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Introduction Partial Index is an extremely powerful feature that allows the creation of an index on only a subset of a table's data, instead of indexing the entire table. This subset is defined by a filtering condition in a WHERE clause when creating the index. In essence, a Partial Index just adds a condition during index creation, so it can be used with all index types (such as B-Tree , Hash , GIN , GiST , ...) and supports all data types. Additionally, a Partial Index can also be used in combination with a Constraint , Expression Index and Composite Index . Advantages Space-saving: The index size is much smaller than a Full Index, which saves RAM and disk space. Increased Write performance (INSERT/UPDATE/DELETE): When adding or modifying data that does not satisfy the index condition, Postgres does not need to update the index tree. Disadvantages Queries must match the condition: The Postgres Query Planner only uses this index if the SELECT query has a WHERE clause that exactl...

Introduction Expression Index is an extremely powerful feature of PostgreSQL, which can be used for any data type (such as text, numbers, time, arrays and more) as long as the result of the expression returns a Deterministic value You can use Expression Index for all index types ( B-Tree , Hash , GIN , GiST and more) as long as the expression you write in the CREATE INDEX command returns a data type that the Index type supports for processing The nature of Expression Index is that instead of indexing on the original column value, Postgres precomputes the result of the function or expression as soon as you INSERT/UPDATE and saves the result directly into the Index file Characteristics After creating an Expression Index, when using a query, you must write it exactly like the expression in the Index, otherwise the index will not work Every time a row of data is modified, Postgres must run that function or expression to get the result to create the Index. Therefore, avoid using function...

Introduction In this article, we will continue exploring GIN Index with the JsonB data type. JsonB, short for JSON Binary, is a data type developed from the JSON data type and supported by PostgreSQL since version 9.2. The key difference between JSON and JsonB lies in how they are stored. JsonB supports binary storage and resolves the limitations of the JSON data type by optimizing the insert process and supporting indexing. Creating an Index When creating an index for a JsonB column, Postgres supports two strategies as follows: jsonb_ops : This is the default strategy that flattens the JSON to extract independent paths, keys and values to create Entries. For example, if you have a JSON like this: { "shop" : "ShopA" , "products" : [ { "product_name" : "mouse" , "price" : 50 } , { "product_name" : "keyboard" , "price" : 100 } ] } It will create a GIN Index as follows, n...