Grouping Reference
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Refer to the grouping guide for an introduction to Vespa's grouping feature.

Group query results using a custom expression (using the group clause):
- A numerical constant.
- A document attribute.
- A function over another expression (xorbit, md5, cat, xor, and, or, add, sub, mul, div, mod) or any other expression.
- The data type of an expression is resolved using best effort, similarly to how you expect common programming languages to resolve arithmetics of different data typed operands.
- The results of any expression are either scalar or single dimension arrays.
  - add(<array>) adds all elements together to produce a scalar.
  - add(<arrayA>, <arrayB>) adds each element together producing a new array whose size is max(|<arrayA>|, |<arrayB>|).
Groups can contain subgroups (by using each and group operations), and may be nested to any level.
Multiple sub-groupings or outputs can be created under the same group level, using multiple parallel each or all clauses, and each one may be labelled using the as(mylabel) construct.
Each level of grouping specifies a set of aggregates to collect for all documents that belong to that group (using the output operation):
- The documents in a group, retrieved using a specified summary class.
- The count of documents in a group.
- The sum, average, min, max, xor or standard deviation of an expression.
Each level of grouping may specify how to order its groups (using the order operation):
- Ordering can be done using any of the available aggregates.
- Multi-level grouping allows strict ordering where primary aggregates may be equal.
- Ordering is either ascending or descending, specified per level of ordering.
You may limit the number of groups returned for each level (using the max operation), returning only first n groups as specified by the order operation.
You may count the number of unique groups for a level using the count aggregator. Note that count operates independently of the max clause.
You may paginate through group- and hit-lists using the "continuations" query parameter.
You may group on multivalued attributes. Most grouping functions will just handle the elements of multivalued attributes separately, as if they were all individual values in separate documents.
The interpolatedlookup function will count elements in a sorted array that are less than an expression, with linear interpolation if the expression is between element values.

Select parameter language grammar

request    ::= group [ "where" "(" ( "true" | "$query" ) ")" ]
group      ::= ( "all" | "each") "(" operations ")" [ "as" "(" identifier ")" ]
operations ::= [ "group" "(" expression ")" ]
               ( ( "alias" "(" identifier "," expression ")" ) |
                 ( "max"   "(" number ")" ) |
                 ( "order" "(" expList | aggrList ")" ) |
                 ( "output" "(" aggrList ")" ) |
                 ( "precision" "(" number ")" ) )*
               group*
aggrList   ::= aggr ( "," aggr )*
aggr       ::= ( ( "count" "(" ")" ) |
                 ( "sum" "(" exp ")" ) |
                 ( "avg" "(" exp ")" ) |
                 ( "max" "(" exp ")" ) |
                 ( "min" "(" exp ")" ) |
                 ( "xor" "(" exp ")" ) |
                 ( "stddev" "(" exp ")" ) |
                 ( "summary" "(" [ identifier ] ")" ) )
               [ "as" "(" identifier ")" ]
expList    ::= exp ( "," exp )*
exp        ::= ( "+" | "-") ( "$" identifier [ "=" math ] ) | ( math ) | ( aggr )
math       ::= value [ ( "+" | "-" | "*" | "/" | "%" ) value ]
value      ::= ( "(" exp ")" ) |
               ( "add" "(" expList ")" ) |
               ( "and" "(" expList ")" ) |
               ( "cat" "(" expList ")" ) |
               ( "div" "(" expList ")" ) |
               ( "docidnsspecific" "(" ")" ) |
               ( "fixedwidth" "(" exp "," number ")" ) |
               ( "interpolatedlookup" "(" attributeName "," exp ")") |
               ( "math" "." (
                              (
                                "exp" | "log" | "log1p" | "log10" | "sqrt" | "cbrt" |
                                "sin" | "cos" | "tan" | "asin" | "acos" | "atan" |
                                "sinh" | "cosh" | "tanh" | "asinh" | "acosh" | "atanh"
                              ) "(" exp ")" |
                              ( "pow" | "hypot" ) "(" exp "," exp ")"
                            )) |
               ( "max" "(" expList ")" ) |
               ( "md5" "(" exp "," number "," number ")" ) |
               ( "min" "(" expList ")" ) |
               ( "mod" "(" expList ")" ) |
               ( "mul" "(" expList ")" ) |
               ( "or" "(" expList ")" ) |
               ( "predefined" "(" exp "," "(" bucket ( "," bucket )* ")" ")" ) |
               ( "reverse" "(" exp ")" ) |
               ( "relevance" "(" ")" ) |
               ( "sort" "(" exp ")" ) |
               ( "strcat" "(" expList ")" ) |
               ( "strlen" "(" exp ")" ) |
               ( "size" "(" exp")" ) |
               ( "sub" "(" expList ")" ) |
               ( "time" "." ( "year" | "monthofyear" | "dayofmonth" | "dayofyear" | "dayofweek" |
                              "hourofday" | "minuteofhour" | "secondofminute" ) "(" exp ")" ) |
               ( "todouble" "(" exp ")" ) |
               ( "tolong" "(" exp ")" ) |
               ( "tostring" "(" exp ")" ) |
               ( "toraw" "(" exp ")" ) |
               ( "uca" "(" exp "," string [ "," string ] ")" ) |
               ( "xor" "(" expList ")" ) |
               ( "xorbit" "(" exp "," number ")" ) |
               ( "ymum" "(" ")" ) |
               ( "zcurve" "." ( "x" | "y" ) "(" exp ")" ) |
               ( attributeName "." "at" "(" number ")") |
               ( attributeName )
bucket     ::= "bucket" ( "(" | "[" | "<" )
                        ( "-inf" | rawvalue | number | string )
                        [ "," ( "inf" | rawvalue | number | string ) ]
                        ( ")" | "]" | ">" )
rawvalue   ::= "{" ( ( string | number ) "," )* "}"

