In this blog, we’ll look at the MySQL 5.7 document store feature, and how it is implemented.
Document Store
MySQL 5.7.12 is a major new release, as it contains quite a number of new features:
- Document store and “MongoDB” like NoSQL interface to JSON storage
- Protocol X / X Plugin, which can be used for asynchronous queries (I will write about it as well)
- New MySQL shell
Peter already wrote the document store overview; in this post, I will look deeper into the document store implementation. In my next post, I will demonstrate how to use document store for Internet of Things (IoT) and event logging.
Older MySQL 5.7 versions already have a JSON data type, and an ability to create virtual columns that can be indexed. The new document store feature is based on the JSON datatype.
So what is the document store anyway? It is an add-on to a normal MySQL table with a JSON field. Let’s take a deep dive into it and see how it works.
First of all: one can interface with the document store’s collections using the X Plugin (default port: 33060). To do that:
- Enable X Plugin and install MySQL shell.
- Login to a shell:1mysqlsh --uri root@localhost
- Run commands (JavaScript mode, can be switched to SQL or Python):12345678910111213141516171819202122mysqlsh --uri root@localhostCreating an X Session to root@localhost:33060Enter password:No default schema selected.Welcome to MySQL Shell 1.0.3 Development PreviewCopyright (c) 2016, Oracle and/or its affiliates. All rights reserved.Oracle is a registered trademark of Oracle Corporation and/or itsaffiliates. Other names may be trademarks of their respectiveowners.Type 'help', 'h' or '?' for help.Currently in JavaScript mode. Use sql to switch to SQL mode and execute queries.mysql-js> db = session.getSchema('world_x') <Schema:world_x>mysql-js> db.getCollections(){"CountryInfo": <Collection:CountryInfo>}
Now, how is the document store’s collection different from a normal table? To find out, I’ve connected to a normal MySQL shell:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 | mysql world_x Reading table information for completion of table and column names You can turn off this feature to get a quicker startup with -A Welcome to the MySQL monitor. Commands end with ; or g. Your MySQL connection id is 2396 Server version: 5.7.12 MySQL Community Server (GPL) Copyright (c) 2000, 2016, Oracle and/or its affiliates. All rights reserved. Oracle is a registered trademark of Oracle Corporation and/or its affiliates. Other names may be trademarks of their respective owners. Type 'help;' or 'h' for help. Type 'c' to clear the current input statement. mysql> show create table CountryInfo *************************** 1. row *************************** Table: CountryInfo Create Table: CREATE TABLE `CountryInfo` ( `doc` json DEFAULT NULL, `_id` varchar(32) GENERATED ALWAYS AS (json_unquote(json_extract(`doc`,'$._id'))) STORED NOT NULL, PRIMARY KEY (`_id`) ) ENGINE=InnoDB DEFAULT CHARSET=utf8 1 row in set (0.00 sec) mysql> show tables; +-------------------+ | Tables_in_world_x | +-------------------+ | City | | Country | | CountryInfo | | CountryLanguage | +-------------------+ 4 rows in set (0.00 sec) |
So the document store is actually an InnoDB table with one field: doc json + Primary key, which is a generated column.
As we can also see, there are four tables in the world_x database, but db.getCollections() only shows one. So how does MySQL distinguish between a “normal” table and a “document store” table? To find out, we can enable the general query log and see which query is being executed:
1 2 3 4 | $ mysql -e 'set global general_log=1' $ tail /var/log/general.log 2016-05-17T20:53:12.772114Z 186 Query SELECT table_name, COUNT(table_name) c FROM information_schema.columns WHERE ((column_name = 'doc' and data_type = 'json') OR (column_name = '_id' and generation_expression = 'json_unquote(json_extract(`doc`,''$._id''))')) AND table_schema = 'world_x' GROUP BY table_name HAVING c = 2 2016-05-17T20:53:12.773834Z 186 Query SHOW FULL TABLES FROM `world_x` |
As you can see, every table that has a specific structure (doc JSON or specific generation_expression) is considered to be a JSON store. Now, how does MySQL translate the .find or .add constructs to actual MySQL queries? Let’s run a sample query:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | mysql-js> db.getCollection("CountryInfo").find('Name= "United States"').limit(1) [ { "GNP": 8510700, "IndepYear": 1776, "Name": "United States", "_id": "USA", "demographics": { "LifeExpectancy": 77.0999984741211, "Population": 278357000 }, "geography": { "Continent": "North America", "Region": "North America", "SurfaceArea": 9363520 }, "government": { "GovernmentForm": "Federal Republic", "HeadOfState": "George W. Bush", "HeadOfState_title": "President" } } ] 1 document in set (0.02 sec) |
and now look at the slow query log again:
1 | 2016-05-17T21:02:21.213899Z 186 Query SELECT doc FROM `world_x`.`CountryInfo` WHERE (JSON_EXTRACT(doc,'$.Name') = 'United States') LIMIT 1 |
We can verify that MySQL translates all document store commands to SQL. That also means that it is 100% transparent to the existing MySQL storage level and will work with other storage engines. Let’s verify that, just for fun:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 | mysql> alter table CountryInfo engine=MyISAM; Query OK, 239 rows affected (0.06 sec) Records: 239 Duplicates: 0 Warnings: 0 mysql-js> db.getCollection("CountryInfo").find('Name= "United States"').limit(1) [ { "GNP": 8510700, "IndepYear": 1776, "Name": "United States", "_id": "USA", "demographics": { "LifeExpectancy": 77.0999984741211, "Population": 278357000 }, "geography": { "Continent": "North America", "Region": "North America", "SurfaceArea": 9363520 }, "government": { "GovernmentForm": "Federal Republic", "HeadOfState": "George W. Bush", "HeadOfState_title": "President" } } ] 1 document in set (0.00 sec) 2016-05-17T21:09:21.074726Z 2399 Query alter table CountryInfo engine=MyISAM 2016-05-17T21:09:41.037575Z 2399 Quit 2016-05-17T21:09:43.014209Z 186 Query SELECT doc FROM `world_x`.`CountryInfo` WHERE (JSON_EXTRACT(doc,'$.Name') = 'United States') LIMIT 1 |
Worked fine!
