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Awesome SQL Tips and Tricks - Voxxed Days Cluj - 2019

Vlad Mihalcea, profile picture
Vlad Mihalcea

This document provides an overview of SQL's evolution from its inception in the 1970s through various updates, including SQL:92 and SQL:1999. It explores features such as pagination, hierarchical data fetching, and common table expressions (CTEs), along with the importance of SQL in modern databases. Additionally, it references relevant surveys and trends in the technology landscape related to SQL usage.

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@vlad_mihalcea vladmihalcea.com Awesome SQL Tips and Tricks
@vlad_mihalcea vladmihalcea.com About me • Java Champion • vladmihalcea.com • @vlad_mihalcea • vladmihalcea
@vlad_mihalcea vladmihalcea.com InfoQ – Trends Report https://www.infoq.com/articles/architecture-trends-2019/
@vlad_mihalcea vladmihalcea.com InfoQ – Trends Report https://www.infoq.com/articles/architecture-trends-2019/
@vlad_mihalcea vladmihalcea.com StackOverflow Survey – Most Popular Technologies https://insights.stackoverflow.com/survey/2019
@vlad_mihalcea vladmihalcea.com SQL is old school https://www.pexels.com/photo/antique-blur-classic-close-up-595699/
@vlad_mihalcea vladmihalcea.com SQL – ‘70s 1970 E.F. Codd’s from IBM Relational Model 1974 D. D. Chamberlin & R. F. Boyce IBM System R 1974 Michael Stonebraker Berkeley Ingres 1979 Relational Software, Inc. Oracle V2 Marketing
@vlad_mihalcea vladmihalcea.com SQL – ‘80s IBM System R 1981 IBM SQL/DS 1983 IBM DB2 1987 IBM DB2 for OS/2 1985 Robert Epstein Sybase Berkeley Ingres 1988 Microsoft Sybase SQL Server 1985 Michael Stonebraker POSTGRES
@vlad_mihalcea vladmihalcea.com SQL – ‘90s 1995 David Axmark & Michael Widenius MySQL Sybase SQL Server 1993 Microsoft SQL Server POSTGRES 1996 PostgreSQL
@vlad_mihalcea vladmihalcea.com Why is SQL still used? https://qr.ae/TWCBD5
@vlad_mihalcea vladmihalcea.com StackOverflow Survey – Most Popular Databases https://insights.stackoverflow.com/survey/2019
@vlad_mihalcea vladmihalcea.com StackOverflow Survey – Most Popular Databases https://insights.stackoverflow.com/survey/2019
@vlad_mihalcea vladmihalcea.com What does SQL stand for? S? Query Language
@vlad_mihalcea vladmihalcea.com What does SQL stand for? https://twitter.com/vlad_mihalcea/status/1172446336131596289
@vlad_mihalcea vladmihalcea.com SQL Standard Photo by Frederick Tubiermont on Unsplash https://unsplash.com/photos/fJSRg-r7LuI
@vlad_mihalcea vladmihalcea.com SQL:92
@vlad_mihalcea vladmihalcea.com SQL:92 • In 1992, a major version of the standard was released. The specification grew from 115 pages to 580. • SQL:92 adds support for: • DATE, TIME, TIMESTAMP, INTERVAL, BIT, VARCHAR, NVARCHAR, • UNION, NATURAL JOIN, • CASE expressions, • CHECK constraints, • Type casting (e.g., CAST (expr AS type))
@vlad_mihalcea vladmihalcea.com SQL:92 • Other SQL:92 features include: • INFORMATION_SCHEMA, • Dynamic query execution (e.g., java.sql.Statement). Previously, only prepared statements were supported. • Temporary tables, • Custom isolation levels, • Database cursors, • Scalar operations like String concatenation, date manipulation.
@vlad_mihalcea vladmihalcea.com Fetching one-to-many relationship with pagination
@vlad_mihalcea vladmihalcea.com Fetching one-to-many relationship with pagination We need to get the first 2 post entries starting with a given string value, along with all their associated post_comment child records.
@vlad_mihalcea vladmihalcea.com post id review post_id 1 SQL:2016 is great! 1 2 SQL:2016 is excellent! 1 3 SQL:20016 is awesome! 1 4 SQL:2011 is great! 2 5 SQL:2011 is excellent! 2 7 SQL:2008 is great! 3 id title 1 SQL:2016 2 SQL:2011 3 SQL:2008 Fetching one-to-many relationship with pagination post_comment post_id post_title comment_id comment_review 1 SQL:2016 1 SQL:2016 is great! 1 SQL:2016 2 SQL:2016 is excellent! 1 SQL:2016 3 SQL:20016 is awesome! Result set
@vlad_mihalcea vladmihalcea.com post id review post_id 1 SQL:2016 is great! 1 2 SQL:2016 is excellent! 1 3 SQL:20016 is awesome! 1 4 SQL:2011 is great! 2 5 SQL:2011 is excellent! 2 7 SQL:2008 is great! 3 id title 1 SQL:2016 2 SQL:2011 3 SQL:2008 Fetching one-to-many relationship with pagination post_comment post_id post_title comment_id comment_review 1 SQL:2016 1 SQL:2016 is great! 1 SQL:2016 2 SQL:2016 is excellent! 1 SQL:2016 3 SQL:20016 is awesome! 2 SQL:2011 4 SQL:2011 is great! 2 SQL:2011 5 SQL:2011 is excellent! Result set
@vlad_mihalcea vladmihalcea.com JPQL – Join fetch with Pagination List<Post> posts = entityManager .createQuery( """ select p from Post p left join fetch p.comments pc where p.title like :title order by p.id, pc.id """, Post.class) .setParameter("title", "SQL%") .setMaxResults(2) .getResultList();
@vlad_mihalcea vladmihalcea.com JPQL – Join fetch with Pagination WARN [main]: QueryTranslatorImpl - HHH000104: firstResult/maxResults specified with collection fetch; applying in memory! SELECT p.id AS id1_0_0_, p.title AS title3_0_0_, pc.id AS id1_1_0__, pc.post_id AS post_id4_1_1_, pc.review AS review3_1_1_ FROM post p LEFT OUTER JOIN post_comment pc ON p.id = pc.post_id WHERE p.title LIKE 'SQL%' ORDER BY p.id, pc.id
@vlad_mihalcea vladmihalcea.com SQL – Join fetch with Pagination SELECT p.id AS post_id, p.title AS post_title, pc.id AS comment_id, pc.review AS comment_review FROM post p LEFT JOIN post_comment pc ON p.id = pc.post_id WHERE p.id IN ( SELECT id FROM post WHERE p.title LIKE 'SQL%' ORDER BY id LIMIT 2 ) ORDER BY post_id, comment_id
@vlad_mihalcea vladmihalcea.com SQL – Derived tables – Oracle Top N SELECT t.* FROM ( SELECT title FROM post ORDER BY created_on DESC, id DESC ) t WHERE ROWNUM <= 5 ORDER BY ROWNUM We must sort the result set prior to assigning the row ranking numbers.
@vlad_mihalcea vladmihalcea.com SQL – Derived tables – Oracle Top N SELECT t.* FROM ( SELECT title FROM post ORDER BY created_on DESC, id DESC ) t WHERE ROWNUM <= 5 ORDER BY ROWNUM The outer query can now limit the result set size.
@vlad_mihalcea vladmihalcea.com SQL – Derived tables – Oracle Next N SELECT t2.* FROM ( SELECT t1.*, ROWNUM AS ROW_NUM FROM ( SELECT title FROM post ORDER BY created_on DESC, id DESC ) t1 WHERE ROWNUM <= 10 ) t2 WHERE ROW_NUM > 5 ORDER BY ROW_NUM We must sort the result set prior to assigning the row ranking numbers.
@vlad_mihalcea vladmihalcea.com SQL – Derived tables – Oracle Next N SELECT t2.* FROM ( SELECT t1.*, ROWNUM AS ROW_NUM FROM ( SELECT title FROM post ORDER BY created_on DESC, id DESC ) t1 WHERE ROWNUM <= 10 ) t2 WHERE ROW_NUM > 5 ORDER BY ROW_NUM The following outer query can now limit the result set size.
@vlad_mihalcea vladmihalcea.com SQL – Derived tables – Oracle Next N SELECT t2.* FROM ( SELECT t1.*, ROWNUM AS ROW_NUM FROM ( SELECT title FROM post ORDER BY created_on DESC, id DESC ) t1 WHERE ROWNUM <= 10 ) t2 WHERE ROW_NUM > 5 ORDER BY ROW_NUM The outer-most query can set the offset where we want to start streaming the result set back to the DB client.
@vlad_mihalcea vladmihalcea.com SQL:92
@vlad_mihalcea vladmihalcea.com SQL Standard timeline SQL:86 SQL:89 SQL:92
@vlad_mihalcea vladmihalcea.com SQL Standard timeline SQL:86 SQL:89 SQL:92 SQL:1999 SQL:2011 SQL:2008 SQL:2006 SQL:2003 SQL:2016
@vlad_mihalcea vladmihalcea.com SQL:1999 • In 1999, a new major version of the standard was released. • It added support for: • Boolean column type, • WITH CTE (Common Table Expression) queries and WITH RECURSIVE queries for hierarchic queries, • ROLLUP, CUBE, GROUPING SETS for GROUP BY, • Initial support for ARRAY types (e.g., UNNEST)
@vlad_mihalcea vladmihalcea.com Pyramid of Doom SELECT t2.* FROM ( SELECT t1.*, ROWNUM AS ROW_NUM FROM ( SELECT title FROM post ORDER BY created_on DESC, id DESC ) t1 WHERE ROWNUM <= 10 ) t2 WHERE ROW_NUM > 5 ORDER BY ROW_NUM
@vlad_mihalcea vladmihalcea.com • Supported databases: • Oracle 9i R2 • SQL Server 2005 • PostgreSQL 8.4 • MySQL 8.0.1 • MariaDB 10.2.1 CTE (Common Table Expression)
@vlad_mihalcea vladmihalcea.com SQL – CTE WITH p AS ( SELECT title FROM post ORDER BY created_on DESC, id DESC ), p_limit AS ( SELECT p.*, ROWNUM AS ROW_NUM FROM p WHERE ROWNUM <= 10 ) SELECT title FROM p_limit WHERE ROW_NUM > 5 ORDER BY ROWNUM
@vlad_mihalcea vladmihalcea.com SQL – CTE WITH p AS ( SELECT title FROM post ORDER BY created_on DESC, id DESC ), p_limit AS ( SELECT p.*, ROWNUM AS ROW_NUM FROM p WHERE ROWNUM <= 10 ) SELECT title FROM p_limit WHERE ROW_NUM > 5 ORDER BY ROWNUM
@vlad_mihalcea vladmihalcea.com SQL – CTE WITH p AS ( SELECT title FROM post ORDER BY created_on DESC, id DESC ), p_limit AS ( SELECT p.*, ROWNUM AS ROW_NUM FROM p WHERE ROWNUM <= 10 ) SELECT title FROM p_limit WHERE ROW_NUM > 5 ORDER BY ROWNUM
@vlad_mihalcea vladmihalcea.com Fetching hierarchical data 6 + 2 + 2 + 1 + … total_score
@vlad_mihalcea vladmihalcea.com Fetching hierarchical data
@vlad_mihalcea vladmihalcea.com Fetch the top 3 comment hierarchies by total score We need to get the top 3 post_comment hierarchies based on their total post_comment score.
@vlad_mihalcea vladmihalcea.com id parent_id review created_on score post_id 1 Comment 1 2019-10-13 12:23:05 1 1 2 1 Comment 1.1 2019-10-14 13:23:10 2 1 3 1 Comment 1.2 2019-10-14 15:45:15 2 1 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 1 5 Comment 2 2019-10-13 15:23:25 1 1 6 5 Comment 2.1 2019-10-14 11:23:30 1 1 7 5 Comment 2.2 2019-10-14 14:45:35 1 1 8 Comment 3 2019-10-15 10:15:40 1 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 1 11 Comment 4 2019-10-19 21:43:55 -5 1 12 Comment 5 2019-10-22 23:45:00 0 1 Fetching hierarchical data – table records post_comment 4 = 1 + 2 + 2 + 1 total_score
@vlad_mihalcea vladmihalcea.com id parent_id review created_on score post_id 1 Comment 1 2019-10-13 12:23:05 1 1 2 1 Comment 1.1 2019-10-14 13:23:10 2 1 3 1 Comment 1.2 2019-10-14 15:45:15 2 1 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 1 5 Comment 2 2019-10-13 15:23:25 1 1 6 5 Comment 2.1 2019-10-14 11:23:30 1 1 7 5 Comment 2.2 2019-10-14 14:45:35 1 1 8 Comment 3 2019-10-15 10:15:40 1 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 1 11 Comment 4 2019-10-19 21:43:55 -5 1 12 Comment 5 2019-10-22 23:45:00 0 1 Fetching hierarchical data – table records post_comment 3 = 1 + 1 + 1 total_score
@vlad_mihalcea vladmihalcea.com id parent_id review created_on score post_id 1 Comment 1 2019-10-13 12:23:05 1 1 2 1 Comment 1.1 2019-10-14 13:23:10 2 1 3 1 Comment 1.2 2019-10-14 15:45:15 2 1 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 1 5 Comment 2 2019-10-13 15:23:25 1 1 6 5 Comment 2.1 2019-10-14 11:23:30 1 1 7 5 Comment 2.2 2019-10-14 14:45:35 1 1 8 Comment 3 2019-10-15 10:15:40 1 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 1 11 Comment 4 2019-10-19 21:43:55 -5 1 12 Comment 5 2019-10-22 23:45:00 0 1 Fetching hierarchical data – table records post_comment 9 = 1 + 10 - 2 total_score
@vlad_mihalcea vladmihalcea.com id parent_id review created_on score post_id 1 Comment 1 2019-10-13 12:23:05 1 1 2 1 Comment 1.1 2019-10-14 13:23:10 2 1 3 1 Comment 1.2 2019-10-14 15:45:15 2 1 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 1 5 Comment 2 2019-10-13 15:23:25 1 1 6 5 Comment 2.1 2019-10-14 11:23:30 1 1 7 5 Comment 2.2 2019-10-14 14:45:35 1 1 8 Comment 3 2019-10-15 10:15:40 1 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 1 11 Comment 4 2019-10-19 21:43:55 -5 1 12 Comment 5 2019-10-22 23:45:00 0 1 Fetching hierarchical data – table records post_comment -5 total_score
@vlad_mihalcea vladmihalcea.com id parent_id review created_on score post_id 1 Comment 1 2019-10-13 12:23:05 1 1 2 1 Comment 1.1 2019-10-14 13:23:10 2 1 3 1 Comment 1.2 2019-10-14 15:45:15 2 1 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 1 5 Comment 2 2019-10-13 15:23:25 1 1 6 5 Comment 2.1 2019-10-14 11:23:30 1 1 7 5 Comment 2.2 2019-10-14 14:45:35 1 1 8 Comment 3 2019-10-15 10:15:40 1 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 1 11 Comment 4 2019-10-19 21:43:55 -5 1 12 Comment 5 2019-10-22 23:45:00 0 1 Fetching hierarchical data – table records post_comment 0 total_score
@vlad_mihalcea vladmihalcea.com id parent_id review created_on score post_id 1 Comment 1 2019-10-13 12:23:05 1 1 2 1 Comment 1.1 2019-10-14 13:23:10 2 1 3 1 Comment 1.2 2019-10-14 15:45:15 2 1 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 1 5 Comment 2 2019-10-13 15:23:25 1 1 6 5 Comment 2.1 2019-10-14 11:23:30 1 1 7 5 Comment 2.2 2019-10-14 14:45:35 1 1 8 Comment 3 2019-10-15 10:15:40 1 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 1 11 Comment 4 2019-10-19 21:43:55 -5 1 12 Comment 5 2019-10-22 23:45:00 0 1 Fetching all data – application-level sorting SELECT id, parent_id, review, created_on, score FROM post_comment WHERE post_id = 1 post_comment
@vlad_mihalcea vladmihalcea.com Fetching all data – application-level sorting Map<Long, PostCommentScore> postCommentScoreMap = postCommentScores .stream() .collect(Collectors.toMap(PostCommentScore::getId, Function.identity())); List<PostCommentScore> postCommentRoots = postCommentScores .stream() .filter(pcs -> { boolean isRoot = pcs.getParentId() == null; if(!isRoot) { postCommentScoreMap.get(pcs.getParentId()).addChild(pcs); } return isRoot; }) .sorted( Comparator.comparing(PostCommentScore::getTotalScore).reversed() ) .limit(ranking) .collect(Collectors.toList());
@vlad_mihalcea vladmihalcea.com id parent_id review created_on score post_id 1 Comment 1 2019-10-13 12:23:05 1 1 2 1 Comment 1.1 2019-10-14 13:23:10 2 1 3 1 Comment 1.2 2019-10-14 15:45:15 2 1 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 1 5 Comment 2 2019-10-13 15:23:25 1 1 6 5 Comment 2.1 2019-10-14 11:23:30 1 1 7 5 Comment 2.2 2019-10-14 14:45:35 1 1 8 Comment 3 2019-10-15 10:15:40 1 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 1 11 Comment 4 2019-10-19 21:43:55 -5 1 12 Comment 5 2019-10-22 23:45:00 0 1 Fetching hierarchical data – 1st level SELECT id, parent_id, review, created_on, score FROM post_comment WHERE post_id = 1 AND parent_id IS NULL Fetch all root-level comments. post_comment
@vlad_mihalcea vladmihalcea.com id parent_id review created_on score post_id 1 Comment 1 2019-10-13 12:23:05 1 1 2 1 Comment 1.1 2019-10-14 13:23:10 2 1 3 1 Comment 1.2 2019-10-14 15:45:15 2 1 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 1 5 Comment 2 2019-10-13 15:23:25 1 1 6 5 Comment 2.1 2019-10-14 11:23:30 1 1 7 5 Comment 2.2 2019-10-14 14:45:35 1 1 8 Comment 3 2019-10-15 10:15:40 1 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 1 11 Comment 4 2019-10-19 21:43:55 -5 1 12 Comment 5 2019-10-22 23:45:00 0 1 Fetching hierarchical data – 2nd level WITH pc_r AS ( SELECT id, parent_id, review, created_on, score FROM post_comment WHERE post_id = 1 AND parent_id IS NULL ) SELECT * FROM pc_r UNION ALL SELECT pc.id, pc.parent_id, pc.review, pc.created_on, pc.score FROM post_comment pc INNER JOIN pc_r ON pc_r.id = pc.parent_id post_comment
@vlad_mihalcea vladmihalcea.com id parent_id review created_on score post_id 1 Comment 1 2019-10-13 12:23:05 1 1 2 1 Comment 1.1 2019-10-14 13:23:10 2 1 3 1 Comment 1.2 2019-10-14 15:45:15 2 1 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 1 5 Comment 2 2019-10-13 15:23:25 1 1 6 5 Comment 2.1 2019-10-14 11:23:30 1 1 7 5 Comment 2.2 2019-10-14 14:45:35 1 1 8 Comment 3 2019-10-15 10:15:40 1 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 1 11 Comment 4 2019-10-19 21:43:55 -5 1 12 Comment 5 2019-10-22 23:45:00 0 1 Fetching hierarchical data – 2nd level WITH pc_r AS ( SELECT id, parent_id, review, created_on, score FROM post_comment WHERE post_id = 1 AND parent_id IS NULL ) SELECT * FROM pc_r UNION ALL SELECT pc.id, pc.parent_id, pc.review, pc.created_on, pc.score FROM post_comment pc INNER JOIN pc_r ON pc_r.id = pc.parent_id post_comment
@vlad_mihalcea vladmihalcea.com Fetching hierarchical data – Nth level This approach of merging manually (using UNION ALL) the result sets of each individual level is cumbersome and requires us knowing the number of levels upfront.
