Unify custom scores
===================

The custom boost factor, custom script boost and the filters function query all do the same thing: They take a query and for each found document compute a new score based on the query score and some script, come custom boost factor or a combination of these two. However, the json format for these three functionalities is very different. This makes it hard to add new functions.

This commit introduces one keyword <code>function_score</code> for all three functions.

The new format can be used to either compute a new score with one function:

	"function_score": {
        "(query|filter)": {},
        "boost": "boost for the whole query",
        "function": {}
    }

or allow to combine the newly computed scores

    "function_score": {
        "(query|filter)": {},
        "boost": "boost for the whole query",
        "functions": [
            {
                "filter": {},
                "function": {}
            },
            {
                "function": {}
            }
        ],
        "score_mode": "(mult|max|...)"
    }

<code>function</code> here can be either

	"script_score": {
    	"lang": "lang",
    	"params": {
        	"param1": "value1",
        	"param2": "value2"
   		 },
    	"script": "some script"
	}

or

	"boost_factor" : number

New custom functions can be added via the function score module.

Changes
---------

The custom boost factor query

	"custom_boost_factor" : {
    	"query" : {
        	....
    	},
    	"boost_factor" : 5.2
	}

becomes

	"function_score" : {
    	"query" : {
        	....
    	},
    	"boost_factor" : 5.2
	}

The custom script score

	"custom_score" : {
    	"query" : {
        	....
	    },
    	"params" : {
        	"param1" : 2,
 	       	"param2" : 3.1
    	},
	    "script" : "_score * doc['my_numeric_field'].value / pow(param1, param2)"
	}

becomes

	"custom_score" : {
    	"query" : {
        	....
	    },
	    "script_score" : {

    		"params" : {
        		"param1" : 2,
 	       		"param2" : 3.1
    		},
	    	"script" : "_score * doc['my_numeric_field'].value / pow(param1, param2)"
	    }
	}

and the custom filters score query

    "custom_filters_score" : {
        "query" : {
            "match_all" : {}
       	 },
        "filters" : [
            {
                "filter" : { "range" : { "age" : {"from" : 0, "to" : 10} } },
                "boost" : "3"
            },
            {
                "filter" : { "range" : { "age" : {"from" : 10, "to" : 20} } },
                "script" : "_score * doc['my_numeric_field'].value / pow(param1, param2)"
            }
        ],
        "score_mode" : "first",
        "params" : {
        	"param1" : 2,
 	       	"param2" : 3.1
    	}
    	"score_mode" : "first"
    }

becomes:

    "function_score" : {
        "query" : {
            "match_all" : {}
       	},
        "functions" : [
            {
                "filter" : { "range" : { "age" : {"from" : 0, "to" : 10} } },
                "boost" : "3"
            },
            {
                "filter" : { "range" : { "age" : {"from" : 10, "to" : 20} } },
                "script_score" : {
                	"script" : "_score * doc['my_numeric_field'].value / pow(param1, param2)",
                	"params" : {
        				"param1" : 2,
 	       				"param2" : 3.1
    				}

            	}
            }
        ],
        "score_mode" : "first",
    }

Partially closes issue #3423
Distance scoring
================

It might sometimes be desirable to have a tool available that allows to multiply the original score for a document with a function that decays depending on the distance of a numeric field value of the document from a user given reference.

These functions could be computed for several numeric fields and eventually be combined as a sum or a product and multiplied on the score of the original query.

This commit adds new score functions similar to boost factor and custom script scoring, that can be used togeter with the <code>function_score</code> keyword in a query.

To use distance scoring, the user has to define

 1. a reference and
 2. a scale

for each field the function should be applied on. A reference is needed to define a distance for the document and a scale to define the rate of decay.

Example use case
----------------

Suppose you are searching for a hotel in a certain town. Your budget is limited. Also, you would like the hotel to be close to the town center, so the farther the hotel is from the desired location the less likely you are to check in.
You would like the query results that match your criterion (for example, "hotel, Berlin, non-smoker") to be scored with respect to distance to the town center and also the price.

Intuitively, you would like to define the town center as the origin and maybe you are willing to walk 2km to the town center from the hotel.
In this case your *reference* for the location field is the town center and the *scale* is ~2km.

If your budget is low, you would probably prefer something cheap above something expensive.
For the price field, the *reference* would be 0 Euros and the *scale* depends on how much you are willing to pay, for example 20 Euros.

Usage
----------------

The distance score functions can be applied in two ways:

In the most simple case, only one numeric field is to be evaluated. To do so, call <code>function_score</code>, with the appropriate function. In the above example, this might be:

    curl 'localhost:9200/hotels/_search/' -d '{
    "query": {
        "function_score": {
            "gauss": {
                "location": {
                    "reference": [
                        52.516272,
                        13.377722
                    ],
                    "scale": "2km"
                }
            },
            "query": {
                "bool": {
                    "must": {
                        "city": "Berlin"
                    }
                }
            }
        }
    }
    }'

which would then search for hotels in berlin with a balcony and weight them depending on how far they are from the Brandenburg Gate.

