PostgreSQL Advanced Queries
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This document provides an overview and introduction to advanced queries in PostgreSQL. It begins with background on the presenter and what is needed to follow along. It then covers SQL basics and the history of PostgreSQL development. The document outlines best practices for SQL queries and explains key PostgreSQL querying concepts like common table expressions, hierarchical queries, window functions, pivoting data, and other advanced features. Overall, the document is intended to prepare attendees to learn about more complex query techniques in PostgreSQL.
PostgreSQL Advanced Queries
- 1. PostgreSQL Advanced Queries COMELABS - MARGONDA DEPOK 14 NOPEMBER 2015
- 2. About Me • Editor PojokProgrammer.net • Writers welcome! • CEO BiruniLabs • Trainers welcome! • CEO Cronos Studio • Developers welcome!
- 3. WhatYou Need • Laptop or Computer • PostgreSQL Installed • SQL Interface • HeidiSQL • SQLyog • phpMyAdmin • Whatever..... • Your Brain
- 4. SQL Basics
- 5. History of PostgreSQL • INGRES, Berkeley 1982 • POSTGRES, Berkeley 1985 • POSTGRES v1, 1989 • PostQUEL, 1990 •PostgreSQL 6.0 (1995) • Initial release •PostgreSQL 7.0 (2000) • SQL92 compliance •PostgreSQL 8.0 (2005) • Multi-Platform support • Analytical Function support •PostgreSQL 9.0 (2010) • Built-in Replication • JSON datatype support
- 6. Rule of Thumb From Tom Kyte (Oracle Evangelist) 1. Use single SQL statement whenever possible 2. Use PL/SQL or Stored Procedure 3. Use Java (or other programming language) 4. Rethink why you want to do it (refine your approach)
- 7. SQL Anatomy • Statements • Queries • Clauses • Predicates • Expressions
- 8. ChangeYour Mindset! • Apa yang akan kalian lakukan jika mendapatkan tugas seperti di bawah ini • Tampilkan angka 1 sampai dengan 100, namun setiap kelipatan 3 ubah angkanya menjadi kata Rumah, setiap kelipatan 5 ubah angkanya menjadi kata Sakit, dan setiap kelipatan 15 ubah angkanya menjadi kata Rumah Sakit.
- 9. SELECT SELECT b,d,e,h FROM some_table ; SELECT * FROM some_table WHERE x IN (3,5,6,8) ; SELECT b,d,e,h FROM some_table WHERE x IN (3,5,6,8) ;
- 10. JOIN vs UNION JOIN ====== SELECT * FROM A JOIN B ON 1=1 UNION (UNION ALL) ====== SELECT * FROM A UNION ALL SELECT * FROM B
- 11. JOIN • INNER JOIN (JOIN) • LEFT OUTER JOIN (LEFT JOIN) • RIGHT OUTER JOIN (RIGHT JOIN) • FULL OUTER JOIN (FULLJOIN) • LEFT JOIN EXCLUDING INNER JOIN (LEFT EXCLUDING JOIN) • RIGHT JOIN EXCLUDING INNER JOIN (RIGHT EXCLUDING JOIN) • OUTER JOIN EXCLUDING INNER JOIN (OUTER EXCLUDINGJOIN)
- 13. ChangeYour Mindset! • Apa yang akan kalian lakukan jika diminta membuat output seperti di bawah ini Tabel A ID Description 1 SUV 2 Sedan 3 Truk 4 Bus 5 MPV Tabel B A_ID Description 1 Toyota Fortuner 1 BMW X5 2 ToyotaVios 2 Honda City 5 Dahihatsu GranMax ID Description Jumlah 1 SUV 2 2 Sedan 2 3 Truk 0 4 Bus 0 5 MPV 1
- 14. Ready for Advanced Queries?
- 15. Common Table Expression • Standard SQL feature • Allows you to split a query statement into distinct parts • Results of each part will appear as a table • More maintainable than subqueries
- 16. Hierarchical Queries • Fixed depth hierarchical data can be solved using simple JOINs • CTE allows recursive query • CTE can process data as hierarchical • CTE can process arbitrarily deep hierarchies with just one query
- 17. Hierarchical Query using CTE
- 18. Aggregates and Window Functions • GROUP BY lets you calculate aggregates of data over a single or multiple columns in a result set. • GROUP BY can only aggregate over a single grouping • GROUP BY only return aggregated data, detail data is not preserved • Window functions make it possible • Indicated by OVER Clause • ROW_NUMBER() OVER() • SUM() OVER() • COUNT() OVER() • MAX() OVER() • MIN() OVER() • AVG() OVER()
- 20. Pivoting data • Sometimes it’s nice to be able to pivot data in a properly normalized data model, so that repeating groups of related entities are folded into parent entity as columns. • Pivoting is very useful reporting purposes and ad- hoc queries. • PostgreSQL can handle pivoting data using • Subqueries and Arrays • UsingCASE clause
- 21. Pivot Sample
- 22. Other Advanced PostgreSQL • JSON built-in support • Pattern matching. Regular expression matching is supported • Geolocation queries. PostGIS extension adds comprehensive support for managing and querying geospatial data • Partitioning • Replication