more sample testing (#136994)

* more sample testing

* more examples

* end of rest api examples

* final sample testing comments

* more sample snippet fixes

* fixing highlighting-examples

* additional fixes

* more example updaters

Author: georgewallace

docs/reference/aggregations/search-aggregations-bucket-adjacency-matrix-aggregation.md

@@ -87,9 +87,9 @@ The response contains buckets with document counts for each filter and combinati
   }
 }
 ```
-%  TESTRESPONSE[s/"took": 9/"took": $body.took/]
-%  TESTRESPONSE[s/"_shards": \.\.\./"_shards": $body._shards/]
-%  TESTRESPONSE[s/"hits": \.\.\./"hits": $body.hits/]
+% TESTRESPONSE[s/"took": 9/"took": $body.took/]
+% TESTRESPONSE[s/"_shards": \.\.\./"_shards": $body._shards/]
+% TESTRESPONSE[s/"hits": \.\.\./"hits": $body.hits/]
 
 ## Parameters [adjacency-matrix-agg-params]
 

docs/reference/aggregations/search-aggregations-bucket-datehistogram-aggregation.md

@@ -89,8 +89,8 @@ POST /sales/_search?size=0
   }
 }
 ```
-%  TEST[setup:sales]
-%  TEST[catch:bad_request]
+% TEST[setup:sales]
+% TEST[catch:bad_request]
 
 ```js
 {
@@ -172,8 +172,8 @@ POST /sales/_search?size=0
   }
 }
 ```
-%  TEST[setup:sales]
-%  TEST[catch:bad_request]
+% TEST[setup:sales]
+% TEST[catch:bad_request]
 
 ```js
 {

docs/reference/aggregations/search-aggregations-bucket-diversified-sampler-aggregation.md

@@ -80,8 +80,8 @@ Response:
   }
 }
 ```
-%  TESTRESPONSE[s/\.\.\./"took": $body.took,"timed_out": false,"_shards": $body._shards,"hits": $body.hits,/]
-%  TESTRESPONSE[s/2.213/$body.aggregations.my_unbiased_sample.keywords.buckets.0.score/]
+% TESTRESPONSE[s/\.\.\./"took": $body.took,"timed_out": false,"_shards": $body._shards,"hits": $body.hits,/]
+% TESTRESPONSE[s/2.213/$body.aggregations.my_unbiased_sample.keywords.buckets.0.score/]
 
 1. 151 documents were sampled in total.
 2. The results of the significant_terms aggregation are not skewed by any single author’s quirks because we asked for a maximum of one post from any one author in our sample.
@@ -158,9 +158,9 @@ Response:
   }
 }
 ```
-%  TESTRESPONSE[s/\.\.\./"took": $body.took,"timed_out": false,"_shards": $body._shards,"hits": $body.hits,/]
-%  TESTRESPONSE[s/2.213/$body.aggregations.my_unbiased_sample.keywords.buckets.0.score/]
-%  TESTRESPONSE[s/1.34/$body.aggregations.my_unbiased_sample.keywords.buckets.1.score/]
+% TESTRESPONSE[s/\.\.\./"took": $body.took,"timed_out": false,"_shards": $body._shards,"hits": $body.hits,/]
+% TESTRESPONSE[s/2.213/$body.aggregations.my_unbiased_sample.keywords.buckets.0.score/]
+% TESTRESPONSE[s/1.34/$body.aggregations.my_unbiased_sample.keywords.buckets.1.score/]
 
 ## shard_size [_shard_size]
 

docs/reference/aggregations/search-aggregations-bucket-filters-aggregation.md

@@ -62,9 +62,9 @@ Response:
   }
 }
 ```
-%  TESTRESPONSE[s/"took": 9/"took": $body.took/]
-%  TESTRESPONSE[s/"_shards": \.\.\./"_shards": $body._shards/]
-%  TESTRESPONSE[s/"hits": \.\.\./"hits": $body.hits/]
+% TESTRESPONSE[s/"took": 9/"took": $body.took/]
+% TESTRESPONSE[s/"_shards": \.\.\./"_shards": $body._shards/]
+% TESTRESPONSE[s/"hits": \.\.\./"hits": $body.hits/]
 
