Bryan,
For specifics, I'll refer you back to my original email where I
specified all the fields/field types/handlers I use. Here's a general
overview.
I really only have 3 fields that I index and search against: "name",
"description", and "content". All of which are just general text
(string) fields. I have a catch-all field called "text" that is only
used for querying. It's indexed but not stored. The "name",
"description", and "content" fields are copied into the "text" field.
For partial word matching, I have 4 more fields: "name_par",
"description_par", "content_par", and "text_par". The "text_par" field
has the same relationship to the "*_par" fields as "text" does to the
others (only used for querying). Those partial word matching fields are
of type "text_general_partial" which I created. That field type is
analyzed different than the regular text field in that it goes through
an EdgeNGramFilterFactory with the minGramSize="2" and maxGramSize="7"
at index time.
I query against both "text" and "text_par" fields using edismax deftype
with my qf set to "text^2 text_par^1" to give full word matches a higher
score. This part returns back very fast as previously stated. It's when
I turn on highlighting that I take the huge performance hit.
Again, I'm using the FastVectorHighlighting. The hl.fl is set to "name
name_par description description_par content content_par" so that it
returns highlights for full and partial word matches. All of those
fields have indexed, stored, termPositions, termVectors, and termOffsets
set to "true".
It all seems redundant just to allow for partial word
matching/highlighting but I didn't know of a better way. Does anything
stand out to you that could be the culprit? Let me know if you need any
more clarification.
Thanks!
- Andy
-----Original Message-----
From: Bryan Loofbourrow [mailto:bloofbour...@knowledgemosaic.com]
Sent: Wednesday, May 29, 2013 5:44 PM
To: solr-user@lucene.apache.org
Subject: RE: Slow Highlighter Performance Even Using
FastVectorHighlighter
Andy,
I don't understand why it's taking 7 secs to return highlights. The
size
of the index is only 20.93 MB. The JVM heap Xms and Xmx are both set
to
1024 for this verification purpose and that should be more than
enough.
The processor is plenty powerful enough as well.
Running VisualVM shows all my CPU time being taken by mainly these 3
methods:
org.apache.lucene.search.vectorhighlight.FieldPhraseList$WeightedPhraseI
nfo.getStartOffset()
org.apache.lucene.search.vectorhighlight.FieldPhraseList$WeightedPhraseI
nfo.getStartOffset()
org.apache.lucene.search.vectorhighlight.FieldPhraseList.addIfNoOverlap(
)
That is a strange and interesting set of things to be spending most of
your CPU time on. The implication, I think, is that the number of term
matches in the document for terms in your query (or, at least, terms
matching exact words or the beginning of phrases in your query) is
extremely high . Perhaps that's coming from this "partial word match"
you
mention -- how does that work?
-- Bryan
My guess is that this has something to do with how I'm handling
partial
word matches/highlighting. I have setup another request handler that
only searches the whole word fields and it returns in 850 ms with
highlighting.
Any ideas?
- Andy
-----Original Message-----
From: Bryan Loofbourrow [mailto:bloofbour...@knowledgemosaic.com]
Sent: Monday, May 20, 2013 1:39 PM
To: solr-user@lucene.apache.org
Subject: RE: Slow Highlighter Performance Even Using
FastVectorHighlighter
My guess is that the problem is those 200M documents.
FastVectorHighlighter is fast at deciding whether a match, especially
a
phrase, appears in a document, but it still starts out by walking the
entire list of term vectors, and ends by breaking the document into
candidate-snippet fragments, both processes that are proportional to
the
length of the document.
It's hard to do much about the first, but for the second you could
choose
to expose FastVectorHighlighter's FieldPhraseList representation, and
return offsets to the caller rather than fragments, building up your
own
snippets from a separate store of indexed files. This would also
permit
you to set stored="false", improving your memory/core size ratio,
which
I'm guessing could use some improving. It would require some work, and
it
would require you to store a representation of what was indexed
outside
the Solr core, in some constant-bytes-to-character representation that
you
can use offsets with (e.g. UTF-16, or ASCII+entity references).