Output format

When grouping results, groups that contain outputs, group lists, and hit lists are generated. Group lists contain sub-groups, and hit lists contain hits that are part of the owning group.

The identity of a group is held by its id. Scalar identities such as long, double and string, are directly available from the id, whereas range identities used for bucket aggregation are separated into the sub-nodes from and to. Refer to the result format reference.

Continue parameter

Pagination of grouping results are managed by "continuations". These are opaque objects that can be combined and re-submitted using the "continuations" annotation on the grouping step of the query to move to the previous or next page in a result list.

All root groups contain a single "this" continuation. That continuation represents the current view, and if submitted as the sole continuation it will reproduce the exact same result as the one that contained it. Other named continuations are available in the result, and these can be appended to the "this" continuation to perform the corresponding pagination operation. E.g. the "next" continuation of a group list can be used to move to the next page of groups in that list.

Any number of continuations can be combined in a query, but the first must always be the "this" continuation. E.g. you may simultaneously move both to the next page of one list, and the previous page of another.

If more than one continuation object are provided for the same group- or hit-list, the one given last is the one that takes effect. This is because continuations are processed in the order given, and they replace whatever continuations they collide with.

If working programmatically with grouping, you will find the Continuation objects within RootGroup, GroupList and HitList result objects. These can then be added back into the continuation list of the GroupingRequest to paginate.

Here is an example of a query that provides a continuation to the grouping statement:

/search/?yql=select (…) | [{ 'continuations':['BGAAABEBCA'] }]all(…);

Labels

Lists created using the each keyword can be assigned a label using the construct each(...) as(mylabel). The outputs created by that each clause will be identified by this label.

