Postgresql: INSERT INTO ... (SELECT * ...)

Going deeper: Advanced execution plans and performance fortification

Remote Table Data Heisting using dblink

When barging data from a remote database, Apache the dblink extension to soar through the data horizons. This extension allows you to take a sneak peek through a remote database window using a SELECT query, and then INSERT the unsuspected data into your local table—a thief in the night:

/* "Sweet dreams, remote_table, you won't feel a thing." */
INSERT INTO local_table
SELECT * FROM dblink('dbname=remote_db', 'SELECT * FROM remote_table')
AS stolen_data(column1 data_type1, column2 data_type2, ...);
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You ought to specify the column names along with their data types to match the target table structure—a perfect disguise.

Handling Gigantic Data Territories

Rather than gulping down mountains of data in one heroic gulp, bracing LIMIT and ORDER BY clauses can help tame the transfer titan:

/* "Let's take it slow, partner. Only 1000 rows at a time." */
INSERT INTO target_table
SELECT * FROM source_table
ORDER BY sort_column
LIMIT 1000;
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Data digestion can also seem lighter and faster to your database if you sort the data beforehand. So, remember to chew, not just swallow!

Complex Data Jigsaw using record pseudo-type

For complex data operations involving multiple tables or functions, PostgreSQL offers a record pseudo-type. It's like a puzzle box that can store pieces from every corner of your database:

/* "One for all, and all for one!" */
INSERT INTO target_table
SELECT (multi_table_function_returning_record).*
FROM source_table;
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Each row is treated accordion-style, capable of stretching and contracting to accommodate complex data composition.

Spelunking deeper into performance optimization

Prepared Statements: An SQL Sandwich

Crafting prepared statements is like putting the cheese before the ham in your sandwich. First, you prepare the INSERT ingredient:

/* "Spread the mayo, place the cheese, and Voila!" */
PREPARE glycerin_bomb AS
INSERT INTO target_table (column1, column2, ...)
VALUES ($1, $2, ...);
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Then, when it's lunch time, add the rest of the fillings:

/* "It's time! Throw in the ham" */
EXECUTE glycerin_bomb(value1, value2, ...);
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A performance-savvy SQL sandwich that also saves your data from the nasty SQL Injection disease.

Overcoming dblink's Gym Hurdles

While dblink is quite the muscle, it does have some gym limitations. For instance, it flexes rigidly when handling transaction contexts across databases. Thus, you must find suitable gym shorts, like dblink_exec, or explore other extensions like postgres_fdw to bypass its two left feet.

Interacting with the PGresult struct and PQexec (C API)

For the adventurous trekkers scaling PostgreSQL’s C API, the PGresult structure and PQexec are your loyal sherpas. Together, they help execute the INSERT command:

/* "Everest, here we come!" */
PGresult *res;
const char *query = "INSERT INTO target_table SELECT * FROM source_table";
res = PQexec(conn, query);
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But, beware of avalanches! You need to manage memory and check for Gerónimo errors to ensure a successful ascent.

Problem-solving precautions and best practices

Implementing a top-down approach

Craft your SQL masterpiece beginning with the rind. Start with the big picture (overall goal) and chisel down to the details of your queries—one SQL artistry stroke at a time.

Ensuring precise data extraction

Column filtering during SELECT crafting is like choosing the freshest of ingredients for your recipe:

/* "Only the freshest for my SQL stew!" */
INSERT INTO target_table (col1, col2)
SELECT colA, colB FROM source_table
WHERE some_condition;
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Sweeping the quirks under the rug

Always remain vigilant for sneaky quirks like data type mismatches and dinner rules (constraints) disobedience. Remember, a meticulous SQL chef is a happy SQL chef:

/* "Begone, pesky NULL values. My SQL stew doesn't need you!" */
INSERT INTO target_table (col1, col2)
SELECT colA::target_type, COALESCE(colB, 'default_value') FROM source_table;
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