 ## Anonymous filters [anonymous-filters]
 
@@ -112,9 +112,9 @@ The filtered buckets are returned in the same order as provided in the request.
   }
 }
 ```
-%  TESTRESPONSE[s/"took": 4/"took": $body.took/]
-%  TESTRESPONSE[s/"_shards": \.\.\./"_shards": $body._shards/]
-%  TESTRESPONSE[s/"hits": \.\.\./"hits": $body.hits/]
+% TESTRESPONSE[s/"took": 4/"took": $body.took/]
+% TESTRESPONSE[s/"_shards": \.\.\./"_shards": $body._shards/]
+% TESTRESPONSE[s/"hits": \.\.\./"hits": $body.hits/]
 
 ## `Other` Bucket [other-bucket]
 
@@ -181,9 +181,9 @@ The response would be something like the following:
   }
 }
 ```
-%  TESTRESPONSE[s/"took": 3/"took": $body.took/]
-%  TESTRESPONSE[s/"_shards": \.\.\./"_shards": $body._shards/]
-%  TESTRESPONSE[s/"hits": \.\.\./"hits": $body.hits/]
+% TESTRESPONSE[s/"took": 3/"took": $body.took/]
+% TESTRESPONSE[s/"_shards": \.\.\./"_shards": $body._shards/]
+% TESTRESPONSE[s/"hits": \.\.\./"hits": $body.hits/]
 
 ## Non-keyed Response [non-keyed-response]
 

docs/reference/aggregations/search-aggregations-bucket-histogram-aggregation.md

@@ -375,7 +375,7 @@ The `histogram` aggregation will sum the counts of each interval computed based
   }
 }
 ```
-%  TESTRESPONSE[s/\.\.\./"took": $body.took,"timed_out": false,"_shards": $body._shards,"hits": $body.hits,/]
+% TESTRESPONSE[s/\.\.\./"took": $body.took,"timed_out": false,"_shards": $body._shards,"hits": $body.hits,/]
 
 ::::{important}
 Histogram aggregation is a bucket aggregation, which partitions documents into buckets rather than calculating metrics over fields like metrics aggregations do. Each bucket represents a collection of documents which sub-aggregations can run on. On the other hand, a histogram field is a pre-aggregated field representing multiple values inside a single field: buckets of numerical data and a count of items/documents for each bucket. This mismatch between the histogram aggregations expected input (expecting raw documents) and the histogram field (that provides summary information) limits the outcome of the aggregation to only the doc counts for each bucket.

docs/reference/aggregations/search-aggregations-bucket-nested-aggregation.md

@@ -86,8 +86,8 @@ GET /products/_search?size=0
   }
 }
 ```
-%  TEST[s/size=0/size=0&filter_path=aggregations/]
-%  TEST[continued]
+% TEST[s/size=0/size=0&filter_path=aggregations/]
+% TEST[continued]
 
 As you can see above, the nested aggregation requires the `path` of the nested documents within the top level documents. Then one can define any type of aggregation over these nested documents.
 
@@ -149,8 +149,8 @@ GET /products/_search?size=0
   }
 }
 ```
-%  TEST[s/size=0/size=0&filter_path=aggregations/]
-%  TEST[continued]
+% TEST[s/size=0/size=0&filter_path=aggregations/]
+% TEST[continued]
 
 The search returns:
 

docs/reference/aggregations/search-aggregations-bucket-range-aggregation.md

@@ -30,8 +30,8 @@ GET sales/_search
   }
 }
 ```
-%  TEST[setup:sales]
-%  TEST[s/_search/_search\?filter_path=aggregations/]
+% TEST[setup:sales]
+% TEST[s/_search/_search\?filter_path=aggregations/]
 
 Response:
 
@@ -88,8 +88,8 @@ GET sales/_search
   }
 }
 ```
-%  TEST[setup:sales]
-%  TEST[s/_search/_search\?filter_path=aggregations/]
+% TEST[setup:sales]
+% TEST[s/_search/_search\?filter_path=aggregations/]
 
 Response:
 
@@ -141,8 +141,8 @@ GET sales/_search
   }
 }
 ```
-%  TEST[setup:sales]
-%  TEST[s/_search/_search\?filter_path=aggregations/]
+% TEST[setup:sales]
+% TEST[s/_search/_search\?filter_path=aggregations/]
 