@vlad_mihalcea vladmihalcea.com SQL – Recursive CTE WITH RECURSIVE post_comment_score(id, root_id, post_id, parent_id, review, created_on, score) AS ( ) The result set table built recursively
@vlad_mihalcea vladmihalcea.com SQL – Recursive CTE WITH RECURSIVE post_comment_score(id, root_id, post_id, parent_id, review, created_on, score) AS ( ) We want to propagate the root_id to all comments belonging to the same hierarchy.
@vlad_mihalcea vladmihalcea.com SQL – Recursive CTE WITH RECURSIVE post_comment_score(id, root_id, post_id, parent_id, review, created_on, score) AS ( SELECT id, id, post_id, parent_id, review, created_on, score FROM post_comment WHERE post_id = 1 AND parent_id IS NULL ) Anchor member – the 1st level
@vlad_mihalcea vladmihalcea.com SQL – Recursive CTE WITH RECURSIVE post_comment_score(id, root_id, post_id, parent_id, review, created_on, score) AS ( SELECT id, id, post_id, parent_id, review, created_on, score FROM post_comment WHERE post_id = 1 AND parent_id IS NULL ) Anchor member – the 1st level
@vlad_mihalcea vladmihalcea.com SQL – Recursive CTE WITH RECURSIVE post_comment_score(id, root_id, post_id, parent_id, review, created_on, score) AS ( SELECT id, id, post_id, parent_id, review, created_on, score FROM post_comment WHERE post_id = 1 AND parent_id IS NULL UNION ALL SELECT pc.id, pcs.root_id, pc.post_id, pc.parent_id, pc.review, pc.created_on, pc.score FROM post_comment pc INNER JOIN post_comment_score pcs ON pc.parent_id = pcs.id ) Recursive member – the 2nd to Nth level
@vlad_mihalcea vladmihalcea.com SQL – Recursive CTE WITH RECURSIVE post_comment_score(id, root_id, post_id, parent_id, review, created_on, score) AS ( SELECT id, id, post_id, parent_id, review, created_on, score FROM post_comment WHERE post_id = 1 AND parent_id IS NULL UNION ALL SELECT pc.id, pcs.root_id, pc.post_id, pc.parent_id, pc.review, pc.created_on, pc.score FROM post_comment pc INNER JOIN post_comment_score pcs ON pc.parent_id = pcs.id ) Joining the current and previous levels
@vlad_mihalcea vladmihalcea.com SQL – Recursive CTE WITH RECURSIVE post_comment_score(id, root_id, post_id, parent_id, review, created_on, score) AS ( SELECT id, id, post_id, parent_id, review, created_on, score FROM post_comment WHERE post_id = 1 AND parent_id IS NULL UNION ALL SELECT pc.id, pcs.root_id, pc.post_id, pc.parent_id, pc.review, pc.created_on, pc.score FROM post_comment pc INNER JOIN post_comment_score pcs ON pc.parent_id = pcs.id ) SELECT id, parent_id, root_id, review, created_on, score FROM post_comment_score Result set projection query
@vlad_mihalcea vladmihalcea.com Recursive CTE – 1st level WITH RECURSIVE post_comment_score( id, root_id, post_id, parent_id, review, created_on, score) AS ( SELECT id, id, post_id, parent_id, review, created_on, score FROM post_comment WHERE post_id = 1 AND parent_id IS NULL UNION ALL SELECT pc.id, pcs.root_id, pc.post_id, pc.parent_id, pc.review, pc.created_on, pc.score FROM post_comment pc INNER JOIN post_comment_score pcs ON pc.parent_id = pcs.id ) SELECT id, parent_id, root_id, review, created_on, score FROM post_comment_score id parent_id review created_on score post_id 1 Comment 1 2019-10-13 12:23:05 1 1 2 1 Comment 1.1 2019-10-14 13:23:10 2 1 3 1 Comment 1.2 2019-10-14 15:45:15 2 1 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 1 5 Comment 2 2019-10-13 15:23:25 1 1 6 5 Comment 2.1 2019-10-14 11:23:30 1 1 7 5 Comment 2.2 2019-10-14 14:45:35 1 1 8 Comment 3 2019-10-15 10:15:40 1 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 1 11 Comment 4 2019-10-19 21:43:55 -5 1 12 Comment 5 2019-10-22 23:45:00 0 1 post_comment
@vlad_mihalcea vladmihalcea.com id parent_id root_id review created_on score 1 1 Comment 1 2019-10-13 12:23:05 1 5 5 Comment 2 2019-10-13 15:23:25 1 8 8 Comment 3 2019-10-15 10:15:40 1 11 11 Comment 4 2019-10-19 21:43:55 -5 12 12 Comment 5 2019-10-22 23:45:00 0 Recursive CTE – 1st level WITH RECURSIVE post_comment_score( id, root_id, post_id, parent_id, review, created_on, score) AS ( SELECT id, id, post_id, parent_id, review, created_on, score FROM post_comment WHERE post_id = 1 AND parent_id IS NULL UNION ALL SELECT pc.id, pcs.root_id, pc.post_id, pc.parent_id, pc.review, pc.created_on, pc.score FROM post_comment pc INNER JOIN post_comment_score pcs ON pc.parent_id = pcs.id ) SELECT id, parent_id, root_id, review, created_on, score FROM post_comment_score post_comment_score
@vlad_mihalcea vladmihalcea.com Recursive CTE – 2nd level WITH RECURSIVE post_comment_score( id, root_id, post_id, parent_id, review, created_on, score) AS ( SELECT id, id, post_id, parent_id, review, created_on, score FROM post_comment WHERE post_id = 1 AND parent_id IS NULL UNION ALL SELECT pc.id, pcs.root_id, pc.post_id, pc.parent_id, pc.review, pc.created_on, pc.score FROM post_comment pc INNER JOIN post_comment_score pcs ON pc.parent_id = pcs.id ) SELECT id, parent_id, root_id, review, created_on, score FROM post_comment_score id parent_id review created_on score post_id 1 Comment 1 2019-10-13 12:23:05 1 1 2 1 Comment 1.1 2019-10-14 13:23:10 2 1 3 1 Comment 1.2 2019-10-14 15:45:15 2 1 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 1 5 Comment 2 2019-10-13 15:23:25 1 1 6 5 Comment 2.1 2019-10-14 11:23:30 1 1 7 5 Comment 2.2 2019-10-14 14:45:35 1 1 8 Comment 3 2019-10-15 10:15:40 1 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 1 11 Comment 4 2019-10-19 21:43:55 -5 1 12 Comment 5 2019-10-22 23:45:00 0 1 post_comment
@vlad_mihalcea vladmihalcea.com id parent_id root_id review created_on score 1 1 Comment 1 2019-10-13 12:23:05 1 5 5 Comment 2 2019-10-13 15:23:25 1 8 8 Comment 3 2019-10-15 10:15:40 1 11 11 Comment 4 2019-10-19 21:43:55 -5 12 12 Comment 5 2019-10-22 23:45:00 0 2 1 1 Comment 1.1 2019-10-14 13:23:10 2 3 1 1 Comment 1.2 2019-10-14 15:45:15 2 6 5 5 Comment 2.1 2019-10-14 11:23:30 1 7 5 5 Comment 2.2 2019-10-14 14:45:35 1 9 8 8 Comment 3.1 2019-10-16 11:15:45 10 10 8 8 Comment 3.2 2019-10-17 18:30:50 -2 Recursive CTE – 2nd level WITH RECURSIVE post_comment_score( id, root_id, post_id, parent_id, review, created_on, score) AS ( SELECT id, id, post_id, parent_id, review, created_on, score FROM post_comment WHERE post_id = 1 AND parent_id IS NULL UNION ALL SELECT pc.id, pcs.root_id, pc.post_id, pc.parent_id, pc.review, pc.created_on, pc.score FROM post_comment pc INNER JOIN post_comment_score pcs ON pc.parent_id = pcs.id ) SELECT id, parent_id, root_id, review, created_on, score FROM post_comment_score post_comment_score
@vlad_mihalcea vladmihalcea.com Recursive CTE – 3rd level WITH RECURSIVE post_comment_score( id, root_id, post_id, parent_id, review, created_on, score) AS ( SELECT id, id, post_id, parent_id, review, created_on, score FROM post_comment WHERE post_id = 1 AND parent_id IS NULL UNION ALL SELECT pc.id, pcs.root_id, pc.post_id, pc.parent_id, pc.review, pc.created_on, pc.score FROM post_comment pc INNER JOIN post_comment_score pcs ON pc.parent_id = pcs.id ) SELECT id, parent_id, root_id, review, created_on, score FROM post_comment_score id parent_id review created_on score post_id 1 Comment 1 2019-10-13 12:23:05 1 1 2 1 Comment 1.1 2019-10-14 13:23:10 2 1 3 1 Comment 1.2 2019-10-14 15:45:15 2 1 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 1 5 Comment 2 2019-10-13 15:23:25 1 1 6 5 Comment 2.1 2019-10-14 11:23:30 1 1 7 5 Comment 2.2 2019-10-14 14:45:35 1 1 8 Comment 3 2019-10-15 10:15:40 1 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 1 11 Comment 4 2019-10-19 21:43:55 -5 1 12 Comment 5 2019-10-22 23:45:00 0 1 post_comment
@vlad_mihalcea vladmihalcea.com id parent_id root_id review created_on score 1 1 Comment 1 2019-10-13 12:23:05 1 5 5 Comment 2 2019-10-13 15:23:25 1 8 8 Comment 3 2019-10-15 10:15:40 1 11 11 Comment 4 2019-10-19 21:43:55 -5 12 12 Comment 5 2019-10-22 23:45:00 0 2 1 1 Comment 1.1 2019-10-14 13:23:10 2 3 1 1 Comment 1.2 2019-10-14 15:45:15 2 6 5 5 Comment 2.1 2019-10-14 11:23:30 1 7 5 5 Comment 2.2 2019-10-14 14:45:35 1 9 8 8 Comment 3.1 2019-10-16 11:15:45 10 10 8 8 Comment 3.2 2019-10-17 18:30:50 -2 4 3 1 Comment 1.2.1 2019-10-15 10:15:20 1 Recursive CTE – 3rd level WITH RECURSIVE post_comment_score( id, root_id, post_id, parent_id, review, created_on, score) AS ( SELECT id, id, post_id, parent_id, review, created_on, score FROM post_comment WHERE post_id = 1 AND parent_id IS NULL UNION ALL SELECT pc.id, pcs.root_id, pc.post_id, pc.parent_id, pc.review, pc.created_on, pc.score FROM post_comment pc INNER JOIN post_comment_score pcs ON pc.parent_id = pcs.id ) SELECT id, parent_id, root_id, review, created_on, score FROM post_comment_score post_comment_score
@vlad_mihalcea vladmihalcea.com id parent_id root_id review created_on score 1 1 Comment 1 2019-10-13 12:23:05 1 5 5 Comment 2 2019-10-13 15:23:25 1 8 8 Comment 3 2019-10-15 10:15:40 1 11 11 Comment 4 2019-10-19 21:43:55 -5 12 12 Comment 5 2019-10-22 23:45:00 0 2 1 1 Comment 1.1 2019-10-14 13:23:10 2 3 1 1 Comment 1.2 2019-10-14 15:45:15 2 6 5 5 Comment 2.1 2019-10-14 11:23:30 1 7 5 5 Comment 2.2 2019-10-14 14:45:35 1 9 8 8 Comment 3.1 2019-10-16 11:15:45 10 10 8 8 Comment 3.2 2019-10-17 18:30:50 -2 4 3 1 Comment 1.2.1 2019-10-15 10:15:20 1 Why use Recursive CTE? post_comment_score
@vlad_mihalcea vladmihalcea.com Window Functions Photo by Numendil on Unsplash https://unsplash.com/photos/sSKNdbv3qNg
@vlad_mihalcea vladmihalcea.com SQL:2003 • SQL:2003 was a minor version of SQL:1999. • It added support for: • Window Functions, • MERGE statement • SEQUNCE generator and IDENTITY column type, • XML column type
@vlad_mihalcea vladmihalcea.com • Supported databases: • Oracle 8i • SQL Server 2005 • PostgreSQL 8.4 • MySQL 8.0.2 • MariaDB 10.2.0 Window Functions
@vlad_mihalcea vladmihalcea.com Summing up comment scores by root_id total_score_comment AS ( SELECT id, parent_id, review, created_on, score, SUM(score) OVER ( PARTITION BY root_id ) AS total_score FROM post_comment_score ),
@vlad_mihalcea vladmihalcea.com id parent_id root_id review created_on score 1 1 Comment 1 2019-10-13 12:23:05 1 5 5 Comment 2 2019-10-13 15:23:25 1 8 8 Comment 3 2019-10-15 10:15:40 1 11 11 Comment 4 2019-10-19 21:43:55 -5 12 12 Comment 5 2019-10-22 23:45:00 0 2 1 1 Comment 1.1 2019-10-14 13:23:10 2 3 1 1 Comment 1.2 2019-10-14 15:45:15 2 6 5 5 Comment 2.1 2019-10-14 11:23:30 1 7 5 5 Comment 2.2 2019-10-14 14:45:35 1 9 8 8 Comment 3.1 2019-10-16 11:15:45 10 10 8 8 Comment 3.2 2019-10-17 18:30:50 -2 4 3 1 Comment 1.2.1 2019-10-15 10:15:20 1 Summing comment scores – 1st root total_score_comment AS ( SELECT id, parent_id, review, created_on, score, SUM(score) OVER ( PARTITION BY root_id ) AS total_score FROM post_comment_score ), post_comment_score
@vlad_mihalcea vladmihalcea.com id parent_id review created_on score total_score 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 6 2 1 Comment 1.1 2019-10-14 13:23:10 2 6 3 1 Comment 1.2 2019-10-14 15:45:15 2 6 1 Comment 1 2019-10-13 12:23:05 1 6 6 5 Comment 2.1 2019-10-14 11:23:30 1 7 5 Comment 2.2 2019-10-14 14:45:35 1 5 Comment 2 2019-10-13 15:23:25 1 8 Comment 3 2019-10-15 10:15:40 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 10 8 Comment 3.2 2019-10-17 18:30:50 -2 11 Comment 4 2019-10-19 21:43:55 -5 12 Comment 5 2019-10-22 23:45:00 0 Summing comment scores – 1st root total_score_comment AS ( SELECT id, parent_id, review, created_on, score, SUM(score) OVER ( PARTITION BY root_id ) AS total_score FROM post_comment_score ), total_score_comment
@vlad_mihalcea vladmihalcea.com id parent_id root_id review created_on score 1 1 Comment 1 2019-10-13 12:23:05 1 5 5 Comment 2 2019-10-13 15:23:25 1 8 8 Comment 3 2019-10-15 10:15:40 1 11 11 Comment 4 2019-10-19 21:43:55 -5 12 12 Comment 5 2019-10-22 23:45:00 0 2 1 1 Comment 1.1 2019-10-14 13:23:10 2 3 1 1 Comment 1.2 2019-10-14 15:45:15 2 6 5 5 Comment 2.1 2019-10-14 11:23:30 1 7 5 5 Comment 2.2 2019-10-14 14:45:35 1 9 8 8 Comment 3.1 2019-10-16 11:15:45 10 10 8 8 Comment 3.2 2019-10-17 18:30:50 -2 4 3 1 Comment 1.2.1 2019-10-15 10:15:20 1 Summing comment scores – 2nd root total_score_comment AS ( SELECT id, parent_id, review, created_on, score, SUM(score) OVER ( PARTITION BY root_id ) AS total_score FROM post_comment_score ), post_comment_score
