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Percolator type
editPercolator type
editThe percolator
field type parses a json structure into a native query and
stores that query, so that the percolate query
can use it to match provided documents.
Any field that contains a json object can be configured to be a percolator
field. The percolator field type has no settings. Just configuring the percolator
field type is sufficient to instruct Elasticsearch to treat a field as a
query.
If the following mapping configures the percolator
field type for the
query
field:
{ "properties": { "query": { "type": "percolator" } } }
Then the following json snippet can be indexed as a native query:
{ "query" : { "match" : { "field" : "value" } } }
Fields referred to in a percolator query must already exist in the mapping
associated with the index used for percolation. In order to make sure these fields exist,
add or update a mapping via the create index or put mapping APIs.
Fields referred in a percolator query may exist in any type of the index containing the percolator
field type.
Dedicated Percolator Index
editPercolate queries can be added to any index. Instead of adding percolate queries to the index the data resides in, these queries can also be added to a dedicated index. The advantage of this is that this dedicated percolator index can have its own index settings (For example the number of primary and replica shards). If you choose to have a dedicated percolate index, you need to make sure that the mappings from the normal index are also available on the percolate index. Otherwise percolate queries can be parsed incorrectly.
Forcing Unmapped Fields to be Handled as Strings
editIn certain cases it is unknown what kind of percolator queries do get registered, and if no field mapping exists for fields
that are referred by percolator queries then adding a percolator query fails. This means the mapping needs to be updated
to have the field with the appropriate settings, and then the percolator query can be added. But sometimes it is sufficient
if all unmapped fields are handled as if these were default string fields. In those cases one can configure the
index.percolator.map_unmapped_fields_as_string
setting to true
(default to false
) and then if a field referred in
a percolator query does not exist, it will be handled as a default string field so that adding the percolator query doesn’t
fail.
Limitations
editParent/child
editBecause the percolate
query is processing one document at a time, it doesn’t support queries and filters that run
against child documents such as has_child
and has_parent
.
Fetching queries
editThere are a number of queries that fetch data via a get call during query parsing. For example the terms
query when
using terms lookup, template
query when using indexed scripts and geo_shape
when using pre-indexed shapes. When these
queries are indexed by the percolator
field type then the get call is executed once. So each time the percolator
query evaluates these queries, the fetches terms, shapes etc. as the were upon index time will be used. Important to note
is that fetching of terms that these queries do, happens both each time the percolator query gets indexed on both primary
and replica shards, so the terms that are actually indexed can be different between shard copies, if the source index
changed while indexing.
Script query
editThe script inside a script
query can only access doc values fields. The percolate
query indexes the provided document
into an in-memory index. This in-memory index doesn’t support stored fields and because of that the _source
field and
other stored fields are not stored. This is the reason why in the script
query the _source
and other stored fields
aren’t available.