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Merge pull request #1461 from rasahner/doc_queryFixes 

minor fixes to TimeseriesQuery and Aggregations
This commit is contained in:
Fangjin Yang 2015-06-24 08:12:09 -07:00
parent 8795792dba a938e65315
commit 9104d08a6a
2 changed files with 4 additions and 4 deletions
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6
docs/content/querying/aggregations.md
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@ -92,7 +92,7 @@ All JavaScript functions must return numerical values.
```json ```json
{ {
"type": "javascript", "type": "javascript",
"name": "sum(log(x)/y) + 10", "name": "sum(log(x)*y) + 10",
"fieldNames": ["x", "y"], "fieldNames": ["x", "y"],
"fnAggregate" : "function(current, a, b) { return current + (Math.log(a) * b); }", "fnAggregate" : "function(current, a, b) { return current + (Math.log(a) * b); }",
"fnCombine" : "function(partialA, partialB) { return partialA + partialB; }", "fnCombine" : "function(partialA, partialB) { return partialA + partialB; }",
@ -137,11 +137,11 @@ SELECT COUNT(DISTINCT(value)) FROM (
#### Cardinality by row #### 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 This is equivalent to something akin to
```sql ```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** **Example**

2
docs/content/querying/timeseriesquery.md
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@ -56,7 +56,7 @@ There are 7 main parts to a timeseries query:
|postAggregations|See [Post Aggregations](../querying/post-aggregations.html)|no| |postAggregations|See [Post Aggregations](../querying/post-aggregations.html)|no|
|context|See [Context](../querying/query-context.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 ```json
[ [