@vlad_mihalcea vladmihalcea.com id parent_id review created_on score total_score 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 6 2 1 Comment 1.1 2019-10-14 13:23:10 2 6 3 1 Comment 1.2 2019-10-14 15:45:15 2 6 1 Comment 1 2019-10-13 12:23:05 1 6 6 5 Comment 2.1 2019-10-14 11:23:30 1 3 7 5 Comment 2.2 2019-10-14 14:45:35 1 3 5 Comment 2 2019-10-13 15:23:25 1 3 8 Comment 3 2019-10-15 10:15:40 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 10 8 Comment 3.2 2019-10-17 18:30:50 -2 11 Comment 4 2019-10-19 21:43:55 -5 12 Comment 5 2019-10-22 23:45:00 0 Summing comment scores – 2nd root total_score_comment AS ( SELECT id, parent_id, review, created_on, score, SUM(score) OVER ( PARTITION BY root_id ) AS total_score FROM post_comment_score ), total_score_comment
@vlad_mihalcea vladmihalcea.com id parent_id root_id review created_on score 1 1 Comment 1 2019-10-13 12:23:05 1 5 5 Comment 2 2019-10-13 15:23:25 1 8 8 Comment 3 2019-10-15 10:15:40 1 11 11 Comment 4 2019-10-19 21:43:55 -5 12 12 Comment 5 2019-10-22 23:45:00 0 2 1 1 Comment 1.1 2019-10-14 13:23:10 2 3 1 1 Comment 1.2 2019-10-14 15:45:15 2 6 5 5 Comment 2.1 2019-10-14 11:23:30 1 7 5 5 Comment 2.2 2019-10-14 14:45:35 1 9 8 8 Comment 3.1 2019-10-16 11:15:45 10 10 8 8 Comment 3.2 2019-10-17 18:30:50 -2 4 3 1 Comment 1.2.1 2019-10-15 10:15:20 1 Summing comment scores – 3rd root total_score_comment AS ( SELECT id, parent_id, review, created_on, score, SUM(score) OVER ( PARTITION BY root_id ) AS total_score FROM post_comment_score ), post_comment_score
@vlad_mihalcea vladmihalcea.com id parent_id review created_on score total_score 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 6 2 1 Comment 1.1 2019-10-14 13:23:10 2 6 3 1 Comment 1.2 2019-10-14 15:45:15 2 6 1 Comment 1 2019-10-13 12:23:05 1 6 6 5 Comment 2.1 2019-10-14 11:23:30 1 3 7 5 Comment 2.2 2019-10-14 14:45:35 1 3 5 Comment 2 2019-10-13 15:23:25 1 3 8 Comment 3 2019-10-15 10:15:40 1 9 9 8 Comment 3.1 2019-10-16 11:15:45 10 9 10 8 Comment 3.2 2019-10-17 18:30:50 -2 9 11 Comment 4 2019-10-19 21:43:55 -5 12 Comment 5 2019-10-22 23:45:00 0 Summing comment scores – 3rd root total_score_comment AS ( SELECT id, parent_id, review, created_on, score, SUM(score) OVER ( PARTITION BY root_id ) AS total_score FROM post_comment_score ), total_score_comment
@vlad_mihalcea vladmihalcea.com id parent_id root_id review created_on score 1 1 Comment 1 2019-10-13 12:23:05 1 5 5 Comment 2 2019-10-13 15:23:25 1 8 8 Comment 3 2019-10-15 10:15:40 1 11 11 Comment 4 2019-10-19 21:43:55 -5 12 12 Comment 5 2019-10-22 23:45:00 0 2 1 1 Comment 1.1 2019-10-14 13:23:10 2 3 1 1 Comment 1.2 2019-10-14 15:45:15 2 6 5 5 Comment 2.1 2019-10-14 11:23:30 1 7 5 5 Comment 2.2 2019-10-14 14:45:35 1 9 8 8 Comment 3.1 2019-10-16 11:15:45 10 10 8 8 Comment 3.2 2019-10-17 18:30:50 -2 4 3 1 Comment 1.2.1 2019-10-15 10:15:20 1 Summing comment scores – 4th root total_score_comment AS ( SELECT id, parent_id, review, created_on, score, SUM(score) OVER ( PARTITION BY root_id ) AS total_score FROM post_comment_score ), post_comment_score
@vlad_mihalcea vladmihalcea.com id parent_id review created_on score total_score 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 6 2 1 Comment 1.1 2019-10-14 13:23:10 2 6 3 1 Comment 1.2 2019-10-14 15:45:15 2 6 1 Comment 1 2019-10-13 12:23:05 1 6 6 5 Comment 2.1 2019-10-14 11:23:30 1 3 7 5 Comment 2.2 2019-10-14 14:45:35 1 3 5 Comment 2 2019-10-13 15:23:25 1 3 8 Comment 3 2019-10-15 10:15:40 1 9 9 8 Comment 3.1 2019-10-16 11:15:45 10 9 10 8 Comment 3.2 2019-10-17 18:30:50 -2 9 11 Comment 4 2019-10-19 21:43:55 -5 -5 12 Comment 5 2019-10-22 23:45:00 0 Summing comment scores – 4th root total_score_comment AS ( SELECT id, parent_id, review, created_on, score, SUM(score) OVER ( PARTITION BY root_id ) AS total_score FROM post_comment_score ), total_score_comment
@vlad_mihalcea vladmihalcea.com id parent_id root_id review created_on score 1 1 Comment 1 2019-10-13 12:23:05 1 5 5 Comment 2 2019-10-13 15:23:25 1 8 8 Comment 3 2019-10-15 10:15:40 1 11 11 Comment 4 2019-10-19 21:43:55 -5 12 12 Comment 5 2019-10-22 23:45:00 0 2 1 1 Comment 1.1 2019-10-14 13:23:10 2 3 1 1 Comment 1.2 2019-10-14 15:45:15 2 6 5 5 Comment 2.1 2019-10-14 11:23:30 1 7 5 5 Comment 2.2 2019-10-14 14:45:35 1 9 8 8 Comment 3.1 2019-10-16 11:15:45 10 10 8 8 Comment 3.2 2019-10-17 18:30:50 -2 4 3 1 Comment 1.2.1 2019-10-15 10:15:20 1 Summing comment scores – 5th root total_score_comment AS ( SELECT id, parent_id, review, created_on, score, SUM(score) OVER ( PARTITION BY root_id ) AS total_score FROM post_comment_score ), post_comment_score
@vlad_mihalcea vladmihalcea.com id parent_id review created_on score total_score 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 6 2 1 Comment 1.1 2019-10-14 13:23:10 2 6 3 1 Comment 1.2 2019-10-14 15:45:15 2 6 1 Comment 1 2019-10-13 12:23:05 1 6 6 5 Comment 2.1 2019-10-14 11:23:30 1 3 7 5 Comment 2.2 2019-10-14 14:45:35 1 3 5 Comment 2 2019-10-13 15:23:25 1 3 8 Comment 3 2019-10-15 10:15:40 1 9 9 8 Comment 3.1 2019-10-16 11:15:45 10 9 10 8 Comment 3.2 2019-10-17 18:30:50 -2 9 11 Comment 4 2019-10-19 21:43:55 -5 -5 12 Comment 5 2019-10-22 23:45:00 0 0 Summing comment scores – 5th root total_score_comment AS ( SELECT id, parent_id, review, created_on, score, SUM(score) OVER ( PARTITION BY root_id ) AS total_score FROM post_comment_score ), total_score_comment
@vlad_mihalcea vladmihalcea.com Ranking comment total scores total_score_ranking AS ( SELECT id, parent_id, review, created_on, score, total_score, DENSE_RANK() OVER ( ORDER BY total_score DESC ) ranking FROM total_score_comment ),
@vlad_mihalcea vladmihalcea.com Ranking comment total scores – 1st rank total_score_ranking AS ( SELECT id, parent_id, review, created_on, score, total_score, DENSE_RANK() OVER ( ORDER BY total_score DESC ) ranking FROM total_score_comment ), id parent_id review created_on score total_score 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 6 2 1 Comment 1.1 2019-10-14 13:23:10 2 6 3 1 Comment 1.2 2019-10-14 15:45:15 2 6 1 Comment 1 2019-10-13 12:23:05 1 6 6 5 Comment 2.1 2019-10-14 11:23:30 1 3 7 5 Comment 2.2 2019-10-14 14:45:35 1 3 5 Comment 2 2019-10-13 15:23:25 1 3 8 Comment 3 2019-10-15 10:15:40 1 9 9 8 Comment 3.1 2019-10-16 11:15:45 10 9 10 8 Comment 3.2 2019-10-17 18:30:50 -2 9 11 Comment 4 2019-10-19 21:43:55 -5 -5 12 Comment 5 2019-10-22 23:45:00 0 0 total_score_comme nt
@vlad_mihalcea vladmihalcea.com Ranking comment total scores – 1st rank total_score_ranking AS ( SELECT id, parent_id, review, created_on, score, total_score, DENSE_RANK() OVER ( ORDER BY total_score DESC ) ranking FROM total_score_comment ), id parent_id review created_on score total_score ranking 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 6 2 1 Comment 1.1 2019-10-14 13:23:10 2 6 3 1 Comment 1.2 2019-10-14 15:45:15 2 6 1 Comment 1 2019-10-13 12:23:05 1 6 6 5 Comment 2.1 2019-10-14 11:23:30 1 3 7 5 Comment 2.2 2019-10-14 14:45:35 1 3 5 Comment 2 2019-10-13 15:23:25 1 3 8 Comment 3 2019-10-15 10:15:40 1 9 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 9 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 9 1 11 Comment 4 2019-10-19 21:43:55 -5 -5 12 Comment 5 2019-10-22 23:45:00 0 0 total_score_ranking
@vlad_mihalcea vladmihalcea.com Ranking comment total scores – 2nd rank total_score_ranking AS ( SELECT id, parent_id, review, created_on, score, total_score, DENSE_RANK() OVER ( ORDER BY total_score DESC ) ranking FROM total_score_comment ), id parent_id review created_on score total_score ranking 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 6 2 2 1 Comment 1.1 2019-10-14 13:23:10 2 6 2 3 1 Comment 1.2 2019-10-14 15:45:15 2 6 2 1 Comment 1 2019-10-13 12:23:05 1 6 2 6 5 Comment 2.1 2019-10-14 11:23:30 1 3 7 5 Comment 2.2 2019-10-14 14:45:35 1 3 5 Comment 2 2019-10-13 15:23:25 1 3 8 Comment 3 2019-10-15 10:15:40 1 9 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 9 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 9 1 11 Comment 4 2019-10-19 21:43:55 -5 -5 12 Comment 5 2019-10-22 23:45:00 0 0 total_score_ranking
@vlad_mihalcea vladmihalcea.com Ranking comment total scores – 3rd rank total_score_ranking AS ( SELECT id, parent_id, review, created_on, score, total_score, DENSE_RANK() OVER ( ORDER BY total_score DESC ) ranking FROM total_score_comment ), id parent_id review created_on score total_score ranking 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 6 2 2 1 Comment 1.1 2019-10-14 13:23:10 2 6 2 3 1 Comment 1.2 2019-10-14 15:45:15 2 6 2 1 Comment 1 2019-10-13 12:23:05 1 6 2 6 5 Comment 2.1 2019-10-14 11:23:30 1 3 3 7 5 Comment 2.2 2019-10-14 14:45:35 1 3 3 5 Comment 2 2019-10-13 15:23:25 1 3 3 8 Comment 3 2019-10-15 10:15:40 1 9 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 9 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 9 1 11 Comment 4 2019-10-19 21:43:55 -5 -5 12 Comment 5 2019-10-22 23:45:00 0 0 total_score_ranking
@vlad_mihalcea vladmihalcea.com Ranking comment total scores – 4th rank total_score_ranking AS ( SELECT id, parent_id, review, created_on, score, total_score, DENSE_RANK() OVER ( ORDER BY total_score DESC ) ranking FROM total_score_comment ), id parent_id review created_on score total_score ranking 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 6 2 2 1 Comment 1.1 2019-10-14 13:23:10 2 6 2 3 1 Comment 1.2 2019-10-14 15:45:15 2 6 2 1 Comment 1 2019-10-13 12:23:05 1 6 2 6 5 Comment 2.1 2019-10-14 11:23:30 1 3 3 7 5 Comment 2.2 2019-10-14 14:45:35 1 3 3 5 Comment 2 2019-10-13 15:23:25 1 3 3 8 Comment 3 2019-10-15 10:15:40 1 9 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 9 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 9 1 11 Comment 4 2019-10-19 21:43:55 -5 -5 12 Comment 5 2019-10-22 23:45:00 0 0 4 total_score_ranking
@vlad_mihalcea vladmihalcea.com Ranking comment total scores – 5th rank total_score_ranking AS ( SELECT id, parent_id, review, created_on, score, total_score, DENSE_RANK() OVER ( ORDER BY total_score DESC ) ranking FROM total_score_comment ), id parent_id review created_on score total_score ranking 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 6 2 2 1 Comment 1.1 2019-10-14 13:23:10 2 6 2 3 1 Comment 1.2 2019-10-14 15:45:15 2 6 2 1 Comment 1 2019-10-13 12:23:05 1 6 2 6 5 Comment 2.1 2019-10-14 11:23:30 1 3 3 7 5 Comment 2.2 2019-10-14 14:45:35 1 3 3 5 Comment 2 2019-10-13 15:23:25 1 3 3 8 Comment 3 2019-10-15 10:15:40 1 9 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 9 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 9 1 11 Comment 4 2019-10-19 21:43:55 -5 -5 5 12 Comment 5 2019-10-22 23:45:00 0 0 4 total_score_ranking
@vlad_mihalcea vladmihalcea.com Filtering by the comment total score SELECT id, parent_id, review, created_on, score, total_score FROM total_score_ranking WHERE ranking <= 3 ORDER BY total_score DESC, id ASC
@vlad_mihalcea vladmihalcea.com Filtering by the comment total score SELECT id, parent_id, review, created_on, score, total_score FROM total_score_ranking WHERE ranking <= 3 ORDER BY total_score DESC, id ASC id parent_id review created_on score total_score ranking 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 6 2 2 1 Comment 1.1 2019-10-14 13:23:10 2 6 2 3 1 Comment 1.2 2019-10-14 15:45:15 2 6 2 1 Comment 1 2019-10-13 12:23:05 1 6 2 6 5 Comment 2.1 2019-10-14 11:23:30 1 3 3 7 5 Comment 2.2 2019-10-14 14:45:35 1 3 3 5 Comment 2 2019-10-13 15:23:25 1 3 3 8 Comment 3 2019-10-15 10:15:40 1 9 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 9 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 9 1 11 Comment 4 2019-10-19 21:43:55 -5 -5 5 12 Comment 5 2019-10-22 23:45:00 0 0 4 total_score_ranking
@vlad_mihalcea vladmihalcea.com Filtering by the comment total score SELECT id, parent_id, review, created_on, score, total_score FROM total_score_ranking WHERE ranking <= 3 ORDER BY total_score DESC, id ASC id parent_id review created_on score total_score 8 Comment 3 2019-10-15 10:15:40 1 9 9 8 Comment 3.1 2019-10-16 11:15:45 10 9 10 8 Comment 3.2 2019-10-17 18:30:50 -2 9 1 Comment 1 2019-10-13 12:23:05 1 6 2 1 Comment 1.1 2019-10-14 13:23:10 2 6 3 1 Comment 1.2 2019-10-14 15:45:15 2 6 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 6 5 Comment 2 2019-10-13 15:23:25 1 3 6 5 Comment 2.1 2019-10-14 11:23:30 1 3 7 5 Comment 2.2 2019-10-14 14:45:35 1 3 Result set
