[
https://issues.apache.org/jira/browse/SOLR-16291?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Dan Rosher updated SOLR-16291:
------------------------------
Description:
h2. Description
This is a Solr version of the Decay functions [available in
Elasticsearch|[https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-function-score-query.html|https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-function-score-query.html#function-decay]
]
To see how the functions work [see
here|https://www.desmos.com/calculator/a7i0bwz5ha]
Decay functions score a document with a function that decays depending on the
distance of a numeric field value of the document from a user given origin.
This is similar to a range query, but with smooth edges instead of boxes.
To use distance scoring on a query that has numerical fields, the user has to
define an origin and a scale for each field. The origin is needed to define the
“central point” from which the distance is calculated, and the scale to define
the rate of decay. The decay function is specified as
{code:java}
<decay_function>(<field-name>,scale,origin,offset,decay) for numerical/date
field
<decay_function>(<field-name>,scale,origin_lat,origin_lon,offset,decay) for geo
fields {code}
* <decay_function> should be one of 'linear', 'exp', or 'gauss'
* The <field-name> must be a NumericFieldType, DatePointField, or
LatLonPointSpatialField field, NOT multi-valued. e.g.
linear("location","23km",52.0247, -0.490,"0km",0.5)
In the above example, the field is a geo_point and origin can be provided in
geo format. scale and offset must be given with a unit in this case. If your
field is a date field, you can set scale and offset as days, hours, as with
DateMath.
e.g. gauss(pdate,"+2DAY+6HOUR","2021-07-20T00:00:00Z","+3DAY",0.5)
pdate: DatePointField "+2DAY+6HOUR": range "2021-07-20T00:00:00Z: origin
(defaults to NOW) "+3DAY: offset (defaults to zero) 0.5: decay{*}{*}
* *origin* The point of origin used for calculating distance. Must be given as
a number for numeric field, date for date fields and geo point for geo fields.
Required for geo and numeric field. For date fields the default is NOW. Date
math (for example NOW-1h) is supported for origin.
* *scale* Required for all types. Defines the distance from origin + offset at
which the computed score will equal decay parameter. For geo fields: Can be
defined as number+unit (1km, 12m,...). Default unit is KM. For date fields: Can
to be defined as a number+unit ("1h", "10d",…). For numeric field: Any number.
* *offset* If an offset is defined, the decay function will only compute the
decay function for documents with a distance greater than the defined offset.
The default is 0.
* *decay* The decay parameter defines how documents are scored at the distance
given at scale. If no decay is defined, documents at the distance scale will be
scored 0.5.
To get a feel for how these function work you can see [here on
desmos|https://www.desmos.com/calculator/a7i0bwz5ha] . Adjust origon, offset,
scale and decay to get a feel of how these parameters adjust the equation for
gauss, exp or linear.
h3. Supported decay functions
The DECAY_FUNCTION determines the shape of the decay:
*gauss* Normal decay, computed as:
score(doc) = exp(- (max(0,|doc.val - origin| - offset)^2)/2sig^2)
where sig is computed to assure that the score takes the value decay at
distance scale from origin+-offset
sig^2 = -scale^2/(2.ln(decay))
*exp* Exponential decay, computed as:
score(doc) = exp(lmda . max(0,|doc.val - origin| - offset))
lmda = ln(decay)/scale
where again the parameter lambda is computed to assure that the score takes the
value decay at distance scale from origin+-offset
*linear* Linear decay, computed as:
score(doc) = max((s-v)/s,0)
where: v = max(0,|doc.val - origin| - offset) s = scale(1.0-decay))
where again the parameter s is computed to assure that the score takes the
value decay at distance scale from origin+-offset
In contrast to the normal and exponential decay, this function actually sets
the score to 0 if the field value exceeds twice the user given scale value.
For single functions the three decay functions together with their parameters
can be visualized like this (the field in this example called "age"):
h3. Detailed example
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, Nancy, 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
origin 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 origin would be 0 Euros and the
scale depends on how much you are willing to pay, for example 20 Euros.
