1. MySQL's JSON Data Type Practical Guide
Oracle Code Austin
March 8th 2017

2. "THE FOLLOWING IS INTENDED TO OUTLINE OUR GENERAL PRODUCT DIRECTION
"THE FOLLOWING IS INTENDED TO OUTLINE OUR GENERAL PRODUCT DIRECTION. IT IS INTENDED FOR INFORMATION PURPOSES ONLY, AND MAY NOT BE INCORPORATED INTO ANY CONTRACT. IT IS NOT A COMMITMENT TO DELIVER ANY MATERIAL, CODE, OR FUNCTIONALITY, AND SHOULD NOT BE RELIED UPON IN MAKING PURCHASING DECISIONS. THE DEVELOPMENT, RELEASE, AND TIMING OF ANY FEATURES OR FUNCTIONALITY DESCRIBED FOR ORACLE'S PRODUCTS REMAINS AT THE SOLE DISCRETION OF ORACLE."
Safe Harbor Agreement

3. Dave Stokes
Started using PHP when it was called Personal Home Page (and moved from Msql to MySQL about the same time)
Was hired at MySQL AB as a PHP Programmer in the MySQL Certification Group
Now MySQL Community Manager for Oracle
Lives in Justin Texas
Have pickup truck and hound dog as required by law
@Stoker
slideshare.net/davidmstokes

4. MySQL Recap JSON Data Type 22 Years Old Doing very well at Oracle
Latest Release is MySQL 5.7, MySQL 8 Announced
Group Replication and Document Store
Plug-ins
Doing very well at Oracle
Hiring
Making $
Oracle’s MySQL Cloud
Enterprise Edition
JSON Data Type

5. https://tools.ietf.org/html/rfc7159
JSON Standard
&

6. JSON Example
{ "id": 1, "name": "A green door", "price": 12.50, "tags": ["home", "green"] }

7. UTF8MB4
The JSON standards specify that all JSON documents will be in the UTF8MB4 character set.

8. Not this Jason

9. JSON is a data type like INT or CHAR in MySQL 5.7
So you can save a document in column of a row in a table of a database!

10. Note:
MySQL handles strings used in JSON context using the utf8mb4 character set and utf8mb4_bin collation. Strings in other character sets are converted to utf8mb4 as necessary. (For strings in the ascii or utf8 character sets, no conversion is needed because ascii and utf8 are subsets of utf8mb4.) --

11. Optimized storage format: JSON documents stored in JSON columns are converted to an internal format that permits quick read access to document elements. When the server later must read a JSON value stored in this binary format, the value need not be parsed from a text representation. The binary format is structured to enable the server to look up subobjects or nested values directly by key or array index without reading all values before or after them in the document. --

12. You could store JSON data in a CHAR/Varchar/text field but there are no easy to use functions to help or you end up using regex -- ughh!!!!

13. mysql>CREATE TABLE foobar (foo INT, bar JSON);
mysql>INSERT INTO foobar VALUES (1,'{ "name" : "dave", "home" : [ "Justin", "Texas", ]}');
mysql> SELECT * FROM foobar;
| foo | bar |
| 1 | {"home": ["Justin", "Texas", 76247], "name": "dave"} |
1 row in set (0.00 sec)

14. JSON Functions to ...
Create JSON values
Search JSON values
Modify JSON value
Return JSON value attributes

15. Name. Description JSON_APPEND()
Name Description JSON_APPEND() Append data to JSON document JSON_ARRAY() Create JSON array JSON_ARRAY_APPEND() Append data to JSON document JSON_ARRAY_INSERT() Insert into JSON array -> Return value from JSON column after evaluating path; equivalent to JSON_EXTRACT(). JSON_CONTAINS() Whether JSON document contains specific object at path JSON_CONTAINS_PATH() Whether JSON document contains any data at path JSON_DEPTH() Maximum depth of JSON document JSON_EXTRACT() Return data from JSON document ->> Return value from JSON column after evaluating path and unquoting the result,JSON_UNQUOTE(JSON_EXTRACT()). JSON_INSERT() Insert data into JSON document JSON_KEYS() Array of keys from JSON document JSON_LENGTH() Number of elements in JSON document JSON_MERGE() Merge JSON documents JSON_OBJECT() Create JSON object JSON_QUOTE() Quote JSON document JSON_REMOVE() Remove data from JSON document JSON_REPLACE() Replace values in JSON document JSON_SEARCH() Path to value within JSON document JSON_SET() Insert data into JSON document JSON_TYPE() Type of JSON value JSON_UNQUOTE() Unquote JSON value JSON_VALID() Whether JSON value is valid

