Highlighting shouldn't fail when the field to highlight is absent.

PlainHighlighter fails with a NPE when the field to highlight is marked as
stored in the mapping but doesn't exist in a hit. This patch makes
FieldsVisitor.fields less error-prone by returning an empty list instead
of null when no matching stored field was found.

Closes #3109
Store _version as a numeric doc values field.

Doc values can be expected to be more compact than payloads and should provide
better flexibility since doc values formats can be picked on a per-field basis.
This patch:
 - makes _version stored as a numeric doc values field,
 - manages backwards compatibility: if a version is not found in doc values,
   then it will look into payloads,
 - uses background merges to upgrade old segments and move _version from
   payloads to doc values.

Closes #3103
add 0.90.2 version
Make it easier to get started with Eclipse.

This patch makes mvn eclipse:eclipse generate additional eclipse configuration
files so that Eclipse:
 - uses Java 1.6 compliance level,
 - truncates lines after 140 chars,
 - uses 4 spaces for indentation,
 - automatically adds a license header when creating a new class file,
 - organizes imports the same way as Intellij Idea (which makes sense I guess
   since most of the code bas has been written with Intellij, this will prevent
   from having large diffs due to the fact that the order of imports has
   changed).
term vector request
================================

Returns information and statistics on terms in the fields of a particular document as stored in the index.

        curl -XGET 'http://localhost:9200/twitter/tweet/1/_termvector?pretty=true'

Tree types of values can be requested: term information, term statistics and field statistics.
By default, all term information and field statistics are returned for all fields but no term statistics.

Optionally, you can specify the fields for which the information is retrieved either with a parameter in the url

	curl -XGET 'http://localhost:9200/twitter/tweet/1/_termvector?fields=text,...'

or adding by adding the requested fields in the request body (see example below).

Term information
-------------------------

- term frequency in the field (always returned)
- term positions ("positions" : true)
- start and end offsets ("offsets" : true)
- term payloads ("payloads" : true), as base64 encoded bytes

If the requested information wasn't stored in the index, it will be omitted without further warning.
See [mapping](http://www.elasticsearch.org/guide/reference/mapping/core-types/) on how to configure your index to store term vectors.

Term statistics
-------------------------

Setting "term_statistics" to "true" (default is "false") will return

- total term frequency (how often a term occurs in all documents)
- document frequency (the number of documents containing the current term)

By default these values are not returned since term statistics can have a serious performance impact.

Field statistics
-------------------------

Setting "field_statistics" to "false" (default is "true") will omit

- document count (how many documents contain this field)
- sum of document frequencies (the sum of document frequencies for all terms in this field)
- sum of total term frequencies (the sum of total term frequencies of each term in this field)

Behavior
-------------------------

The term and field statistics are not accurate. Deleted documents are not taken into account. The information is only retrieved for the shard the requested document resides in. The term and field statistics are therefore only useful as relative measures whereas the absolute numbers have no meaning in this context.

Example
-------------------------

First, we create an index that stores term vectors, payloads etc. :

    curl -s -XPUT 'http://localhost:9200/twitter/' -d '{
        "mappings": {
            "tweet": {
                "properties": {
                    "text": {
                                "type": "string",
                                "term_vector": "with_positions_offsets_payloads",
                                "store" : "yes",
                                "index_analyzer" : "fulltext_analyzer"
                         },
                     "fullname": {
                                "type": "string",
                                "term_vector": "with_positions_offsets_payloads",
                                "index_analyzer" : "fulltext_analyzer"
                         }
                 }
            }
        },
        "settings" : {
            "index" : {
                "number_of_shards" : 1,
                "number_of_replicas" : 0
            },
            "analysis": {
                    "analyzer": {
                        "fulltext_analyzer": {
                            "type": "custom",
                            "tokenizer": "whitespace",
                            "filter": [
                                "lowercase",
                                "type_as_payload"
                            ]
                        }
                    }
            }
         }
    }'

Second, we add some documents:

    curl -XPUT 'http://localhost:9200/twitter/tweet/1?pretty=true' -d '{
      "fullname" : "John Doe",
      "text" : "twitter test test test "

    }'

    curl -XPUT 'http://localhost:9200/twitter/tweet/2?pretty=true' -d '{
      "fullname" : "Jane Doe",
      "text" : "Another twitter test ..."

    }'

The following request returns all information and statistics for field "text" in document "1" (John Doe):

     curl -XGET 'http://localhost:9200/twitter/tweet/1/_termvector?pretty=true' -d '{
                    "fields" : ["text"],
                    "offsets" : true,
                    "payloads" : true,
                    "positions" : true,
                    "term_statistics" : true,
                    "field_statistics" : true
            }'
Equivalently, all parameters can be passed as URI parameters:
     curl -GET 'http://localhost:9200/twitter/tweet/1/_termvector?pretty=true&fields=text&offsets=true&payloads=true&positions=true&term_statistics=true&field_statistics=true'

Response:

     {
      "_index" : "twitter",
      "_type" : "tweet",
      "_id" : "1",
      "_version" : 1,
      "exists" : true,
      "term_vectors" : {
        "text" : {
          "field_statistics" : {
            "sum_doc_freq" : 6,
            "doc_count" : 2,
            "sum_ttf" : 8
          },
          "terms" : {
            "test" : {
              "doc_freq" : 2,
              "ttf" : 4,
              "term_freq" : 3,
              "pos" : [ 1, 2, 3 ],
              "start" : [ 8, 13, 18 ],
              "end" : [ 12, 17, 22 ],
              "payload" : [ "[64 32 39 79 5a 41 3d 3d]", "[64 32 39 79 5a 41 3d 3d]", "[64 32 39 79 5a 41 3d 3d]" ]
            },
            "twitter" : {
              "doc_freq" : 2,
              "ttf" : 2,
              "term_freq" : 1,
              "pos" : [ 0 ],
              "start" : [ 0 ],
              "end" : [ 7 ],
              "payload" : [ "[64 32 39 79 5a 41 3d 3d]" ]
            }
          }
        }
      }
    }

Further changes:
-------------------------

XContentBuilder
new method
public XContentBuilder field(XContentBuilderString name, int offset, int length, int... value)
to put an integer array.

IndicesAnalysisService
make token filter for saving payloads available in elasticsearch

AbstractFieldMapper/TypeParser
make term vector options string available and also fix the parsing of this string:
with_positions_payloads is actually allowed as can be seen in TermVectorsConsumerPerFields.

Closes #3114