Locate — where it appears
Named by 16 essays across 6 fields — each of them below, with the objects they name alongside it.
The sampling that goes the other way
An FM-index hands the text back, and the way it does it is to walk from the last character to the first. So thirty-two characters from the end cost thirty-three steps and thirty-two characters from the beginning cost eight thousand one hundred and ninety-two. The repair is a second array the same size as the first, indexed the other way round.
The sampling that follows the runs
A run-length index over thirty-two copies of one text spends 11,286 bits on its suffix-array sampling and 5,605 on the transform it was built to compress. Sample at the run boundaries instead and the sampling is 10,942 bits that stop moving — two values per run, and a function that fills in everything between them.
A function with r pieces
Computed at every one of eight thousand positions across four texts, a function defined on the whole suffix array agrees exactly with r−1 anchors and one addition. Anchor it at the successor instead of the predecessor — one character of code — and it disagrees at 506 of 800 positions while still returning plausible numbers.
The occurrence carried through the search
Backward search returns how many and not where, and every index on this site pays for the second question separately. Carrying one occurrence along with the interval costs a lookup on 75% of the steps for a two-character pattern and on 18% of them for a sixteen-character one, and it is what makes a run-boundary sampling usable at all.
What is still proportional to n
An index whose size is a function of the run count still has an n in it, and at thirty-two copies of a text the n is half of it. Everything that stores the transform grew by 45 per cent; the two arrays that answer "where" grew by eighteen times, and neither of them has anything to do with repetition.
An index with z in its size
Over thirty-two copies of one text, an index built on the parse is 8,892 bits, the r-index is 17,047 and the entropy-bounded index is 34,615. Over eight thousand characters of four-symbol text the same three are 7,844, 25,177 and 20,413, and the smallest of the three has changed places twice.
The occurrences that cross a boundary
One pattern, thirty-two copies of a text, thirty-two occurrences. The search finds one of them and produces the other thirty-one by arithmetic, and the count it finds is the same one at two copies, at eight and at thirty-two — the searching does not grow when the answer does.
The collection decides which index is small
Three compressed self-indexes over one text of five hundred characters measure 3,511, 7,285 and 10,974 bits. Repeat that text thirty-two times and the same three measure 34,615, 8,892 and 17,047 — the ordering has completely reversed, and nothing about any of the structures changed.
Every occurrence at the same price
A regular sampling has one dial and it moves two costs together — 1,495 bits at 63 LF steps an occurrence, 131,088 bits at none. A sampling at the run boundaries sits at 10,244 bits and one predecessor query, which is a point the curve reaches only at 69,649.
The candidates a filter cannot avoid
A phrase index answers a search by intersecting two ranges of boundaries, and it does the intersection by walking the smaller one. On a collection of thirty-two copies that is 4,355 phrase examinations to produce 32 occurrences — 136 examinations each, and rising.
The character that costs a chain
The index over thirty-two copies is 8,892 bits and does not grow. Producing one character of the text it indexes costs 17.89 phrase-follows on average and 38 in the worst case, against 2.38 and 7 at one copy — the size stopped growing and the price of reading it did not.
A list of documents is not a list of occurrences
A pattern occurring 790 times in eight documents has an answer of size eight. Reading every occurrence to find out costs 790 array reads; the question a collection has that a text does not is the one its index does not answer.
The half that is never asked where
A bidirectional index is two indexes and one interval. One of them is asked for ranks several hundred times a search and for a position never — and the parts that answer "where" are two of the five it is made of.
An index that cannot locate
Take an FM-index, remove the sampled positions and the bit vector marking them, and refuse every request for a position. What is left still counts, still extends intervals, still runs a whole search — and is a third smaller.
A sixth of what, exactly
The saving from a counting-only reverse half is 30.5% at one sampled position in four and 14.0% at one in a hundred and twenty-eight. A number quoted without its sampling rate is a number about a setting somebody chose.
The saving, spent
A bidirectional index whose reverse half cannot locate is a sixth smaller. Give that sixth back to the half that does locate, and the same total size answers a locate five times faster.
Named alongside it
The objects these essays reach for when they reach for this one.
Index sizeMeasurementSelf-indexFM-indexSamplingTrade offR-indexSuffix arrayRepetitionRun-lengthSpace overheadLempel ziv parse