However, you may not need to do this -- it may be that you just need
more
memory for your search machine. Not JVM memory, but memory that the
O/S
can use as a file cache. What do you have now? That is, how much
memory
do
you have that is not used by the JVM or other apps, and how big is
your
Solr core?
One way to start getting a handle on where time is being spent is to
set
up VisualVM. Turn on CPU sampling, send in a bunch of the slow
highlight
queries, and look at where the time is being spent. If it's mostly in
methods that are just reading from disk, buy more memory. If you're on
Linux, look at what top is telling you. If the CPU usage is low and
the
"wa" number is above 1% more often than not, buy more memory (I don't
know
why that wa number makes sense, I just know that it has been a good
rule
of thumb for us).
-- Bryan
-----Original Message-----
From: Andy Brown [mailto:andy_br...@rhoworld.com]
Sent: Monday, May 20, 2013 9:53 AM
To: solr-user@lucene.apache.org
Subject: Slow Highlighter Performance Even Using
FastVectorHighlighter
I'm providing a search feature in a web app that searches for
documents
that range in size from 1KB to 200MB of varying MIME types (PDF,
DOC,
etc). Currently there are about 3000 documents and this will
continue
to
grow. I'm providing full word search and partial word search. For
each
document, there are three source fields that I'm interested in
searching
and highlighting on: name, description, and content. Since I'm
providing
both full and partial word search, I've created additional fields
that
get tokenized differently: name_par, description_par, and
content_par.
Those are indexed and stored as well for querying and highlighting.
As
suggested in the Solr wiki, I've got two catch all fields text and
text_par for faster querying.
An average search results page displays 25 results and I provide
paging.
I'm just returning the doc ID in my Solr search results and response
times have been quite good (1 to 10 ms). The problem in performance
occurs when I turn on highlighting. I'm already using the
FastVectorHighlighter and depending on the query, it has taken as
long
as 15 seconds to get the highlight snippets. However, this isn't
always
the case. Certain query terms result in 1 sec or less response time.
In
any case, 15 seconds is way too long.
I'm fairly new to Solr but I've spent days coming up with what I've
got
so far. Feel free to correct any misconceptions I have. Can anyone
advise me on what I'm doing wrong or offer a better way to setup my
core
to improve highlighting performance?
A typical query would look like:
/select?q=foo&start=0&rows=25&fl=id&hl=true
I'm using Solr 4.1. Below the relevant core schema and config
details:
<!-- Misc fields -->
<field name="_version_" type="long" indexed="true" stored="true"/>
<field name="id" type="string" indexed="true" stored="true"
required="true" multiValued="false"/>
<!-- Fields for whole word matches -->
<field name="name" type="text_general" indexed="true" stored="true"
multiValued="true" termPositions="true" termVectors="true"
termOffsets="true"/>
<field name="description" type="text_general" indexed="true"
stored="true" multiValued="true" termPositions="true"
termVectors="true"
termOffsets="true"/>
<field name="content" type="text_general" indexed="true"
stored="true"
multiValued="true" termPositions="true" termVectors="true"
termOffsets="true"/>
<field name="text" type="text_general" indexed="true" stored="false"
multiValued="true"/>
<!-- Fields for partial word matches -->
<field name="name_par" type="text_general_partial" indexed="true"
stored="true" multiValued="true" termPositions="true"
termVectors="true"
termOffsets="true"/>
<field name="description_par" type="text_general_partial"
indexed="true"
stored="true" multiValued="true" termPositions="true"
