Fixed build errors.

060_Distributed_Search/10_Fetch_phase.asciidoc

@@ -58,6 +58,6 @@ after page until your servers crumble at the knees.
 
 If you _do_ need to fetch large numbers of docs from your cluster, you can
 do so efficiently by disabling sorting with the `scroll` query,
-which we discuss <<scan-scroll,later in this chapter>>.
+which we discuss <<scroll,later in this chapter>>.
 
 ****

070_Index_Mgmt/50_Reindexing.asciidoc

@@ -15,7 +15,7 @@ whole document available to you in Elasticsearch itself. You don't have to
 rebuild your index from the database, which is usually much slower.
 
 To reindex all of the documents from the old index efficiently,  use
-<<scan-scroll,_scroll_>> to retrieve batches((("using in reindexing documents"))) of documents from the old index,
+<<scroll,_scroll_>> to retrieve batches((("using in reindexing documents"))) of documents from the old index,
 and the <<bulk,`bulk` API>> to push them into the new index.
 
 .Reindexing in Batches

300_Aggregations/20_basic_example.asciidoc

@@ -49,9 +49,9 @@ using a simple aggregation.  We will do this using a `terms` bucket:
 GET /cars/transactions/_search
 {
     "size" : 0,
-    "aggs" : {
-        "popular_colors" : {
-            "terms" : {
+    "aggs" : { <1>
+        "popular_colors" : { <2>
+            "terms" : { <3>
               "field" : "color"
             }
         }
@@ -62,7 +62,7 @@ GET /cars/transactions/_search
 
 <1> Aggregations are placed under the ((("aggregations", "aggs parameter")))top-level `aggs` parameter (the longer `aggregations`
 will also work if you prefer that).
-<2> We then name the aggregation whatever we want: `colors`, in this example
+<2> We then name the aggregation whatever we want: `popular_colors`, in this example
 <3> Finally, we define a single bucket of type `terms`.
 
 Aggregations are executed in the context of search results,((("searching", "aggregations executed in context of search results"))) which means it is

400_Relationships/25_Concurrency.asciidoc

@@ -11,7 +11,7 @@ The more important issue is that, if the user were to change his name, all
 of his blog posts would need to be updated too. Fortunately, users don't
 often change names.  Even if they did, it is unlikely that a user would have
 written more than a few thousand blog posts, so updating blog posts with
-the <<scan-scroll,`scroll`>> and <<bulk,`bulk`>> APIs would take less than a
+the <<scroll,`scroll`>> and <<bulk,`bulk`>> APIs would take less than a
 second.
 
 However, let's consider a more complex scenario in which changes are common, far
@@ -182,7 +182,7 @@ PUT /fs/file/1?version=2 <1>
 We can even rename a directory, but this means updating all of the files that
 exist anywhere in the path hierarchy beneath that directory.  This may be
 quick or slow, depending on how many files need to be updated.  All we would
-need to do is to use <<scan-scroll,`scroll`>> to retrieve all the
+need to do is to use <<scroll,`scroll`>> to retrieve all the
 files, and the <<bulk,`bulk` API>> to update them.  The process isn't
 atomic, but all files will quickly move to their new home.
 

400_Relationships/26_Concurrency_solutions.asciidoc

@@ -166,7 +166,7 @@ PUT /fs/lock/_bulk
 --------------------------
 <1> The `refresh` call ensures that all `lock` documents are visible to
     the search request.
-<2> You can use a <<scan-scroll,`scroll`>> query when you need to retrieve large 
+<2> You can use a <<scroll,`scroll`>> query when you need to retrieve large 
 numbers of results with a single search request.
 
 Document-level locking enables fine-grained access control, but creating lock

410_Scaling/45_Index_per_timeframe.asciidoc

@@ -29,7 +29,7 @@ data.
 
 If we were to have one big index for documents of this type, we would soon run
 out of space. Logging events just keep on coming, without pause or
-interruption. We could delete the old events with a <<scan-scroll,`scroll`>> 
+interruption. We could delete the old events with a <<scroll,`scroll`>> 
 query and bulk delete,  but this approach is _very inefficient_.  When you delete a
 document, it is only _marked_ as deleted (see <<deletes-and-updates>>). It won't
 be physically deleted until the segment containing it is merged away.

410_Scaling/75_One_big_user.asciidoc

@@ -23,7 +23,7 @@ PUT /baking_v1
 ------------------------------
 
 The next step is to migrate the data from the shared index into the dedicated
-index, which can be done using a <<scan-scroll, `scroll`>> query and the
+index, which can be done using a <<scroll, `scroll`>> query and the
 <<bulk,`bulk` API>>.  As soon as the migration is finished, the index alias
 can be updated to point to the new index:
 

510_Deployment/40_config.asciidoc

@@ -1,3 +1,4 @@
+[[important-configuration-changes]]
 === Important Configuration Changes
 Elasticsearch ships with _very good_ defaults,((("deployment", "configuration changes, important")))((("configuration changes, important"))) especially when it comes to performance-
 related settings and options.  When in doubt, just leave