Aggregators

Name	Description	Arguments	Result
Group list aggregators
count	Counts the number of unique groups (As produced by the `group` clause).	None	Long
Group aggregators
Name	Description	Arguments	Result
count	Increments a long counter everytime it is invoked.	None	Long
sum	Sums the argument over all selected documents.	Numeric	Numeric
avg	Computes the average over all selected documents.	Numeric	Numeric
min	Keeps the minimum value of selected documents.	Numeric	Numeric
max	Keeps the maximum value of selected documents.	Numeric	Numeric
xor	XOR the values (their least significant 64 bits) of all selected documents.	Any	Long
stddev	Computes the population standard deviation over all selected documents.	Numeric	Double
Hit aggregators
Name	Description	Arguments	Result
summary	Produces a summary of the requested summary class.	Name of summary class	Summary

When all arguments are numeric, the result type is resolved by looking at the argument types. If all arguments are longs, the result is an long, if at least one argument is a double, the result is a double.

When using order(), aggregators can also be used in expressions, in order to get increased control over group sorting. This does not work with expressions that takes attributes as an argument, unless the expression is enclosed within an aggregator.

Expressions

Name	Description	Arguments	Result
Arithmetic expressions
add	Add the arguments together.	Numeric+	Numeric
+	Add left and right argument.	Numeric, Numeric	Numeric
mul	Multiply the arguments together.	Numeric+	Numeric
*	Multiply left and right argument.	Numeric, Numeric	Numeric
sub	Subtract second argument from first, third from result, etc.	Numeric+	Numeric
-	Subtract right argument from left.	Numeric, Numeric	Numeric
div	Divide first argument by second, result by third, etc.	Numeric+	Numeric
/	Divide left argument by right.	Numeric, Numeric	Numeric
mod	Modulo first argument by second, result by third, etc.	Numeric+	Numeric
%	Modulo left argument by right.	Numeric, Numeric	Numeric
neg	Negate argument.	Numeric	Numeric
-	Negate right argument.	Numeric	Numeric
Bitwise expressions
Name	Description	Arguments	Result
and	AND the arguments in order.	Long+	Long
or	OR the arguments in order.	Long+	Long
xor	XOR the arguments in order.	Long+	Long
String expressions
Name	Description	Arguments	Result
strlen	Count the number of bytes in argument.	String	Long
strcat	Concatenate arguments in order.	String+	String
Type conversion expressions
Name	Description	Arguments	Result
todouble	Convert argument to double.	Any	Double
tolong	Convert argument to long.	Any	Long
tostring	Convert argument to string.	Any	String
toraw	Convert argument to raw.	Any	Raw
Raw data expressions
Name	Description	Arguments	Result
cat	Cat the binary representation of the arguments together.	Any+	Raw
md5	Does an md5 over the binary representation of the argument, and keeps the lowest 'width' bits.	Any, Numeric(width)	Raw
xorbit	Does an xor of 'width' bits over the binary representation of the argument. Width is rounded up to a multiple of 8.	Any, Numeric(width)	Raw
Accessor expressions
Name	Description	Arguments	Result
relevance	Return the computed rank of a document.	None	Double
docidnsspecific	Return the docid without namespace.	None	String
	Applies only to streaming mode.
ymum	Return the ymum part of docid.	None	Long
	Applies only to streaming search.
<attribute-name>	Return the value of the named attribute.	None	Any
Bucket expressions
Name	Description	Arguments	Result
fixedwidth	Maps the value of the first argument into consecutive buckets whose width equals the second argument.	Any, Numeric	NumericBucketList
predefined	Maps the value of the first argument into the given buckets.	Any, Bucket+	BucketList
Time expressions Use the query parameter "timezone" to set the timezone to use when running these expressions. E.g. `&timezone=GMT-1`. See Sun's documentation on TimeZone for format reference.
Name	Description	Arguments	Result
time.dayofmonth	Returns the day of month (1-31) for the given timestamp.	Long	Long
time.dayofweek	Returns the day of week (0-6) for the given timestamp, Monday being 0.	Long	Long
time.dayofyear	Returns the day of year (0-365) for the given timestamp.	Long	Long
time.hourofday	Returns the hour of day (0-23) for the given timestamp.	Long	Long
time.minuteofhour	Returns the minute of hour (0-59) for the given timestamp.	Long	Long
time.monthofyear	Returns the month of year (1-12) for the given timestamp.	Long	Long
time.secondofminute	Returns the second of minute (0-59) for the given timestamp.	Long	Long
time.year	Returns the full year (e.g. 2009) of the given timestamp.	Long	Long
List expressions
Name	Description	Arguments	Result
size	Return the number of elements in the argument if it is a list. If not return 1.	Any	Long
sort	Sort the elements in argument in ascending order if argument is a list If not it is a NOP.	Any	Any
reverse	Reverse the elements in the argument if argument is a list If not it is a NOP.	Any	Any
Other expressions
Name	Description	Arguments	Result
zcurve.x	Returns the X component of the given zcurve encoded 2d point. All fields of type "position" have an accompanying "<fieldName>_zcurve" attribute that can be decoded using this expression, e.g. `zcurve.x(foo_zcurve)`.	Long	Long
zcurve.y	Returns the Y component of the given zcurve encoded 2d point.	Long	Long
uca	Converts the attribute string using unicode collation algorithm, useful for sorting.	Any, Locale(String), Strength(String)	Raw
Single argument standard mathematical expressions These are the standard mathematical functions as found in the Java Math class.
Name	Description	Arguments	Result
math.exp		Double	Double
math.log		Double	Double
math.log1p		Double	Double
math.log10		Double	Double
math.sqrt		Double	Double
math.cbrt		Double	Double
math.sin		Double	Double
math.cos		Double	Double
math.tan		Double	Double
math.asin		Double	Double
math.acos		Double	Double
math.atan		Double	Double
math.sinh		Double	Double
math.cosh		Double	Double
math.tanh		Double	Double
math.asinh		Double	Double
math.acosh		Double	Double
math.atanh		Double	Double
Dual argument standard mathematical expressions We also implement a few other convenient expressions. One very nice for geometrical distance calculations.
Name	Description	Arguments	Result
math.pow	Return X^Y.	Double, Double	Double
math.hypot	Return length of hypotenuse given X and Y sqrt(X^2 + Y^2).	Double, Double	Double

