Documentation: Update example expressions to follow convention. (#7195)

Based out of conversation on #7193

Signed-off-by: Harold Dost <h.dost@criteo.com>

docs/configuration/recording_rules.md

@@ -62,7 +62,7 @@ groups:
   - name: example
     rules:
     - record: job:http_inprogress_requests:sum
-      expr: sum(http_inprogress_requests) by (job)
+      expr: sum by (job) (http_inprogress_requests)
 ```
 
 ### `<rule_group>`

docs/migration.md

@@ -88,7 +88,7 @@ An example of a recording rule and alert in the old format:
 
 ```
 job:request_duration_seconds:histogram_quantile99 =
-  histogram_quantile(0.99, sum(rate(request_duration_seconds_bucket[1m])) by (le, job))
+  histogram_quantile(0.99, sum by (le, job) (rate(request_duration_seconds_bucket[1m])))
 
 ALERT FrontendRequestLatency
   IF job:request_duration_seconds:histogram_quantile99{job="frontend"} > 0.1
@@ -105,8 +105,7 @@ groups:
 - name: example.rules
   rules:
   - record: job:request_duration_seconds:histogram_quantile99
-    expr: histogram_quantile(0.99, sum(rate(request_duration_seconds_bucket[1m]))
+    expr: histogram_quantile(0.99, sum by (le, job) (rate(request_duration_seconds_bucket[1m])))
-      BY (le, job))
   - alert: FrontendRequestLatency
     expr: job:request_duration_seconds:histogram_quantile99{job="frontend"} > 0.1
     for: 5m

docs/querying/api.md

@@ -523,7 +523,7 @@ $ curl http://localhost:9090/api/v1/rules
                     {
                         "health": "ok",
                         "name": "job:http_inprogress_requests:sum",
-                        "query": "sum(http_inprogress_requests) by (job)",
+                        "query": "sum by (job) (http_inprogress_requests)",
                         "type": "recording"
                     }
                 ],

docs/querying/functions.md

@@ -166,11 +166,11 @@ around the `rate()` function. Since the `le` label is required by
 `histogram_quantile()`, it has to be included in the `by` clause. The following
 expression aggregates the 90th percentile by `job`:
 
-    histogram_quantile(0.9, sum(rate(http_request_duration_seconds_bucket[10m])) by (job, le))
+    histogram_quantile(0.9, sum by (job, le) (rate(http_request_duration_seconds_bucket[10m])))
 
 To aggregate everything, specify only the `le` label:
 
-    histogram_quantile(0.9, sum(rate(http_request_duration_seconds_bucket[10m])) by (le))
+    histogram_quantile(0.9, sum by (le) (rate(http_request_duration_seconds_bucket[10m])))
 
 The `histogram_quantile()` function interpolates quantile values by
 assuming a linear distribution within a bucket. The highest bucket