@vlad_mihalcea vladmihalcea.com Application-level vs database processing 20 104 656 2040 4640 15024 34880 0 10 20 30 40 50 60 70 80 90 100 Data set size Time(ms) Application-level Recursive CTE
@vlad_mihalcea vladmihalcea.com SQL:2003 • SQL:2003 was a minor version of SQL:1999. • It added support for: • Window Functions, • MERGE statement • SEQUNCE generator and IDENTITY column type, • XML column type
@vlad_mihalcea vladmihalcea.com • Supported databases: • Oracle 9i • SQL Server 2008 • PostgreSQL and MySQL offer non-standard UPSERT alternatives. MERGE
@vlad_mihalcea vladmihalcea.com Oracle MERGE – Ignore on constraint violation MERGE INTO book USING (SELECT 1 FROM dual) ON (id = 1) WHEN NOT MATCHED THEN INSERT ( id, title, isbn ) VALUES ( 1, 'High-Performance Java Persistence', '978-9730228236' )
@vlad_mihalcea vladmihalcea.com Oracle MERGE – UPDATE on constraint violation MERGE INTO book USING (SELECT 1 FROM dual) ON (id = 1) WHEN MATCHED THEN UPDATE SET title = 'High-Performance Java Persistence, 2nd Edition', isbn = '978-9730228236' WHEN NOT MATCHED THEN INSERT ( id, title, isbn ) VALUES ( 1, 'High-Performance Java Persistence', '978-9730228236' )
@vlad_mihalcea vladmihalcea.com SQL:2006 • SQL:2006 added support for: • XQuery, • SQL/XML functions (e.g., XMLELEMENT)
@vlad_mihalcea vladmihalcea.com SQL:2008 • SQL:2008 added support for: • TRUNCATE TABLE, • Multiple WHEN clauses in CASE expressions, • INSTEAD OF database triggers (override INSERT, UPDATE, DELETE), • XQuery regular expression/pattern matching, • Derived column list to override a derived table column names, • Standard pagination using: • FETCH FIRST N ROWS ONLY • OFFSET M ROWS
@vlad_mihalcea vladmihalcea.com SQL – Oracle legacy Top N SELECT t.* FROM ( SELECT title FROM post ORDER BY created_on DESC, id DESC ) t WHERE ROWNUM <= 5 ORDER BY ROWNUM
@vlad_mihalcea vladmihalcea.com SQL – Standard Top N SELECT title FROM post ORDER BY created_on DESC, id DESC FETCH FIRST 5 ROWS ONLY
@vlad_mihalcea vladmihalcea.com SQL – Oracle legacy Next N SELECT t2.* FROM ( SELECT t1.*, ROWNUM AS ROW_NUM FROM ( SELECT title FROM post ORDER BY created_on DESC, id DESC ) t1 WHERE ROWNUM <= 10 ) t2 WHERE ROW_NUM > 5 ORDER BY ROW_NUM
@vlad_mihalcea vladmihalcea.com SQL – Standard Next N SELECT title FROM post ORDER BY created_on DESC, id DESC OFFSET 5 ROWS FETCH NEXT 5 ROWS ONLY
@vlad_mihalcea vladmihalcea.com SQL:2011 • SQL: 2011 added support for • Temporal database, • System-versioned tables
@vlad_mihalcea vladmihalcea.com SQL:2016 • SQL: 2016 added support for: • JSON, • MATCH_RECOGNIZE (Row Pattern Recognition), • LISTAGG (aggregate multiple values to a delimited string value), • DECFLOAT column type (e.g., decimal floating arithmetic), • Date and Time formatting (e.g., CAST(.. AS .. FORMAT ..), EXTRACT(.. FROM <datetime>))
@vlad_mihalcea vladmihalcea.com • Supported databases: • Oracle 12c • SQL Server 2016 • PostgreSQL 9.2 • MySQL 5.6 • PostgreSQL and MySQL offer non-standard alternatives. JSON
@vlad_mihalcea vladmihalcea.com MySQL – storing JSON CREATE TABLE book ( id bigint NOT NULL PRIMARY KEY, isbn VARCHAR(15), properties JSON )
@vlad_mihalcea vladmihalcea.com MySQL – Get scalar attribute SELECT id, CAST( properties -> '$.price' AS DECIMAL(4, 2) ) AS price FROM book WHERE properties -> '$.title' = 'High-Performance Java Persistence' Without casting to DECIMAL, the result will be returned as a String.
@vlad_mihalcea vladmihalcea.com MySQL – Get scalar attribute id isbn properties 1 978-9730228236 { "title":"High-Performance Java Persistence", "author":"Vlad Mihalcea", "publisher":"Amazon", "price":44.99, "reviews":[ … ] } book SELECT id, CAST( properties -> '$.price' AS DECIMAL(4, 2) ) AS price FROM book WHERE properties -> '$.title' = 'High-Performance Java Persistence' id price 1 44.99 Result set
@vlad_mihalcea vladmihalcea.com SELECT id, properties -> '$.reviews' AS reviews FROM book WHERE isbn = '978-9730228236' MySQL – Get JSON object
@vlad_mihalcea vladmihalcea.com MySQL – Get JSON object SELECT id, properties -> '$.reviews' AS reviews FROM book WHERE isbn = '978-9730228236' id isbn properties 1 978-9730228236 { "title":"High-Performance Java Persistence", "author":"Vlad Mihalcea", "publisher":"Amazon", "price":44.99, "reviews":[ { "reviewer":"Cristiano", "review":"Excellent book to understand Java Persistence", "date":"2017-11-14", "rating":5 }, { "reviewer":"T.W", "review":"The best JPA ORM book out there", "date":"2019-01-27", "rating":5 }, { "reviewer":"Shaikh", "review":"The most informative book", "date":"2016-12-24", "rating":4 } ] } book id reviews 1 [ {..}, {..}, {..} ] Result set
@vlad_mihalcea vladmihalcea.com SELECT r.* FROM book, JSON_TABLE( properties, '$.reviews[*]' COLUMNS( reviewer VARCHAR(4000) PATH '$.reviewer', review VARCHAR(4000) PATH '$.review', review_date DATETIME PATH '$.date’, rating INT PATH '$.rating' ) ) AS r WHERE isbn = '978-9730228236' MySQL – JSON to SQL table
@vlad_mihalcea vladmihalcea.com SELECT r.* FROM book, JSON_TABLE( properties, '$.reviews[*]' COLUMNS( reviewer VARCHAR(4000) PATH '$.reviewer', review VARCHAR(4000) PATH '$.review', review_date DATETIME PATH '$.date’, rating INT PATH '$.rating' ) ) AS r WHERE isbn = '978-9730228236' MySQL – JSON to SQL table "reviews":[ { "reviewer":"Cristiano", "review":"Excellent book to understand Java Persistence", "date":"2017-11-14", "rating":5 }, { "reviewer":"T.W", "review":"The best JPA ORM book out there", "date":"2019-01-27", "rating":5 }, { "reviewer":"Shaikh", "review":"The most informative book", "date":"2016-12-24", "rating":4 } ] reviewer review review_date rating book
@vlad_mihalcea vladmihalcea.com SELECT r.* FROM book, JSON_TABLE( properties, '$.reviews[*]' COLUMNS( reviewer VARCHAR(4000) PATH '$.reviewer', review VARCHAR(4000) PATH '$.review', review_date DATETIME PATH '$.date’, rating INT PATH '$.rating' ) ) AS r WHERE isbn = '978-9730228236' MySQL – JSON to SQL table "reviews":[ { "reviewer":"Cristiano", "review":"Excellent book to understand Java Persistence", "date":"2017-11-14", "rating":5 }, { "reviewer":"T.W", "review":"The best JPA ORM book out there", "date":"2019-01-27", "rating":5 }, { "reviewer":"Shaikh", "review":"The most informative book", "date":"2016-12-24", "rating":4 } ] reviewer review review_date rating Cristiano Excellent book to understand Java Persistence 14-Nov-2017 5 book
@vlad_mihalcea vladmihalcea.com SELECT r.* FROM book, JSON_TABLE( properties, '$.reviews[*]' COLUMNS( reviewer VARCHAR(4000) PATH '$.reviewer', review VARCHAR(4000) PATH '$.review', review_date DATETIME PATH '$.date’, rating INT PATH '$.rating' ) ) AS r WHERE isbn = '978-9730228236' MySQL – JSON to SQL table "reviews":[ { "reviewer":"Cristiano", "review":"Excellent book to understand Java Persistence", "date":"2017-11-14", "rating":5 }, { "reviewer":"T.W", "review":"The best JPA ORM book out there", "date":"2019-01-27", "rating":5 }, { "reviewer":"Shaikh", "review":"The most informative book", "date":"2016-12-24", "rating":4 } ] reviewer review review_date rating Cristiano Excellent book to understand Java Persistence 14-Nov-2017 5 T.W The best JPA ORM book out there 27-Jan-2019 5 book
@vlad_mihalcea vladmihalcea.com SELECT r.* FROM book, JSON_TABLE( properties, '$.reviews[*]' COLUMNS( reviewer VARCHAR(4000) PATH '$.reviewer', review VARCHAR(4000) PATH '$.review', review_date DATETIME PATH '$.date’, rating INT PATH '$.rating' ) ) AS r WHERE isbn = '978-9730228236' MySQL – JSON to SQL table "reviews":[ { "reviewer":"Cristiano", "review":"Excellent book to understand Java Persistence", "date":"2017-11-14", "rating":5 }, { "reviewer":"T.W", "review":"The best JPA ORM book out there", "date":"2019-01-27", "rating":5 }, { "reviewer":"Shaikh", "review":"The most informative book", "date":"2016-12-24", "rating":4 } ] reviewer review review_date rating Cristiano Excellent book to understand Java Persistence 14-Nov-2017 5 T.W The best JPA ORM book out there 27-Jan-2019 5 Shaikh The most informative book 24-Dec-2016 4book
@vlad_mihalcea vladmihalcea.com SQL timeline SQL NoSQL NewSQL 1974 2009 2011
@vlad_mihalcea vladmihalcea.com NewSQL https://www.pexels.com/photo/architectural-design-architecture-blue-brazil-416998/
@vlad_mihalcea vladmihalcea.com CockroachDB – SQL support https://www.cockroachlabs.com/docs/v19.1/sql-statements.html
@vlad_mihalcea vladmihalcea.com VoltDB – SQL support https://www.voltdb.com/product/features-benefits/sql-database/
@vlad_mihalcea vladmihalcea.com VoltDB – SQL support https://www.voltdb.com/product/features-benefits/sql-database/
@vlad_mihalcea vladmihalcea.com VoltDB – SQL support https://www.voltdb.com/product/features-benefits/sql-database/
@vlad_mihalcea vladmihalcea.com Google BigQuery – SQL support https://cloud.google.com/bigquery/docs/release-notes#March_23_2016
@vlad_mihalcea vladmihalcea.com Google Spanner – SQL support https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/46103.pdf
@vlad_mihalcea vladmihalcea.com Thank you • Twitter: @vlad_mihalcea • Blog: https://vladmihalcea.com/ • Courses: https://vladmihalcea.com/courses/ • Training: https://vladmihalcea.com/trainings/ • Book: https://vladmihalcea.com/books/high-performance-java-persistence/

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Awesome SQL Tips and Tricks - Voxxed Days Cluj - 2019

  • 2. @vlad_mihalcea vladmihalcea.com About me • Java Champion • vladmihalcea.com • @vlad_mihalcea • vladmihalcea
  • 3. @vlad_mihalcea vladmihalcea.com InfoQ – Trends Report https://www.infoq.com/articles/architecture-trends-2019/
  • 4. @vlad_mihalcea vladmihalcea.com InfoQ – Trends Report https://www.infoq.com/articles/architecture-trends-2019/
  • 5. @vlad_mihalcea vladmihalcea.com StackOverflow Survey – Most Popular Technologies https://insights.stackoverflow.com/survey/2019
  • 6. @vlad_mihalcea vladmihalcea.com SQL is old school https://www.pexels.com/photo/antique-blur-classic-close-up-595699/
  • 7. @vlad_mihalcea vladmihalcea.com SQL – ‘70s 1970 E.F. Codd’s from IBM Relational Model 1974 D. D. Chamberlin & R. F. Boyce IBM System R 1974 Michael Stonebraker Berkeley Ingres 1979 Relational Software, Inc. Oracle V2 Marketing
  • 8. @vlad_mihalcea vladmihalcea.com SQL – ‘80s IBM System R 1981 IBM SQL/DS 1983 IBM DB2 1987 IBM DB2 for OS/2 1985 Robert Epstein Sybase Berkeley Ingres 1988 Microsoft Sybase SQL Server 1985 Michael Stonebraker POSTGRES
  • 9. @vlad_mihalcea vladmihalcea.com SQL – ‘90s 1995 David Axmark & Michael Widenius MySQL Sybase SQL Server 1993 Microsoft SQL Server POSTGRES 1996 PostgreSQL
  • 10. @vlad_mihalcea vladmihalcea.com Why is SQL still used? https://qr.ae/TWCBD5
  • 11. @vlad_mihalcea vladmihalcea.com StackOverflow Survey – Most Popular Databases https://insights.stackoverflow.com/survey/2019
  • 12. @vlad_mihalcea vladmihalcea.com StackOverflow Survey – Most Popular Databases https://insights.stackoverflow.com/survey/2019
  • 13. @vlad_mihalcea vladmihalcea.com What does SQL stand for? S? Query Language
  • 14. @vlad_mihalcea vladmihalcea.com What does SQL stand for? https://twitter.com/vlad_mihalcea/status/1172446336131596289
  • 15. @vlad_mihalcea vladmihalcea.com SQL Standard Photo by Frederick Tubiermont on Unsplash https://unsplash.com/photos/fJSRg-r7LuI
  • 17. @vlad_mihalcea vladmihalcea.com SQL:92 • In 1992, a major version of the standard was released. The specification grew from 115 pages to 580. • SQL:92 adds support for: • DATE, TIME, TIMESTAMP, INTERVAL, BIT, VARCHAR, NVARCHAR, • UNION, NATURAL JOIN, • CASE expressions, • CHECK constraints, • Type casting (e.g., CAST (expr AS type))
  • 18. @vlad_mihalcea vladmihalcea.com SQL:92 • Other SQL:92 features include: • INFORMATION_SCHEMA, • Dynamic query execution (e.g., java.sql.Statement). Previously, only prepared statements were supported. • Temporary tables, • Custom isolation levels, • Database cursors, • Scalar operations like String concatenation, date manipulation.
