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 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