Examples

TopN / Full corpus

Simple grouping where you count the number of documents in each group:

/search/?yql=select (…) | all(group(a) each(output(count())));

Two parallel groupings:

/search/?yql=select (…) | all(all(group(a) each(output(count())))
                              all(group(b) each(output(count()))));

Only the 1000 best hits will be grouped at each backend node. Lower accuracy, but higher speed:

/search/?yql=select (…) | all(max(1000) all(group(a) each(output(count()))));

In streaming search you may also group all searched documents by adding a where(true) clause:

/search/?yql=select (…) | all(group(a) each(output(count()))) where(true);

Selecting groups

Perform a modulo 5 operation before selecting the group you want:

/search/?yql=select (…) | all(group(a % 5) each(output(count())));

Perform a + b * c before selecting the group you want:

/search/?yql=select (…) | all(group(a + b * c) each(output(count())));

Grouping on maps

The following syntax can be used when grouping on map attribute fields. It creates a group for values whose keys match the specified key. The key can either be specified directly or indirectly via a key source attribute.

Direct key on a primitive map:

/search/?yql=select (…) | all(group(my_map{"my_key"}) each(output(count())));

Direct key on a map of struct:

/search/?yql=select (…) | all(group(my_map{"my_key"}.my_field) each(output(count())));

Indirect key via a key source attribute:

/search/?yql=select (…) | all(group(my_map{attribute(my_key_source)}) each(output(count())));

The key is retrieved from the key source attribute for each document. Note that the key source attribute must be single value and have the same data type as the key type of the map. Using a key source attribute is not supported for streaming search.

