PostgreSQL多表合并与查询：点表、线表分表合并方法

Hey there! I’ve worked with plenty of split table scenarios like this, so let’s break down how to merge your point and line datasets into single, unified tables.

Merging Your Point Tables (ab_p1_point, ab_p2_point, ab_p3_point) #

You have two main approaches here, depending on whether you need to create a new table or add to an existing one:

Option 1: Create a new combined point table from scratch #

If you don’t already have a consolidated point table, use this SQL to create one and populate it with all data from the three splits:

CREATE TABLE ab_combined_point AS
SELECT * FROM ab_p1_point
UNION ALL
SELECT * FROM ab_p2_point
UNION ALL
SELECT * FROM ab_p3_point;

• Why UNION ALL instead of UNION? UNION automatically removes duplicate rows, but that adds extra processing overhead. Since your split tables should have non-overlapping data (or you want to retain all raw records), UNION ALL is faster and preserves all your data.
• Pro tip: If your split tables have slightly different column structures (unlikely, but possible), replace SELECT * with explicit column names (e.g., SELECT id, coord_x, coord_y, created_at FROM ...) to ensure alignment.

Option 2: Insert data into an existing point table #

If you already have a target table (ab_combined_point) with the same structure as your splits, use an INSERT statement to add all the split data:

INSERT INTO ab_combined_point
SELECT * FROM ab_p1_point
UNION ALL
SELECT * FROM ab_p2_point
UNION ALL
SELECT * FROM ab_p3_point;

Merging Your Line Tables (bc_p1_line, bc_p2_line, bc_p3_line) #

The process is identical to the point tables—just swap out the table names:

Option 1: Create a new combined line table #

CREATE TABLE bc_combined_line AS
SELECT * FROM bc_p1_line
UNION ALL
SELECT * FROM bc_p2_line
UNION ALL
SELECT * FROM bc_p3_line;

Option 2: Insert into an existing line table #

INSERT INTO bc_combined_line
SELECT * FROM bc_p1_line
UNION ALL
SELECT * FROM bc_p2_line
UNION ALL
SELECT * FROM bc_p3_line;

Key Things to Verify Before Merging #

• Table structure consistency: Make sure all split tables have matching column names, data types, and column order. Mismatches will throw errors during the merge.
• Performance considerations: If your tables are extremely large, consider adding indexes after merging (not during) to speed up future queries. Also, some databases let you batch inserts if you’re dealing with millions of rows.
• Regular syncs: If your split tables are updated regularly, you can turn these SQL statements into scheduled tasks (using your database’s event scheduler or external scripts like Python/Shell) to keep the consolidated table up to date.

内容的提问来源于stack exchange，提问作者Nawaz Sharif