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SOLR-7800: avg facet function should skip missing values 

git-svn-id: https://svn.apache.org/repos/asf/lucene/dev/trunk@1691430 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Yonik Seeley 2015-07-16 18:28:57 +00:00
parent e8a5ffbea3
commit 58ec4d8824
3 changed files with 13 additions and 5 deletions
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6
solr/CHANGES.txt
View File

@ -329,6 +329,12 @@ Other Changes
* SOLR-7703: Authentication plugin is now loaded using the RessourceLoader.
(Avi Digmi via Anshum Gupta)
* SOLR-7800: JSON Facet API: the avg() facet function now skips missing values
rather than treating them as a 0 value. The def() function can be used to
treat missing values as 0 if that is desired.
Example: facet:{ mean:"avg(def(myfield,0))" }
================== 5.2.1 ==================
Consult the LUCENE_CHANGES.txt file for additional, low level, changes in this release

4
solr/core/src/java/org/apache/solr/search/facet/SlotAcc.java
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@ -348,10 +348,12 @@ class AvgSlotAcc extends DoubleFuncSlotAcc {
@Override
public void collect(int doc, int slotNum) {
double val = values.doubleVal(doc); // todo: worth trying to share this value across multiple stats that need it?
double val = values.doubleVal(doc);
if (val != 0 || values.exists(doc)) {
result[slotNum] += val;
counts[slotNum] += 1;
}
}
private double avg(double tot, int count) {
return count==0 ? 0 : tot/count; // returns 0 instead of NaN.. todo - make configurable? if NaN, we need to handle comparisons though...

4
solr/core/src/test/org/apache/solr/search/facet/TestJsonFacets.java
View File

@ -737,13 +737,13 @@ public class TestJsonFacets extends SolrTestCaseHS {
// stats at top level
client.testJQ(params(p, "q", "*:*"
, "json.facet", "{ sum1:'sum(${num_d})', sumsq1:'sumsq(${num_d})', avg1:'avg(${num_d})', min1:'min(${num_d})', max1:'max(${num_d})'" +
, "json.facet", "{ sum1:'sum(${num_d})', sumsq1:'sumsq(${num_d})', avg1:'avg(${num_d})', avg2:'avg(def(${num_d},0))', min1:'min(${num_d})', max1:'max(${num_d})'" +
", numwhere:'unique(${where_s})', unique_num_i:'unique(${num_i})', unique_num_d:'unique(${num_d})', unique_date:'unique(${date})'" +
", where_hll:'hll(${where_s})', hll_num_i:'hll(${num_i})', hll_num_d:'hll(${num_d})', hll_date:'hll(${date})'" +
", med:'percentile(${num_d},50)', perc:'percentile(${num_d},0,50.0,100)' }"
)
, "facets=={ 'count':6, " +
"sum1:3.0, sumsq1:247.0, avg1:0.5, min1:-9.0, max1:11.0" +
"sum1:3.0, sumsq1:247.0, avg1:0.6, avg2:0.5, min1:-9.0, max1:11.0" +
", numwhere:2, unique_num_i:4, unique_num_d:5, unique_date:5" +
", where_hll:2, hll_num_i:4, hll_num_d:5, hll_date:5" +
", med:2.0, perc:[-9.0,2.0,11.0] }"