These clauses filter the document space without affecting scoring and map to
Lucene's BooleanClause.Occur.FILTER. The `filtered` query is now deprecated and
```json
{
"filtered": {
"query": { //query },
"filter": { //filter }
}
}
```
should be replaced with
```json
{
"bool": {
"must": { //query },
"filter": { //filter }
}
}
```
Meta fields were locked down to not allow exotic options to the
underlying field types in #8143. This change fixes the docs
to no longer refer to the old settings.
closes#10879
This commit makes queries and filters parsed the same way using the
QueryParser abstraction. This allowed to remove duplicate code that we had
for similar queries/filters such as `range`, `prefix` or `term`.
This removes Elasticsearch's filter cache and uses Lucene's instead. It has some
implications:
- custom cache keys (`_cache_key`) are unsupported
- decisions are made internally and can't be overridden by users ('_cache`)
- not only filters can be cached but also all queries that do not need scores
- parent/child queries can now be cached, however cached entries are only
valid for the current top-level reader so in practice it will likely only
be used on read-only indices
- the cache deduplicates filters, which plays nicer with large keys (eg. `terms`)
- better stats: we already had ram usage and evictions, but now also hit count,
miss count, lookup count, number of cached doc id sets and current number of
doc id sets in the cache
- dynamically changing the filter cache size is not supported anymore
Internally, an important change is that it removes the NoCacheFilter infrastructure
in favour of making Query.rewrite specializing the query for the current reader so
that it will only be cached on this reader (look for IndexCacheableQuery).
Note that consuming filters with the query API (createWeight/scorer) instead of
the filter API (getDocIdSet) is important for parent/child queries because
otherwise a QueryWrapperFilter(ParentQuery) would run the wrapped query per
segment while relations might be cross segments.
Expose new span queries from https://issues.apache.org/jira/browse/LUCENE-6083
Within returns matches from 'little' that are enclosed inside of a match from 'big'.
Containing returns matches from 'big' that enclose matches from 'little'.
field_value_factor now takes a default that is used if the document doesn't
have a value for that field. It looks like:
"field_value_factor": {
"field": "popularity",
"missing": 1
}
Closes#10841
Hi there. I've been experimenting with the search templates recently and I'm a bit confused. Shouldn't the Mustache tags be written like `{{tagname}}` instead of `{tagname}`? Your using `{{...}}` [here](http://www.elastic.co/guide/en/elasticsearch/reference/current/search-template.html) BTW.
Using the first example in that page seems to indicate that something's wrong, or am I missing something?
```
$ curl 'localhost:9200/test/_search' -d '{"query":{"template":{"query":{"match":{"text":"{keywords}"}},"params":{"keywords":"value1_foo"}}}}'
{"took":1,"timed_out":false,"_shards":{"total":1,"successful":1,"failed":0},"hits":{"total":0,"max_score":null,"hits":[]}}
$ curl 'localhost:9200/test/_search' -d '{"query":{"template":{"query":{"match":{"text":"{{keywords}}"}},"params":{"keywords":"value1_foo"}}}}'
{"took":1,"timed_out":false,"_shards":{"total":1,"successful":1,"failed":0},"hits":{"total":1,"max_score":1.0,"hits":[{"_index":"test","_type":"testtype","_id":"1","_score":1.0,"_source":{"text":"value1_foo"}}]}}
```
In Lucene 5.1 lots of filters got deprecated in favour of equivalent queries.
Additionally, random-access to filters is now replaced with approximations on
scorers. This commit
- replaces the deprecated NumericRangeFilter, PrefixFilter, TermFilter and
TermsFilter with NumericRangeQuery, PrefixQuery, TermQuery and TermsQuery,
wrapped in a QueryWrapperFilter
- replaces XBooleanFilter, AndFilter and OrFilter with a BooleanQuery in a
QueryWrapperFilter
- removes DocIdSets.isBroken: the new two-phase iteration API will now help
execute slow filters efficiently
- replaces FilterCachingPolicy with QueryCachingPolicy
Close#8960
This adds a new feature to the Term Vectors API which allows for filtering of
terms based on their tf-idf scores. With `dfs` option on, this could be useful
for finding out a good characteric vector of a document or a set of documents.
The parameters are similar to the ones used in the MLT Query.
