Accumulators are special types of variables that accumulate information about the graph during its traversal and exploration. Because they are a unique and important feature of the GSQL query language, we devote a separate section for their introduction, but additional detail on their usage will be covered in other sections, the "SELECT Statement" section in particular. This section covers the following subset of the EBNF language definitions:

There are a number of different types of accumulators, each providing specific accumulation functions. Accumulators are declared to have one of two types of association: global or vertex-attached .

More technically, accumulators are mutable mutex variables shared among all the graph computation threads exploring the graph within a given query. To improve performance, the graph processing engine employs multithreaded processing. Modification of accumulators is coordinated at run-time so the accumulation operator works correctly (i.e., mutually exclusively) across all threads. This is particularly relevant in the ACCUM clause. During traversal of the graph, the selected set of edges or vertices is partitioned among a group of threads. These threads have shared mutually exclusive access to the accumulators.

Declaration of Accumulators

All accumulator variables must be declared at the beginning of a query, immediately after any typedefs, and before any other type of statement. The scope of the accumulator variables is the entire query.

The name of a vertex-attached accumulator begins with a single "@". The name of a global accumulator begins with "@@". Additionally, a global accumulator may be declared to be static.

Vertex-attached Accumulators

Vertex-attached accumulators are mutable state variables that are attached to each vertex in the graph for the duration of the query's lifetime. They act as run-time attributes of a vertex. They are shared, mutual exclusively, among all of the query's processes. Vertex-attached accumulators can be set to a value with the = operator. Additionally, an accumulate operator += can be used to update the state of the accumulator; the function of += depends on the accumulator type. In the example below, there are two accumulators attached to each vertex. The initial value of an accumulator of a given type is predefined, however it can be changed at declaration as in the accumulator @weight below. All vertex-attached accumulator names have a single leading at-sign "@".

If there is a graph with 10 vertices, then there is an instance of @neighbors and @weight for each vertex (hence 10 of each, and 20 total accumulator instances). These are accessed via the dot operator on a vertex variable or a vertex alias (e.g., v.@neighbor ). The accumulator operator += only impacts the accumulator for the specific vertex being referenced. A statement such as v1.@neighbors += 1will only impact v1 's @neighbors and not the @neighbors for other vertices.

Vertex-attached accumulators can only be accessed or updated (via = or +=) in an ACCUM or POST-ACCUM clause within a SELECT block. The only exception to this rule is that vertex-attached accumulators can be referenced in a PRINT statement, as the PRINT has access to all information attached to a vertex set.

Global Accumulators

A global accumulator is a single mutable accumulator that can be accessed or updated within a query. The names of global accumulators start with a double at-sign "@@".

Global accumulators can only be assigned (using the = operator) outside a SELECT block (i.e., not within an ACCUM or POST-ACCUM clause). Global accumulators can be accessed or updated via the accumulate operator += anywhere within a query, including inside a SELECT block.

It is important to note that the accumulation operation for global accumulators in an ACCUM clause executes once for each process. That is, if the FROM clause uses an edge-induced selection (introduced in Section "SELECT Statement"), the ACCUM clause executes one process for each edge in the selected edge set. If the FROM clause uses a vertex-induced selection (introduced in Section "SELECT Statement"), the ACCUM clause executes one process for each vertex in the selected vertex set. Since global accumulators are shared in a mutually exclusive manner among processes, they behave very differently than a non-accumulator variable (see Section "Variable Types" for more details) in an ACCUM clause. Take the following code example. The global accumulator@@globalRelationshipCount is accumulated for every worksFor edge traversed since it is shared among processes. Conversely, relationshipCount appears to have only been incremented once. This is because a non-accumulator variable is not shared among processes. Each process has its own separate unshared copy of relationshipCount and increments the original value by one. (E.g., each process increments relationshipCount from 0 to 1.) There is no accumulation and the final value is one.

Static Global Accumulators

A static global accumulator retains its value after the execution of a query. To declare a static global accumulator, include the STATIC keyword at the beginning of the declaration statement. For example, if a static global accumulator is incremented by 1 each time a query is executed, then its value is equal to the number of times the query has been run, since the query was installed. Each static global accumulator belongs to the particular query in which it is declared; it cannot be shared among different queries. The value only persists in the context of running the same query multiple times. The value will reset to the default value when the GPE is restarted.

