I wouldn’t worry about performance with that setup. I just checked on a
production
system with 13 million docs in four shards, so 3+ million per shard. I searched
on
the most common term in the title field and got a response in 31 milliseconds.
This was probably not cached, because the collection
yup. youre going to find solr is WAY more efficient than you think when it
comes to complex queries.
On Wed, Oct 9, 2019 at 3:17 PM Audrey Lorberfeld - audrey.lorberf...@ibm.com
wrote:
> True...I guess another rub here is that we're using the edismax parser, so
> all of our queries are inherent
True...I guess another rub here is that we're using the edismax parser, so all
of our queries are inherently OR queries. So for a query like 'the ibm way',
the search engine would have to:
1) retrieve a document list for:
--> "ibm" (this list is probably 80% of the documents)
--> "the" (th
if you have anything close to a decent server you wont notice it all. im
at about 21 million documents, index varies between 450gb to 800gb
depending on merges, and about 60k searches a day and stay sub second non
stop, and this is on a single core/non cloud environment
On Wed, Oct 9, 2019 at 2:5
only in my more like this tools, but they have a very specific purpose,
otherwise no
On Wed, Oct 9, 2019 at 2:31 PM Audrey Lorberfeld - audrey.lorberf...@ibm.com
wrote:
> Wow, thank you so much, everyone. This is all incredibly helpful insight.
>
> So, would it be fair to say that the majority o
oh and by 'non stop' i mean close enough for me :)
On Wed, Oct 9, 2019 at 2:59 PM David Hastings
wrote:
> if you have anything close to a decent server you wont notice it all. im
> at about 21 million documents, index varies between 450gb to 800gb
> depending on merges, and about 60k searches a
Also, in terms of computational cost, it would seem that including most
terms/not having a stop ilst would take a toll on the system. For instance,
right now we have "ibm" as a stop word because it appears everywhere in our
corpus. If we did not include it in the stop words file, we would have t
Yeah, I dont use it as a search, only well, finding more documents like
that one :) . for my purposes i tested between 2 to 5 part shingles and
ended up that the 2 part was actually giving me better results, for my use
case, than using any more.
I dont suppose you could point me to any of the phra
We did something like that with Infoseek and Ultraseek. We had a set of
“glue words” that made noun phrases and indexed patterns like “noun glue noun”
as single tokens.
I remember Doug Cutting saying that Nutch did something similar using pairs,
but using that as a prefilter instead of as a relev
Wow, thank you so much, everyone. This is all incredibly helpful insight.
So, would it be fair to say that the majority of you all do NOT use stop words?
--
Audrey Lorberfeld
Data Scientist, w3 Search
IBM
audrey.lorberf...@ibm.com
On 10/9/19, 11:14 AM, "David Hastings" wrote:
However,
However, with all that said, stopwords CAN be useful in some situations. I
combine stopwords with the shingle factory to create "interesting phrases"
(not really) that i use in "my more like this" needs. for example,
europe for vacation
europe on vacation
will create the shingle
europe_vacation
w
another add on, as the previous two were pretty much spot on:
https://www.google.com/search?rlz=1C5CHFA_enUS814US819&sxsrf=ACYBGNTi2tQTQH6TycDKwRNEn9g2km9awg%3A1570632176627&ei=8PGdXa7tJeem_QaatJ_oAg&q=drive+in&oq=drive+in&gs_l=psy-ab.3..0l10.35669.36730..37042...0.4..1.434.1152.4j3j4-1..0
The theory behind stopwords is that they are “safe” to remove when calculating
relevance, so we can squeeze every last bit of usefulness out of very
constrained hardware (think 64K of memory. Yes kilobytes). We’ve come a long
way since then and the necessity of removing stopwords from the indexe
Stopwords (it was discussed on mailing list several times I recall):
The ideas is that it used to be part of the tricks to make the index
as small as possible to allow faster search. Stopwords being the most
common words
This days, disk space is not an issue most of the time and there have
been
Stopwords were used when we were running search engines on 16-bit computers
with 50 Megabyte disks, like the PDP-11. They avoided storing and processing
long posting lists.
Think of removing stopwords as a binary weighting on frequent terms, either on
or off (not in the index). With idf, we hav
Hey Alex,
Thank you!
Re: stopwords being a thing of the past due to the affordability of
hardware...can you expand? I'm not sure I understand.
--
Audrey Lorberfeld
Data Scientist, w3 Search
IBM
audrey.lorberf...@ibm.com
On 10/8/19, 1:01 PM, "David Hastings" wrote:
Another thing to ad
Another thing to add to the above,
>
> IT:ibm. In this case, we would want to maintain the colon and the
> capitalization (otherwise “it” would be taken out as a stopword).
>
stopwords are a thing of the past at this point. there is no benefit to
using them now with hardware being so cheap.
On Tu
If you don't want it to be touched by a tokenizer, how would the
protection step know that the sequence of characters you want to
protect is "IT:ibm" and not "this is an IT:ibm term I want to
protect"?
What it sounds to me is that you may want to:
1) copyField to a second field
2) Apply a much lig
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