How To Dev

Introduction When performing a table join that compares multiple columns simultaneously (such as ON A.col1 = B.col1 AND A.col2 = B.col2), PostgreSQL will still use familiar algorithms like Hash Join, Merge Join or Nested Loop Join. However, the way these algorithms process multiple columns involves very distinctive strategies as follows. Hash Join This is usually the number one choice for Postgres when joining multiple columns on large tables. Instead of hashing each individual column, Postgres performs string concatenation to hash the combination of all those columns at the same time. Build Phase: Postgres takes the values of all participating join columns and groups them together (like combining value = col1 + col2 + col3), then inputs this entire combined string into the Hash Function to calculate the Hash Number to be placed into the Bucket. Probe Phase: Next, it also combines the corresponding columns of the remaining table to hash similarly and then compares it with the Hash Tabl...

Introduction A Composite Index is an index type that contains two or more columns on the same table. It includes the following characteristics A Composite Index can be created for a maximum of 32 columns This is the default configuration according to the INDEX_MAX_KEYS constant of Postgres In practice, you should not create an index with more than 3 to 4 columns because it increases the index size, slowing down INSERT/UPDATE/DELETE operations The column order is sorted ascendingly by default However, unlike a standard index where you can sort ascending or descending at will, when using a Composite Index, you can only sort the columns all ascending, all descending or in the exact order specified at creation time For example, when using ON table (c1, c2) (default is all ascending), then You can query ORDER BY c1 ASC, c2 ASC You can query ORDER BY c1 DESC, c2 DESC But the index will not work with the query ORDER BY c1 ASC, c2 DESC Operation Order When using a Composite Index, you must ...

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...