There is no command to deallocate a static global accumulator. If a static global accumulator is a collection accumulator and it no longer needed, it should be cleared to minimize the memory usage.

Accumulator Types

The following are the accumulator types we currently support. Each type of accumulator supports one or more data types .

The accumulators fall into two major groups :

  • Scalar Accumulators store a single value:

    • SumAccum

    • MinAccum, MaxAccum

    • AvgAccum

    • AndAccum, OrAccum

    • BitwiseAndAccum, BitwiseOrAccum

  • Collection Accumulators store a set of values:

    • ListAccum

    • SetAccum

    • BagAccum

    • MapAccum

    • ArrayAccum

    • HeapAccum

    • GroupByAccum

The details of each accumulator type are summarized in the table below. The Accumulation Operation column explains how the accumulator accumName is updated when the statement accumName += newVal is executed. Following the table are example queries for each accumulator type.

Table Ac1: Accumulator Types and Their Accumulation Behavior


The SumAccum type computes and stores the cumulative sum of numeric values or the cumulative concatenation of text values. The output of a SumAccum is a single numeric or string value. SumAccum variables operate on values of type INT , UINT, FLOAT, DOUBLE, or STRING only.

The += operator updates the accumulator's state. For INT, FLOAT, and DOUBLE types, += arg performs a numeric addition, while for the STRING value type += arg concatenates arg to the current value of the SumAccum.

MinAccum / MaxAccum

The MinAccum and MaxAccum types calculate and store the cumulative minimum or the cumulative maximum of a series of values. The output of a MinAccum or a MaxAccum is a single value of the type that was passed in. MinAccum and MaxAccum variables operate on values of type INT, UINT, FLOAT, DOUBLE, STRING, TUPLE, and VERTEX (with optional specific vertex type) only.

For MinAccum, += arg checks if the current value held is less than arg and stores the smaller of the two. MaxAccum behaves the same, with the exception that it checks for and stores the greater instead of the lesser of the two.

String minimum and maximum values are based on their UTF-8 codes, which is a multilingual superset of the ASCII codes. Within ASCII, a < z, uppercase is less than lowercase, and digits are less than alphabetic characters.

MinAccum and MaxAccum operating on VERTEX type have a special comparison. They do not compare vertex ids, but TigerGraph internal ids, which might not be in the same order as the external ids. Comparing internal ids is much faster, so MinAccum/MaxAccum<VERTEX> provide an efficient way to compare and select vertices. This is helpful for some graph algorithms that require the vertices to be numbered and sortable . For example, the following query returns one post from each person. The returned vertex is not necessarily the vertex with alphabetically largest id.

Tuple data types are treated as hierarchical structures, where the first field used for ordering is the leftmost one.


The AvgAccum type calculates and stores the cumulative mean of a series of numeric values. Internally, its state information includes the sum value of all inputs and a count of how many input values it has accumulated. The output is the mean value; the sum and the count values are not accessible to the user. The data type of a AvgAccum variable is not declared; all AvgAccum accumulators accept inputs of type INT, UINT, FLOAT, and DOUBLE. The output is always DOUBLE type.

The += arg operation updates the AvgAccum variable's state to be the mean of all the previous arguments along with the current argument; The = arg operation clears all the previously accumulated state and sets the new state to be arg with a count of one.

AndAccum / OrAccum

The AndAccum and OrAccum types calculate and store the cumulative result of a series of boolean operations. The output of an AndAccum or an OrAccum is a single boolean value (True or False). AndAccum and OrAccum variables operate on boolean values only. The data type does not need to be declared.

For AndAccum, += arg updates the state to be the logical AND between the current boolean state and arg . OrAccum behaves the same, with the exception that it stores the result of a logical OR operation.

BitwiseAndAccum / BitwiseOrAccum

The BitwiseAndAccum and BitwiseOrAccum types calculate and store the cumulative result of a series of bitwise boolean operations and store the resulting bit sequences. BitwiseAndAccum and BitwiseOrAccum operator on INT only. The data type does not need to be declared.