If you have more that one numeric field, you can combine them by defining a series of functions and filters, like, for example, this:

    curl 'localhost:9200/hotels/_search/' -d '{
    "query": {
        "function_score": {
            "functions": [
                {
                    "filter": {
                        "match_all": {}
                    },
                    "gauss": {
                        "location": {
                            "reference": "11,12",
                            "scale": "2km"
                        }
                    }
                },
                {
                    "filter": {
                        "match_all": {}
                    },
                    "linear": {
                        "price": {
                            "reference": "0",
                            "scale": "20"
                        }
                    }
                }
            ],
            "query": {
                "bool": {
                    "must": {
                        "city": "Berlin"
                    }
                }
            },
            "score_mode": "multiply"
        }
    }
    }'

This would effectively compute the decay function for "location" and "price" and multiply them onto the score. See <code> function_score</code> for the different options for combining functions.

Supported fields
----------------
Only single valued numeric fields, including time and geo locations, are be supported.

What is a field is missing?
----------------

Is the numeric field is missing in the document, that field will not be taken into account at all for this document. The function value for this field is set to 1 for this document. Suppose you have two hotels both of which are in Berlin and cost the same. If one of the documents does not have a "location", this document would get a higher score than the document having the "location" field set.

To avoid this, you could, for example, use the exists or the missing filter and add a custom boost factor to the functions.

      …
     "functions": [
        {
            "filter": {
                "match_all": {}
            },
            "gauss": {
                "location": {
                    "reference": "11, 12",
                    "scale": "2km"
                }
            }
        },
        {
            "filter": {
                "match_all": {}
            },
            "linear": {
                "price": {
                    "reference": "0",
                    "scale": "20"
                }
            }
        },
        {
            "boost_factor": 0.001,
            "filter": {
                "bool": {
                    "must_not": {
                        "missing": {
                            "existence": true,
                            "field": "coordinates",
                            "null_value": true
                        }
                    }
                }
            }
        }
    ],
    ...

Closes #3423
add assertion for cast double->float

ScoreFunction scoring might result in under or overflow, for example if a user
decides to use the timestamp as a boost in the script scorer. Therefore, check
if cast causes a huge precision loss. Note that this does not always detect
casting issues. For example in
ScriptFunction.score()
the function
SearchScript.runAsDouble()
is called. AbstractFloatSearchScript implements it as follows:
@Override     public double runAsDouble() {         return runAsFloat();     }
In this case the cast happens before the assertion and therfore precision
lossor over/underflows cannot be detected by the assertion.
Add highlighting support for suggester.

This commit adds general highlighting support to the suggest feature.
The only implementation that implements this functionality at this
point is the phrase suggester.
The API supports a 'pre_tag' and a 'post_tag' that are used
to wrap suggested parts of the given user input changed by the
suggester.

Closes #3442
added explicit creation of parent type in create index
Add binary protocol backwards compatibility for suggest highlights

This change requires different request processing on the binary protocol
level since it has been we provide compatibilty across minor version.
Yet, the suggest feature is still experimental but we try best effort
to make upgrades as seamless as possible.
Added `size` option to percolate api

The `size` option in the percolate api will limit the number of matches being returned:
 ```bash
 curl -XGET 'localhost:9200/my-index/my-type/_percolate' -d '{
    "size" : 10,
    "doc" : {...}
 }'
 ```
 In the above request no more than 10 matches will be returned. The `count` field will still return the total number of matches the document matched with.

 The `size` option is not applicable for the count percolate api.

 Closes #3440
added Lucene upgrade reminder
Improved filtering by _parent field

In the _parent field the type and id of the parent are stored as type#id, because of this a term filter on the _parent field with the parent id is always resolved to a terms filter with a type / id combination for each type in the mapping.

This can be improved by automatically use the most optimized filter (either term or terms) based on the number of parent types in the mapping.

Also added support to use the parent type in the term filter for the _parent field. Like this:
```json
{
   "term" : {
        "_parent" : "parent_type#1"
    }
}
```
This will then always automatically use the term filter.

Closes #3454
Return nothing instead of everything in MLT if no field is supported.

Today due the optimizations in the boolean query builder we adjust
a pure negative query with a 'match_all'. This is not the desired
behavior in the MLT API if all the fields in a document are unsupported.
If that happens today we return all documents but the one MLT is
executed on.

Closes #3453
Improved error message when the mapping document is malformed
Added tests for malformed mappings with no root object

This commit also makes the error message more consistent with
other exception messages in the DocumentMapperParser.
Added improvements for terms filter on _parent field similar to what has been for term filter.

Relates to #3454
improve effort into figuring out the shard associated with a search failure
Remove random empty string from test since it triggers a different exception
Assert on index delete in tests to ensure all indices are wiped even on disk
make sure we add the _uid as the first field in a doc
this will improve early termination loading times, but requires potential improvements in Lucene in terms of decompression
Simplified checks
Use DiscoveryModule instead of ClusterService to obtain local node id

The ClusterService might not see the latest cluster state and therefore
might not contain the local node id. Discovery will always see the local
node id since it's set on startup.
Catch RejectedExecutionException on node shutdown