This is an automated email from the ASF dual-hosted git repository.
jbernste pushed a commit to branch branch_9_0
in repository https://gitbox.apache.org/repos/asf/solr.git
The following commit(s) were added to refs/heads/branch_9_0 by this push:
new f6b91d6 SOLR-14476: Ref guide update
f6b91d6 is described below
commit f6b91d6a4a2d348a2664a9b13b5d714bdee73154
Author: Joel Bernstein <[email protected]>
AuthorDate: Wed Jan 26 12:37:56 2022 -0500
SOLR-14476: Ref guide update
---
solr/solr-ref-guide/src/stream-source-reference.adoc | 10 +++++++---
1 file changed, 7 insertions(+), 3 deletions(-)
diff --git a/solr/solr-ref-guide/src/stream-source-reference.adoc
b/solr/solr-ref-guide/src/stream-source-reference.adoc
index 2363de0..b1169ce 100644
--- a/solr/solr-ref-guide/src/stream-source-reference.adoc
+++ b/solr/solr-ref-guide/src/stream-source-reference.adoc
@@ -214,7 +214,7 @@ This is incompatible with rows, offset and overfetch.
This value is applied to each dimension.
'-1' will fetch all the buckets.
* `metrics`: List of metrics to compute for the buckets.
-Currently supported metrics are `sum(col)`, `avg(col)`, `min(col)`,
`max(col)`, `count(*)`, `per(col, 50)`.
+Currently supported metrics are `sum(col)`, `avg(col)`, `min(col)`,
`max(col)`, `count(*)`,`countDist(col)`, `std(col)`, `per(col, 50)`.
The `per` metric calculates a percentile
for a numeric column and can be specified multiple times in the same facet
function.
* `tiered`: (Default true) Flag governing whether the `facet` stream should
parallelize JSON Facet requests to multiple Solr collections using a `plist`
expression; this option only applies if the `collection` is an alias backed by
multiple collections.
@@ -240,6 +240,7 @@ facet(collection1,
max(a_f),
avg(a_i),
avg(a_f),
+ std(a_f),
per(a_f, 50),
per(a_f, 75),
count(*))
@@ -265,6 +266,7 @@ facet(collection1,
max(a_f),
avg(a_i),
avg(a_f),
+ std(a_f),
per(a_f, 50),
per(a_f, 75),
count(*))
@@ -582,7 +584,7 @@ The stats function currently supports the following
metrics: `count(*)`, `sum()`
* `collection`: (Mandatory) Collection the stats will be aggregated from.
* `q`: (Mandatory) The query to build the aggregations from.
* `metrics`: (Mandatory) The metrics to include in the result tuple.
-Current supported metrics are `sum(col)`, `avg(col)`, `min(col)`, `max(col)`,
`count(*)`, `per(col, 50)`.
+Current supported metrics are `sum(col)`, `avg(col)`, `min(col)`, `max(col)`,
`count(*)`, `countDist(col)`, `std(col)`, `per(col, 50)`.
The `per` metric calculates a percentile
for a numeric column and can be specified multiple times in the same stats
function.
@@ -601,6 +603,7 @@ stats(collection1,
max(a_f),
avg(a_i),
avg(a_f),
+ std(a_f),
per(a_f, 50),
per(a_f, 75),
count(*))
@@ -625,7 +628,7 @@ JSON Facet API as its high performance aggregation engine.
* `format`: (Optional) Date template to format the date field in the output
tuples.
Formatting is performed by Java's SimpleDateFormat class.
* `metrics`: (Mandatory) The metrics to include in the result tuple.
-Current supported metrics are `sum(col)`, `avg(col)`, `min(col)`, `max(col)`,
`count(*)`, `per(col, 50)`.
+Current supported metrics are `sum(col)`, `avg(col)`, `min(col)`, `max(col)`,
`count(*)`, `countDist(col)`, `std(col)`, `per(col, 50)`.
The `per` metric calculates a percentile
for a numeric column and can be specified multiple times in the same
timeseries function.
@@ -648,6 +651,7 @@ timeseries(collection1,
max(a_f),
avg(a_i),
avg(a_f),
+ std(a_f),
per(a_f, 50),
per(a_f, 75),
count(*))
