Merge pull request #434 from GuiSim/master

Small typo fixes in documentation

docs/content/Coordinator.md

@@ -20,7 +20,7 @@ io.druid.cli.Main server coordinator
 Rules
 -----
 
-Segments are loaded and dropped from the cluster based on a set of rules. Rules indicate how segments should be assigned to different historical node tiers and how many replicants of a segment should exist in each tier. Rules may also indicate when segments should be dropped entirely from the cluster. The coordinator loads a set of rules from the database. Rules may be specific to a certain datasource and/or a default set of rules can be configured. Rules are read in order and hence the ordering of rules is important. The coordinator will cycle through all available segments and match each segment with the first rule that applies. Each segment may only match a single rule
+Segments are loaded and dropped from the cluster based on a set of rules. Rules indicate how segments should be assigned to different historical node tiers and how many replicants of a segment should exist in each tier. Rules may also indicate when segments should be dropped entirely from the cluster. The coordinator loads a set of rules from the database. Rules may be specific to a certain datasource and/or a default set of rules can be configured. Rules are read in order and hence the ordering of rules is important. The coordinator will cycle through all available segments and match each segment with the first rule that applies. Each segment may only match a single rule.
 
 For more information on rules, see [Rule Configuration](Rule-Configuration.html).
 

docs/content/GroupByQuery.md

@@ -2,7 +2,7 @@
 layout: doc_page
 ---
 # groupBy Queries
-These types of queries take a groupBy query object and return an array of JSON objects where each object represents a grouping asked for by the query. Note: If you only want to do straight aggreagates for some time range, we highly recommend using [TimeseriesQueries](TimeseriesQuery.html) instead. The performance will be substantially better.
+These types of queries take a groupBy query object and return an array of JSON objects where each object represents a grouping asked for by the query. Note: If you only want to do straight aggregates for some time range, we highly recommend using [TimeseriesQueries](TimeseriesQuery.html) instead. The performance will be substantially better.
 An example groupBy query object is shown below:
 
 ``` json

docs/content/SearchQuery.md

@@ -37,7 +37,7 @@ There are several main parts to a search query:
 |intervals|A JSON Object representing ISO-8601 Intervals. This defines the time ranges to run the query over.|yes|
 |searchDimensions|The dimensions to run the search over. Excluding this means the search is run over all dimensions.|no|
 |query|See [SearchQuerySpec](SearchQuerySpec.html).|yes|
-|sort|How the results of the search should sorted. Two possible types here are "lexicographic" and "strlen".|yes|
+|sort|How the results of the search should be sorted. Two possible types here are "lexicographic" and "strlen".|yes|
 |context|An additional JSON Object which can be used to specify certain flags.|no|
 
 The format of the result is:

docs/content/SegmentMetadataQuery.md

@@ -15,7 +15,7 @@ Segment metadata queries return per segment information about:
 {
   "queryType":"segmentMetadata",
   "dataSource":"sample_datasource",
-  "intervals":["2013-01-01/2014-01-01"],
+  "intervals":["2013-01-01/2014-01-01"]
 }
 ```
 

docs/content/TopNQuery.md

@@ -9,6 +9,7 @@ TopN queries return a sorted set of results for the values in a given dimension
 A topN query object looks like:
 
 ```json
+{
   "queryType": "topN",
   "dataSource": "sample_data",
   "dimension": "sample_dim",