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Describe the way we want to group the facet strings
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milli/src/search/facet/facet_string.rs
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123
milli/src/search/facet/facet_string.rs
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//! This module contains helpers iterators for facet strings.
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//!
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//! The purpose is to help iterate over the quite complex system of facets strings. A simple
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//! description of the system would be that every facet string value is stored into an LMDB database
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//! and that every value is associated with the document ids which are associated with this facet
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//! string value.
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//!
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//! In reality it is a little bit more complex as we have to create aggregations of runs of facet
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//! string values, those aggregations helps in choosing the right groups of facets to follow.
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//!
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//! ## A typical algorithm run
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//!
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//! If a group of aggregated facets values contains one of the documents ids, we must continue
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//! iterating over the sub-groups.
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//!
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//! If this group is the lowest level and contain at least one document id we yield the associated
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//! facet documents ids.
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//!
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//! If the group doesn't contain one of our documents ids, we continue to the next group at this
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//! same level.
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//!
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//! ## The complexity comes from the strings
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//!
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//! This algorithm is exactly the one that we use for facet numbers. It is quite easy to create
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//! aggregated facet number, groups of facets are easy to define in the LMDB key, we just put the
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//! two numbers bounds, the left and the right bound of the group, both inclusive.
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//!
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//! It is easy to make sure that the groups are ordered, LMDB sort its keys lexicographically and
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//! puting two numbers big-endian encoded one after the other gives us ordered groups. The values
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//! are simple unions of the documents ids coming from the groups below.
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//!
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//! ### Example of what a facet number LMDB database contain
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//!
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//! | level | left-bound | right-bound | docs |
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//! |-------|------------|-------------|------------------|
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//! | 0 | 0 | _skipped_ | 1, 2 |
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//! | 0 | 1 | _skipped_ | 6, 7 |
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//! | 0 | 3 | _skipped_ | 4, 7 |
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//! | 0 | 5 | _skipped_ | 2, 3, 4 |
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//! | 1 | 0 | 1 | 1, 2, 6, 7 |
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//! | 1 | 3 | 5 | 2, 3, 4, 7 |
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//! | 2 | 0 | 5 | 1, 2, 3, 4, 6, 7 |
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//!
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//! As you can see the level 0 have two equal bounds, therefore we skip serializing the second
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//! bound, that's the base level where you can directly fetch the documents ids associated with an
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//! exact number.
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//!
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//! The next levels have two different bounds and the associated documents ids are simply the result
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//! of an union of all the documents ids associated with the aggregated groups above.
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//!
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//! ## The complexity of defining groups of facet strings
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//!
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//! As explained above, defining groups of facet numbers is easy, LMDB stores the keys in
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//! lexicographical order, it means that whatever the key represent the bytes are read in their raw
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//! form and a simple `strcmp` will define the order in which keys will be read from the store.
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//!
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//! That's easy for types with a known size, like floats or integers, they are 64 bytes long and
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//! appending one after the other in big-endian is consistent. LMDB will simply sort the keys by the
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//! first number then by the second if the the first number is equal on two keys.
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//!
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//! For strings it is a lot more complex as those types are unsized, it means that the size of facet
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//! strings is different for each facet value.
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//!
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//! ### Basic approach: padding the keys
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//!
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//! A first approach would be to simply define the maximum size of a facet string and pad the keys
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//! with zeroes. The big problem of this approach is that it:
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//! 1. reduces the maximum size of facet strings by half, as we need to put two keys one after the
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//! other.
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//! 2. makes the keys of facet strings very big (approximately 250 bytes), impacting a lot LMDB
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//! performances.
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//!
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//! ### Better approach: number the facet groups
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//!
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//! A better approach would be to number the groups, this way we don't have the downsides of the
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//! previously described approach but we need to be able to describe the groups by using a number.
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//!
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//! #### Example of facet strings with numbered groups
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//!
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//! | level | left-bound | right-bound | left-string | right-string | docs |
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//! |-------|------------|-------------|-------------|--------------|------------------|
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//! | 0 | alpha | _skipped_ | _skipped_ | _skipped_ | 1, 2 |
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//! | 0 | beta | _skipped_ | _skipped_ | _skipped_ | 6, 7 |
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//! | 0 | gamma | _skipped_ | _skipped_ | _skipped_ | 4, 7 |
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//! | 0 | omega | _skipped_ | _skipped_ | _skipped_ | 2, 3, 4 |
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//! | 1 | 0 | 1 | alpha | beta | 1, 2, 6, 7 |
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//! | 1 | 3 | 5 | gamma | omega | 2, 3, 4, 7 |
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//! | 2 | 0 | 5 | _skipped_ | _skipped_ | 1, 2, 3, 4, 6, 7 |
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//!
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//! As you can see the level 0 doesn't actually change much, we skip nearly everything, we do not
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//! need to store the facet string value two times.
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//!
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//! In the value, not in the key, you can see that we added two new values:
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//! the left-string and the right-string, which defines the original facet strings associated with
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//! the given group.
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//!
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//! We put those two strings inside of the value, this way we do not limit the maximum size of the
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//! facet string values, and the impact on performances is not important as, IIRC, LMDB put big
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//! values on another page, this helps in iterating over keys fast enough and only fetch the page
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//! with the values when required.
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//!
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//! The other little advantage with this solution is that there is no a big overhead, compared with
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//! the facet number levels, we only duplicate the facet strings once for the level 1.
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//!
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//! #### A typical algorithm run
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//!
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//! Note that the algorithm is always moving from the highest level to the lowest one, one level
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//! by one level, this is why it is ok to only store the facets string on the level 1.
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//!
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//! If a group of aggregated facets values, a group with numbers contains one of the documents ids,
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//! we must continue iterating over the sub-groups. To do so:
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//! - If we are at a level >= 2, we just do the same as with the facet numbers, get both bounds
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//! and iterate over the facet groups defined by these numbers over the current level - 1.
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//! - If we are at level 1, we retrieve both keys, the left-string and right-string, from the
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//! value and just do the same as with the facet numbers but with strings: iterate over the
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//! current level - 1 with both keys.
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//!
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//! If this group is the lowest level (level 0) and contain at least one document id we yield the
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//! associated facet documents ids.
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//!
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//! If the group doesn't contain one of our documents ids, we continue to the next group at this
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//! same level.
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//!
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@ -5,5 +5,6 @@ pub(crate) use self::parser::Rule as ParserRule;
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mod facet_distribution;
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mod facet_distribution;
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mod facet_number;
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mod facet_number;
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mod facet_string;
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mod filter_condition;
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mod filter_condition;
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mod parser;
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mod parser;
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