In this example, the fields might be called "price" for the price of the hotel
and "location" for the coordinates of this hotel.
The function for price in this case could be:
{noformat}
gauss("price",20,0) //or linear,exp {noformat}
and for location:
{noformat}
gauss("location","2km",11,12) //or linear,exp{noformat}
Suppose you want to multiply these two functions on the original score, the
request would look like this:
{noformat}
b=mul( gauss("price",20,0),gauss("location","2km",11,12))
&q={!boost b=$b v=$qq}
&qq={!edismax }*:*
&sort=score+desc
&fl=*,score{noformat}
Suppose your original search results matches three hotels :
* "Backback Nap"
* "Drink n Drive"
* "BnB Bellevue".
"Drink n Drive" is pretty far from your defined location (nearly 2 km) and is
not too cheap (about 13 Euros) so it gets a low factor a factor of 0.56.
"BnB Bellevue" and "Backback Nap" are both pretty close to the defined location
but "BnB Bellevue" is cheaper, so it gets a multiplier of 0.86 whereas
"Backpack Nap" gets a value of 0.66.
was:
h2. Description
This is a Solr version of the Decay functions [available in
Elasticsearch|[https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-function-score-query.html|https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-function-score-query.html#function-decay]
]
To see how the functions work [see
here|https://www.desmos.com/calculator/a7i0bwz5ha]
Decay functions score a document with a function that decays depending on the
distance of a numeric field value of the document from a user given origin.
This is similar to a range query, but with smooth edges instead of boxes.
To use distance scoring on a query that has numerical fields, the user has to
define an origin and a scale for each field. The origin is needed to define the
“central point” from which the distance is calculated, and the scale to define
the rate of decay. The decay function is specified as
{code:java}
<decay_function>(<field-name>,scale,origin,offset,decay) for numerical/date
field
<decay_function>(<field-name>,scale,origin_lat,origin_lon,offset,decay) for geo
fields {code}
* <decay_function> should be one of 'linear', 'exp', or 'gauss'
* The <field-name> must be a NumericFieldType, DatePointField, or
LatLonPointSpatialField field, NOT multi-valued. e.g.
linear("location","23km",52.0247, -0.490,"0km",0.5)
In the above example, the field is a geo_point and origin can be provided in
geo format. scale and offset must be given with a unit in this case. If your
field is a date field, you can set scale and offset as days, hours, as with
DateMath.
e.g. gauss(pdate,"+2DAY+6HOUR","2021-07-20T00:00:00Z","+3DAY",0.5)
pdate: DatePointField "+2DAY+6HOUR": range "2021-07-20T00:00:00Z: origin
(defaults to NOW) "+3DAY: offset (defaults to zero) 0.5: decay
* *origin* The point of origin used for calculating distance. Must be given
as a number for numeric field, date for date fields and geo point for geo
fields. Required for geo and numeric field. For date fields the default is NOW.
Date math (for example NOW-1h) is supported for origin.
* *scale* Required for all types. Defines the distance from origin + offset at
which the computed score will equal decay parameter. For geo fields: Can be
defined as number+unit (1km, 12m,...). Default unit is KM. For date fields: Can
to be defined as a number+unit ("1h", "10d",…). For numeric field: Any number.
* *offset* If an offset is defined, the decay function will only compute the
decay function for documents with a distance greater than the defined offset.
The default is 0.
* *decay* The decay parameter defines how documents are scored at the distance
given at scale. If no decay is defined, documents at the distance scale will be
scored 0.5.