Fundamental for understanding and using bitwise operations is the knowledge that integers are stored in base-2 representation as a 64-bit sequence of 1s and 0s. "Bitwise" means that each bit is treated as a separate boolean value, with 1 representing true and 0 representing false. Hence, an integer is equivalent to a sequence of boolean values. Computing the Bitwise AND of two numbers A and B means to compute the bit sequence C where the j th bit of C, denoted C j , is equal to (A j AND B j ).

For BitwiseAndAccum, += arg updates the accumulator's state to be the Bitwise AND of the current state and arg . BitwiseOrAccum behaves the same, with the exception that it computes a Bitwise OR.


The ListAccum type maintains a sequential collection of elements. The output of a ListAccum is a list of values in the order the elements were added. The element type can be any base type, tuple, or STRING COMPRESS. Additionally, a ListAccum can contain a nested collection of type ListAccum. Nesting of ListAccums is limited to a depth of three.

The += arg operation appends arg to the end of the list. In this case, arg may be either a single element or another ListAccum.

ListAccum supports two additional operations:

  • @list1 + @list2 creates a new ListAccum, which contains the elements of @list1 followed by the elements of @list2. The two ListAccums must have identical data types.

  • @list1 * @list2 (STRING data only) generates a new list of strings consisting of all permutations of an element of the first list followed by an element of the second list.

ListAccum also supports the following class functions.


The SetAccum type maintains a collection of unique elements. The output of a SetAccum is a list of elements in arbitrary order. A SetAccum instance can contain values of one type. The element type can be any base type, tuple, or STRING COMPRESS.

For SetAccum, the += arg operation adds a non-duplicate element or set of elements to the set. If an element is already represented in the set, then the SetAccum state does not change.

SetAccum also can be used with the three canonical set operators: UNION, INTERSECT, and MINUS (see Section "Set/Bag Expression and Operators" for more details).

SetAccum also supports the following class functions.


The BagAccum type maintains a collection of elements with duplicated elements allowed. The output of a BagAccum is a list of elements in arbitrary order. A BagAccum instance can contain values of one type. The element type can be any base type, tuple, or STRING COMPRESS.

For BagAccum, the += arg operation adds an element or bag of elements to the bag.

BagAccum also supports the + operator:

  • @bag1 + @bag2 creates a new BagAccum, which contains the elements of @bag1 and the elements of @bag2. The two BagAccums must have identical data types.

BagAccum also supports the following class functions.


The MapAccum type maintains a collection of (key -> value) pairs. The output of a MapAccum is a set of key and value pairs in which the keys are unique.

The key type of a MapAccum can be all base types or tuples. If the key type is VERTEX, then only the vertex's id is stored and displayed.

The value type of a MapAccum can be all base types, tuples, or any type of accumulator, except for HeapAccum.

For MapAccum, the += (key->val) operation adds a key-value element to the collection if key is not yet used in the MapAccum. If the MapAccum already contains key , then val is accumulated to the current value, where the accumulation operation depends on the data type of val . (Strings would get concatenated, lists would be appended, numerical values would be added, etc.)

MapAccum also supports the + operator:

  • @map1 + @map2 creates a new MapAccum, which contains the (key,value) pairs of @map2 added to the (key,value) pairs of @map1. The two MapAccums must have identical data types.

MapAccum also supports the following class functions.


The ArrayAccum type maintains an array of accumulators. An array is a fixed-length sequence of elements, with direct access to elements by position. The ArrayAccum has these particular characteristics:

  • The elements are accumulators, not primitive or base data types. All accumulators, except HeapAccum, MapAccum, and GroupByAccum, can be used.

  • An ArrayAccum instance can be multidimensional. There is no limit to the number of dimensions.

  • The size can be set at run-time (dynamically).

  • There are operators which update the entire array efficiently.

When an ArrayAccum is declared, the instance name should be followed by a pair of brackets for each dimension. The brackets may either contain an integer constant to set the size of the array, or they may be empty. In that case, the size must be set with the reallocate function before the ArrayAccum can be used.

