String Functions is a practical SQL concept used to design, query, secure, operate, or analyze relational data correctly.
SELECT UPPER(name), ROUND(price, 2), CURRENT_DATE FROM products;Use the smallest correct statement, test it with representative data, and verify constraints and performance before production use.
A sales manager needs a monthly report showing revenue, order counts, rankings, and changes over time without exporting raw data to a spreadsheet.
BEGIN;\n-- Preview the exact target set first.\nSELECT id FROM orders WHERE status = 'pending';\n-- Apply the String Functions operation, verify affected rows, then commit.\nCOMMIT;The query returns only the intended rows and columns, with deterministic ordering where order matters.
This lesson reuses picostore. Relevant tables: customers, products, orders, order_items. Keep the starter rows from the Introduction lesson so results remain comparable.
SELECT category,\n COUNT(*) AS products,\n ROUND(AVG(price), 2) AS average_price,\n SUM(stock) AS units_available\nFROM products\nGROUP BY category\nHAVING SUM(stock) > 0;Run the verification query, compare the returned rows with the starter data, and explain why every included or excluded row is correct.
This catalog covers the practical public SQL surface. Check the exact server-version documentation before using a vendor-specific item.
UPPER — uppercase textLOWER — lowercase textCHAR_LENGTH / CHARACTER_LENGTH — number of charactersOCTET_LENGTH — number of bytesTRIM — remove leading/trailing charactersLTRIM — remove leading whitespaceRTRIM — remove trailing whitespaceSUBSTRING / SUBSTR — extract part of textPOSITION — find substring positionREPLACE — replace matching textCONCAT — join valuesNULLIF — return NULL when values matchCOALESCE — first non-null valueLENGTH — byte lengthLOCATE / INSTR — find substringLEFT / RIGHT — take characters from an endLPAD / RPAD — pad textREPEAT — repeat textREVERSE — reverse textSPACE — produce spacesSTRCMP — compare stringsFIND_IN_SET — find value in comma-separated textFIELD — position in a value listFORMAT — locale-aware number formattingGROUP_CONCAT — aggregate stringsREGEXP_REPLACE / REGEXP_SUBSTR — regular-expression operationsLENGTH — character lengthSTRPOS — find substringLEFT / RIGHT — take characters from an endLPAD / RPAD — pad textREPEAT — repeat textREVERSE — reverse textSPLIT_PART — select a delimited partSTRING_TO_ARRAY — split into an arrayARRAY_TO_STRING — join an arraySTRING_AGG — aggregate stringsFORMAT — formatted textINITCAP — capitalize wordsREGEXP_REPLACE / REGEXP_MATCH — regular-expression operationsTRANSLATE — character-by-character replacementASCII / CHR — character code conversionStart with a small customer table and retrieve active customers in a predictable order.
SELECT customer_id, name, email\nFROM customers\nWHERE status = 'active'\nORDER BY name;Use a CTE and a window function to rank customer revenue while keeping the query readable and testable.
WITH customer_revenue AS (\n SELECT customer_id, SUM(total_amount) AS revenue\n FROM orders\n WHERE order_status = 'completed'\n GROUP BY customer_id\n)\nSELECT customer_id, revenue,\n DENSE_RANK() OVER (ORDER BY revenue DESC) AS revenue_rank\nFROM customer_revenue\nORDER BY revenue_rank, customer_id;Prefer standard SQL functions when portability matters. MySQL and PostgreSQL differ most in date formatting, type conversion, string aggregation, and error handling for invalid values.
String Functions is a practical SQL concept used to design, query, secure, operate, or analyze relational data correctly.
SELECT UPPER(name), ROUND(price, 2), CURRENT_DATE FROM products;Use the smallest correct statement, test it with representative data, and verify constraints and performance before production use.
A sales manager needs a monthly report showing revenue, order counts, rankings, and changes over time without exporting raw data to a spreadsheet.
BEGIN;\n-- Preview the exact target set first.\nSELECT id FROM orders WHERE status = 'pending';\n-- Apply the String Functions operation, verify affected rows, then commit.\nCOMMIT;The query returns only the intended rows and columns, with deterministic ordering where order matters.
This lesson reuses picostore. Relevant tables: customers, products, orders, order_items. Keep the starter rows from the Introduction lesson so results remain comparable.
SELECT category,\n COUNT(*) AS products,\n ROUND(AVG(price), 2) AS average_price,\n SUM(stock) AS units_available\nFROM products\nGROUP BY category\nHAVING SUM(stock) > 0;Run the verification query, compare the returned rows with the starter data, and explain why every included or excluded row is correct.
This catalog covers the practical public SQL surface. Check the exact server-version documentation before using a vendor-specific item.
UPPER — uppercase textLOWER — lowercase textCHAR_LENGTH / CHARACTER_LENGTH — number of charactersOCTET_LENGTH — number of bytesTRIM — remove leading/trailing charactersLTRIM — remove leading whitespaceRTRIM — remove trailing whitespaceSUBSTRING / SUBSTR — extract part of textPOSITION — find substring positionREPLACE — replace matching textCONCAT — join valuesNULLIF — return NULL when values matchCOALESCE — first non-null valueLENGTH — byte lengthLOCATE / INSTR — find substringLEFT / RIGHT — take characters from an endLPAD / RPAD — pad textREPEAT — repeat textREVERSE — reverse textSPACE — produce spacesSTRCMP — compare stringsFIND_IN_SET — find value in comma-separated textFIELD — position in a value listFORMAT — locale-aware number formattingGROUP_CONCAT — aggregate stringsREGEXP_REPLACE / REGEXP_SUBSTR — regular-expression operationsLENGTH — character lengthSTRPOS — find substringLEFT / RIGHT — take characters from an endLPAD / RPAD — pad textREPEAT — repeat textREVERSE — reverse textSPLIT_PART — select a delimited partSTRING_TO_ARRAY — split into an arrayARRAY_TO_STRING — join an arraySTRING_AGG — aggregate stringsFORMAT — formatted textINITCAP — capitalize wordsREGEXP_REPLACE / REGEXP_MATCH — regular-expression operationsTRANSLATE — character-by-character replacementASCII / CHR — character code conversionStart with a small customer table and retrieve active customers in a predictable order.
SELECT customer_id, name, email\nFROM customers\nWHERE status = 'active'\nORDER BY name;Use a CTE and a window function to rank customer revenue while keeping the query readable and testable.
WITH customer_revenue AS (\n SELECT customer_id, SUM(total_amount) AS revenue\n FROM orders\n WHERE order_status = 'completed'\n GROUP BY customer_id\n)\nSELECT customer_id, revenue,\n DENSE_RANK() OVER (ORDER BY revenue DESC) AS revenue_rank\nFROM customer_revenue\nORDER BY revenue_rank, customer_id;Prefer standard SQL functions when portability matters. MySQL and PostgreSQL differ most in date formatting, type conversion, string aggregation, and error handling for invalid values.