Table: `ndb.entitysamples`#

Description#

No description available in database.

TODO: Expand this description with:

What data does this table store?
What is the business/research purpose?
How is this data collected or generated?
Are there any important caveats or data quality issues?

Table Structure#

Schema: ndb | Table Comment: No description available

Statistics#

Metric	Value
Row Count	123
Total Size	56 kB
Table Size	8192 bytes
Indexes Size	16 kB

Relationships#

Primary Key: entityid

Foreign Keys:

entityid → speleothems.entityid

Referenced By:

TODO: Document which tables reference this table (will be auto-detected in validation).

Data Dictionary#

Column	Type	Nullable	Default	Constraints
`entityid`	integer	✗	`-`	FOREIGN KEY, PRIMARY KEY
`organics`	boolean	✓	`-`	-
`fluid_inclusions`	boolean	✓	`-`	-
`mineralogy_petrology_fabric`	boolean	✓	`-`	-
`clumped_isotopes`	boolean	✓	`-`	-
`noble_gas_temperatures`	boolean	✓	`-`	-
`c14`	boolean	✓	`-`	-
`odl`	boolean	✓	`-`	-

TODO: Review column descriptions and add comments where missing.

Usage Examples#

Example 1: Basic Selection#

-- Get recent records from entitysamples
SELECT *
FROM ndb.entitysamples
ORDER BY entityid DESC
LIMIT 10;

Purpose: Retrieve the 10 most recent records from entitysamples

Example 2: Count Records#

-- Count total records
SELECT COUNT(*) as total_records
FROM ndb.entitysamples;

Purpose: Get the total number of records in entitysamples

Example 3: Join with speleothems#

-- Join with related table
SELECT 
    t1.*,
    t2.*
FROM ndb.entitysamples t1
INNER JOIN speleothems t2 
    ON t1.entityid = t2.entityid
LIMIT 100;

Purpose: Retrieve entitysamples records with related data from speleothems

Example 4: Aggregate Data#

-- Aggregate records by organics
SELECT 
    organics,
    COUNT(*) as count
FROM ndb.entitysamples
GROUP BY organics
ORDER BY count DESC
LIMIT 10;

Purpose: Count records grouped by organics

TODO: Add more specific examples relevant to common research questions or operational tasks.

Data Quality Notes#

TODO: Document:

Known data quality issues
Validation rules
Expected data ranges
Update frequency and mechanisms
Any ETL processes that populate this table

Maintenance#

Data Owner: TODO: Assign owner
Update Frequency: TODO: Document frequency
Last Major Schema Change: TODO: Document when schema last changed

Table: ndb.entitysamples#