Docs: Clean up for asciidoctor

docs/src/reference/asciidoc/core/configuration.adoc

@@ -554,12 +554,16 @@ added[2.1]
 
 added[2.2]
 `es.net.proxy.https.host`:: Https proxy host name
+
 added[2.2]
 `es.net.proxy.https.port`:: Https proxy port
+
 added[2.2]
 `es.net.proxy.https.user`:: Https proxy user name
+
 added[2.2]
 `es.net.proxy.https.pass`:: <<keystore,Securable>>. Https proxy password
+
 added[2.2]
 `es.net.proxy.https.use.system.props`(default yes):: Whether the use the system Https proxy properties (namely `https.proxyHost` and `https.proxyPort`) or not
 

docs/src/reference/asciidoc/core/pig.adoc

@@ -164,7 +164,7 @@ For example:
 [source,sql]
 ----
 STORE B INTO  '...' USING org.elasticsearch.hadoop.pig.EsStorage(
-	'es.mapping.names=date:@timestamp, uRL:url')         <1>
+    'es.mapping.names=date:@timestamp, uRL:url')         <1>
 ----
 
 <1> Pig column `date` mapped in {es} to `@timestamp`; Pig column `uRL` mapped in {es} to `url`

docs/src/reference/asciidoc/core/spark.adoc

@@ -294,7 +294,7 @@ saveToEs(javaRDD, "my-collection-{media_type}/doc");  <1>
 [[spark-write-meta]]
 ==== Handling document metadata
 
-{es} allows each document to have its own http://www.elasticsearch.org/guide/en/elasticsearch/guide/current/\_document\_metadata.html[metadata]. As explained above, through the various <<cfg-mapping, mapping>> options one can customize these parameters so that their values are extracted from their belonging document. Further more, one can even include/exclude what parts of the data are sent back to {es}. In Spark, {eh} extends this functionality allowing metadata to be supplied _outside_ the document itself through the use of http://spark.apache.org/docs/latest/programming-guide.html#working-with-key-value-pairs[_pair_ ++RDD++s].
+{es} allows each document to have its own {ref}/mapping-fields.html[metadata]. As explained above, through the various <<cfg-mapping, mapping>> options one can customize these parameters so that their values are extracted from their belonging document. Further more, one can even include/exclude what parts of the data are sent back to {es}. In Spark, {eh} extends this functionality allowing metadata to be supplied _outside_ the document itself through the use of http://spark.apache.org/docs/latest/programming-guide.html#working-with-key-value-pairs[_pair_ ++RDD++s].
 In other words, for ++RDD++s containing a key-value tuple, the metadata can be extracted from the key and the value used as the document source.
 
 The metadata is described through the +Metadata+ Java http://docs.oracle.com/javase/tutorial/java/javaOO/enum.html[enum] within +org.elasticsearch.spark.rdd+ package which identifies its type - +id+, +ttl+, +version+, etc...
@@ -922,7 +922,7 @@ jssc.start();
 [[spark-streaming-write-meta]]
 ==== Handling document metadata
 
-{es} allows each document to have its own http://www.elasticsearch.org/guide/en/elasticsearch/guide/current/\_document\_metadata.html[metadata]. As explained above, through the various <<cfg-mapping, mapping>> options one can customize these parameters so that their values are extracted from their belonging document. Further more, one can even include/exclude what parts of the data are sent back to {es}. In Spark, {eh} extends this functionality allowing metadata to be supplied _outside_ the document itself through the use of http://spark.apache.org/docs/latest/programming-guide.html#working-with-key-value-pairs[_pair_ ++RDD++s].
+{es} allows each document to have its own {ref}/mapping-fields.html[metadata]. As explained above, through the various <<cfg-mapping, mapping>> options one can customize these parameters so that their values are extracted from their belonging document. Further more, one can even include/exclude what parts of the data are sent back to {es}. In Spark, {eh} extends this functionality allowing metadata to be supplied _outside_ the document itself through the use of http://spark.apache.org/docs/latest/programming-guide.html#working-with-key-value-pairs[_pair_ ++RDD++s].
 
 This is no different in Spark Streaming. For ++DStreams++s containing a key-value tuple, the metadata can be extracted from the key and the value used as the document source.