this lays the foundation for supporting the new firestorm
indexing scheme. i'm merging these changes ahead of
the rest of the firestorm branch so i can continue
to make changes to the analysis pipeline in parallel
refactor to share code in emulated batch
refactor to share code in emulated merge
refactor index kvstore benchmarks to share more code
refactor index kvstore benchmarks to be more repeatable
improvements uncovered some issues with how k/v data was copied
or not. to address this, kv abstraction layer now lets impl
specify if the bytes returned are safe to use after a reader
(or writer since writers are also readers) are closed
See index/store/KVReader - BytesSafeAfterClose() bool
false is the safe value if you're not sure
it will cause index impls to copy the data
Some kv impls already have created a copy a the C-api barrier
in which case they can safely return true.
Overall this yields ~25% speedup for searches with leveldb.
It yields ~10% speedup for boltdb.
Returning stored fields is now slower with boltdb, as previously
we were returning unsafe bytes.
this introduces disk format v4
now the summary rows for a term are stored in their own
"dictionary row" format, previously the same information
was stored in special term frequency rows
this now allows us to easily iterate all the terms for a field
in sorted order (useful for many other fuzzy data structures)
at the top-level of bleve you can now browse terms within a field
using the following api on the Index interface:
FieldDict(field string) (index.FieldDict, error)
FieldDictRange(field string, startTerm []byte, endTerm []byte) (index.FieldDict, error)
FieldDictPrefix(field string, termPrefix []byte) (index.FieldDict, error)
fixes#127
more things can return error now
in a couple of places we had to swallow errors because they didn't
fit the existing API. in these case and proactively in a few
others we now return error as well.
also the batch API has been updated to allow performing
set/delete internal within the batch
you can do a manual fuzzy term search using the FuzzyQuery struct
or, more suitable for most users the MatchQuery now supports
some fuzzy options. Here you can specify fuzziness and
prefix_length, to turn the underlying term search into a fuzzy
term search. This has the benefit that analysis is performed
on your input, just like the analyzed field, prior to computing
the fuzzy variants.
closes#82
1. text analysis is now done before the write lock is acquired
2. there is now a pool of analysis workers
3. the size of this pool is configurable
4. this allows for documents in a batch to be analyzed concurrently
as a part of benchmarking these changes i've also introduce a new
null storage implementation. this should never be used, as it
does not actualy build an index. it does however let us go
through all the normal indexing machinery, without incuring
any indexing I/O. this is very helpful in measuring improvements
made to the text analsysis pipeline, which are often overshadowed
by indexing times in benchmarks actually building an index.
In the index/store package
introduce KVReader
creates snapshot
all read operations consistent from this snapshot
must close to release
introduce KVWriter
only one writer active
access to all operations
allows for consisten read-modify-write
must close to release
introduce AssociativeMerge operation on batch
allows efficient read-modify-write
for associative operations
used to consolidate updates to the term summary rows
saves 1 set and 1 get op per shared instance of term in field
In the index package
introduced an IndexReader
exposes a consisten snapshot of the index for searching
At top level
All searches now operate on a consisten snapshot of the index
this started initially to relocate highlighting into
a self contained package, which would then also use
the registry
however, it turned into a much larger refactor in
order to avoid cyclic imports
now facets, searchers, scorers and collectors
are also broken out into subpackages of search