 Response:
 
@@ -208,8 +208,8 @@ GET sales/_search
   }
 }
 ```
-%  TEST[setup:sales]
-%  TEST[s/_search/_search\?filter_path=aggregations/]
+% TEST[setup:sales]
+% TEST[s/_search/_search\?filter_path=aggregations/]
 
 ## Sub Aggregations [_sub_aggregations_2]
 
@@ -239,8 +239,8 @@ GET sales/_search
   }
 }
 ```
-%  TEST[setup:sales]
-%  TEST[s/_search/_search\?filter_path=aggregations/]
+% TEST[setup:sales]
+% TEST[s/_search/_search\?filter_path=aggregations/]
 
 Response:
 

docs/reference/aggregations/search-aggregations-bucket-reverse-nested-aggregation.md

@@ -82,8 +82,8 @@ GET /issues/_search
   }
 }
 ```
-%  TEST[continued]
-%  TEST[s/_search/_search\?filter_path=aggregations/]
+% TEST[continued]
+% TEST[s/_search/_search\?filter_path=aggregations/]
 
 As you can see above, the `reverse_nested` aggregation is put in to a `nested` aggregation as this is the only place in the dsl where the `reverse_nested` aggregation can be used. Its sole purpose is to join back to a parent doc higher up in the nested structure.
 

docs/reference/aggregations/search-aggregations-bucket-sampler-aggregation.md

@@ -138,9 +138,9 @@ Response:
   }
 }
 ```
-%  TESTRESPONSE[s/\.\.\./"took": $body.took,"timed_out": false,"_shards": $body._shards,"hits": $body.hits,/]
-%  TESTRESPONSE[s/0.02777/$body.aggregations.low_quality_keywords.buckets.0.score/]
-%  TESTRESPONSE[s/0.0069/$body.aggregations.low_quality_keywords.buckets.2.score/]
+% TESTRESPONSE[s/\.\.\./"took": $body.took,"timed_out": false,"_shards": $body._shards,"hits": $body.hits,/]
+% TESTRESPONSE[s/0.02777/$body.aggregations.low_quality_keywords.buckets.0.score/]
+% TESTRESPONSE[s/0.0069/$body.aggregations.low_quality_keywords.buckets.2.score/]
 
 ## shard_size [_shard_size_2]
 

docs/reference/aggregations/search-aggregations-bucket-significantterms-aggregation.md

@@ -98,8 +98,8 @@ Response:
   }
 }
 ```
-%  TESTRESPONSE[s/\.\.\.//]
-%  TESTRESPONSE[s/: (0\.)?[0-9]+/: $body.$_path/]
+% TESTRESPONSE[s/\.\.\.//]
+% TESTRESPONSE[s/: (0\.)?[0-9]+/: $body.$_path/]
 
 When querying an index of all crimes from all police forces, what these results show is that the British Transport Police force stand out as a force dealing with a disproportionately large number of bicycle thefts. Ordinarily, bicycle thefts represent only 1% of crimes (66799/5064554) but for the British Transport Police, who handle crime on railways and stations, 7% of crimes (3640/47347) is a bike theft. This is a significant seven-fold increase in frequency and so this anomaly was highlighted as the top crime type.
 
@@ -182,9 +182,9 @@ Response:
   }
 }
 ```
-%  TESTRESPONSE[s/\.\.\.//]
-%  TESTRESPONSE[s/: (0\.)?[0-9]+/: $body.$_path/]
-%  TESTRESPONSE[s/: "[^"]*"/: $body.$_path/]
+% TESTRESPONSE[s/\.\.\.//]
+% TESTRESPONSE[s/: (0\.)?[0-9]+/: $body.$_path/]
+% TESTRESPONSE[s/: "[^"]*"/: $body.$_path/]
 
 Now we have anomaly detection for each of the police forces using a single request.