termVectors="true"
termOffsets="true"/>
<field name="content_par" type="text_general_partial" indexed="true"
stored="true" multiValued="true" termPositions="true"
termVectors="true"
termOffsets="true"/>
<field name="text_par" type="text_general_partial" indexed="true"
stored="false" multiValued="true"/>
<!-- Copy source name, description, and content fields to name_par,
description_par, and content_par for partial word searches -->
<copyField source="name" dest="name_par"/>
<copyField source="description" dest="description_par"/>
<copyField source="content" dest="content_par"/>
<!-- Copy source name, description, and content fields to catch-all
text
field for faster querying. -->
<copyField source="name" dest="text"/>
<copyField source="description" dest="text"/>
<copyField source="content" dest="text"/>
<!-- Copy source name, description, and content fields to catch-all
text_par field for faster querying of partial word searches. -->
<copyField source="name" dest="text_par"/>
<copyField source="description" dest="text_par"/>
<copyField source="content" dest="text_par"/>
<!-- A text field for whole word matches -->
<fieldType name="text_general" class="solr.TextField"
positionIncrementGap="100">
<analyzer type="index">
<tokenizer class="solr.StandardTokenizerFactory"/>
<filter class="solr.StopFilterFactory" ignoreCase="true"
words="stopwords.txt" enablePositionIncrements="true" />
<filter class="solr.LowerCaseFilterFactory"/>
</analyzer>
<analyzer type="query">
<tokenizer class="solr.StandardTokenizerFactory"/>
<filter class="solr.StopFilterFactory" ignoreCase="true"
words="stopwords.txt" enablePositionIncrements="true" />
<filter class="solr.SynonymFilterFactory"
synonyms="synonyms.txt"
ignoreCase="true" expand="true"/>
<filter class="solr.LowerCaseFilterFactory"/>
</analyzer>
</fieldType>
<!-- A text field for parital matches -->
<fieldType name="text_general_partial" class="solr.TextField"
positionIncrementGap="100">
<analyzer type="index">
<tokenizer class="solr.StandardTokenizerFactory"/>
<filter class="solr.StopFilterFactory" ignoreCase="true"
words="stopwords.txt" enablePositionIncrements="true" />
<filter class="solr.LowerCaseFilterFactory"/>
<filter class="solr.EdgeNGramFilterFactory" minGramSize="2"
maxGramSize="7"/>
</analyzer>
<analyzer type="query">
<tokenizer class="solr.StandardTokenizerFactory"/>
<filter class="solr.StopFilterFactory" ignoreCase="true"
words="stopwords.txt" enablePositionIncrements="true" />
<filter class="solr.SynonymFilterFactory"
synonyms="synonyms.txt"
ignoreCase="true" expand="true"/>
<filter class="solr.LowerCaseFilterFactory"/>
</analyzer>
</fieldType>
<requestHandler name="/select" class="solr.SearchHandler">
<!-- default values for query parameters can be specified, these
will be overridden by parameters in the request. -->
<lst name="defaults">
<str name="echoParams">explicit</str>
<int name="rows">10</int>
<str name="df">text</str>
<str name="defType">edismax</str>
<str name="qf">text^2 text_par^1</str> <!-- Boost whole
word matches more than partial matches in the scroing. -->
<bool name="termVectors">true</bool>
<bool name="termPositions">true</bool>
<bool name="termOffsets">true</bool>
<bool name="hl.useFastVectorHighlighter">true</bool>
<str name="hl.boundaryScanner">breakIterator</str>
<str name="hl.snippets">2</str>
<str name="hl.fl">name name_par description description_par
content content_par</str>
<int name="hl.fragsize">162</int>
<str name="hl.fragListBuilder">simple</str>
<str name="hl.fragmentsBuilder">default</str>
<str name="hl.simple.pre"><![CDATA[<strong>]]></str>
<str name="hl.simple.post"><![CDATA[</strong>]]></str>
<str name="hl.tag.pre"><![CDATA[<strong>]]></str>
<str name="hl.tag.post"><![CDATA[</strong>]]></str>
</lst>
</requestHandler>
Cheers!
- Andy
