A compute query executes a Pregel algorithm to determine information about the knowledge graph in parallel. Called within the Graql shell or dashboard, the general syntax is:
compute goal [in subgraph], (using [strategy] where [modifiers];)

goal
can be any of the available statistics
or graph queries.

subgraph
(optional) is a comma separated list of types to be visited by the Pregel algorithm.
Additionally, for graph queries

strategy
(optional) is actual algorithm used 
modifiers
(optional) are different depending on the specific query and algorithm.
The simplest query count
can be executed using the following:
compute count;
The following query compute the clusters, in the subgraph containing only person and marriage, using connected component, and return the members of each cluster.
compute cluster in [person, marriage], using connectedcomponent, where members=true;
Subgraph
The subgraph syntax is provided to control the types that a chosen algorithm operates upon.
By default, the compute methods include instances of every type in the calculation.
Using the in
keyword followed by a comma separated list of types will restrict the calculations to instances of those types only.
For example,
compute count in person;
will return just the number of instances of the concept type person.
Subgraphs can be applied to all compute queries and therefore are different to strategy
and modifiers
.
The specific compute queries fall into two main categories and more information is given in the sections below.
Available Statistics Methods
The following methods are available to perform simple statistics computations. A summary of the statistics algorithms is given in the table below.
Algorithm  Description 

count 
Count the number of instances. 
max 
Compute the maximum value of an attribute. 
min 
Compute the minimum value of an attribute. 
mean 
Compute the mean value of an attribute. 
median 
Compute the median value of an attribute. 
std 
Compute the standard deviation of an attribute. 
sum 
Compute the sum of an attribute. 
For further information see the statistics queries
.
Available Graph Queries
The following algorithms all compute values based on the structure of the graph. A summary of the graph algorithms is given in the table below.
Algorithm  Description 

cluster 
Find the clusters of instances. 
centrality 
Compute the centrality of each instance in the graph. 
path 
Find the shortest path(s) between two instances. 
For further information see the individual sections.