The SELECT statement has countless unknown features which make loading data more effective.
ORDER BY with nullable columns
When ordering a nullable column the NULL values are sorted in a database-specific order.
But the sorting can be changed to an application-specific ordering.
For each loops with LATERAL Joins
A join can normally only link two static result sets together, but with LATERAL joins an efficient for-each loop with dependent subqueries can be used.
Cycle Detection for Recursive Search in Hierarchical Trees
Recursive queries searching within a hierarchical tree need to be protected for not failing on accidental loops in the data's references.
Fill Gaps in Statistical Time Series Results
Statistical calculations on a timeframe may have gaps due to missing that can be filled easily directly in the query.
Transactional Locking to Prevent Race Conditions
Race conditions are a common problem when updating rows but databases provide an easy-to-use locking solution.
Multiple Aggregates in One Query
One query can scan the data once and calculate multiple aggregates instead of executing multiple queries to do the same.
Modify existing data or insert new records with techniques going beyond standard CRUD operation.
UPDATE from SELECT
Update rows based on values of another table or the result of another query by combining an update with a join.
Delete Duplicate Rows
Duplicate rows can be easily found and deleted with a single query including a selection of which ones to keep.
RETURNING Modified Rows
Workflows fetching some rows, processing and updating them can be optimized by merging those multiple SQL statements into one.
Resolve bottlenecks and improve the performance of your application with some indexing magic not shared in tutorials.
Create specialized indexes for expressions like lower(email), because an index on email will not be used when the column in wrapped in a function call.
Changing the sorting direction for multi-column mixed-ordering indexes increases a query's performance by skipping the sorting operation.
Unique Indexes With Some Rows Excluded
Use partial indexes to ignore duplicated values of e.g. soft-deleted rows to create a unique index without duplicate value errors.
Ghost Conditions For Unindexed Columns
Artificial indexes added to queries can help the database to choose better indexes when a perfect one does not exist.
Make Indexes Invisible Before Deleting Them
Deleting an index is a high-risk operation. By changing its visibility first, you can limit the performance impact.
Simplify your database model with uncommon but very effective schema modeling approaches not taught in database classes.
The power of schema-full and schema-free data can be combined with JSON columns by copying ideas of NoSQL databases.
JSON schema validation
Schema-free JSON documents can be checked to comply with a defined to get a schema-full NoSQL JSON column.
Sorted Tables for Faster Range-Scans
Storing rows pre-sorted in tables instead of by insertion order will boost the performance for large databases significantly.
UUIDs to prevent Enumeration Attacks
Most applications are vulnerable to scrapers because of incrementing IDs. Retrofitting a UUID columns will solve the issue.
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