Locale aware sorting

Groups are sorted using locale aware sorting, with the default and primary strength values, respectively:

/search/?yql=select (…) | all(group(s) order(max(uca(s, "sv")))
                              each(output(count())));

/search/?yql=select (…) | all(group(s) order(max(uca(s, "sv", "PRIMARY")))
                              each(output(count())));

Ordering groups

Perform a modulo 5 operation before selecting the group you want. The groups are then ordered by their aggregated sum of attribute "b":

/search/?yql=select (…) | all(group(a % 5) order(sum(b))
                              each(output(count())));

Perform a + b * c before selecting the group you want. Ordering is given by the maximum value of attribute "d" in each group:

/search/?yql=select (…) | all(group(a + b * c) order(max(d))
                              each(output(count())));

Take the average relevance of the groups and multiply it with the number of groups to get a cumulative count:

/search/?yql=select (…) | all(group(a) order(avg(relevance()) * count())
                              each(output(count())));

You can not, however, directly reference an attribute in your order clause, as this:

/search/?yql=select (…) | all(group(a) order(attr * count())
                              each(output(count())));

But, you can do this:

/search/?yql=select (…) | all(group(a) order(max(attr) * count())
                              each(output(count())));

Collecting aggregates

Simple grouping where you count number of documents in each group and return the best hit in each group:

/search/?yql=select (…) |
             all(group(a) each(max(1) each(output(summary()))));

Also return the sum of attribute "b":

/search/?yql=select (…) |
             all(group(a) each(max(1) output(count(), sum(b))
                               each(output(summary()))));

Also return an xor of the 64 most significant bits of an md5 over the concatenation of attributes "a", "b" and "c":

/search/?yql=select (…) |
             all(group(a) each(max(1) output(count(), sum(b), xor(md5(cat(a, b, c), 64)))
                               each(output(summary()))));

Predefined buckets

Group on predefined buckets for raw attribute and use infinity to make sure the buckets cover the whole possible range:

/search/?yql=select (…) |
             all(group(predefined(r, bucket(-inf, {0, 'a', 3}), bucket({1, 'u', 4}, inf)))
                 each(output(count())));

Standard mathematical start and end specifiers may be used to define the width of a bucket. The "(" and ")" evaluates to "[" and ">" by default. Here, make a bucket that can only with one exact group, and use different width specifiers:

/search/?yql=select (…) |
             all(group(predefined(r, bucket[-inf, "bar">, bucket["bar"], bucket<"bar", inf]))
                 each(output(count())));

Grouping

Single level grouping on "a" attribute, returning at most 5 groups with full hit count as well as the 69 best hits.

/search/?yql=select (…) |
             all(group(a) max(5) each(max(69) output(count())
                 each(output(summary()))));

Two level grouping on "a" and "b" attribute:

/search/?yql=select (…) |
             all(group(a) max(5) each(output(count())
                 all(group(b) max(5) each(max(69) output(count())
                     each(output(summary()))))));

Three level grouping on "a", "b" and "c" attribute:

/search/?yql=select (…) |
             all(group(a) max(5) each(output(count())
                 all(group(b) max(5) each(output(count())
                     all(group(c) max(5) each(max(69) output(count())
                         each(output(summary()))))));

As above example, but also collect best hit in level 2:

/search/?yql=select (…) |
             all(group(a) max(5) each(output(count())
                 all(group(b) max(5) each(output(count())
                     all(max(1) each(output(summary())))
                     all(group(c) max(5) each(max(69) output(count())
                         each(output(summary()))))));

As above example, but also collect best hit in level 1:

/search/?yql=select (…) |
             all(group(a) max(5) each(output(count())
                 all(max(1) each(output(summary())))
                 all(group(b) max(5) each(output(count())
                     all(max(1) each(output(summary())))
                     all(group(c) max(5) each(max(69) output(count())
                         each(output(summary()))))));

As above example, but using different document summaries on each level:

/search/?yql=select (…) |
             all(group(a) max(5) each(output(count())
                 all(max(1) each(output(summary(complexsummary))))
                 all(group(b) max(5) each(output(count())
                     all(max(1) each(output(summary(simplesummary))))
                     all(group(c) max(5) each(max(69) output(count())
                         each(output(summary(fastsummary)))))));