  • 20. @vlad_mihalcea vladmihalcea.com Fetching one-to-many relationship with pagination We need to get the first 2 post entries starting with a given string value, along with all their associated post_comment child records.
  • 21. @vlad_mihalcea vladmihalcea.com post id review post_id 1 SQL:2016 is great! 1 2 SQL:2016 is excellent! 1 3 SQL:20016 is awesome! 1 4 SQL:2011 is great! 2 5 SQL:2011 is excellent! 2 7 SQL:2008 is great! 3 id title 1 SQL:2016 2 SQL:2011 3 SQL:2008 Fetching one-to-many relationship with pagination post_comment post_id post_title comment_id comment_review 1 SQL:2016 1 SQL:2016 is great! 1 SQL:2016 2 SQL:2016 is excellent! 1 SQL:2016 3 SQL:20016 is awesome! Result set
  • 22. @vlad_mihalcea vladmihalcea.com post id review post_id 1 SQL:2016 is great! 1 2 SQL:2016 is excellent! 1 3 SQL:20016 is awesome! 1 4 SQL:2011 is great! 2 5 SQL:2011 is excellent! 2 7 SQL:2008 is great! 3 id title 1 SQL:2016 2 SQL:2011 3 SQL:2008 Fetching one-to-many relationship with pagination post_comment post_id post_title comment_id comment_review 1 SQL:2016 1 SQL:2016 is great! 1 SQL:2016 2 SQL:2016 is excellent! 1 SQL:2016 3 SQL:20016 is awesome! 2 SQL:2011 4 SQL:2011 is great! 2 SQL:2011 5 SQL:2011 is excellent! Result set
  • 23. @vlad_mihalcea vladmihalcea.com JPQL – Join fetch with Pagination List<Post> posts = entityManager .createQuery( """ select p from Post p left join fetch p.comments pc where p.title like :title order by p.id, pc.id """, Post.class) .setParameter("title", "SQL%") .setMaxResults(2) .getResultList();
  • 24. @vlad_mihalcea vladmihalcea.com JPQL – Join fetch with Pagination WARN [main]: QueryTranslatorImpl - HHH000104: firstResult/maxResults specified with collection fetch; applying in memory! SELECT p.id AS id1_0_0_, p.title AS title3_0_0_, pc.id AS id1_1_0__, pc.post_id AS post_id4_1_1_, pc.review AS review3_1_1_ FROM post p LEFT OUTER JOIN post_comment pc ON p.id = pc.post_id WHERE p.title LIKE 'SQL%' ORDER BY p.id, pc.id
  • 25. @vlad_mihalcea vladmihalcea.com SQL – Join fetch with Pagination SELECT p.id AS post_id, p.title AS post_title, pc.id AS comment_id, pc.review AS comment_review FROM post p LEFT JOIN post_comment pc ON p.id = pc.post_id WHERE p.id IN ( SELECT id FROM post WHERE p.title LIKE 'SQL%' ORDER BY id LIMIT 2 ) ORDER BY post_id, comment_id
  • 26. @vlad_mihalcea vladmihalcea.com SQL – Derived tables – Oracle Top N SELECT t.* FROM ( SELECT title FROM post ORDER BY created_on DESC, id DESC ) t WHERE ROWNUM <= 5 ORDER BY ROWNUM We must sort the result set prior to assigning the row ranking numbers.
  • 27. @vlad_mihalcea vladmihalcea.com SQL – Derived tables – Oracle Top N SELECT t.* FROM ( SELECT title FROM post ORDER BY created_on DESC, id DESC ) t WHERE ROWNUM <= 5 ORDER BY ROWNUM The outer query can now limit the result set size.
  • 28. @vlad_mihalcea vladmihalcea.com SQL – Derived tables – Oracle Next N SELECT t2.* FROM ( SELECT t1.*, ROWNUM AS ROW_NUM FROM ( SELECT title FROM post ORDER BY created_on DESC, id DESC ) t1 WHERE ROWNUM <= 10 ) t2 WHERE ROW_NUM > 5 ORDER BY ROW_NUM We must sort the result set prior to assigning the row ranking numbers.
  • 29. @vlad_mihalcea vladmihalcea.com SQL – Derived tables – Oracle Next N SELECT t2.* FROM ( SELECT t1.*, ROWNUM AS ROW_NUM FROM ( SELECT title FROM post ORDER BY created_on DESC, id DESC ) t1 WHERE ROWNUM <= 10 ) t2 WHERE ROW_NUM > 5 ORDER BY ROW_NUM The following outer query can now limit the result set size.
  • 30. @vlad_mihalcea vladmihalcea.com SQL – Derived tables – Oracle Next N SELECT t2.* FROM ( SELECT t1.*, ROWNUM AS ROW_NUM FROM ( SELECT title FROM post ORDER BY created_on DESC, id DESC ) t1 WHERE ROWNUM <= 10 ) t2 WHERE ROW_NUM > 5 ORDER BY ROW_NUM The outer-most query can set the offset where we want to start streaming the result set back to the DB client.
  • 32. @vlad_mihalcea vladmihalcea.com SQL Standard timeline SQL:86 SQL:89 SQL:92
  • 33. @vlad_mihalcea vladmihalcea.com SQL Standard timeline SQL:86 SQL:89 SQL:92 SQL:1999 SQL:2011 SQL:2008 SQL:2006 SQL:2003 SQL:2016
  • 34. @vlad_mihalcea vladmihalcea.com SQL:1999 • In 1999, a new major version of the standard was released. • It added support for: • Boolean column type, • WITH CTE (Common Table Expression) queries and WITH RECURSIVE queries for hierarchic queries, • ROLLUP, CUBE, GROUPING SETS for GROUP BY, • Initial support for ARRAY types (e.g., UNNEST)
  • 35. @vlad_mihalcea vladmihalcea.com Pyramid of Doom SELECT t2.* FROM ( SELECT t1.*, ROWNUM AS ROW_NUM FROM ( SELECT title FROM post ORDER BY created_on DESC, id DESC ) t1 WHERE ROWNUM <= 10 ) t2 WHERE ROW_NUM > 5 ORDER BY ROW_NUM
  • 36. @vlad_mihalcea vladmihalcea.com • Supported databases: • Oracle 9i R2 • SQL Server 2005 • PostgreSQL 8.4 • MySQL 8.0.1 • MariaDB 10.2.1 CTE (Common Table Expression)
  • 37. @vlad_mihalcea vladmihalcea.com SQL – CTE WITH p AS ( SELECT title FROM post ORDER BY created_on DESC, id DESC ), p_limit AS ( SELECT p.*, ROWNUM AS ROW_NUM FROM p WHERE ROWNUM <= 10 ) SELECT title FROM p_limit WHERE ROW_NUM > 5 ORDER BY ROWNUM
  • 38. @vlad_mihalcea vladmihalcea.com SQL – CTE WITH p AS ( SELECT title FROM post ORDER BY created_on DESC, id DESC ), p_limit AS ( SELECT p.*, ROWNUM AS ROW_NUM FROM p WHERE ROWNUM <= 10 ) SELECT title FROM p_limit WHERE ROW_NUM > 5 ORDER BY ROWNUM
  • 39. @vlad_mihalcea vladmihalcea.com SQL – CTE WITH p AS ( SELECT title FROM post ORDER BY created_on DESC, id DESC ), p_limit AS ( SELECT p.*, ROWNUM AS ROW_NUM FROM p WHERE ROWNUM <= 10 ) SELECT title FROM p_limit WHERE ROW_NUM > 5 ORDER BY ROWNUM
  • 40. @vlad_mihalcea vladmihalcea.com Fetching hierarchical data 6 + 2 + 2 + 1 + … total_score
  • 42. @vlad_mihalcea vladmihalcea.com Fetch the top 3 comment hierarchies by total score We need to get the top 3 post_comment hierarchies based on their total post_comment score.
  • 43. @vlad_mihalcea vladmihalcea.com id parent_id review created_on score post_id 1 Comment 1 2019-10-13 12:23:05 1 1 2 1 Comment 1.1 2019-10-14 13:23:10 2 1 3 1 Comment 1.2 2019-10-14 15:45:15 2 1 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 1 5 Comment 2 2019-10-13 15:23:25 1 1 6 5 Comment 2.1 2019-10-14 11:23:30 1 1 7 5 Comment 2.2 2019-10-14 14:45:35 1 1 8 Comment 3 2019-10-15 10:15:40 1 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 1 11 Comment 4 2019-10-19 21:43:55 -5 1 12 Comment 5 2019-10-22 23:45:00 0 1 Fetching hierarchical data – table records post_comment 4 = 1 + 2 + 2 + 1 total_score
  • 44. @vlad_mihalcea vladmihalcea.com id parent_id review created_on score post_id 1 Comment 1 2019-10-13 12:23:05 1 1 2 1 Comment 1.1 2019-10-14 13:23:10 2 1 3 1 Comment 1.2 2019-10-14 15:45:15 2 1 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 1 5 Comment 2 2019-10-13 15:23:25 1 1 6 5 Comment 2.1 2019-10-14 11:23:30 1 1 7 5 Comment 2.2 2019-10-14 14:45:35 1 1 8 Comment 3 2019-10-15 10:15:40 1 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 1 11 Comment 4 2019-10-19 21:43:55 -5 1 12 Comment 5 2019-10-22 23:45:00 0 1 Fetching hierarchical data – table records post_comment 3 = 1 + 1 + 1 total_score
  • 45. @vlad_mihalcea vladmihalcea.com id parent_id review created_on score post_id 1 Comment 1 2019-10-13 12:23:05 1 1 2 1 Comment 1.1 2019-10-14 13:23:10 2 1 3 1 Comment 1.2 2019-10-14 15:45:15 2 1 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 1 5 Comment 2 2019-10-13 15:23:25 1 1 6 5 Comment 2.1 2019-10-14 11:23:30 1 1 7 5 Comment 2.2 2019-10-14 14:45:35 1 1 8 Comment 3 2019-10-15 10:15:40 1 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 1 11 Comment 4 2019-10-19 21:43:55 -5 1 12 Comment 5 2019-10-22 23:45:00 0 1 Fetching hierarchical data – table records post_comment 9 = 1 + 10 - 2 total_score
  • 46. @vlad_mihalcea vladmihalcea.com id parent_id review created_on score post_id 1 Comment 1 2019-10-13 12:23:05 1 1 2 1 Comment 1.1 2019-10-14 13:23:10 2 1 3 1 Comment 1.2 2019-10-14 15:45:15 2 1 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 1 5 Comment 2 2019-10-13 15:23:25 1 1 6 5 Comment 2.1 2019-10-14 11:23:30 1 1 7 5 Comment 2.2 2019-10-14 14:45:35 1 1 8 Comment 3 2019-10-15 10:15:40 1 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 1 11 Comment 4 2019-10-19 21:43:55 -5 1 12 Comment 5 2019-10-22 23:45:00 0 1 Fetching hierarchical data – table records post_comment -5 total_score
  • 47. @vlad_mihalcea vladmihalcea.com id parent_id review created_on score post_id 1 Comment 1 2019-10-13 12:23:05 1 1 2 1 Comment 1.1 2019-10-14 13:23:10 2 1 3 1 Comment 1.2 2019-10-14 15:45:15 2 1 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 1 5 Comment 2 2019-10-13 15:23:25 1 1 6 5 Comment 2.1 2019-10-14 11:23:30 1 1 7 5 Comment 2.2 2019-10-14 14:45:35 1 1 8 Comment 3 2019-10-15 10:15:40 1 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 1 11 Comment 4 2019-10-19 21:43:55 -5 1 12 Comment 5 2019-10-22 23:45:00 0 1 Fetching hierarchical data – table records post_comment 0 total_score
  • 48. @vlad_mihalcea vladmihalcea.com id parent_id review created_on score post_id 1 Comment 1 2019-10-13 12:23:05 1 1 2 1 Comment 1.1 2019-10-14 13:23:10 2 1 3 1 Comment 1.2 2019-10-14 15:45:15 2 1 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 1 5 Comment 2 2019-10-13 15:23:25 1 1 6 5 Comment 2.1 2019-10-14 11:23:30 1 1 7 5 Comment 2.2 2019-10-14 14:45:35 1 1 8 Comment 3 2019-10-15 10:15:40 1 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 1 11 Comment 4 2019-10-19 21:43:55 -5 1 12 Comment 5 2019-10-22 23:45:00 0 1 Fetching all data – application-level sorting SELECT id, parent_id, review, created_on, score FROM post_comment WHERE post_id = 1 post_comment
  • 49. @vlad_mihalcea vladmihalcea.com Fetching all data – application-level sorting Map<Long, PostCommentScore> postCommentScoreMap = postCommentScores .stream() .collect(Collectors.toMap(PostCommentScore::getId, Function.identity())); List<PostCommentScore> postCommentRoots = postCommentScores .stream() .filter(pcs -> { boolean isRoot = pcs.getParentId() == null; if(!isRoot) { postCommentScoreMap.get(pcs.getParentId()).addChild(pcs); } return isRoot; }) .sorted( Comparator.comparing(PostCommentScore::getTotalScore).reversed() ) .limit(ranking) .collect(Collectors.toList());
  • 50. @vlad_mihalcea vladmihalcea.com id parent_id review created_on score post_id 1 Comment 1 2019-10-13 12:23:05 1 1 2 1 Comment 1.1 2019-10-14 13:23:10 2 1 3 1 Comment 1.2 2019-10-14 15:45:15 2 1 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 1 5 Comment 2 2019-10-13 15:23:25 1 1 6 5 Comment 2.1 2019-10-14 11:23:30 1 1 7 5 Comment 2.2 2019-10-14 14:45:35 1 1 8 Comment 3 2019-10-15 10:15:40 1 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 1 11 Comment 4 2019-10-19 21:43:55 -5 1 12 Comment 5 2019-10-22 23:45:00 0 1 Fetching hierarchical data – 1st level SELECT id, parent_id, review, created_on, score FROM post_comment WHERE post_id = 1 AND parent_id IS NULL Fetch all root-level comments. post_comment
  • 51. @vlad_mihalcea vladmihalcea.com id parent_id review created_on score post_id 1 Comment 1 2019-10-13 12:23:05 1 1 2 1 Comment 1.1 2019-10-14 13:23:10 2 1 3 1 Comment 1.2 2019-10-14 15:45:15 2 1 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 1 5 Comment 2 2019-10-13 15:23:25 1 1 6 5 Comment 2.1 2019-10-14 11:23:30 1 1 7 5 Comment 2.2 2019-10-14 14:45:35 1 1 8 Comment 3 2019-10-15 10:15:40 1 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 1 11 Comment 4 2019-10-19 21:43:55 -5 1 12 Comment 5 2019-10-22 23:45:00 0 1 Fetching hierarchical data – 2nd level WITH pc_r AS ( SELECT id, parent_id, review, created_on, score FROM post_comment WHERE post_id = 1 AND parent_id IS NULL ) SELECT * FROM pc_r UNION ALL SELECT pc.id, pc.parent_id, pc.review, pc.created_on, pc.score FROM post_comment pc INNER JOIN pc_r ON pc_r.id = pc.parent_id post_comment
  • 52. @vlad_mihalcea vladmihalcea.com id parent_id review created_on score post_id 1 Comment 1 2019-10-13 12:23:05 1 1 2 1 Comment 1.1 2019-10-14 13:23:10 2 1 3 1 Comment 1.2 2019-10-14 15:45:15 2 1 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 1 5 Comment 2 2019-10-13 15:23:25 1 1 6 5 Comment 2.1 2019-10-14 11:23:30 1 1 7 5 Comment 2.2 2019-10-14 14:45:35 1 1 8 Comment 3 2019-10-15 10:15:40 1 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 1 11 Comment 4 2019-10-19 21:43:55 -5 1 12 Comment 5 2019-10-22 23:45:00 0 1 Fetching hierarchical data – 2nd level WITH pc_r AS ( SELECT id, parent_id, review, created_on, score FROM post_comment WHERE post_id = 1 AND parent_id IS NULL ) SELECT * FROM pc_r UNION ALL SELECT pc.id, pc.parent_id, pc.review, pc.created_on, pc.score FROM post_comment pc INNER JOIN pc_r ON pc_r.id = pc.parent_id post_comment
  • 53. @vlad_mihalcea vladmihalcea.com Fetching hierarchical data – Nth level This approach of merging manually (using UNION ALL) the result sets of each individual level is cumbersome and requires us knowing the number of levels upfront.
  • 54. @vlad_mihalcea vladmihalcea.com SQL – Recursive CTE WITH RECURSIVE post_comment_score(id, root_id, post_id, parent_id, review, created_on, score) AS ( ) The result set table built recursively
  • 55. @vlad_mihalcea vladmihalcea.com SQL – Recursive CTE WITH RECURSIVE post_comment_score(id, root_id, post_id, parent_id, review, created_on, score) AS ( ) We want to propagate the root_id to all comments belonging to the same hierarchy.
  • 56. @vlad_mihalcea vladmihalcea.com SQL – Recursive CTE WITH RECURSIVE post_comment_score(id, root_id, post_id, parent_id, review, created_on, score) AS ( SELECT id, id, post_id, parent_id, review, created_on, score FROM post_comment WHERE post_id = 1 AND parent_id IS NULL ) Anchor member – the 1st level
  • 57. @vlad_mihalcea vladmihalcea.com SQL – Recursive CTE WITH RECURSIVE post_comment_score(id, root_id, post_id, parent_id, review, created_on, score) AS ( SELECT id, id, post_id, parent_id, review, created_on, score FROM post_comment WHERE post_id = 1 AND parent_id IS NULL ) Anchor member – the 1st level
  • 58. @vlad_mihalcea vladmihalcea.com SQL – Recursive CTE WITH RECURSIVE post_comment_score(id, root_id, post_id, parent_id, review, created_on, score) AS ( SELECT id, id, post_id, parent_id, review, created_on, score FROM post_comment WHERE post_id = 1 AND parent_id IS NULL UNION ALL SELECT pc.id, pcs.root_id, pc.post_id, pc.parent_id, pc.review, pc.created_on, pc.score FROM post_comment pc INNER JOIN post_comment_score pcs ON pc.parent_id = pcs.id ) Recursive member – the 2nd to Nth level
  • 59. @vlad_mihalcea vladmihalcea.com SQL – Recursive CTE WITH RECURSIVE post_comment_score(id, root_id, post_id, parent_id, review, created_on, score) AS ( SELECT id, id, post_id, parent_id, review, created_on, score FROM post_comment WHERE post_id = 1 AND parent_id IS NULL UNION ALL SELECT pc.id, pcs.root_id, pc.post_id, pc.parent_id, pc.review, pc.created_on, pc.score FROM post_comment pc INNER JOIN post_comment_score pcs ON pc.parent_id = pcs.id ) Joining the current and previous levels
  • 60. @vlad_mihalcea vladmihalcea.com SQL – Recursive CTE WITH RECURSIVE post_comment_score(id, root_id, post_id, parent_id, review, created_on, score) AS ( SELECT id, id, post_id, parent_id, review, created_on, score FROM post_comment WHERE post_id = 1 AND parent_id IS NULL UNION ALL SELECT pc.id, pcs.root_id, pc.post_id, pc.parent_id, pc.review, pc.created_on, pc.score FROM post_comment pc INNER JOIN post_comment_score pcs ON pc.parent_id = pcs.id ) SELECT id, parent_id, root_id, review, created_on, score FROM post_comment_score Result set projection query
  • 61. @vlad_mihalcea vladmihalcea.com Recursive CTE – 1st level WITH RECURSIVE post_comment_score( id, root_id, post_id, parent_id, review, created_on, score) AS ( SELECT id, id, post_id, parent_id, review, created_on, score FROM post_comment WHERE post_id = 1 AND parent_id IS NULL UNION ALL SELECT pc.id, pcs.root_id, pc.post_id, pc.parent_id, pc.review, pc.created_on, pc.score FROM post_comment pc INNER JOIN post_comment_score pcs ON pc.parent_id = pcs.id ) SELECT id, parent_id, root_id, review, created_on, score FROM post_comment_score id parent_id review created_on score post_id 1 Comment 1 2019-10-13 12:23:05 1 1 2 1 Comment 1.1 2019-10-14 13:23:10 2 1 3 1 Comment 1.2 2019-10-14 15:45:15 2 1 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 1 5 Comment 2 2019-10-13 15:23:25 1 1 6 5 Comment 2.1 2019-10-14 11:23:30 1 1 7 5 Comment 2.2 2019-10-14 14:45:35 1 1 8 Comment 3 2019-10-15 10:15:40 1 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 1 11 Comment 4 2019-10-19 21:43:55 -5 1 12 Comment 5 2019-10-22 23:45:00 0 1 post_comment
  • 62. @vlad_mihalcea vladmihalcea.com id parent_id root_id review created_on score 1 1 Comment 1 2019-10-13 12:23:05 1 5 5 Comment 2 2019-10-13 15:23:25 1 8 8 Comment 3 2019-10-15 10:15:40 1 11 11 Comment 4 2019-10-19 21:43:55 -5 12 12 Comment 5 2019-10-22 23:45:00 0 Recursive CTE – 1st level WITH RECURSIVE post_comment_score( id, root_id, post_id, parent_id, review, created_on, score) AS ( SELECT id, id, post_id, parent_id, review, created_on, score FROM post_comment WHERE post_id = 1 AND parent_id IS NULL UNION ALL SELECT pc.id, pcs.root_id, pc.post_id, pc.parent_id, pc.review, pc.created_on, pc.score FROM post_comment pc INNER JOIN post_comment_score pcs ON pc.parent_id = pcs.id ) SELECT id, parent_id, root_id, review, created_on, score FROM post_comment_score post_comment_score
  • 63. @vlad_mihalcea vladmihalcea.com Recursive CTE – 2nd level WITH RECURSIVE post_comment_score( id, root_id, post_id, parent_id, review, created_on, score) AS ( SELECT id, id, post_id, parent_id, review, created_on, score FROM post_comment WHERE post_id = 1 AND parent_id IS NULL UNION ALL SELECT pc.id, pcs.root_id, pc.post_id, pc.parent_id, pc.review, pc.created_on, pc.score FROM post_comment pc INNER JOIN post_comment_score pcs ON pc.parent_id = pcs.id ) SELECT id, parent_id, root_id, review, created_on, score FROM post_comment_score id parent_id review created_on score post_id 1 Comment 1 2019-10-13 12:23:05 1 1 2 1 Comment 1.1 2019-10-14 13:23:10 2 1 3 1 Comment 1.2 2019-10-14 15:45:15 2 1 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 1 5 Comment 2 2019-10-13 15:23:25 1 1 6 5 Comment 2.1 2019-10-14 11:23:30 1 1 7 5 Comment 2.2 2019-10-14 14:45:35 1 1 8 Comment 3 2019-10-15 10:15:40 1 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 1 11 Comment 4 2019-10-19 21:43:55 -5 1 12 Comment 5 2019-10-22 23:45:00 0 1 post_comment
  • 64. @vlad_mihalcea vladmihalcea.com id parent_id root_id review created_on score 1 1 Comment 1 2019-10-13 12:23:05 1 5 5 Comment 2 2019-10-13 15:23:25 1 8 8 Comment 3 2019-10-15 10:15:40 1 11 11 Comment 4 2019-10-19 21:43:55 -5 12 12 Comment 5 2019-10-22 23:45:00 0 2 1 1 Comment 1.1 2019-10-14 13:23:10 2 3 1 1 Comment 1.2 2019-10-14 15:45:15 2 6 5 5 Comment 2.1 2019-10-14 11:23:30 1 7 5 5 Comment 2.2 2019-10-14 14:45:35 1 9 8 8 Comment 3.1 2019-10-16 11:15:45 10 10 8 8 Comment 3.2 2019-10-17 18:30:50 -2 Recursive CTE – 2nd level WITH RECURSIVE post_comment_score( id, root_id, post_id, parent_id, review, created_on, score) AS ( SELECT id, id, post_id, parent_id, review, created_on, score FROM post_comment WHERE post_id = 1 AND parent_id IS NULL UNION ALL SELECT pc.id, pcs.root_id, pc.post_id, pc.parent_id, pc.review, pc.created_on, pc.score FROM post_comment pc INNER JOIN post_comment_score pcs ON pc.parent_id = pcs.id ) SELECT id, parent_id, root_id, review, created_on, score FROM post_comment_score post_comment_score
  • 65. @vlad_mihalcea vladmihalcea.com Recursive CTE – 3rd level WITH RECURSIVE post_comment_score( id, root_id, post_id, parent_id, review, created_on, score) AS ( SELECT id, id, post_id, parent_id, review, created_on, score FROM post_comment WHERE post_id = 1 AND parent_id IS NULL UNION ALL SELECT pc.id, pcs.root_id, pc.post_id, pc.parent_id, pc.review, pc.created_on, pc.score FROM post_comment pc INNER JOIN post_comment_score pcs ON pc.parent_id = pcs.id ) SELECT id, parent_id, root_id, review, created_on, score FROM post_comment_score id parent_id review created_on score post_id 1 Comment 1 2019-10-13 12:23:05 1 1 2 1 Comment 1.1 2019-10-14 13:23:10 2 1 3 1 Comment 1.2 2019-10-14 15:45:15 2 1 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 1 5 Comment 2 2019-10-13 15:23:25 1 1 6 5 Comment 2.1 2019-10-14 11:23:30 1 1 7 5 Comment 2.2 2019-10-14 14:45:35 1 1 8 Comment 3 2019-10-15 10:15:40 1 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 1 11 Comment 4 2019-10-19 21:43:55 -5 1 12 Comment 5 2019-10-22 23:45:00 0 1 post_comment
  • 66. @vlad_mihalcea vladmihalcea.com id parent_id root_id review created_on score 1 1 Comment 1 2019-10-13 12:23:05 1 5 5 Comment 2 2019-10-13 15:23:25 1 8 8 Comment 3 2019-10-15 10:15:40 1 11 11 Comment 4 2019-10-19 21:43:55 -5 12 12 Comment 5 2019-10-22 23:45:00 0 2 1 1 Comment 1.1 2019-10-14 13:23:10 2 3 1 1 Comment 1.2 2019-10-14 15:45:15 2 6 5 5 Comment 2.1 2019-10-14 11:23:30 1 7 5 5 Comment 2.2 2019-10-14 14:45:35 1 9 8 8 Comment 3.1 2019-10-16 11:15:45 10 10 8 8 Comment 3.2 2019-10-17 18:30:50 -2 4 3 1 Comment 1.2.1 2019-10-15 10:15:20 1 Recursive CTE – 3rd level WITH RECURSIVE post_comment_score( id, root_id, post_id, parent_id, review, created_on, score) AS ( SELECT id, id, post_id, parent_id, review, created_on, score FROM post_comment WHERE post_id = 1 AND parent_id IS NULL UNION ALL SELECT pc.id, pcs.root_id, pc.post_id, pc.parent_id, pc.review, pc.created_on, pc.score FROM post_comment pc INNER JOIN post_comment_score pcs ON pc.parent_id = pcs.id ) SELECT id, parent_id, root_id, review, created_on, score FROM post_comment_score post_comment_score
  • 67. @vlad_mihalcea vladmihalcea.com id parent_id root_id review created_on score 1 1 Comment 1 2019-10-13 12:23:05 1 5 5 Comment 2 2019-10-13 15:23:25 1 8 8 Comment 3 2019-10-15 10:15:40 1 11 11 Comment 4 2019-10-19 21:43:55 -5 12 12 Comment 5 2019-10-22 23:45:00 0 2 1 1 Comment 1.1 2019-10-14 13:23:10 2 3 1 1 Comment 1.2 2019-10-14 15:45:15 2 6 5 5 Comment 2.1 2019-10-14 11:23:30 1 7 5 5 Comment 2.2 2019-10-14 14:45:35 1 9 8 8 Comment 3.1 2019-10-16 11:15:45 10 10 8 8 Comment 3.2 2019-10-17 18:30:50 -2 4 3 1 Comment 1.2.1 2019-10-15 10:15:20 1 Why use Recursive CTE? post_comment_score
  • 68. @vlad_mihalcea vladmihalcea.com Window Functions Photo by Numendil on Unsplash https://unsplash.com/photos/sSKNdbv3qNg
  • 69. @vlad_mihalcea vladmihalcea.com SQL:2003 • SQL:2003 was a minor version of SQL:1999. • It added support for: • Window Functions, • MERGE statement • SEQUNCE generator and IDENTITY column type, • XML column type
  • 70. @vlad_mihalcea vladmihalcea.com • Supported databases: • Oracle 8i • SQL Server 2005 • PostgreSQL 8.4 • MySQL 8.0.2 • MariaDB 10.2.0 Window Functions
  • 71. @vlad_mihalcea vladmihalcea.com Summing up comment scores by root_id total_score_comment AS ( SELECT id, parent_id, review, created_on, score, SUM(score) OVER ( PARTITION BY root_id ) AS total_score FROM post_comment_score ),
  • 72. @vlad_mihalcea vladmihalcea.com id parent_id root_id review created_on score 1 1 Comment 1 2019-10-13 12:23:05 1 5 5 Comment 2 2019-10-13 15:23:25 1 8 8 Comment 3 2019-10-15 10:15:40 1 11 11 Comment 4 2019-10-19 21:43:55 -5 12 12 Comment 5 2019-10-22 23:45:00 0 2 1 1 Comment 1.1 2019-10-14 13:23:10 2 3 1 1 Comment 1.2 2019-10-14 15:45:15 2 6 5 5 Comment 2.1 2019-10-14 11:23:30 1 7 5 5 Comment 2.2 2019-10-14 14:45:35 1 9 8 8 Comment 3.1 2019-10-16 11:15:45 10 10 8 8 Comment 3.2 2019-10-17 18:30:50 -2 4 3 1 Comment 1.2.1 2019-10-15 10:15:20 1 Summing comment scores – 1st root total_score_comment AS ( SELECT id, parent_id, review, created_on, score, SUM(score) OVER ( PARTITION BY root_id ) AS total_score FROM post_comment_score ), post_comment_score
  • 73. @vlad_mihalcea vladmihalcea.com id parent_id review created_on score total_score 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 6 2 1 Comment 1.1 2019-10-14 13:23:10 2 6 3 1 Comment 1.2 2019-10-14 15:45:15 2 6 1 Comment 1 2019-10-13 12:23:05 1 6 6 5 Comment 2.1 2019-10-14 11:23:30 1 7 5 Comment 2.2 2019-10-14 14:45:35 1 5 Comment 2 2019-10-13 15:23:25 1 8 Comment 3 2019-10-15 10:15:40 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 10 8 Comment 3.2 2019-10-17 18:30:50 -2 11 Comment 4 2019-10-19 21:43:55 -5 12 Comment 5 2019-10-22 23:45:00 0 Summing comment scores – 1st root total_score_comment AS ( SELECT id, parent_id, review, created_on, score, SUM(score) OVER ( PARTITION BY root_id ) AS total_score FROM post_comment_score ), total_score_comment
  • 74. @vlad_mihalcea vladmihalcea.com id parent_id root_id review created_on score 1 1 Comment 1 2019-10-13 12:23:05 1 5 5 Comment 2 2019-10-13 15:23:25 1 8 8 Comment 3 2019-10-15 10:15:40 1 11 11 Comment 4 2019-10-19 21:43:55 -5 12 12 Comment 5 2019-10-22 23:45:00 0 2 1 1 Comment 1.1 2019-10-14 13:23:10 2 3 1 1 Comment 1.2 2019-10-14 15:45:15 2 6 5 5 Comment 2.1 2019-10-14 11:23:30 1 7 5 5 Comment 2.2 2019-10-14 14:45:35 1 9 8 8 Comment 3.1 2019-10-16 11:15:45 10 10 8 8 Comment 3.2 2019-10-17 18:30:50 -2 4 3 1 Comment 1.2.1 2019-10-15 10:15:20 1 Summing comment scores – 2nd root total_score_comment AS ( SELECT id, parent_id, review, created_on, score, SUM(score) OVER ( PARTITION BY root_id ) AS total_score FROM post_comment_score ), post_comment_score
  • 75. @vlad_mihalcea vladmihalcea.com id parent_id review created_on score total_score 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 6 2 1 Comment 1.1 2019-10-14 13:23:10 2 6 3 1 Comment 1.2 2019-10-14 15:45:15 2 6 1 Comment 1 2019-10-13 12:23:05 1 6 6 5 Comment 2.1 2019-10-14 11:23:30 1 3 7 5 Comment 2.2 2019-10-14 14:45:35 1 3 5 Comment 2 2019-10-13 15:23:25 1 3 8 Comment 3 2019-10-15 10:15:40 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 10 8 Comment 3.2 2019-10-17 18:30:50 -2 11 Comment 4 2019-10-19 21:43:55 -5 12 Comment 5 2019-10-22 23:45:00 0 Summing comment scores – 2nd root total_score_comment AS ( SELECT id, parent_id, review, created_on, score, SUM(score) OVER ( PARTITION BY root_id ) AS total_score FROM post_comment_score ), total_score_comment
  • 76. @vlad_mihalcea vladmihalcea.com id parent_id root_id review created_on score 1 1 Comment 1 2019-10-13 12:23:05 1 5 5 Comment 2 2019-10-13 15:23:25 1 8 8 Comment 3 2019-10-15 10:15:40 1 11 11 Comment 4 2019-10-19 21:43:55 -5 12 12 Comment 5 2019-10-22 23:45:00 0 2 1 1 Comment 1.1 2019-10-14 13:23:10 2 3 1 1 Comment 1.2 2019-10-14 15:45:15 2 6 5 5 Comment 2.1 2019-10-14 11:23:30 1 7 5 5 Comment 2.2 2019-10-14 14:45:35 1 9 8 8 Comment 3.1 2019-10-16 11:15:45 10 10 8 8 Comment 3.2 2019-10-17 18:30:50 -2 4 3 1 Comment 1.2.1 2019-10-15 10:15:20 1 Summing comment scores – 3rd root total_score_comment AS ( SELECT id, parent_id, review, created_on, score, SUM(score) OVER ( PARTITION BY root_id ) AS total_score FROM post_comment_score ), post_comment_score
  • 77. @vlad_mihalcea vladmihalcea.com id parent_id review created_on score total_score 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 6 2 1 Comment 1.1 2019-10-14 13:23:10 2 6 3 1 Comment 1.2 2019-10-14 15:45:15 2 6 1 Comment 1 2019-10-13 12:23:05 1 6 6 5 Comment 2.1 2019-10-14 11:23:30 1 3 7 5 Comment 2.2 2019-10-14 14:45:35 1 3 5 Comment 2 2019-10-13 15:23:25 1 3 8 Comment 3 2019-10-15 10:15:40 1 9 9 8 Comment 3.1 2019-10-16 11:15:45 10 9 10 8 Comment 3.2 2019-10-17 18:30:50 -2 9 11 Comment 4 2019-10-19 21:43:55 -5 12 Comment 5 2019-10-22 23:45:00 0 Summing comment scores – 3rd root total_score_comment AS ( SELECT id, parent_id, review, created_on, score, SUM(score) OVER ( PARTITION BY root_id ) AS total_score FROM post_comment_score ), total_score_comment
  • 78. @vlad_mihalcea vladmihalcea.com id parent_id root_id review created_on score 1 1 Comment 1 2019-10-13 12:23:05 1 5 5 Comment 2 2019-10-13 15:23:25 1 8 8 Comment 3 2019-10-15 10:15:40 1 11 11 Comment 4 2019-10-19 21:43:55 -5 12 12 Comment 5 2019-10-22 23:45:00 0 2 1 1 Comment 1.1 2019-10-14 13:23:10 2 3 1 1 Comment 1.2 2019-10-14 15:45:15 2 6 5 5 Comment 2.1 2019-10-14 11:23:30 1 7 5 5 Comment 2.2 2019-10-14 14:45:35 1 9 8 8 Comment 3.1 2019-10-16 11:15:45 10 10 8 8 Comment 3.2 2019-10-17 18:30:50 -2 4 3 1 Comment 1.2.1 2019-10-15 10:15:20 1 Summing comment scores – 4th root total_score_comment AS ( SELECT id, parent_id, review, created_on, score, SUM(score) OVER ( PARTITION BY root_id ) AS total_score FROM post_comment_score ), post_comment_score
  • 79. @vlad_mihalcea vladmihalcea.com id parent_id review created_on score total_score 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 6 2 1 Comment 1.1 2019-10-14 13:23:10 2 6 3 1 Comment 1.2 2019-10-14 15:45:15 2 6 1 Comment 1 2019-10-13 12:23:05 1 6 6 5 Comment 2.1 2019-10-14 11:23:30 1 3 7 5 Comment 2.2 2019-10-14 14:45:35 1 3 5 Comment 2 2019-10-13 15:23:25 1 3 8 Comment 3 2019-10-15 10:15:40 1 9 9 8 Comment 3.1 2019-10-16 11:15:45 10 9 10 8 Comment 3.2 2019-10-17 18:30:50 -2 9 11 Comment 4 2019-10-19 21:43:55 -5 -5 12 Comment 5 2019-10-22 23:45:00 0 Summing comment scores – 4th root total_score_comment AS ( SELECT id, parent_id, review, created_on, score, SUM(score) OVER ( PARTITION BY root_id ) AS total_score FROM post_comment_score ), total_score_comment
  • 80. @vlad_mihalcea vladmihalcea.com id parent_id root_id review created_on score 1 1 Comment 1 2019-10-13 12:23:05 1 5 5 Comment 2 2019-10-13 15:23:25 1 8 8 Comment 3 2019-10-15 10:15:40 1 11 11 Comment 4 2019-10-19 21:43:55 -5 12 12 Comment 5 2019-10-22 23:45:00 0 2 1 1 Comment 1.1 2019-10-14 13:23:10 2 3 1 1 Comment 1.2 2019-10-14 15:45:15 2 6 5 5 Comment 2.1 2019-10-14 11:23:30 1 7 5 5 Comment 2.2 2019-10-14 14:45:35 1 9 8 8 Comment 3.1 2019-10-16 11:15:45 10 10 8 8 Comment 3.2 2019-10-17 18:30:50 -2 4 3 1 Comment 1.2.1 2019-10-15 10:15:20 1 Summing comment scores – 5th root total_score_comment AS ( SELECT id, parent_id, review, created_on, score, SUM(score) OVER ( PARTITION BY root_id ) AS total_score FROM post_comment_score ), post_comment_score
  • 81. @vlad_mihalcea vladmihalcea.com id parent_id review created_on score total_score 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 6 2 1 Comment 1.1 2019-10-14 13:23:10 2 6 3 1 Comment 1.2 2019-10-14 15:45:15 2 6 1 Comment 1 2019-10-13 12:23:05 1 6 6 5 Comment 2.1 2019-10-14 11:23:30 1 3 7 5 Comment 2.2 2019-10-14 14:45:35 1 3 5 Comment 2 2019-10-13 15:23:25 1 3 8 Comment 3 2019-10-15 10:15:40 1 9 9 8 Comment 3.1 2019-10-16 11:15:45 10 9 10 8 Comment 3.2 2019-10-17 18:30:50 -2 9 11 Comment 4 2019-10-19 21:43:55 -5 -5 12 Comment 5 2019-10-22 23:45:00 0 0 Summing comment scores – 5th root total_score_comment AS ( SELECT id, parent_id, review, created_on, score, SUM(score) OVER ( PARTITION BY root_id ) AS total_score FROM post_comment_score ), total_score_comment
  • 82. @vlad_mihalcea vladmihalcea.com Ranking comment total scores total_score_ranking AS ( SELECT id, parent_id, review, created_on, score, total_score, DENSE_RANK() OVER ( ORDER BY total_score DESC ) ranking FROM total_score_comment ),
  • 83. @vlad_mihalcea vladmihalcea.com Ranking comment total scores – 1st rank total_score_ranking AS ( SELECT id, parent_id, review, created_on, score, total_score, DENSE_RANK() OVER ( ORDER BY total_score DESC ) ranking FROM total_score_comment ), id parent_id review created_on score total_score 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 6 2 1 Comment 1.1 2019-10-14 13:23:10 2 6 3 1 Comment 1.2 2019-10-14 15:45:15 2 6 1 Comment 1 2019-10-13 12:23:05 1 6 6 5 Comment 2.1 2019-10-14 11:23:30 1 3 7 5 Comment 2.2 2019-10-14 14:45:35 1 3 5 Comment 2 2019-10-13 15:23:25 1 3 8 Comment 3 2019-10-15 10:15:40 1 9 9 8 Comment 3.1 2019-10-16 11:15:45 10 9 10 8 Comment 3.2 2019-10-17 18:30:50 -2 9 11 Comment 4 2019-10-19 21:43:55 -5 -5 12 Comment 5 2019-10-22 23:45:00 0 0 total_score_comme nt
  • 84. @vlad_mihalcea vladmihalcea.com Ranking comment total scores – 1st rank total_score_ranking AS ( SELECT id, parent_id, review, created_on, score, total_score, DENSE_RANK() OVER ( ORDER BY total_score DESC ) ranking FROM total_score_comment ), id parent_id review created_on score total_score ranking 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 6 2 1 Comment 1.1 2019-10-14 13:23:10 2 6 3 1 Comment 1.2 2019-10-14 15:45:15 2 6 1 Comment 1 2019-10-13 12:23:05 1 6 6 5 Comment 2.1 2019-10-14 11:23:30 1 3 7 5 Comment 2.2 2019-10-14 14:45:35 1 3 5 Comment 2 2019-10-13 15:23:25 1 3 8 Comment 3 2019-10-15 10:15:40 1 9 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 9 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 9 1 11 Comment 4 2019-10-19 21:43:55 -5 -5 12 Comment 5 2019-10-22 23:45:00 0 0 total_score_ranking
  • 85. @vlad_mihalcea vladmihalcea.com Ranking comment total scores – 2nd rank total_score_ranking AS ( SELECT id, parent_id, review, created_on, score, total_score, DENSE_RANK() OVER ( ORDER BY total_score DESC ) ranking FROM total_score_comment ), id parent_id review created_on score total_score ranking 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 6 2 2 1 Comment 1.1 2019-10-14 13:23:10 2 6 2 3 1 Comment 1.2 2019-10-14 15:45:15 2 6 2 1 Comment 1 2019-10-13 12:23:05 1 6 2 6 5 Comment 2.1 2019-10-14 11:23:30 1 3 7 5 Comment 2.2 2019-10-14 14:45:35 1 3 5 Comment 2 2019-10-13 15:23:25 1 3 8 Comment 3 2019-10-15 10:15:40 1 9 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 9 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 9 1 11 Comment 4 2019-10-19 21:43:55 -5 -5 12 Comment 5 2019-10-22 23:45:00 0 0 total_score_ranking
  • 86. @vlad_mihalcea vladmihalcea.com Ranking comment total scores – 3rd rank total_score_ranking AS ( SELECT id, parent_id, review, created_on, score, total_score, DENSE_RANK() OVER ( ORDER BY total_score DESC ) ranking FROM total_score_comment ), id parent_id review created_on score total_score ranking 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 6 2 2 1 Comment 1.1 2019-10-14 13:23:10 2 6 2 3 1 Comment 1.2 2019-10-14 15:45:15 2 6 2 1 Comment 1 2019-10-13 12:23:05 1 6 2 6 5 Comment 2.1 2019-10-14 11:23:30 1 3 3 7 5 Comment 2.2 2019-10-14 14:45:35 1 3 3 5 Comment 2 2019-10-13 15:23:25 1 3 3 8 Comment 3 2019-10-15 10:15:40 1 9 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 9 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 9 1 11 Comment 4 2019-10-19 21:43:55 -5 -5 12 Comment 5 2019-10-22 23:45:00 0 0 total_score_ranking
  • 87. @vlad_mihalcea vladmihalcea.com Ranking comment total scores – 4th rank total_score_ranking AS ( SELECT id, parent_id, review, created_on, score, total_score, DENSE_RANK() OVER ( ORDER BY total_score DESC ) ranking FROM total_score_comment ), id parent_id review created_on score total_score ranking 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 6 2 2 1 Comment 1.1 2019-10-14 13:23:10 2 6 2 3 1 Comment 1.2 2019-10-14 15:45:15 2 6 2 1 Comment 1 2019-10-13 12:23:05 1 6 2 6 5 Comment 2.1 2019-10-14 11:23:30 1 3 3 7 5 Comment 2.2 2019-10-14 14:45:35 1 3 3 5 Comment 2 2019-10-13 15:23:25 1 3 3 8 Comment 3 2019-10-15 10:15:40 1 9 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 9 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 9 1 11 Comment 4 2019-10-19 21:43:55 -5 -5 12 Comment 5 2019-10-22 23:45:00 0 0 4 total_score_ranking
  • 88. @vlad_mihalcea vladmihalcea.com Ranking comment total scores – 5th rank total_score_ranking AS ( SELECT id, parent_id, review, created_on, score, total_score, DENSE_RANK() OVER ( ORDER BY total_score DESC ) ranking FROM total_score_comment ), id parent_id review created_on score total_score ranking 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 6 2 2 1 Comment 1.1 2019-10-14 13:23:10 2 6 2 3 1 Comment 1.2 2019-10-14 15:45:15 2 6 2 1 Comment 1 2019-10-13 12:23:05 1 6 2 6 5 Comment 2.1 2019-10-14 11:23:30 1 3 3 7 5 Comment 2.2 2019-10-14 14:45:35 1 3 3 5 Comment 2 2019-10-13 15:23:25 1 3 3 8 Comment 3 2019-10-15 10:15:40 1 9 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 9 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 9 1 11 Comment 4 2019-10-19 21:43:55 -5 -5 5 12 Comment 5 2019-10-22 23:45:00 0 0 4 total_score_ranking
  • 89. @vlad_mihalcea vladmihalcea.com Filtering by the comment total score SELECT id, parent_id, review, created_on, score, total_score FROM total_score_ranking WHERE ranking <= 3 ORDER BY total_score DESC, id ASC
  • 90. @vlad_mihalcea vladmihalcea.com Filtering by the comment total score SELECT id, parent_id, review, created_on, score, total_score FROM total_score_ranking WHERE ranking <= 3 ORDER BY total_score DESC, id ASC id parent_id review created_on score total_score ranking 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 6 2 2 1 Comment 1.1 2019-10-14 13:23:10 2 6 2 3 1 Comment 1.2 2019-10-14 15:45:15 2 6 2 1 Comment 1 2019-10-13 12:23:05 1 6 2 6 5 Comment 2.1 2019-10-14 11:23:30 1 3 3 7 5 Comment 2.2 2019-10-14 14:45:35 1 3 3 5 Comment 2 2019-10-13 15:23:25 1 3 3 8 Comment 3 2019-10-15 10:15:40 1 9 1 9 8 Comment 3.1 2019-10-16 11:15:45 10 9 1 10 8 Comment 3.2 2019-10-17 18:30:50 -2 9 1 11 Comment 4 2019-10-19 21:43:55 -5 -5 5 12 Comment 5 2019-10-22 23:45:00 0 0 4 total_score_ranking
  • 91. @vlad_mihalcea vladmihalcea.com Filtering by the comment total score SELECT id, parent_id, review, created_on, score, total_score FROM total_score_ranking WHERE ranking <= 3 ORDER BY total_score DESC, id ASC id parent_id review created_on score total_score 8 Comment 3 2019-10-15 10:15:40 1 9 9 8 Comment 3.1 2019-10-16 11:15:45 10 9 10 8 Comment 3.2 2019-10-17 18:30:50 -2 9 1 Comment 1 2019-10-13 12:23:05 1 6 2 1 Comment 1.1 2019-10-14 13:23:10 2 6 3 1 Comment 1.2 2019-10-14 15:45:15 2 6 4 3 Comment 1.2.1 2019-10-15 10:15:20 1 6 5 Comment 2 2019-10-13 15:23:25 1 3 6 5 Comment 2.1 2019-10-14 11:23:30 1 3 7 5 Comment 2.2 2019-10-14 14:45:35 1 3 Result set
  • 92. @vlad_mihalcea vladmihalcea.com Application-level vs database processing 20 104 656 2040 4640 15024 34880 0 10 20 30 40 50 60 70 80 90 100 Data set size Time(ms) Application-level Recursive CTE
  • 93. @vlad_mihalcea vladmihalcea.com SQL:2003 • SQL:2003 was a minor version of SQL:1999. • It added support for: • Window Functions, • MERGE statement • SEQUNCE generator and IDENTITY column type, • XML column type
  • 94. @vlad_mihalcea vladmihalcea.com • Supported databases: • Oracle 9i • SQL Server 2008 • PostgreSQL and MySQL offer non-standard UPSERT alternatives. MERGE
  • 95. @vlad_mihalcea vladmihalcea.com Oracle MERGE – Ignore on constraint violation MERGE INTO book USING (SELECT 1 FROM dual) ON (id = 1) WHEN NOT MATCHED THEN INSERT ( id, title, isbn ) VALUES ( 1, 'High-Performance Java Persistence', '978-9730228236' )
  • 96. @vlad_mihalcea vladmihalcea.com Oracle MERGE – UPDATE on constraint violation MERGE INTO book USING (SELECT 1 FROM dual) ON (id = 1) WHEN MATCHED THEN UPDATE SET title = 'High-Performance Java Persistence, 2nd Edition', isbn = '978-9730228236' WHEN NOT MATCHED THEN INSERT ( id, title, isbn ) VALUES ( 1, 'High-Performance Java Persistence', '978-9730228236' )
  • 97. @vlad_mihalcea vladmihalcea.com SQL:2006 • SQL:2006 added support for: • XQuery, • SQL/XML functions (e.g., XMLELEMENT)
  • 98. @vlad_mihalcea vladmihalcea.com SQL:2008 • SQL:2008 added support for: • TRUNCATE TABLE, • Multiple WHEN clauses in CASE expressions, • INSTEAD OF database triggers (override INSERT, UPDATE, DELETE), • XQuery regular expression/pattern matching, • Derived column list to override a derived table column names, • Standard pagination using: • FETCH FIRST N ROWS ONLY • OFFSET M ROWS
  • 99. @vlad_mihalcea vladmihalcea.com SQL – Oracle legacy Top N SELECT t.* FROM ( SELECT title FROM post ORDER BY created_on DESC, id DESC ) t WHERE ROWNUM <= 5 ORDER BY ROWNUM
  • 100. @vlad_mihalcea vladmihalcea.com SQL – Standard Top N SELECT title FROM post ORDER BY created_on DESC, id DESC FETCH FIRST 5 ROWS ONLY
  • 101. @vlad_mihalcea vladmihalcea.com SQL – Oracle legacy Next N SELECT t2.* FROM ( SELECT t1.*, ROWNUM AS ROW_NUM FROM ( SELECT title FROM post ORDER BY created_on DESC, id DESC ) t1 WHERE ROWNUM <= 10 ) t2 WHERE ROW_NUM > 5 ORDER BY ROW_NUM
  • 102. @vlad_mihalcea vladmihalcea.com SQL – Standard Next N SELECT title FROM post ORDER BY created_on DESC, id DESC OFFSET 5 ROWS FETCH NEXT 5 ROWS ONLY
  • 103. @vlad_mihalcea vladmihalcea.com SQL:2011 • SQL: 2011 added support for • Temporal database, • System-versioned tables
  • 104. @vlad_mihalcea vladmihalcea.com SQL:2016 • SQL: 2016 added support for: • JSON, • MATCH_RECOGNIZE (Row Pattern Recognition), • LISTAGG (aggregate multiple values to a delimited string value), • DECFLOAT column type (e.g., decimal floating arithmetic), • Date and Time formatting (e.g., CAST(.. AS .. FORMAT ..), EXTRACT(.. FROM <datetime>))
  • 105. @vlad_mihalcea vladmihalcea.com • Supported databases: • Oracle 12c • SQL Server 2016 • PostgreSQL 9.2 • MySQL 5.6 • PostgreSQL and MySQL offer non-standard alternatives. JSON
  • 106. @vlad_mihalcea vladmihalcea.com MySQL – storing JSON CREATE TABLE book ( id bigint NOT NULL PRIMARY KEY, isbn VARCHAR(15), properties JSON )
  • 107. @vlad_mihalcea vladmihalcea.com MySQL – Get scalar attribute SELECT id, CAST( properties -> '$.price' AS DECIMAL(4, 2) ) AS price FROM book WHERE properties -> '$.title' = 'High-Performance Java Persistence' Without casting to DECIMAL, the result will be returned as a String.
  • 108. @vlad_mihalcea vladmihalcea.com MySQL – Get scalar attribute id isbn properties 1 978-9730228236 { "title":"High-Performance Java Persistence", "author":"Vlad Mihalcea", "publisher":"Amazon", "price":44.99, "reviews":[ … ] } book SELECT id, CAST( properties -> '$.price' AS DECIMAL(4, 2) ) AS price FROM book WHERE properties -> '$.title' = 'High-Performance Java Persistence' id price 1 44.99 Result set
  • 109. @vlad_mihalcea vladmihalcea.com SELECT id, properties -> '$.reviews' AS reviews FROM book WHERE isbn = '978-9730228236' MySQL – Get JSON object
  • 110. @vlad_mihalcea vladmihalcea.com MySQL – Get JSON object SELECT id, properties -> '$.reviews' AS reviews FROM book WHERE isbn = '978-9730228236' id isbn properties 1 978-9730228236 { "title":"High-Performance Java Persistence", "author":"Vlad Mihalcea", "publisher":"Amazon", "price":44.99, "reviews":[ { "reviewer":"Cristiano", "review":"Excellent book to understand Java Persistence", "date":"2017-11-14", "rating":5 }, { "reviewer":"T.W", "review":"The best JPA ORM book out there", "date":"2019-01-27", "rating":5 }, { "reviewer":"Shaikh", "review":"The most informative book", "date":"2016-12-24", "rating":4 } ] } book id reviews 1 [ {..}, {..}, {..} ] Result set
  • 111. @vlad_mihalcea vladmihalcea.com SELECT r.* FROM book, JSON_TABLE( properties, '$.reviews[*]' COLUMNS( reviewer VARCHAR(4000) PATH '$.reviewer', review VARCHAR(4000) PATH '$.review', review_date DATETIME PATH '$.date’, rating INT PATH '$.rating' ) ) AS r WHERE isbn = '978-9730228236' MySQL – JSON to SQL table
  • 112. @vlad_mihalcea vladmihalcea.com SELECT r.* FROM book, JSON_TABLE( properties, '$.reviews[*]' COLUMNS( reviewer VARCHAR(4000) PATH '$.reviewer', review VARCHAR(4000) PATH '$.review', review_date DATETIME PATH '$.date’, rating INT PATH '$.rating' ) ) AS r WHERE isbn = '978-9730228236' MySQL – JSON to SQL table "reviews":[ { "reviewer":"Cristiano", "review":"Excellent book to understand Java Persistence", "date":"2017-11-14", "rating":5 }, { "reviewer":"T.W", "review":"The best JPA ORM book out there", "date":"2019-01-27", "rating":5 }, { "reviewer":"Shaikh", "review":"The most informative book", "date":"2016-12-24", "rating":4 } ] reviewer review review_date rating book
  • 113. @vlad_mihalcea vladmihalcea.com SELECT r.* FROM book, JSON_TABLE( properties, '$.reviews[*]' COLUMNS( reviewer VARCHAR(4000) PATH '$.reviewer', review VARCHAR(4000) PATH '$.review', review_date DATETIME PATH '$.date’, rating INT PATH '$.rating' ) ) AS r WHERE isbn = '978-9730228236' MySQL – JSON to SQL table "reviews":[ { "reviewer":"Cristiano", "review":"Excellent book to understand Java Persistence", "date":"2017-11-14", "rating":5 }, { "reviewer":"T.W", "review":"The best JPA ORM book out there", "date":"2019-01-27", "rating":5 }, { "reviewer":"Shaikh", "review":"The most informative book", "date":"2016-12-24", "rating":4 } ] reviewer review review_date rating Cristiano Excellent book to understand Java Persistence 14-Nov-2017 5 book
  • 114. @vlad_mihalcea vladmihalcea.com SELECT r.* FROM book, JSON_TABLE( properties, '$.reviews[*]' COLUMNS( reviewer VARCHAR(4000) PATH '$.reviewer', review VARCHAR(4000) PATH '$.review', review_date DATETIME PATH '$.date’, rating INT PATH '$.rating' ) ) AS r WHERE isbn = '978-9730228236' MySQL – JSON to SQL table "reviews":[ { "reviewer":"Cristiano", "review":"Excellent book to understand Java Persistence", "date":"2017-11-14", "rating":5 }, { "reviewer":"T.W", "review":"The best JPA ORM book out there", "date":"2019-01-27", "rating":5 }, { "reviewer":"Shaikh", "review":"The most informative book", "date":"2016-12-24", "rating":4 } ] reviewer review review_date rating Cristiano Excellent book to understand Java Persistence 14-Nov-2017 5 T.W The best JPA ORM book out there 27-Jan-2019 5 book
  • 115. @vlad_mihalcea vladmihalcea.com SELECT r.* FROM book, JSON_TABLE( properties, '$.reviews[*]' COLUMNS( reviewer VARCHAR(4000) PATH '$.reviewer', review VARCHAR(4000) PATH '$.review', review_date DATETIME PATH '$.date’, rating INT PATH '$.rating' ) ) AS r WHERE isbn = '978-9730228236' MySQL – JSON to SQL table "reviews":[ { "reviewer":"Cristiano", "review":"Excellent book to understand Java Persistence", "date":"2017-11-14", "rating":5 }, { "reviewer":"T.W", "review":"The best JPA ORM book out there", "date":"2019-01-27", "rating":5 }, { "reviewer":"Shaikh", "review":"The most informative book", "date":"2016-12-24", "rating":4 } ] reviewer review review_date rating Cristiano Excellent book to understand Java Persistence 14-Nov-2017 5 T.W The best JPA ORM book out there 27-Jan-2019 5 Shaikh The most informative book 24-Dec-2016 4book
  • 116. @vlad_mihalcea vladmihalcea.com SQL timeline SQL NoSQL NewSQL 1974 2009 2011
  • 118. @vlad_mihalcea vladmihalcea.com CockroachDB – SQL support https://www.cockroachlabs.com/docs/v19.1/sql-statements.html
  • 119. @vlad_mihalcea vladmihalcea.com VoltDB – SQL support https://www.voltdb.com/product/features-benefits/sql-database/
  • 120. @vlad_mihalcea vladmihalcea.com VoltDB – SQL support https://www.voltdb.com/product/features-benefits/sql-database/
  • 121. @vlad_mihalcea vladmihalcea.com VoltDB – SQL support https://www.voltdb.com/product/features-benefits/sql-database/
  • 122. @vlad_mihalcea vladmihalcea.com Google BigQuery – SQL support https://cloud.google.com/bigquery/docs/release-notes#March_23_2016
  • 123. @vlad_mihalcea vladmihalcea.com Google Spanner – SQL support https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/46103.pdf
  • 124. @vlad_mihalcea vladmihalcea.com Thank you • Twitter: @vlad_mihalcea • Blog: https://vladmihalcea.com/ • Courses: https://vladmihalcea.com/courses/ • Training: https://vladmihalcea.com/trainings/ • Book: https://vladmihalcea.com/books/high-performance-java-persistence/