It adds notes about:
- how preference can help optimize cache usage
- the fact that too many replicas can hurt search performance due to lower
utilization of the filesystem cache
- how index sorting can improve _source compression
- how always putting fields in the same order in documents can improve _source
compression
This snapshot has faster range queries on range fields (LUCENE-7828), more
accurate norms (LUCENE-7730) and the ability to use fake term frequencies
(LUCENE-7854).
This is a tentative to revive #15939 motivated by elastic/beats#1941.
Half-floats are a pretty bad option for storing percentages. They would likely
require 2 bytes all the time while they don't need more than one byte.
So this PR exposes a new `scaled_float` type that requires a `scaling_factor`
and internally indexes `value*scaling_factor` in a long field. Compared to the
original PR it exposes a lower-level API so that the trade-offs are clearer and
avoids any reference to fixed precision that might imply that this type is more
accurate (actually it is *less* accurate).
In addition to being more space-efficient for some use-cases that beats is
interested in, this is also faster that `half_float` unless we can improve the
efficiency of decoding half-float bits (which is currently done using software)
or until Java gets first-class support for half-floats.
This moves the "Performance Considerations for Elasticsearch Indexing" blog post
to the reference guide and adds similar recommendations for tuning disk usage
and search speed.
Adrien Grand
Glen Smith
Elijah
Pascal Borreli
Jason Tedor
Tanguy Leroux