In Elasticsearch 5.0.0, by default unquoted field names in JSON will be
rejected. This can cause issues, however, for documents that were
already indexed with unquoted field names. To alleviate this, a system
property has been added that can be enabled so migration can occur.
This system property will be removed in Elasticsearch 6.0.0
Resolves#17674
* Added an extra `field` parameter to the `percolator` query to indicate what percolator field should be used. This must be an existing field in the mapping of type `percolator`.
* The `.percolator` type is now forbidden. (just like any type that starts with a `.`)
This only applies for new indices created on 5.0 and later. Indices created on previous versions the .percolator type is still allowed to exist.
The new `percolator` field type isn't active in such indices and the `PercolatorQueryCache` knows how to load queries from these legacy indices.
The `PercolatorQueryBuilder` will not enforce that the `field` parameter is of type `percolator`.
This makes all numeric fields including `date`, `ip` and `token_count` use
points instead of the inverted index as a lookup structure. This is expected
to perform worse for exact queries, but faster for range queries. It also
requires less storage.
Notes about how the change works:
- Numeric mappers have been split into a legacy version that is essentially
the current mapper, and a new version that uses points, eg.
LegacyDateFieldMapper and DateFieldMapper.
- Since new and old fields have the same names, the decision about which one
to use is made based on the index creation version.
- If you try to force using a legacy field on a new index or a field that uses
points on an old index, you will get an exception.
- IP addresses now support IPv6 via Lucene's InetAddressPoint and store them
in SORTED_SET doc values using the same encoding (fixed length of 16 bytes
and sortable).
- The internal MappedFieldType that is stored by the new mappers does not have
any of the points-related properties set. Instead, it keeps setting the index
options when parsing the `index` property of mappings and does
`if (fieldType.indexOptions() != IndexOptions.NONE) { // add point field }`
when parsing documents.
Known issues that won't fix:
- You can't use numeric fields in significant terms aggregations anymore since
this requires document frequencies, which points do not record.
- Term queries on numeric fields will now return constant scores instead of
giving better scores to the rare values.
Known issues that we could work around (in follow-up PRs, this one is too large
already):
- Range queries on `ip` addresses only work if both the lower and upper bounds
are inclusive (exclusive bounds are not exposed in Lucene). We could either
decide to implement it, or drop range support entirely and tell users to
query subnets using the CIDR notation instead.
- Since IP addresses now use a different representation for doc values,
aggregations will fail when running a terms aggregation on an ip field on a
list of indices that contains both pre-5.0 and 5.0 indices.
- The ip range aggregation does not work on the new ip field. We need to either
implement range aggs for SORTED_SET doc values or drop support for ip ranges
and tell users to use filters instead. #17700Closes#16751Closes#17007Closes#11513
The change adds a new option to the geo_* queries: ignore_unmapped. If this option is set to false, the toQuery method on the QueryBuilder will throw an exception if the field specified in the query is unmapped. If the option is set to true, the toQuery method on the QueryBuilder will return a MatchNoDocsQuery. The default value is false so the queries work how they do today (throwing an exception on unmapped field)
The change adds a new option to the `nested`, `has_parent`, `has_children` and `parent_id` queries: `ignore_unmapped`. If this option is set to false, the `toQuery` method on the QueryBuilder will throw an exception if the type/path specified in the query is unmapped. If the option is set to true, the `toQuery` method on the QueryBuilder will return a MatchNoDocsQuery. The default value is `false`so the queries work how they do today (throwing an exception on unmapped paths/types)
With this commit we limit the size of all in-flight requests on
transport level. The size is guarded by a circuit breaker and is
based on the content size of each request.
By default we use 100% of available heap meaning that the parent
circuit breaker will limit the maximum available size. This value
can be changed by adjusting the setting
network.breaker.inflight_requests.limit
Relates #16011
This commit adds a new configuration file jvm.options to centralize and
simplify management of JVM options. This separates the configuration of
the JVM from the packaging scripts (bin/elasticsearch*, bin/service.bat,
and init.d/elasticsearch) simplifying end-user operational management of
custom JVM options.
CBOR is natively supported in Elasticsearch and allows for byte arrays.
This means, that by using CBOR the user can prevent base64 conversions
for the data being sent back and forth.
This PR adds support to extract data from a byte array in addition to
a string. This also required to add a ByteArrayValueSource class.
The doc mentions match_path in one place but the correct syntax is path_match which is mentioned everywhere else. Using the wrong string leads to errors because the mapping becomes too greedy, and matches things it shouldn't.