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: explicit 10 text edismax text^2 text_par^1 true true true true breakIterator 2 name name_par description description_par content content_par 162 simple default Cheers! - Andy
RE: Slow Highlighter Performance Even Using FastVectorHighlighter
After taking your advice on profiling, I didn't see any memory issues. I wanted to verify this with a small set of data. So I created a new sandbox core with the exact same schema and config file settings. I indexed only 25 PDF documents with an average size of 2.8 MB, the largest is approx 5 MB (39 pages). I run the exact same query on that core and I'm seeing response times of 7 secs or more. Without highlighting the response is usually 1 ms. 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( ) 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 i
RE: Slow Highlighter Performance Even Using FastVectorHighlighter
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: > > > > > > > > > required="true" multiValued="false"/> > > > > > > > > > multiValued="true" termPositions="true" termVectors="true" > > termOffsets="true"/> > > > stored="true" multiValued="true" termPositions="true" > termVectors="true" > > termOffsets="true"/> > > > multiValued="true" termPositions="true" termVectors="true" > > termOffsets="true"/> > > > multiValued="true"/> > > > > > > > stored="true" multiValued="true" termPositions="true" > termVectors="true" > > termOffsets="true"/> > > indexed="true" > > stored="true" multiValued="true" termPositions="true" > termVectors="true" > > termOffsets="true"/> > > > stored="true" multiValued="true" termPositions="true" > termVectors="true" > > termOffsets="true"/> > > > stored="false" multiValued="true"/> > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > positionIncrementGap="100"> > > > > > > > words="stopwords.txt" enablePositionIncrements="true" /> > > > > > > > > > > > words="stopwords.txt" enablePositionIncrements="true" /> > > > ignoreCase="true" expand="true"/> > > > > > > > > > > > > > positionIncrementGap="100"> > > > > > > > words="stopwords.txt" enablePositionIncrements="true" /> > > > > > maxGramSize="7"/> > > > > > > > > > words="stopwords.txt" enablePositionIncrements="true" /> > > > ignoreCase="true" expand="true"/> > > > > > > > > > > > > > > > > > > > >explicit > >10 > >text > >edismax > >text^2 text_par^1 > >true > >true > >true > >true > >breakIterator > >2 > >name name_par description description_par > > content content_par > >162 > >simple > >default > > > > > > > > > > > > > > > > > > Cheers! > > > > - Andy
