmean 139.86exact400 runsn = 32, pivot chosen uniformlysampled mean 140.19

A distribution computed rather than sampled

Quicksort with a random pivot makes a random number of comparisons, and every plate on this site reports one draw from that distribution. The distribution itself can be computed exactly — every pivot, every split, weighed — and on sixty-four elements its mean is 360.706 and its standard deviation 36.741. A hundred real runs average 365.98; two thousand average 360.74. The exact answer says how many runs a sample needs, and it is fewer as the input grows.

counting · Count
00.2500.5000.7501010203040age of an arrival, secondsweight it carries nowexponential, half-life 4.0 sbackward polynomial, α = 2, scale 4.0 sforward, β = 2, landmark 20 s backforward, β = 2, landmark 160 s backdotted: half weightweights at the moment of reading

A decay measured from where it started

An exponentially decayed counter is one number because its weights fade by elapsed time alone. Forward decay keeps a polynomial weight in one number too, by measuring each arrival from a fixed landmark. Its memory is then a share of the time since that landmark: at β = 2 an arrival counts half at 29% of that time. Anchored at the start of a stream, it takes 5.3 seconds to register a fourfold rise twenty seconds in and 83 seconds when the rise comes at five minutes.

streaming · Decay

Named alongside it

The objects these essays reach for when they reach for this one.

EstimatorRelative errorState bitsDistributionRandomised algorithmSketchUnbiased estimatorStreaming algorithmWorst caseGuaranteeHash familyHash function

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