A Demo of the NoSQL JSON schemaless solution that is native in MySQL aka Document Store. Presented at SPOUG Technical Conference 25-Sep-18, Madrid, Spain.

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MySQL Document Store dirigido a
Desarrolladores
Keith Hollman
MySQL Principal Solution Architect
keith.hollman@oracle.com
DEMO

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Install MySQL 8.0
$ export PATH=$PATH:/usr/local/mysql/mysql-shell-commercial-8.0.11-linux-
glibc2.12-x86-64bit/bin:/usr/local/mysql/mysql-commercial-8.0.11-linux-
glibc2.12-x86_64/bin
$ cd /usr/local/mysql/mysql-commercial-8.0.11-linux-glibc2.12-x86_64/bin
$ mysqld --defaults-file=my.cnf --initialize-insecure
$ mysqld --defaults-file=my.cnf &

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Download & install Mongo
$ tar zxvf mongodb-linux-x86_64-4.0.0.tar.gz
$ cd /usr/local/mongodb-linux-x86_64-4.0.0
$ export PATH=$PATH:/usr/local/mongodb-linux-x86_64-4.0.0/bin
$ mkdir -p /opt/mongo/data mongo/log
$ vi mongod.conf
systemLog:
destination: file
path: "/opt/mongo/log/mongod.log"
logAppend: true
storage:
dbPath: "/opt/mongo/data"
...
$ mongod --config /usr/local/mongodb-linux-x86_64-4.0.0/mongod.conf

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Download data to import into mongo
• https://docs.mongodb.com/manual/tutorial/geospatial-tutorial/index.html
• File to be downloaded is:
– https://raw.githubusercontent.com/mongodb/docs-
assets/geospatial/restaurants.json
$ mongoimport DocStore/demo/restaurants.json -c restaurants

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Export data for importing into MySQL
• This example is inspired by @datacharmer's work:
https://www.slideshare.net/datacharmer/mysql-documentstore
• And also:
https://www.slideshare.net/lefred.descamps/mysql-document-store-how-to-replace-a-
nosql-database-by-mysql-without-effort-but-with-a-lot-gains
$ mongo --quiet --eval 'DBQuery.shellBatchSize=30000;
db.restaurants.find().shellPrint()'
| perl -pe 's/(?:ObjectId|ISODate)(("[^"]+"))/ $1/g'
> DocStore/demo/all_recs.json

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• Before we start loading data, let's
tail the general_log:
$ cd /opt/mysql/8011/data
$ tail -100f tail -100f
khollman_8011.log
• Create the environment within
MySQL:
$ cd DocStore/demo
$ mysqlsh --uri root@localhost
session.createSchema('test')
use test
db.createCollection('restaurants')
py
import json
import re
with open ('all_recs.json', 'r') as
json_data:
for line in json_data:
skip = re.match('Type', line)
if not skip:
rec = json.loads(line)
db.restaurants.add(rec).execute()
Loading data into MySQL

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• Now the data is imported, let's
query it:
db.restaurants.find()
db.restaurants.find().limit(1)
db.restaurants.find().fields(["_id","na
me","cuisine"]).limit(2)
• Using sql still? For whatever reason:
session.sql("show create table
restaurants")
session.sql("select * from
restaurants")
session.sql("select * from restaurants
limit 2")
• Let's update an attribute of the
collection, using the id:
db.restaurants.modify("_id='55cba2476c
522cafdb053add'").set("cuisine","Itali
an")
db.restaurants.find("_id='55cba2476c52
2cafdb053add'")
Querying data

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Querying data (cont.)
• We're ACID, and can still do transactions:
session.startTransaction()
db.restaurants.remove("_id='55cba2476c522cafdb053add'")
db.restaurants.find("_id='55cba2476c522cafdb053add'")
db.restaurants.modify("_id ='55cba2476c522cafdb053ade'").set("name", "The
Hybrid Lunch")
db.restaurants.find("_id = '55cba2476c522cafdb053ade'")
session.rollback()
db.restaurants.find("_id='55cba2476c522cafdb053add'")
db.restaurants.find("_id = '55cba2476c522cafdb053ade'")
• Using SQL and formatting:
SELECT doc->>"$.name" AS name, doc->>"$.cuisine" AS cuisine FROM restaurants
where doc->>"$.cuisine" is not null;

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• Getting data out of the Collection,
dynamically:
ALTER TABLE restaurants ADD COLUMN
borough VARCHAR(20) GENERATED ALWAYS
AS
(json_unquote(json_extract(`doc`,'$.bo
rough'))) VIRTUAL;
• same as:
ALTER TABLE restaurants ADD COLUMN
borough VARCHAR(20) GENERATED ALWAYS
AS
(doc->>"$.borough") VIRTUAL;
• Using MySQL 8.0 CTE:
WITH cte1 AS (SELECT doc->>"$.name" AS
name, doc->>"$.cuisine" AS cuisine,
(SELECT AVG(score) FROM
json_table(doc, "$.grades[*]" COLUMNS
(score INT PATH"$.score")) AS r) AS
avg_score FROM restaurants) SELECT
*, RANK() OVER (PARTITION BY cuisine
ORDER BY avg_score) AS `rank`
FROM cte1 ORDER BY `rank`, avg_score
DESC LIMIT 30;
Querying data (cont.)

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More examples & Information
• https://elephantdolphin.blogspot.com/2018/06/mongodb-versus-mysql-
document-store.html
• https://mysqlserverteam.com/mysql-8-0-from-sql-tables-to-json-
documents-and-back-again/
• https://www.mysql.com/news-and-events/web-seminars/nosql-
development-for-mysql-document-store-using-java/

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Preguntas?

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