The approaches described in this section are approaches that could be pursued, but not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section.
Database Systems
A database management system (DBMS) manages a database. A DBMS may comprise one or more database servers. A database comprises database data and a database dictionary that are stored on a persistent memory mechanism, such as a set of hard disks. Database data may be stored in one or more data containers. Each container contains records. The data within each record is organized into one or more fields. In relational DBMSs, the data containers are referred to as tables, the records are referred to as rows, and the fields are referred to as columns. In object-oriented databases, the data containers are referred to as object classes, the records are referred to as objects, and the fields are referred to as attributes. Other database architectures may use other terminology.
Users interact with a database server of a DBMS by submitting to the database server commands that cause the database server to perform operations on data stored in a database. A user may be one or more applications running on a client computer that interact with a database server. Multiple users may also be referred to herein collectively as a user.
A database command may be in the form of a database statement that conforms to a database language. A database language for expressing the database commands is the Structured Query Language (SQL). There are many different versions of SQL, some versions are standard and some proprietary, and there are a variety of extensions. Data definition language (“DDL”) commands are issued to a database server to create or configure database objects, such as tables, views, or complex data types. SQL/XML is a common extension of SQL used when manipulating XML data in an object-relational database.
A multi-node database management system is made up of interconnected nodes that share access to the same database. Typically, the nodes are interconnected via a network and share access, in varying degrees, to shared storage, e.g. shared access to a set of disk drives and data blocks stored thereon. The nodes in a multi-node database system may be in the form of a group of computers (e.g. work stations, personal computers) that are interconnected via a network. Alternately, the nodes may be the nodes of a grid, which is composed of nodes in the form of server blades interconnected with other server blades on a rack.
Each node in a multi-node database system hosts a database server. A server, such as a database server, is a combination of integrated software components and an allocation of computational resources, such as memory, a node, and processes on the node for executing the integrated software components on a processor, the combination of the software and computational resources being dedicated to performing a particular function on behalf of one or more clients.
Resources from multiple nodes in a multi-node database system can be allocated to running a particular database server's software. Each combination of the software and allocation of resources from a node is a server that is referred to herein as a “server instance” or “instance”. A database server may comprise multiple database instances, some or all of which are running on separate computers, including separate server blades.
Multitenant Architecture
A container is a collection of schemas, objects, and related structures in a multitenant container database (CDB) that appears logically to an application as a separate database. Within a CDB, each container has a unique ID and name. The root database and every pluggable database (PDB) is considered a container. PDBs isolate data and operations so that from the perspective of a user or application, each PDB appears as if it were a traditional non-CDB. Each PDB is defined by its own separate database dictionary. A database dictionary comprises metadata that defines database objects contained in a database. In effect, a database dictionary defines the totality of a database. Database objects include tables, table columns, and tablespaces. A tablespace is a set of one or more files that are used to store the data for various types of database objects, such as tables. If data for a database object is stored in a tablespace, a database dictionary maps a database object to one or more tablespaces that hold the data for that database object.
The root container, also called “the root”, is a collection of schemas, schema objects, and nonschema objects to which all PDBs within a particular CDB belong. Every CDB has one root which stores the system metadata required to manage all PDBs within the CDB. In some implementations, the root does not store “user” data but instead stores data that is common across the PDBs of the CDB, such as definitions for common users and roles, shared tables, code packages, and so forth. A PDB is a user-created set of schemas, objects, and related structures that appears logically to an application as a separate database. As a result, each PDB can potentially be used to store data related to a different application, such as one PDB being dedicated to hosting a human resources application and another PDB being dedicated to hosting a sales application. However, since shared resources are stored just once in the root database and linked to by the database dictionaries of the PDBs, duplication of data is avoided compared to hosting each application with a completely separate traditional database. Furthermore, since PDBs are essentially self-contained databases in their own right, PDBs can be easily transferred between different CDBs for upgrade or load balancing purposes.