Group on fixed width buckets for numeric attribute, then on "a" attribute, count hits in leaf nodes:

/search/?yql=select (…) |
             all(group(fixedwidth(n, 3)) each(group(a) max(2) each(output(count()))));

As above example, but limiting groups in level 1, and returning hits from level 2:

/search/?yql=select (…) |
             all(group(fixedwidth(n, 3)) max(5) each(group(a) max(2) each(output(count())
                 each(output(summary())))));

Deep grouping with counting and hit collection on all levels:

/search/?yql=select (…) |
             all(group(a) max(5) each(output(count())
                 all(max(1) each(output(summary())))
                 all(group(b) each(output(count())
                     all(max(1) each(output(summary())))
                     all(group(c) each(output(count())
                         all(max(1) each(output(summary())))))))));

Time aware grouping

Group by year:

/search/?yql=select (…) |
             all(group(time.year(a)) each(output(count())));

Group by year, then by month:

/search/?yql=select (…) |
             all(group(time.year(a)) each(output(count())
                 all(group(time.month(a)) each(output(count())))));

Group by year, then by month, then day, then by hour:

/search/?yql=select (…) |
             all(group(time.year(a)) each(output(count())
                 all(group(time.monthofyear(a)) each(output(count())
                     all(group(time.dayofmonth(a)) each(output(count())
                         all(group(time.hourofday(a)) each(output(count())))))))));

Groups today, yesterday, lastweek, and lastmonth using predefined aggregator, and groups each day within each of these separately:

/search/?yql=select (…) |
             all(group(predefined((now() - a) / (60 * 60 * 24),
                                  bucket(0,1), bucket(1,2),
                                  bucket(3,7), bucket(8,31))) each(output(count())
                 all(max(2) each(output(summary())))
                     all(group((now() - a) / (60 * 60 * 24)) each(output(count())
                         all(max(2) each(output(summary())))))));

Counting unique groups

The count aggregator can be applied on list of groups to determine the number of unique groups without having to explicitly retrieve all groups. Another use case for this aggregator is counting the number of unique instances matching a given expression.

The following query outputs the number of groups, which is equivalent to the number of unique values for attribute "a".

/search/?yql=select (…) |
             all(group(a) output(count()))

The following query outputs the number of unique string lengths for the attribute "name".

/search/?yql=select (…) |
             all(group(strlen(name)) output(count()))

The following query outputs the sum of the "b" attribute for each group in addition to the overall group count.

/search/?yql=select (…) |
             all(group(a) output(count()) each(output(sum(b))))

The max clause is used to restrict the number of groups returned. The query outputs the sum for the 3 best groups. The count clause outputs the actual number of groups (potentially >3).

/search/?yql=select (…) |
             all(group(a) max(3) output(count()) each(output(sum(b))))

The following query outputs the number of top level groups, and for the 10 best groups, outputs the number of unique values for attribute "b".

/search/?yql=select (…) |
             all(group(a) max(10) output(count()) each(group(b) output(count())))

Using the grouping session cache

When having multi-level grouping expressions, the search query is normally re-run for each level. The drawback of this is that if you have an expensive ranking function, the query will take more time than strictly necessary.

To avoid this, you can set the groupingSessionCache query flag. This causes the query and grouping expression to be performed only once.

However, the flag is only useful if the grouping expression does not have a order() clause. The drawback of using this flag is that when max() is specified in the grouping expression, it might cause inaccuracies in aggregated values such as count(). We therefore recommend that you test whether or not this is an issue for your queries, and (if it is an issue) adjust the precision parameter to still get correct counts.

Grouping of multivalue attributes

Some grouping operators may be used with multivalue attributes. Note that using a multivalued attribute (such as an array of doubles) in a grouping expression is likely to have a large, adverse impact on performance, particularly if the set of hits to be processed is large, since it means a large amount of data is streamed through the CPU. Such operations is therefore likely to hit a bottleneck on memory bandwidth.

