in a recent commit, we changed the code to reuse
TermFrequencyRow objects intsead of constantly allocating new
ones. unfortunately, one of the original methods was not coded
with this reuse in mind, and a lazy initialization cause us to
leak data from previous uses of the same object.
in particular this caused term vector information from previous
hits to still be applied to subsequent hits. eventually this
causes the highlighter to try and highlight invalid regions
of a slice.
fixes#404
The UpsideDownCouchTermFieldReader.Next() only needs the doc ID from
the key, so this change provides a specialized parseKDoc() method for
that optimization.
Additionally, fields in various structs are more 64-bit aligned, in an
attempt to reduce the invocations of runtime.typedmemmove() and
runtime.heapBitsBulkBarrier(), which the go compiler seems to
automatically insert to transparently handle misaligned data.
Before this change, upside down's reader would alloc a new
TermFrequencyRow on every Next(), which would be immediately
transformed into an index.TermFieldDoc{}. This change reuses a
pre-allocated TermFrequencyRow that's a field in the reader.
This is somewhat unlikely, but if a term is (incredibly) popular, its
uvarint count value representation might go beyond 8 bytes.
Some KVStore implementations (like forestdb) provide a BatchEx cgo
optimization that depends on proper preallocated counting, so this
change provides a proper worst-case estimate based on the max-unvarint
of 10 bytes instead of the previously incorrect 8 bytes.
Rows content is an implementation detail of bleve index and may change
in the future. That said, they also contains information valuable to
assess the quality of the index or understand its performances. So, as
long as we agree that type asserting rows should only be done if you
know what you are doing and are ready to deal with future changes, I see
no reason to hide the row fields from external packages.
Fix#268
the logic for reading the docID from the keys
in this row relies on the keys NEVER containing
the byte separator character (0xff), this is OK
as we require that all keys be valid utf-8
however, it turns out that in the case where this
rule was violated, we would panic, because we
return nil, nil and later try to print the doc id
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
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
now can track array positions for field values
stored fields now include this in the key
and the back index now uses protobufs to simplify serialization
closes#73
ultimately this is make it more convenient for us to wire up
different elements of the analysis pipeline, without having to
preload everything into memory before we need it
separately the index layer now has a mechanism for storing
internal key/value pairs. this is expected to be used to
store the mapping, and possibly other pieces of data by the
top layer, but not exposed to the user at the top.
previously we used the format:
't' <utf-8 term> <byte separator> <16-bit field id> <utf-8 docID> <byte separator>
now we have moved the field before the term, resulting in:
't' <16-bit field id> <utf-8 term> <byte separator> <utf-8 docID> <byte separator>
this means now instead of all fields with the same term being grouped together
all terms within the same field are grouped together
this allows us to enumerate the terms used with a field
this allows us to implement prefix search, and possibly improve numeric range queries
