Solr Buildout Configuration#
Solr Multi Core#
Solr allows creating multiple cores which can be indexed and queried independently. However, collective.solr does not currently support multicore setups. It always uses the default core for indexing and searching.
A core is defined by creating a file called core.properties. In our example setup there is exactly one of these files. It specifies the name of the core.
It could also contain other property definitions. To define more cores we could add more files of the same name in other directories.
For indexes with a lot of text, common uninteresting words like "the", "a", and so on, make the index large and slow down phrase queries. To deal with this problem, it is best to remove them from fields where they show up often.
We need to add the StopFilterFactory with a reference to a text file with one stop word per line to the Solr configuration:
<fieldType name="text" class="solr.TextField" positionIncrementGap="100"> [...] <analyzer type="index"> <filter class="solr.StopFilterFactory" ignoreCase="true" words="stopwords.txt" /> [...]
a the i
For some common language specific examples see the Solr git repository:
Stemming is a language specific operation which tries to reduce terms to a base form.
Here is an example:
"riding", "rides", "horses" ==> "ride", "ride", "hors".
This can help in some situations but may hurt in others.
For example, if you run an intranet and people usally know exactly what they are looking for it is probably not a good idea, but if you provide a Google-like search where you browse more than search then stemming is probably for you.
If you are interested in this feature look at the Solr documentation here:
A short example to include a German stemming factory is here:
<fieldType name="text" class="solr.TextField" positionIncrementGap="100"> [...] <analyzer type="index"> <tokenizer class="solr.StandardTokenizerFactory"/> <!-- <filter class="solr.GermanMinimalStemFilterFactory"/> # Less aggressive --> <!-- <filter class="solr.GermanLightStemFilterFactory"/> # Moderately aggressiv --> <!-- <filter class="solr.SnowballPorterFilterFactory" language="German2"/> More aggressive --> <filter class="solr.StemmerOverrideFilterFactory" dictionary="stemdict.txt" ignoreCase="false" />
# english stemming monkeys monkey otters otter # some crazy ones that a stemmer would never do dogs cat # German stemming gelaufen lauf lief lauf risiken risiko
Solr can deal with synonyms. Maybe you run a shop for selling smartphones and you want people typing "iphone", "i-phone" or even "ephone", "ifone", or "iphnoe" to get the latest "iPhone" offers.
A simple synonym like solution is to use the searchwords extension which is provided by collective.solr. It is a schemaextender for all types and allows to specify terms which are boosted by factor 1000 in the default search query. For "real" synonyms implemented in Solr you can use the SynonymGraphFilterFactory:
<fieldType name="text" class="solr.TextField" positionIncrementGap="100"> [...] <analyzer type="index"> <filter class="solr.SynonymGraphFilterFactory" synonyms="synonyms.txt" ignoreCase="true" expand="true"/> [...]
Note that the SynonymFilterFactory is an index filter and not a query filter.
#Explicit mappings match any token sequence on the LHS of "=>" #and replace with all alternatives on the RHS. These types of mappings #ignore the expand parameter in the schema. #Examples: ipod => i-pod, i pod => ipod, #Equivalent synonyms may be separated with commas and give no explicit mapping. # In this case the mapping behavior will be taken from the expand parameter in the schema. # This allows the same synonym file to be used in different synonym handling strategies. #Examples: ipod, i-pod, i pod foozball , foosball universe , cosmos # expand: (optional; default: true) If true, a synonym will be expanded to all # equivalent synonyms. If false, all equivalent synonyms will be reduced # to the first in the list. #multiple synonym mapping entries are merged. foo => foo bar foo => baz #is equivalent to foo => foo bar, baz
For a full list of index and query filter factories consult the Solr documentation:
Experiment with stemming, stop words and synonyms. Add your own values and see how Solr behaves.