Term	Definition
PlinyCompute	a system for development of high-performance, data-intensive, distributed computing tools and libraries. Offering users a very high-level, declarative interface, relying on automatic, relational-database style optimization to figure out how to stage distributed computations.
Client Code	this is C++ user code that runs on a client machine (e.g. a personal computer or laptop) and is used to supply instructions to a PlinyCompute cluster. A connection to the manager node requires the following statement PDBClient pdbClient(8108, "localhost");, where the arguments correspond to the port and IP address of the manager node in the cluster, here is an example.
Node	a physical machine where an instance of plinyCompute runs. There are two types of nodes: manager and workers.
Manager	a node (machine) that runs manager services, only one manager is allowed in plinyCompute.
Worker	a node (machine) that runs worker services. It is possible to use one ore more workers in plinyCompute. This is determined by the content of the file conf/serverlist, which contains one IP address per line (each specifying a worker node in a cluster).
PlinyCompute Object Model	is an API for storing and manipulating objects, co-designed with PlinyCompte’s memory management system and execution engine to provide maximum performance. It is responsible for data layout and within-page memory management. All data processed by PlinyCompute are managed by the object model. Because all dynamic object allocation is in-place, directly on a page, there is no need for object serialization and de-serialization before data are transferred to/from storage or over a network. For more details, see the Object Model FAQ’s.
TCAP	(pronounced tee-cap) is a functional, domain-specific language that serves as an intermediate representation of user-supplied computations. It can then be used for optimizing queries and pipeline executions. From a logical stand point, TCAP operates over sets of columns of PlinyCompute Objects.
User-defined types	PlinyCompute allows users to create their own data types. Users have to defined these types in a shared library and register them in PlinyCompute using the PDBClient::registerType() function.
Lambdas in PlinyCompute	to write computations in PlinyCompute, programmers write various C++ codes using a domain-specific lambda calculus. A major difference with other analytics systems is that a programmer is not supplying a computation over input data, but rather an expression in the lambda calculus that specifies how to construct the computation. For example, to implement a SelectionComp over PC Objects of type DataPoint, a programmer must implement the lambda term construction function getSelection (Handle ) which returns a lambda term describing how DataPoint objects should be processed.
PlinyCompute Server Functionalities	a manager node in PlinyCompute offers the following server functionalities: Catalog manager, serving system meta-data (including the master copy of the mapping between type codes and PC Object types) and compiled, shared libraries for performing computations over PC Objects. Distributed storage manager, is the centralized server that manages PlinyCompute’s storage subsystem. TCAP optimizer, which is responsible for optimizing programs that have been compiled into PlinyCompute’s domain-specific TCAP language. Distributed query scheduler that is responsible for accepting optimized TCAP computations.
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