16. JSON_EXTRACT JSON_EXTRACT(json_doc, path[, path …])
mysql> SELECT json_extract(bar,'$.Breed') FROM foo; | json_extract(bar,'$.Breed') | | NULL | | ["Beagle", "Small"] | rows in set (0.00 sec)

17. JSON_EXTRACT shorthand ->
column->path
mysql> SELECT bar->'$.Breed' FROM foo; | bar->'$.Breed' | | NULL | | ["Beagle", "Small"] | rows in set (0.00 sec)

18. Chaining down
SELECT * FROM countryinfo WHERE doc->"$.geography.SurfaceArea" = 199;
{"GNP": 334, "_id": "ASM", "Name": "American Samoa", "IndepYear": null, "geogr aphy": {"Region": "Polynesia", "Continent": "Oceania", "SurfaceArea": 199}, "gov ernment": {"HeadOfState": "George W. Bush", "GovernmentForm": "US Territory"}, "demographics": {"Population": 68000, "LifeExpectancy": }} | ASM | |

19. Example
mysql> select * from foo; | id | bar | | 1 | {"name": "Dave"} | | 2 | {"name": "Jack", "Breed": ["Beagle", "Small"]} | rows in set (0.00 sec)

20. JSON_contains
mysql> select * from foo; | id | bar | | 1 | {"name": "Dave"} | | 2 | {"name": "Jack", "Breed": ["Beagle", "Small"]} | rows in set (0.00 sec) mysql> SELECT json_contains(bar,'{\"name\": \"Dave\"}') FROM foo; | json_contains(bar,'{\"name\": \"Dave\"}') | | | | |

21. JSON_contains_path
mysql> select * from foo; | id | bar | | 1 | {"name": "Dave"} | | 2 | {"name": "Jack", "Breed": ["Beagle", "Small"]} | rows in set (0.00 sec) mysql> select json_contains_path(bar,'one','$.Breed') from foo; [ONE\ALL] | json_contains_path(bar,'one','$.Breed') | | | | | rows in set (0.00 sec)

22. JSON_contains_path An example using a WHERE clause.
mysql> select json_contains_path(bar,'one','$.Breed') from foo; | json_contains_path(bar,'one','$.Breed') | | | | | rows in set (0.00 sec)
mysql> select * from foo where json_contains_path(bar,’one’,’$.Breed);
An example using a WHERE clause.

23. JSON_INSERT
mysql> UPDATE foo set bar = JSON_INSERT(bar, '$[99]', 'x'); Query OK, 2 rows affected (0.01 sec) Rows matched: 2 Changed: 2 Warnings: 0 mysql> select * from foo; | id | bar | | 1 | [{"name": "Dave"}, "x"] | | 2 | [{"name": "Jack", "Breed": ["Beagle", "Small"]}, "x"] | rows in set (0.00 sec)
Insert position, append to end if not exist

24. JSON_REPLACE
UPDATE foo set bar =
JSON_REPLACE(bar, '$[0]',JSON_ARRAY(1,2,3)); Query OK, 2 rows affected (0.00 sec) Rows matched: 2 Changed: 2 Warnings: 0 mysql> select * from foo; | id | bar | | 1 | [[1, 2, 3], "x"] | | 2 | [[1, 2, 3], "x"] |

25. JSON_depth
mysql> select * from foo; | id | bar | | 1 | [{"name": "Dave"}, "x"] | | 2 | [{"name": "Jack", "Breed": ["Beagle", "Small"]}, "x"] | rows in set (0.00 sec) mysql> select json_depth(bar) from foo; | json_depth(bar) | | | | |

26. JSON_KEYS
select json_keys('{"name" : "dave", "food" : "pizza" }'); | json_keys('{"name" : "dave", "food" : "pizza" }') | | ["food", "name"] | row in set (0.00 sec)
Note: Keys are sorted!!

