This change unifies the way scripts and templates are specified for all instances in the codebase. It builds on the Script class added previously and adds request building and parsing support as well as the ability to transfer script objects between nodes. It also adds a Template class which aims to provide the same functionality for template APIs
Closes#11091
The default `false` for `require_field_match` is a bit odd and confusing for users, given that field names get ignored by default and every field gets highlighted if it contains terms extracted out of the query, regardless of which fields were queries. Changed the default to `true`, it can always be changed per request.
Closes#10627Closes#11067
Our own fork of the lucene PostingsHighlighter is not easy to maintain and doesn't give us any added value at this point. In particular, it was introduced to support the require_field_match option and discrete per value highlighting, used in case one wants to highlight the whole content of a field, but get back one snippet per value. These two features won't
make it into lucene as they slow things down and shouldn't have been supported from day one on our end probably.
One other customization we had was support for a wider range of queries via custom rewrite etc. (yet another way to slow
things down), which got added to lucene and works much much better than what we used to do (instead of or rewrite, term
s are pulled out of the automata for multi term queries).
Removing our fork means the following in terms of features:
- dropped support for require_field_match: the postings highlighter will only highlight fields that were queried
- some custom es queries won't be supported anymore, meaning they won't be highlighted. The only one I found up until now is the phrase_prefix. Postings highlighter rewrites against an empty reader to avoid slow operations (like the ones that we were performing with the fork that we are removing here), thus the prefix will not be expanded to any term. What the postings highlighter does instead is pulling the automata out of multi term queries, but this is not supported at the moment with our MultiPhrasePrefixQuery.
Closes#10625Closes#11077
Previously, collate feature would be executed on all shards of an index using the client,
this leads to a deadlock when concurrent collate requests are run from the _search API,
due to the fact that both the external request and internal collate requests use the
same search threadpool.
As phrase suggestions are generated from the terms of the local shard, in most cases the
generated suggestion, which does not yield a hit for the collate query on the local shard
would not yield a hit for collate query on non-local shards.
Instead of using the client for collating suggestions, collate query is executed against
the ContextIndexSearcher. This PR removes the ability to specify a preference for a collate
query, as the collate query is only run on the local shard.
closes#9377
Add methods to operate on multi-valued fields in the expressions language.
Note that users will still not be able to access individual values
within a multi-valued field.
The following methods will be included:
* min
* max
* avg
* median
* count
* sum
Additionally, changes have been made to MultiValueMode to support the
new median method.
closes#11105
Removes the More Like This API, users should now use the More Like This query.
The MLT API tests were converted to their query equivalent. Also some clean
ups in MLT tests.
Closes#10736Closes#11003
The assumption is that gaps in histogram are generally undesirable, for instance
if you want to build a visualization from it. Additionally, we are building new
aggregations that require that there are no gaps to work correctly (eg.
derivatives).
Remove the ability to specify search type ‘query_and_fetch’ and
‘df_query_and_fetch’ from the REST API.
- Adds REST tests
- Updates REST API spec to remove ‘query_and_fetch’ and
‘df_query_and_fetch’ as options
- Removes documentation for these options
Closes#9606
* Removed the docs for `index.compound_format` and `index.compound_on_flush` - these are expert settings which should probably be removed (see https://github.com/elastic/elasticsearch/issues/10778)
* Removed the docs for `index.index_concurrency` - another expert setting
* Labelled the segments verbose output as experimental
* Marked the `compression`, `precision_threshold` and `rehash` options as experimental in the cardinality and percentile aggs
* Improved the experimental text on `significant_terms`, `execution_hint` in the terms agg, and `terminate_after` param on count and search
* Removed the experimental flag on the `geobounds` agg
* Marked the settings in the `merge` and `store` modules as experimental, rather than the modules themselves
Closes#10782
The field stats api returns field level statistics such as lowest, highest values and number of documents that have at least one value for a field.
An api like this can be useful to explore a data set you don't know much about. For example you can figure at with the lowest and highest response times are, so that you can create a histogram or range aggregation with sane settings.
This api doesn't run a search to figure this statistics out, but rather use the Lucene index look these statics up (using Terms class in Lucene). So finding out these stats for fields is cheap and quick.
The min/max values are based on the type of the field. So for a numeric field min/max are numbers and date field the min/max date and other fields the min/max are term based.
Closes#10523
This commit adds a `rewrite` parameter to the validate API in order to shown
how the given query is re-written into primitive queries. For example, an MLT
query is re-written into a disjunction of the selected terms. Other use cases
include `fuzzy`, `common_terms`, or `match` query especially with a
`cutoff_frequency` parameter. Note that the explanation is only given for a
single randomly chosen shard only, so the output may vary from one shard to
another.
Relates #1412Closes#10147
Today we check every regular expression eagerly against every possible term.
This can be very slow if you have lots of unique terms, and even the bottleneck
if your query is selective.
This commit switches to Lucene regular expressions instead of Java (not exactly
the same syntax yet most existing regular expressions should keep working) and
uses the same logic as RegExpQuery to intersect the regular expression with the
terms dictionary. I wrote a quick benchmark (in the PR) to make sure it made
things faster and the same request that took 750ms on master now takes 74ms with
this change.
Close#7526