Now, how about the performance? We can simply take the SQL query and run explain:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | mysql> explain SELECT doc FROM `world_x`.`CountryInfo` WHERE (JSON_EXTRACT(doc,'$.Name') = 'United States') LIMIT 1 *************************** 1. row *************************** id: 1 select_type: SIMPLE table: CountryInfo partitions: NULL type: ALL possible_keys: NULL key: NULL key_len: NULL ref: NULL rows: 239 filtered: 100.00 Extra: Using where 1 row in set, 1 warning (0.00 sec) |
Hmm, it looks like it is not using an index. That’s because there is no index on Name. Can we add one? Sure, we can add a virtual column and then index it:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | mysql> alter table CountryInfo add column Name varchar(255) -> GENERATED ALWAYS AS (json_unquote(json_extract(`doc`,'$.Name'))) VIRTUAL; Query OK, 0 rows affected (0.12 sec) Records: 0 Duplicates: 0 Warnings: 0 mysql> alter table CountryInfo add key (Name); Query OK, 0 rows affected (0.02 sec) Records: 0 Duplicates: 0 Warnings: 0 mysql> explain SELECT doc FROM `world_x`.`CountryInfo` WHERE (JSON_EXTRACT(doc,'$.Name') = 'United States') LIMIT 1 *************************** 1. row *************************** id: 1 select_type: SIMPLE table: CountryInfo partitions: NULL type: ref possible_keys: name key: name key_len: 768 ref: const rows: 1 filtered: 100.00 Extra: NULL 1 row in set, 1 warning (0.00 sec) |
That is really cool! We have added an index, and now the original query starts using it. Note that we do not have to reference the new field, the MySQL optimizer is smart enough to translate the (JSON_EXTRACT(doc,'$.Name') = 'United States' to an index scan on the virtual column.
But please note: JSON attributes are case-sensitive. If you will use (doc,'$.name') instead of (doc,'$.Name') it will not generate an error, but will simply break the search and all queries looking for “Name” will return 0 rows.
Finally, if you looked closely at the output of db.getCollection("CountryInfo").find('Name= "United States"').limit(1) , you noticed that the database has outdated info:
1 2 3 4 5 | "government": { "GovernmentForm": "Federal Republic", "HeadOfState": "George W. Bush", "HeadOfState_title": "President" } |
Let’s change “George W. Bush” to “Barack Obama” using the .modify clause:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | mysql-js> db.CountryInfo.modify("Name = 'United States'").set("government.HeadOfState", "Barack Obama" ); Query OK, 1 item affected (0.02 sec) mysql-js> db.CountryInfo.find('Name= "United States"') [ { "GNP": 8510700, "IndepYear": 1776, "Name": "United States", "_id": "USA", "demographics": { "LifeExpectancy": 77.0999984741211, "Population": 278357000 }, "geography": { "Continent": "North America", "Region": "North America", "SurfaceArea": 9363520 }, "government": { "GovernmentForm": "Federal Republic", "HeadOfState": "Barack Obama", "HeadOfState_title": "President" } } ] 1 document in set (0.00 sec) |
Conclusion
Document store is an interesting concept and a good add-on on top of the existing MySQL JSON feature. Using the new .find/.add/.modify methods instead of the original SQL statements can be convenient in some cases.
Some might ask, “why do you want to use document store and store information in JSON inside the database if it is relational anyway?” Storing data in JSON can be quite useful in some cases, for example:
- You already have a JSON (i.e., from external feeds) and need to store it anyway. Using the JSON datatype will be more convenient and more efficient.
- You have a flexible schema, typical for the Internet of Things for example, where some sensors might only send temperature data, some might send temperature/humidity/light (but light information is only recorded during the day), etc. Storing it in the JSON format can be more convenient so that you do not have to declare all possible fields in advance, and do not have to run “alter table” if a new sensor starts sending new types of data.
In the next two blog posts, I will show how to use document store for Internet of Things / event streaming, and how to use X Protocol for asynchronous queries in MySQL.
Maybe this is too far ahead, but:
Is there a possibility to integrate stored procedures with this new JSON interface to simulate a database API layer?
Because that can possibly cut out a lot of work for developers.
Hi,
I have to find data by id.. But my id does not exist.. so it is giving timeout error..
Any way to handle this and return message as “ID Does not exist”
Hi,
If I want to modify multiple fields instead of just one field, how should I do it?