27. Output JSON from database
SELECT JSON_ARRAY(Name, District, Population) FROM City;
'[\"Kabul\", \"Kabol\", ]'
'[\"Qandahar\", \"Qandahar\", ]'
... or
SELECT JSON_OBJECT('City', Name, 'Dist', District, 'Pop', Population) FROM City;
'{\"Pop\": , \"City\": \"Kabul\", \"Dist\": \"Kabol\"}'
'{\"Pop\": , \"City\": \"Qandahar\", \"Dist\": \"Qandahar\"}'

28. Output JSON MySQL 8 mysql> SELECT col FROM t1;
| col |
| {"key1": "value1", "key2": "value2"} |
| {"keyA": "valueA", "keyB": "valueB"} |
2 rows in set (0.00 sec)
mysql> SELECT JSON_ARRAYAGG(col) FROM t1;
| JSON_ARRAYAGG(col) |
| [{"key1": "value1", "key2": "value2"}, {"keyA": "valueA", "keyB": "valueB"}] |
1 row in set (0.00 sec)

29. Output JSON MySQL 8
mysql> SELECT id, name FROM t3 WHERE id < 10;
| id | name |
| 2 | joe |
| 5 | fred |
2 rows in set (0.00 sec)
mysql> SELECT JSON_OBJECTAGG(id, name) FROM t3 WHERE id < 10;
| JSON_OBJECTAGG(id, name) |
| {"2": "joe", "5": "fred"} |
1 row in set (0.00 sec)

30. No Indexes
JSON columns, like columns of other binary types, are not indexed directly; instead, you can create an index on a generated column that extracts a scalar value from the JSON column. --

31. Generated JSON data index
mysql> CREATE TABLE snafu (stuff JSON,
idx INT GENERATED ALWAYS AS ('stuff->$.id'));
Query OK, 0 rows affected (0.04 sec)
This index can be used in a SQL query to quickly find particular IDs
SELECT * FROM snafu WHERE idx = 17;
Generated JSON data index

32. IS THIS JSON STUFF GOOD IDEA?
Schemaless data is handy, easy to implement, and needs no data architecting. Or DBA
But their is no enforced rigor to the data, is can be messy, inconsistent ( , , e_mail, ), and it is hard to get insights into the nature of the data. Also confusing as data evolves.
But if you need to store JSON formatted data, this is a pretty good way to do so.

33. Mysql 8 - developer milestone release
New JSON Functions
This release adds an unquoting extraction operator ->>, sometimes also referred to as an inline path operator, for use with JSON documents stored in MySQL. The new operator is similar to the -> operator, but performs JSON unquoting of the value as well. For a JSON column mycol and JSON path expression mypath, the following three expressions are equivalent: JSON_UNQUOTE( JSON_EXTRACT(mycol, "$.mypath") ) JSON_UNQUOTE(mycol->"$.mypath") mycol->>"$.mypath" The ->> operator can be used in SQL statements wherever JSON_UNQUOTE(JSON_EXTRACT()) would be allowed. This includes (but is not limited to) SELECT lists, WHERE and HAVING clauses, and ORDER BY and GROUP BY clauses.

34. pre production release
The MySQL Document Store is a schema-less and therefore schema-flexible, storage system for documents. When using MySQL as a document store, to create documents describing products you do not need to know and define all possible attributes of any products before storing them and operating with them. This differs from working with a relational database and storing products in a table, when all columns of the table must be known and defined before adding any products to the database.

35. CRUD Operations -- Create, Read, Update and Delete (CRUD) operations are the four basic operations that can be performed on a database Collection or Table. In terms of MySQL this means: X Plugin The MySQL Server plugin which enables communication using X Protocol. Supports clients that implement X DevAPI and enables you to use MySQL as a document store. X Protocol A protocol to communicate with a MySQL Server running X Plugin. X Protocol supports both CRUD and SQL operations, authentication via SASL, allows streaming (pipelining) of commands and is extensible on the protocol and the message layer
See chapter 3 of the MySQL 5.7 Documentation

36. No SQL! mysql-py> db.countryinfo.find("_id = 'AUS'") [ {
"GNP": ,
"IndepYear": 1901,
"Name": "Australia",
"_id": "AUS",
"demographics": {
"LifeExpectancy": ,
"Population": },
"geography": {
"Continent": "Oceania",
"Region": "Australia and New Zealand",
"SurfaceArea":
"government": {
"GovernmentForm": "Constitutional Monarchy, Federation",
"HeadOfState": "Elisabeth II" } ]
1 document in set (0.01 sec)

38. slideshare.net/davidmstokes
Q/A
@Stoker
opensourcedba.wordpress.com
elephantanddolphin.blogger.com
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