This change make single shard requests fail when no routing is specified and routing has been configured to be required in the mapping. Thi
Closes#4506
The following APIs now accept the query in a top level `query` field like:
* delete_by_query
* validate_query
* count
These APIs used to accept the query directly in the request body which was inconsistent with the search and explain APIs. For this reason t
Closes#4074
Test can be run with `-Dtests.assertion.disabled=org.elasticsearch`
to run the tests without assertions to make sure assertions
don't hide any assignements etc. that introduce bugs in production.
We are mocking out some functionality to add assertions etc. or
randomize store types. We should randomly run with our defaults to make
sure we don't hide any potential problems.
Currently we only test if readers are correctly released when exceptions
occur during reopen or flush. This commit adds a test that
randomly throws exceptions during the search execution ie. when Terms
are pulled or if a docs enum is created.
This commits add doc values support to geo point using the exact same approach
as for numeric data: geo points for a given document are stored uncompressed
and sequentially in a single binary doc values field.
Close#4207
Until now, RangeAggregator was a PER_BUCKET aggregator, expecting to be always
collected with owningBUcketOrdinal == 0. However, since the number of buckets
it creates is known in advance, it can be changed to a MULTI_BUCKETS aggregator
by just multiplying the bucket ordinal by the number of ranges.
This makes aggregations that have ranges as sub aggregations of PER_BUCKET
aggregators more efficient.
Close#4550
Although SORTED_SET doc values make things like terms aggregations very fast
thanks to the use of ordinals, ordinals are usually not that useful on numeric
data. We are more interested in the values themselves in order to be able to
compute sums, averages, etc. on these values. However, SORTED_SET is quite slow
at accessing values, so BINARY doc values are better suited at storing numeric
data.
floats and doubles are encoded without compression with little-endian byte order
(so that it may be optimizable through sun.misc.Unsafe in the future given that
most computers nowadays use the little-endian byte order) and byte, short, int,
and long are encoded using vLong encoding: they first encode the minimum value
using zig-zag encoding (so that negative values become positive) and then deltas
between successive values.
Close#3993
This prevents missing very short timeouts which fire before the calling thread had the chance to add the task to the queue and are therefore ignored. This is mostly of importance for testing where we explicitly want tasks to timeout and set it to a very low value.
- also, in geo distance, because it's based on range agg and that by default the order of the geo point per doc is unknown, always wrap it in a dedicated field data source which sorts the values if needed. But most of the times, a doc will be associated with a single point and therefore most of this wrapping is redundant and adds perf. cost for nothing.
- the idea here is for every request that "hits" a field data agg, we'll first iterate over the searchable segments and load their field data and compute the cross-segment info out of them. This info will be placed in the field context with which the value sources are created.
- we currently have some of this info on the IndexFieldData, but problem with getting it from there is that we may easily end up getting wrong info that originate in unsearchable segments.
Britta Weber
Martijn van Groningen
Simon Willnauer
Alexander Reelsen
Shay Banon
David Pilato
Adrien Grand
Luca Cavanna
Florian Schilling
Boaz Leskes
Andrew Raines
uboness