Reference for Big Data Service
This guide lists the predefined objects in Resource Analytics for Big Data Service. You can find information about views, entity relationships, subject areas, and sample queries.
Views
This section provides information about views within Resource Analytics Big Data Service and their columns, data types, keys, and the referred view and column names. The following views are available:
| Name | Description |
|---|---|
| BIG_DATA_API_KEY_DIM_V | This view stores information on API keys. |
| BIG_DATA_INSTANCE_DIM_V | This view stores information on clusters. |
| BIG_DATA_IDENTITY_CONFIGURATION_DIM_V | This view stores information on identity configurations. |
| BIG_DATA_METASTORE_CONFIGURATION_DIM_V | This view stores information on metastore configurations. |
| BIG_DATA_NODE_BACKUP_CONFIGURATION_DIM_V | This view stores information on NodeBackupConfigurations. |
| BIG_DATA_NODE_BACKUP_DIM_V | This view stores information on Node backups. |
| BIG_DATA_NODE_REPLACE_CONFIGURATION_DIM_V | This view stores information on NodeReplaceConfigurations. |
| BIG_DATA_RESOURCE_PRINCIPAL_CONFIGURATION_DIM_V | This view stores information on Resource Principal Session Tokens. |
| BIG_DATA_METASTORE_CONFIGURATION_FACT_V | Fact table for Big Data metastore configurations. |
The suffixes in the view names specify the view type:
- FACT_V: Fact
- DIM_V: Dimension
Relationship Diagram
This section provides diagrams that define the logical relationship of a fact table with different dimension tables.
The contents of each view and their relationships are listed in the following file: Big Data Service views.
This diagram shows the relationship of the Big Data Service fact view with different dimension views.

Relationships exist among dimensions. Dimensions can be joined directly to each other. These diagrams show the relationship between dimension views.






Sample Queries
Sample queries for Big Data Service.
SELECT
BDS_METASTORE_CONFIGURATION_ID,
DISPLAY_NAME,
COMPARTMENT_ID,
LIFECYCLE_STATE,
METASTORE_TYPE,
TIME_CREATED
FROM
OCIRA.BIG_DATA_METASTORE_CONFIGURATION_FACT_V
WHERE
LIFECYCLE_STATE = 'ACTIVE'
AND METASTORE_TYPE = 'EXTERNAL'SELECT
ID,
DISPLAY_NAME,
COMPARTMENT_ID,
LIFECYCLE_STATE,
TIME_CREATED
FROM
OCIRA.BIG_DATA_INSTANCE_DIM_V
WHERE
LIFECYCLE_STATE IN ('ACTIVE','FAILED');SELECT
NB.ID AS BACKUP_ID,
NB.DISPLAY_NAME AS BACKUP_DISPLAY_NAME,
NB.BACKUP_TYPE AS BACKUP_TYPE,
NB.LIFECYCLE_STATE AS BACKUP_LIFECYCLE_STATE,
NB.TIME_CREATED AS BACKUP_TIME_CREATED,
NBC.ID AS CONFIG_ID,
NBC.DISPLAY_NAME AS CONFIG_DISPLAY_NAME,
NBC.BACKUP_TYPE AS CONFIG_BACKUP_TYPE,
NBC.SCHEDULE AS CONFIG_SCHEDULE
FROM
OCIRA.BIG_DATA_NODE_BACKUP_DIM_V NB
JOIN
OCIRA.BIG_DATA_NODE_BACKUP_CONFIGURATION_DIM_V NBC
ON
NB.OCIRA_NODE_BACKUP_CONFIG_KEY = NBC.OCIRA_CONFIGURATION_KEY
WHERE
NB.LIFECYCLE_STATE = 'ACTIVE';Data Lineage
The Customer Experience Semantic Model Lineage spreadsheet and Metric Calculation Logic spreadsheet for Big Data Service provides an end-to-end data lineage summary report for physical and logical relationships in your data.
For more information, see Data Lineage.
Subject Areas
This section provides information on the subject areas with data you maintain in Big Data Service. These subject areas, with their corresponding data, are available for you to use when creating and editing analyses and reports. The information for each subject area includes:
Description of the subject area.
Business questions that can be answered by data in the subject area, with a link to more detailed information about each business question.
Job-specific groups and duty roles that can be used to secure access to the subject area, with a link to more detailed information about each job role and duty role.
Primary navigation to the work area that's represented by the subject area.
Time reporting considerations in using the subject area, such as whether the subject area reports historical data or only the current data. Historical reporting refers to reporting on historical transactional data in a subject area. With a few exceptions, all dimensional data are current as of the primary transaction dates or system date.
The lowest grain of transactional data in a subject area. The lowest transactional data grain decides how data are joined in a report.
Special considerations, tips, and things to look out for in using the subject area to create analyses and reports.