To get a feel for how these function work you can see [here on
desmos|https://www.desmos.com/calculator/a7i0bwz5ha] . Adjust origon, offset,
scale and decay to get a feel of how these parameters adjust the equation for
gauss, exp or linear.
h3. Supported decay functions
The DECAY_FUNCTION determines the shape of the decay:
*gauss* Normal decay, computed as:
score(doc) = exp(- (max(0,|doc.val - origin| - offset)^2)/2sig^2)
where sig is computed to assure that the score takes the value decay at
distance scale from origin+-offset
sig^2 = -scale^2/(2.ln(decay))
*exp* Exponential decay, computed as:
score(doc) = exp(lmda . max(0,|doc.val - origin| - offset))
lmda = ln(decay)/scale
where again the parameter lambda is computed to assure that the score takes the
value decay at distance scale from origin+-offset
*linear* Linear decay, computed as:
score(doc) = max((s-v)/s,0)
where: v = max(0,|doc.val - origin| - offset) s = scale(1.0-decay))
where again the parameter s is computed to assure that the score takes the
value decay at distance scale from origin+-offset
In contrast to the normal and exponential decay, this function actually sets
the score to 0 if the field value exceeds twice the user given scale value.
For single functions the three decay functions together with their parameters
can be visualized like this (the field in this example called "age"):
h3. Detailed example
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, Nancy, 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
origin 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 origin would be 0 Euros and the
scale depends on how much you are willing to pay, for example 20 Euros.
In this example, the fields might be called "price" for the price of the hotel
and "location" for the coordinates of this hotel.
The function for price in this case could be:
{noformat}
gauss("price",20,0) //or linear,exp {noformat}
and for location:
{noformat}
gauss("location","2km",11,12) //or linear,exp{noformat}
Suppose you want to multiply these two functions on the original score, the
request would look like this:
{noformat}
b=mul( gauss("price",20,0),gauss("location","2km",11,12))
&q={!boost b=$b v=$qq}
&qq={!edismax }*:*
&sort=score+desc
&fl=*,score{noformat}
Suppose your original search results matches three hotels :
* "Backback Nap"
* "Drink n Drive"
* "BnB Bellevue".
"Drink n Drive" is pretty far from your defined location (nearly 2 km) and is
not too cheap (about 13 Euros) so it gets a low factor a factor of 0.56.
"BnB Bellevue" and "Backback Nap" are both pretty close to the defined location
but "BnB Bellevue" is cheaper, so it gets a multiplier of 0.86 whereas
"Backpack Nap" gets a value of 0.66.
> Decay function queries gauss,linear,exponential
> -----------------------------------------------
>
> Key: SOLR-16291
> URL: https://issues.apache.org/jira/browse/SOLR-16291
> Project: Solr
> Issue Type: Improvement
> Security Level: Public(Default Security Level. Issues are Public)
> Components: query parsers, search
> Affects Versions: 9.0
> Reporter: Dan Rosher
> Priority: Minor
> Time Spent: 10m
> Remaining Estimate: 0h
>
> h2. Description
> This is a Solr version of the Decay functions [available in
> Elasticsearch|[https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-function-score-query.html|https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl-function-score-query.html#function-decay]
> ]
> To see how the functions work [see
> here|https://www.desmos.com/calculator/a7i0bwz5ha]
> Decay functions score a document with a function that decays depending on the
> distance of a numeric field value of the document from a user given origin.
> This is similar to a range query, but with smooth edges instead of boxes.
> To use distance scoring on a query that has numerical fields, the user has to
> define an origin and a scale for each field. The origin is needed to define
> the “central point” from which the distance is calculated, and the scale to
> define the rate of decay. The decay function is specified as
>
> {code:java}
> <decay_function>(<field-name>,scale,origin,offset,decay) for numerical/date
> field
> <decay_function>(<field-name>,scale,origin_lat,origin_lon,offset,decay) for
> geo fields {code}
> * <decay_function> should be one of 'linear', 'exp', or 'gauss'
> * The <field-name> must be a NumericFieldType, DatePointField, or
> LatLonPointSpatialField field, NOT multi-valued. e.g.
> linear("location","23km",52.0247, -0.490,"0km",0.5)
> In the above example, the field is a geo_point and origin can be provided in
> geo format. scale and offset must be given with a unit in this case. If your
> field is a date field, you can set scale and offset as days, hours, as with
> DateMath.
