The schema in a Analyzer detail view database consists of resource types, attribute definitions, and resource definitions.
The following diagram shows the components of the Analyzer detail view database.
The Analyzer detail view database is organized in dataset and data subsets that consist of scalar and time series data:
Attribute and resource definitions
Attribute and resource definitions together define the schema. The Analyzer detail view server contains the predefined schema, attribute definitions, and resource definitions. You can view this predefined schema using APIs; see Viewing the existing schema using REST APIs.
You can also view the existing schema in Schema Reference.xlsx provided with this document.
- Attribute definition Defines how the attribute is shown and consists of the following:
- ID A unique identifier for attribute definition within a given dataset; for example, name, ipAddress, and cpuUsage.
- Name Display name for the attribute definition.
- Type Type can be scalar or time series.
- Unit Specifies the unit in which the value is stored (percent, MBps, or KBps ). For more information, see Creating a custom resource definition.
- Attribute A property attached to a resource that provides more information about a resource. Two types of attributes are:
- Scalar attributes These attributes do not change frequently; for example, host name or IP address of a host, size of a storage volume.
- Timeseries attributes These attributes are expected to change frequently; for example, CPU usage of a host, number of IOPS occurring on a storage volume.
- Resource definition Defines how the resource is shown and consists of the following:
- Type A unique identifier for resource definition within a given dataset; for example, LHost represents a Linux Host, and LHostCPU represents the CPUs in a host.
- Scalar attributes Can exist on that resource; for example, name, ipAddress, capacity, and so on.
- Timeseries attributes Can exist on that resource; for example, cpuUsage, memUsage, readIOPS, and so on.
- Relations The relation between resources; for example, LHost is related to LHostCPU, and so on.
- Resource data Resource data consists of either scalar or timeseries data, or both in the
Analyzer detail view database. Each resource data instance is associated with a timestamp when it is captured. Resources are real-world entities, such as a host, CPU, storage volume, storage system, NIC card, and virtual machine.
- Scalar data The resource could have zero or more scalar attributes.
- Timeseries data The resource could have zero or more time series attributes.
Relations
Relations define resource hierarchies. A resource does not operate independently and is either dependent on another resource or contains more resources. For example, a VM is dependent on the host it runs, while the host contains a number of VMs running on it. Two resources are considered related if one resource depends on another resource or one resource contains the other resource.
Data subset
A data subset is a logical grouping of the resource data. For example, VMware data is associated with one data subset and NetApp data is associated with another data subset.
Dataset
Analyzer detail view and traditional relational database similarities
Relational database | Analyzer detail view database |
---|---|
Database | Dataset |
Table Name | Resource Type |
Table Definition | Resource Definition |
Table Column | Attribute Definition |
Table Row | Resource Data |
Primary Key | Each resource data has an implicit attribute called signature that automatically becomes a Primary Key. |
Foreign Key | Relations define hierarchies and are specified using signatures of other (related) resources. |
SQL | Uses MQL, specifically designed for operations on the Analyzer detail view database. For more information, see the Hitachi Ops Center Analyzer Detail View Query Language User Guide. |
JOIN | Sub-path traversal in MQL query. |
WHERE, GROUP BY, HAVING clauses | MQL supports almost all SQL constructs and offers a more expressive and powerful syntax for complex operations as well as filters that support regex-based filtering, aggregation, rollups, grouping, and so on. For more information, see the Hitachi Ops Center Analyzer Detail View Query Language User Guide. |