Before Elasticsearch 1.0, the type was allowed to be passed as the root
element when uploading a document. However, this was ambiguous if the
mappings also contained a field with the same name as the type. The
behavior was changed in 1.0 to not allow this, but a setting was added
for backwards compatibility. This change removes the setting for 2.0.
The header indicates to how many shard copies (primary and replicas shards) a write was supposed to go to, to how many
shard copies to write succeeded and potentially captures shard failures if writing into a replica shard fails.
For async writes it also includes the number of shards a write is still pending.
Closes#7994
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
Related to #8667:
Some QueryBuilders have been deprecated in 1.x branches. We removed them in 2.0.
Removed
-------
* `textPhrase(...)`
* `textPhrasePrefix(...)`
* `textPhrasePrefixQuery(...)`
* `filtered(...)`
* `inQuery(...)`
* `commonTerms(...)`
* `queryString(...)`
* `simpleQueryString(...)`
Closes#8721.
We speak of the term vectors of a document, where each field has an associated
stored term vector. Since by default we are requesting all the term vectors of
a document, the HTTP request endpoint should rather be called `_termvectors`
instead of `_termvector`. The usage of `_termvector` is now deprecated, as
well as the transport client call to termVector and prepareTermVector.
Closes#8484
Previous to this change all features (_alias,_mapping,_settings,_warmer) are run regardless of which features are actually requested. This change fixes the request object to resolve this bug
We currently use the djb2 hash function in order to compute the shard a
document should go to. Unfortunately this hash function is not very
sophisticated and you can sometimes hit adversarial cases, such as numeric ids
on 33 shards.
Murmur3 generates hashes with a better distribution, which should avoid the
adversarial cases.
Here are some examples of how 100000 incremental ids are distributed to shards
using either djb2 or murmur3.
5 shards:
Murmur3: [19933, 19964, 19940, 20030, 20133]
DJB: [20000, 20000, 20000, 20000, 20000]
3 shards:
Murmur3: [33185, 33347, 33468]
DJB: [30100, 30000, 39900]
33 shards:
Murmur3: [2999, 3096, 2930, 2986, 3070, 3093, 3023, 3052, 3112, 2940, 3036, 2985, 3031, 3048, 3127, 2961, 2901, 3105, 3041, 3130, 3013, 3035, 3031, 3019, 3008, 3022, 3111, 3086, 3016, 2996, 3075, 2945, 2977]
DJB: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 900, 900, 900, 900, 1000, 1000, 10000, 10000, 10000, 10000, 9100, 9100, 9100, 9100, 9000, 9000, 0, 0, 0, 0, 0, 0]
Even if djb2 looks ideal in some cases (5 shards), the fact that the
distribution of its hashes has some patterns can raise issues with some shard
counts (eg. 3, or even worse 33).
Some tests have been modified because they relied on implementation details of
the routing hash function.
Close#7954
The MLT field query is simply replaced by a MLT query set to specififc field.
To simplify code maintenance we should deprecate it in 1.4 and remove it in
2.0.
Closes#8238
Ryan Ernst
Martijn van Groningen
Adrien Grand
David Pilato
Alex Ksikes
Simon Willnauer
Colin Goodheart-Smithe