Because each element of an ArrayAccum itself is an accumulator, the operators =, +=, and + can be used in two contexts: accumulator-level and element-level.

Element-level operations

If @A is an ArrayAccum of length 6, then @A[0] and @A[5] refer to its first and last elements, respectively. Referring to an ArrayAccum element is like referring to an accumulator of that type. For example, given the following definitions:

then @@Sums[0], @@Sums[1], and @@Sums[2] each refer to an individual SumAccum<INT>, and @@Lists[0] and @@Lists[1] each refer to a ListAccum<STRING>, supporting all the operations for those accumulator and data types.

Accumulator-level operations

The operators =, +=, and + have special meanings when applied to an ArrayAccum as a whole. There operations efficiently update an entire ArrayAccum. All of the ArrayAccums must have the same element type.

ArrayAccum also supports the following class functions.


The HeapAccum type maintains a sorted collection of tuples and enforces a maximum number of tuples in the collection. The output of a HeapAccum is a sorted collection of tuple elements. The += arg operation adds a tuple to the collection in sorted order. If the HeapAccum is already at maximum capacity when the += operator is applied, then the tuple which is last in the sorted order is dropped from the HeapAccum. Sorting of tuples is performed on one or more defined tuple fields ordered either ascending or descending. Sorting precedence is performed based on defined tuple fields from left to right.

The declaration of a HeapAccum is more complex than for most other accumulators, because the user must define a custom tuple type, set the maximum capacity of the HeapAccum, and specify how the HeapAccum should be sorted. The declaration syntax is outlined in the figure below:

First, the HeapAccum declaration must be preceded by a TYPEDEF statement which defines the tuple type. At least one of the fields (field_1, ..., field_n) must be of a data type that can be sorted.

In the declaration of the HeapAccum itself, the keyword "HeapAccum" is followed by the tuple type in angle brackets < >. This is followed by a parenthesized list of two or more parameters. The first parameter is the maximum number of tuples that the HeapAccum may store. This parameter must be a positive integer. The subsequent parameters are a subset of the tuple's field, which are used as sort keys. The sort key hierarchy is from left to right, with the leftmost key being the primary sort key. The keywords ASC and DESC indicate Ascending (lowest value first) or Descending (highest value first) sort order. Ascending order is the default.

HeapAccum also supports the following class functions.


The GroupByAccum is compound accumulator, an accumulator of accumulators. At the top level, it is a MapAccum where both the key and the value can have multiple fields. Moreover, each of the value fields is an accumulator type.

In the EBNF above, the type terms form the key set, and the accumType terms form the map's value. Since they are accumulators, they perform a grouping. Like a MapAccum, if we try to store a (key->value) whose key has already been used, then the new value will accumulate to the data which is already stored. In this case, each field of the multiple-field value has its own accumulation function. One way to think about GroupByAccum is that each unique key is a group ID.

In GroupByAccum, the key types can be base type, tuple, or STRING COMPRESS. The accumulators are used for aggregating group values. Each accumulator type can be any type including HeapAccum. Each base type and each accumulator type must be followed an alias. Below is an example declaration.

To add new data to this GroupByAccum, the data should be formatted as (key1, key2 -> value1, value2) .

GroupByAccum also supports the following class functions.

Nested Accumulators

Certain collection accumulators may be nested. That is, an accumulator may contain a collection of elements where the elements themselves are accumulators. For example:

Only ListAccum, ArrayAccum, MapAccum, and GroupByAccum can contain other accumulators. However, not all combinations of collection accumulators are allowed. The following constraints apply:

  1. ListAccum: ListAccum is the only accumulator type which can be nested within ListAccum, up to a depth of 3:

2. MapAccum: All accumulator types, except for HeapAccum, can be nested within MapAccum as the value type. For example,

3. GroupByAccum: All accumulator types, except for HeapAccum, can be nested within GroupByAccum as the accumulator type. For example:

4. ArrayAccum: Unlike the other accumulators in this list, where nesting is optional, nesting is mandatory for ArrayAccum. See the ArrayAccum section above.

It is legal to define nested ListAccums to form a multi-dimensional array. Note the declaration statements and the nested [ bracket ] notation in the example below: