Awesome SQL Tips and Tricks - Voxxed Days Cluj - 2019

@vlad_mihalcea vladmihalcea.com
Awesome
SQL
Tips and Tricks

About me
• Java Champion
• vladmihalcea.com
• @vlad_mihalcea
• vladmihalcea

InfoQ – Trends Report
https://www.infoq.com/articles/architecture-trends-2019/

StackOverflow Survey – Most Popular Technologies
https://insights.stackoverflow.com/survey/2019

SQL is old school
https://www.pexels.com/photo/antique-blur-classic-close-up-595699/

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

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

SQL – ‘90s
1995
David Axmark & Michael Widenius
MySQL
Sybase SQL Server
1993
Microsoft
SQL Server
POSTGRES
1996
PostgreSQL

Why is SQL still used?
https://qr.ae/TWCBD5

StackOverflow Survey – Most Popular Databases
https://insights.stackoverflow.com/survey/2019

What does SQL stand for?
S? Query Language

What does SQL stand for?
https://twitter.com/vlad_mihalcea/status/1172446336131596289

SQL Standard
Photo by Frederick Tubiermont on Unsplash https://unsplash.com/photos/fJSRg-r7LuI

SQL:92

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))

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.

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.

post
id review post_id
1 SQL:2016 is great! 1
2 SQL:2016 is excellent! 1
3
SQL:20016 is awesome!
1
id title
1 SQL:2016
2 SQL:2011
3 SQL:2008
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
Result set

post
id review post_id
3
1
id title
1 SQL:2016
2 SQL:2011
3 SQL:2008
post_comment
post_id post_title comment_id comment_review
1 SQL:2016 3
Result set

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();

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

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

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.

SQL – Derived tables – Oracle Top N
SELECT t.*
FROM (
SELECT title
FROM post
) t
WHERE ROWNUM <= 5
ORDER BY ROWNUM
The outer query can now limit the result set size.

SQL – Derived tables – Oracle Next N
SELECT t2.*
FROM (
SELECT t1.*, ROWNUM AS ROW_NUM
FROM (
SELECT title
FROM post
) 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.

SELECT t2.*
FROM (
FROM (
SELECT title
FROM post
) t1
WHERE ROWNUM <= 10
) t2
WHERE ROW_NUM > 5
ORDER BY ROW_NUM
The following outer query can now limit the result
set size.

SELECT t2.*
FROM (
FROM (
SELECT title
FROM post
) 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.

SQL Standard timeline
SQL:86 SQL:89 SQL:92

SQL Standard timeline
SQL:86 SQL:89 SQL:92 SQL:1999
SQL:2011 SQL:2008 SQL:2006 SQL:2003
SQL:2016

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)

Pyramid of Doom
SELECT t2.*
FROM (
FROM (
SELECT title
FROM post
) t1
WHERE ROWNUM <= 10
) t2
WHERE ROW_NUM > 5
ORDER BY ROW_NUM

• Supported databases:
• Oracle 9i R2
• SQL Server 2005
• PostgreSQL 8.4
• MySQL 8.0.1
• MariaDB 10.2.1
CTE (Common Table Expression)

SQL – CTE
WITH
p AS (
SELECT title
FROM post
),
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

Fetching hierarchical data
6 + 2 + 2 + 1 + …
total_score

Fetching hierarchical data

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.

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

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
3 = 1 + 1 + 1
total_score

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
9 = 1 + 10 - 2
total_score

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
-5
total_score

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
0
total_score

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

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());

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

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

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.

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

WITH RECURSIVE
)
We want to propagate the root_id
to all comments belonging to the
same hierarchy.

WITH RECURSIVE
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

WITH RECURSIVE
SELECT
FROM post_comment
UNION ALL
SELECT
pc.id, pcs.root_id, pc.post_id, pc.parent_id, pc.review, pc.created_on, pc.score
INNER JOIN post_comment_score pcs ON pc.parent_id = pcs.id
)
Recursive member – the 2nd to Nth level

WITH RECURSIVE
SELECT
FROM post_comment
UNION ALL
SELECT
)
Joining the current and previous levels

WITH RECURSIVE
SELECT
FROM post_comment
UNION ALL
SELECT
)
SELECT
id, parent_id, root_id, review, created_on, score
FROM post_comment_score
Result set projection query

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
UNION ALL
SELECT
pc.id, pcs.root_id, pc.post_id, pc.parent_id,
pc.review, pc.created_on, pc.score
INNER JOIN post_comment_score pcs
ON pc.parent_id = pcs.id
)
SELECT
id, parent_id, root_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

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
AS (
SELECT
FROM post_comment
UNION ALL
SELECT
)
SELECT
post_comment_score

Recursive CTE – 2nd level
AS (
SELECT
FROM post_comment
UNION ALL
SELECT
)
SELECT
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

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
AS (
SELECT
FROM post_comment
UNION ALL
SELECT
)
SELECT
post_comment_score

Recursive CTE – 3rd level
AS (
SELECT
FROM post_comment
UNION ALL
SELECT
)
SELECT
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

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
AS (
SELECT
FROM post_comment
UNION ALL
SELECT
)
SELECT
post_comment_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

Window Functions
Photo by Numendil on Unsplash https://unsplash.com/photos/sSKNdbv3qNg

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

• Oracle 8i
• SQL Server 2005
• PostgreSQL 8.4
• MySQL 8.0.2
• MariaDB 10.2.0
Window Functions

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
),

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 (
) AS total_score
),
post_comment_score

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 (
) AS total_score
),
total_score_comment

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 (
) AS total_score
),
post_comment_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 (
) AS total_score
),
total_score_comment

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 (
) AS total_score
),
post_comment_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 (
) AS total_score
),
total_score_comment

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 (
) AS total_score
),
post_comment_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
total_score_comment
AS (
SELECT
id,
parent_id,
review,
created_on,
score,
SUM(score) OVER (
) AS total_score
),
total_score_comment

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
total_score_comment
AS (
SELECT
id,
parent_id,
review,
created_on,
score,
SUM(score) OVER (
) AS total_score
),
post_comment_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_comment
AS (
SELECT
id,
parent_id,
review,
created_on,
score,
SUM(score) OVER (
) AS total_score
),
total_score_comment

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
),

Ranking comment total scores – 1st rank
total_score_ranking
AS (
SELECT
id,
parent_id,
review,
created_on,
score,
total_score,
DENSE_RANK() OVER (
) 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
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

Ranking comment total scores – 1st rank
total_score_ranking
AS (
SELECT
id,
parent_id,
review,
created_on,
score,
total_score,
DENSE_RANK() OVER (
) ranking
),
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

Ranking comment total scores – 2nd rank
total_score_ranking
AS (
SELECT
id,
parent_id,
review,
created_on,
score,
total_score,
DENSE_RANK() OVER (
) 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

Ranking comment total scores – 3rd rank
total_score_ranking
AS (
SELECT
id,
parent_id,
review,
created_on,
score,
total_score,
DENSE_RANK() OVER (
) 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

Ranking comment total scores – 4th rank
total_score_ranking
AS (
SELECT
id,
parent_id,
review,
created_on,
score,
total_score,
DENSE_RANK() OVER (
) 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

Ranking comment total scores – 5th rank
total_score_ranking
AS (
SELECT
id,
parent_id,
review,
created_on,
score,
total_score,
DENSE_RANK() OVER (
) 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

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

SELECT
id,
parent_id,
review,
created_on,
score,
total_score
WHERE
ranking <= 3
ORDER BY
total_score DESC,
id ASC
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

SELECT
id,
parent_id,
review,
created_on,
score,
total_score
WHERE
ranking <= 3
ORDER BY
total_score DESC,
id ASC
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

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

• Oracle 9i
• SQL Server 2008
• PostgreSQL and MySQL offer non-standard UPSERT alternatives.
MERGE

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'
)

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'
)

SQL:2006
• SQL:2006 added support for:
• XQuery,
• SQL/XML functions (e.g., XMLELEMENT)

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

SQL – Oracle legacy Top N
SELECT t.*
FROM (
SELECT title
FROM post
) t
WHERE ROWNUM <= 5
ORDER BY ROWNUM

SQL – Standard Top N
SELECT title
FROM post
FETCH FIRST 5 ROWS ONLY

SQL – Oracle legacy Next N
SELECT t2.*
FROM (
FROM (
SELECT title
FROM post
) t1
WHERE ROWNUM <= 10
) t2
WHERE ROW_NUM > 5
ORDER BY ROW_NUM

SQL – Standard Next N
SELECT title
FROM post
OFFSET 5 ROWS
FETCH NEXT 5 ROWS ONLY

SQL:2011
• SQL: 2011 added support for
• Temporal database,
• System-versioned tables

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>))

• Oracle 12c
• SQL Server 2016
• PostgreSQL 9.2
• MySQL 5.6
• PostgreSQL and MySQL offer non-standard alternatives.
JSON

MySQL – storing JSON
CREATE TABLE book (
id bigint NOT NULL PRIMARY KEY,
isbn VARCHAR(15),
properties JSON
)

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.

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

SELECT
id,
properties -> '$.reviews' AS reviews
FROM book
WHERE
isbn = '978-9730228236'
MySQL – Get JSON object

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

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

SELECT r.*
FROM
book, JSON_TABLE(
properties,
'$.reviews[*]'
COLUMNS(
)
) AS r
WHERE isbn = '978-9730228236'
"reviews":[
{
"date":"2017-11-14",
"rating":5
},
{
"reviewer":"T.W",
"date":"2019-01-27",
"rating":5
},
{
"date":"2016-12-24",
"rating":4
}
]
reviewer review review_date rating
book

SELECT r.*
FROM
book, JSON_TABLE(
properties,
'$.reviews[*]'
COLUMNS(
)
) AS r
WHERE isbn = '978-9730228236'
"reviews":[
{
"date":"2017-11-14",
"rating":5
},
{
"reviewer":"T.W",
"date":"2019-01-27",
"rating":5
},
{
"date":"2016-12-24",
"rating":4
}
]
Cristiano
Excellent book to understand Java
Persistence
14-Nov-2017 5
book

SELECT r.*
FROM
book, JSON_TABLE(
properties,
'$.reviews[*]'
COLUMNS(
)
) AS r
WHERE isbn = '978-9730228236'
"reviews":[
{
"date":"2017-11-14",
"rating":5
},
{
"reviewer":"T.W",
"date":"2019-01-27",
"rating":5
},
{
"date":"2016-12-24",
"rating":4
}
]
Cristiano
Persistence
14-Nov-2017 5
T.W The best JPA ORM book out there 27-Jan-2019 5
book

SELECT r.*
FROM
book, JSON_TABLE(
properties,
'$.reviews[*]'
COLUMNS(
)
) AS r
WHERE isbn = '978-9730228236'
"reviews":[
{
"date":"2017-11-14",
"rating":5
},
{
"reviewer":"T.W",
"date":"2019-01-27",
"rating":5
},
{
"date":"2016-12-24",
"rating":4
}
]
Cristiano
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

SQL timeline
SQL NoSQL NewSQL
1974 2009 2011

NewSQL
https://www.pexels.com/photo/architectural-design-architecture-blue-brazil-416998/

CockroachDB – SQL support
https://www.cockroachlabs.com/docs/v19.1/sql-statements.html

VoltDB – SQL support
https://www.voltdb.com/product/features-benefits/sql-database/

Google BigQuery – SQL support
https://cloud.google.com/bigquery/docs/release-notes#March_23_2016

Google Spanner – SQL support
https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/46103.pdf

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/

Awesome SQL Tips and Tricks - Voxxed Days Cluj - 2019

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