>
> e.g. gauss(pdate,"+2DAY+6HOUR","2021-07-20T00:00:00Z","+3DAY",0.5)
>
> pdate: DatePointField "+2DAY+6HOUR": range "2021-07-20T00:00:00Z: origin
> (defaults to NOW) "+3DAY: offset (defaults to zero) 0.5: decay{*}{*}
>
> * *origin* The point of origin used for calculating distance. Must be given
> as a number for numeric field, date for date fields and geo point for geo
> fields. Required for geo and numeric field. For date fields the default is
> NOW. Date math (for example NOW-1h) is supported for origin.
> * *scale* Required for all types. Defines the distance from origin + offset
> at which the computed score will equal decay parameter. For geo fields: Can
> be defined as number+unit (1km, 12m,...). Default unit is KM. For date
> fields: Can to be defined as a number+unit ("1h", "10d",…). For numeric
> field: Any number.
> * *offset* If an offset is defined, the decay function will only compute the
> decay function for documents with a distance greater than the defined offset.
> The default is 0.
> * *decay* The decay parameter defines how documents are scored at the
> distance given at scale. If no decay is defined, documents at the distance
> scale will be scored 0.5.
>
> To get a feel for how these function work you can see [here on
> desmos|https://www.desmos.com/calculator/a7i0bwz5ha] . Adjust origon, offset,
> scale and decay to get a feel of how these parameters adjust the equation for
> gauss, exp or linear.
> h3. Supported decay functions
>
> The DECAY_FUNCTION determines the shape of the decay:
> *gauss* Normal decay, computed as:
> score(doc) = exp(- (max(0,|doc.val - origin| - offset)^2)/2sig^2)
> where sig is computed to assure that the score takes the value decay at
> distance scale from origin+-offset
> sig^2 = -scale^2/(2.ln(decay))
> *exp* Exponential decay, computed as:
> score(doc) = exp(lmda . max(0,|doc.val - origin| - offset))
> lmda = ln(decay)/scale
> where again the parameter lambda is computed to assure that the score takes
> the value decay at distance scale from origin+-offset
> *linear* Linear decay, computed as:
> score(doc) = max((s-v)/s,0)
> where: v = max(0,|doc.val - origin| - offset) s = scale(1.0-decay))
> where again the parameter s is computed to assure that the score takes the
> value decay at distance scale from origin+-offset
> In contrast to the normal and exponential decay, this function actually sets
> the score to 0 if the field value exceeds twice the user given scale value.
> For single functions the three decay functions together with their parameters
> can be visualized like this (the field in this example called "age"):
> h3. Detailed example
> 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, Nancy, 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 origin 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 origin would be 0 Euros and the
> scale depends on how much you are willing to pay, for example 20 Euros.
> In this example, the fields might be called "price" for the price of the
> hotel and "location" for the coordinates of this hotel.
> The function for price in this case could be:
> {noformat}
> gauss("price",20,0) //or linear,exp {noformat}
> and for location:
> {noformat}
> gauss("location","2km",11,12) //or linear,exp{noformat}
> Suppose you want to multiply these two functions on the original score, the
> request would look like this:
> {noformat}
> b=mul( gauss("price",20,0),gauss("location","2km",11,12))
> &q={!boost b=$b v=$qq}
> &qq={!edismax }*:*
> &sort=score+desc
> &fl=*,score{noformat}
> Suppose your original search results matches three hotels :
> * "Backback Nap"
> * "Drink n Drive"
> * "BnB Bellevue".
> "Drink n Drive" is pretty far from your defined location (nearly 2 km) and is
> not too cheap (about 13 Euros) so it gets a low factor a factor of 0.56.
> "BnB Bellevue" and "Backback Nap" are both pretty close to the defined
> location but "BnB Bellevue" is cheaper, so it gets a multiplier of 0.86
> whereas "Backpack Nap" gets a value of 0.66.
>
>
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