minor fixes to TimeseriesQuery and Aggregations

swimfish09 · Jun 24, 2015 · a938e65 · a938e65
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diff --git a/docs/content/querying/aggregations.md b/docs/content/querying/aggregations.md
@@ -92,7 +92,7 @@ All JavaScript functions must return numerical values.
 ```json
 {
   "type": "javascript",
-  "name": "sum(log(x)/y) + 10",
+  "name": "sum(log(x)*y) + 10",
   "fieldNames": ["x", "y"],
   "fnAggregate" : "function(current, a, b)      { return current + (Math.log(a) * b); }",
   "fnCombine"   : "function(partialA, partialB) { return partialA + partialB; }",
@@ -137,11 +137,11 @@ SELECT COUNT(DISTINCT(value)) FROM (
 
 #### Cardinality by row
 
-When setting `byRow` to `true` it computes the cardinality by row, i.e. the cardinality of distinct dimension combinations
+When setting `byRow` to `true` it computes the cardinality by row, i.e. the cardinality of distinct dimension combinations.
 This is equivalent to something akin to
 
 ```sql
-SELECT COUNT(*) FROM ( SELECT DIM1, DIM2, DIM3 FROM <datasource> GROUP BY DIM1, DIM2, DIM3
+SELECT COUNT(*) FROM ( SELECT DIM1, DIM2, DIM3 FROM <datasource> GROUP BY DIM1, DIM2, DIM3 )
 ```
 
 **Example**

diff --git a/docs/content/querying/timeseriesquery.md b/docs/content/querying/timeseriesquery.md
@@ -56,7 +56,7 @@ There are 7 main parts to a timeseries query:
 |postAggregations|See [Post Aggregations](../querying/post-aggregations.html)|no|
 |context|See [Context](../querying/query-context.html)|no|
 
-To pull it all together, the above query would return 2 data points, one for each day between 2012-01-01 and 2012-01-03, from the "sample\_datasource" table. Each data point would be the (long) sum of sample\_fieldName1, the (double) sum of sample\_fieldName2 and the (double) the result of sample\_fieldName1 divided by sample\_fieldName2 for the filter set. The output looks like this:
+To pull it all together, the above query would return 2 data points, one for each day between 2012-01-01 and 2012-01-03, from the "sample\_datasource" table. Each data point would be the (long) sum of sample\_fieldName1, the (double) sum of sample\_fieldName2 and the (double) result of sample\_fieldName1 divided by sample\_fieldName2 for the filter set. The output looks like this:
 
 ```json
 [