Caveats

For streaming search, multi-value fields such as maps, arrays etc. can be used for grouping. However, using aggregation functions such as sum() on such fields can give misleading results. Assume a map from strings to integers, where the strings are some sort of key you wish to use for grouping. The following expression will provide the sum of the values for all keys:

/search/?yql=select (…) | all(group(mymap.key) each(output(sum(mymap.value))));

and not the sum of the values within each key, as one would expect. It is still, however, possible to run the following expression to get the sum of values within a specific key:

/search/?yql=select (…) | all(group(mymap{"foo"}) each(output(sum(mymap.value))));

This syntax is map-specific, it does NOT apply to weighted sets.

Using sum, max, etc on a multivalued attribute

Doing an operation such as output(sum(myarray)) will run the sum over each element value in each document. The result is the sum of sums of values. Similarly max(myarray) will yield the maximal element over all elements in all documents, and so on.

Array at: element access

The expression array.at(myarray, idx) will yield one value per document by evaluating the idx expression and using it as an index into the given array. The expression will be capped to the range [0, size(myarray)-1]. If it's larger than the array size you always get the last element, while if it's smaller than zero you always get the first element. This expression can then be used to build bigger expressions such as output(sum(array.at(myarray, 0))) which will sum the first element in the array of each document.

Interpolated lookup (BETA)

The operation interpolatedlookup(myarray, expr) is intended for generic graph/function lookup. The data in myarray should be numerical values sorted in ascending order. The operation will then scan from the start of the array to find the position where the element values become equal to (or greater than) the value of the expr lookup argument, and return the index of that position. When the lookup argument's value is between two consecutive array element values, the returned position will be a linear interpolation between their respective indexes. The return value is always in the range [0, size(myarray)-1] of the legal index values for an array.

Given an example where myarray is a sorted array of type array<double> in each document. The expression interpolatedlookup(myarray, 4.2) is now a per-document expression that first evaluates the lookup argument, here a constant expression 4.2, and then looks at the contents of myarray in the document. The scan starts at the first element and proceeds until it hits an element value greater than 4.2 in the array. This means that:

If the first element in the array is greater than 4.2, the expression returns 0.
If the first element in the array is exactly 4.2, the expression still returns 0.
If the first element in the array is 1.7 while the second element value is exactly 4.2, the expression return 1.0 – the index of the second element.
If all the elements in the array are less than 4.2, the last valid array index size(myarray)-1 is returned.
If the 5 first elements in the array have values smaller than the lookup argument, and the lookup argument is halfway between the fifth and sixth element, a value of 4.5 is returned – halfway between the array indexes of the fifth and sixth elements.
Similarly, if the elements in the array are {0, 1, 2, 4, 8} then passing a lookup argument of "5" would return 3.25 (linear interpolation between indexOf(4)==3 and indexOf(8)==4).

Use case: Impression counting

If you have the impression logs for a specific user, you can make a function that maps from rankscore to the number of impressions an advertisement would get. So you would have a table like this:

Score   Integer (# impressions for this user)
0.200   0
0.210   1
0.220   2
0.240   3
0.320   4
0.420   5
0.560   6
0.700   7
0.800   8
0.880   9
0.920  10
0.940  11
0.950  12

Storing just the first column (the rank scores, including a rank score for 0 impressions) in an array attribute named "impressions", we could then use the grouping operation interpolatedlookup(impressions, relevance()) to figure out how many times a given advertisement would have been shown to this particular user. So if the rankscore is 0.420 for a specific user/ad/bid combination, then interpolatedlookup(impressions,relevance()) would return 5.0. If the the bid is increased so the rankscore gets to 0.490 it would get 5.5 as the return value instead. In this context a count of 5.5 isn't meaningful for the past of a single user, but it gives more information that may be used as a forecast. Summing this across many different users may then be used to forecast the total of future impressions for the advertisement.

Grouping Reference edit page

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