Closes#9561
This is really a Collector instead of a filter. This commit deprecates the
`limit` filter, makes it a no-op and recommends to use the `terminate_after`
parameter instead that we introduced in the meantime.
Relates to #10154 and #10150
Adds link to additional information on how document frequencies are treated across shards to the cutoff_frequency parameter documentation.
Closes#10451
The analysis chain should be used instead of relying on this, as it is
confusing when dealing with different per-field analysers.
The `locale` option was only used for `lowercase_expanded_terms`, which,
once removed, is no longer needed, so it was removed as well.
Fixes#9978
Relates to #9973
Double negatives are confusing, but a triple negative (1 no, 2 non, 3 null)? It takes five minutes to understand this little sentence. Cleaned that up a bit.
Closes#9789
This is our only cache which is not 'exact' and might allow for stalled results.
Additionally, a similar cache that we have and needs to perform lookups in other
indices in order to run queries is the script index, and for this index we rely
on the filesystem cache, so we should probably do the same with terms filters
lookups.
Close#9056
Up to now, all filters could be cached using the `_cache` flag that could be
set to `true` or `false` and the default was set depending on the type of the
`filter`. For instance, `script` filters are not cached by default while
`terms` are. For some filters, the default is more complicated and eg. date
range filters are cached unless they use `now` in a non-rounded fashion.
This commit adds a 3rd option called `auto`, which becomes the default for
all filters. So for all filters a cache wrapper will be returned, and the
decision will be made at caching time, per-segment. Here is the default logic:
- if there is already a cache entry for this filter in the current segment,
then return the cache entry.
- else if the doc id set cannot iterate (eg. script filter) then do not cache.
- else if the doc id set is already cacheable and it has been used twice or
more in the last 1000 filters then cache it.
- else if the filter is costly (eg. multi-term) and has been used twice or more
in the last 1000 filters then cache it.
- else if the doc id set is not cacheable and it has been used 5 times or more
in the last 1000 filters, then load it into a cacheable set and cache it.
- else return the uncached set.
So for instance geo-distance filters and script filters are going to use this
new default and are not going to be cached because of their iterators.
Similarly, date range filters are going to use this default all the time, but
it is very unlikely that those that use `now` in a not rounded fashion will get
reused so in practice they won't be cached.
`terms`, `range`, ... filters produce cacheable doc id sets with good iterators
so they will be cached as soon as they have been used twice.
Filters that don't produce cacheable doc id sets such as the `term` filter will
need to be used 5 times before being cached. This ensures that we don't spend
CPU iterating over all documents matching such filters unless we have good
evidence of reuse.
One last interesting point about this change is that it also applies to compound
filters. So if you keep on repeating the same `bool` filter with the same
underlying clauses, it will be cached on its own while up to now it used to
never be cached by default.
`_cache: true` has been changed to only cache on large segments, in order to not
pollute the cache since small segments should not be the bottleneck anyway.
However `_cache: false` still has the same semantics.
Close#8449
I replaced "high frequent terms" with "high frequency terms" and "low frequent terms" with "low frequency terms".
Alternatively, we could write, "highly frequent terms" and "minimally frequent terms" (or just "rare terms").
Closes#8962
Adds a `ignore_like` parameter to the MLT Query, which simply tells the
algorithm to skip all the terms from the given documents. This could be useful
in order to better guide nearest neighbor search by telling the algorithm to
never explore the space spanned by the given `ignore_like` docs. In essence we
are interested about the characteristic of a given item, but not of the ones
provided by `ignore_like`, thereby forcing the algorithm to go deeper in its
selection of terms. Note that this is different than simply performing a must
not boolean query on the unliked items. The syntax is exactly the same as the
`like` parameter.
Closes#8674
functon_score matched each document regardless of the computed score.
This commit adds a query parameter `min_score` (-Float.MAX_VALUE default).
Documents that have a score lower than this threshold will not be mached.
closes#6952
Clinton Gormley
Martijn van Groningen
Adrien Grand
Ryan Ernst
Pascal Borreli
Clément Salaün
Robert Muir
Nik Everett
navins
Christine
Mark Mulder
Oliver Eilhard
Alex Ksikes
Benoit Delbosc
Isabel Drost-Fromm
joelbourbon
Patrick Peschlow
Lee Hinman
cgp
Michael Sander
Blake Niemyjski
Alfredo Serafini
Adam
Timothy Perisho
John Michael Luy
pmamat
Britta Weber