Abstract: Techniques are disclosed for querying for members in multiple groups. A list of unique members in the multiple groups may be received in response to the query. An example methodology implementing the techniques may include generating a group contexts dictionary and a job stack. The group contexts dictionary may include group context objects, each group context object associated with a group within a domain. The job stack may include one or more group context hashset keys, wherein a group context hashset key identifies a group context object. The method may include retrieving one or more group context hashset keys from the job stack and, for each retrieved group context hashset key, traversing a group associated with a group context object identified by a group context hashset key to determine membership information of the group, and generating a list of unique members by removing duplicate entries in the membership information.

Abstract: An example methodology includes generating a dynamic Bloom filter. The dynamic Bloom filter may be generated based on a target false positive rate, a total number of elements to be inserted within a data structure of the dynamic Bloom filter, and at least one hash function. The total number of elements correspond to the number of first elements encoded in a data structure of an existing Bloom filter and a number of second elements to be added to the existing Bloom filter. The first elements may be inserted into the data structure of the dynamic Bloom filter by translating indexes with a bit having a first value in the data structure of the existing Bloom filter to the data structure of the dynamic Bloom filter. The second elements may be inserted into the data structure of the dynamic Bloom filter based on corresponding hash values.

Abstract: Techniques are disclosed for querying for members in multiple groups. A list of unique members in the multiple groups may be received in response to the query. An example methodology implementing the techniques may include generating a group contexts dictionary and a job stack. The group contexts dictionary may include group context objects, each group context object associated with a group within a domain. The job stack may include one or more group context hashset keys, wherein a group context hashset key identifies a group context object. The method may include retrieving one or more group context hashset keys from the job stack and, for each retrieved group context hashset key, traversing a group associated with a group context object identified by a group context hashset key to determine membership information of the group, and generating a list of unique members by removing duplicate entries in the membership information.