I am starting a series of videos on the MySQL Document Store. The Document Store allows those who do not know Structured Query Language (SQL) to use a database without having to know the basics of relational databases, set theory, or data normalization. The goal is to have sort 2-3 minute episodes on the various facets of the Document Store including the basics, using various programming languages (Node.JS, PHP, Python), and materializing free form schemaless, NoSQL data into columns for use with SQL.

The first Episode, Introduction, can be found here.

Please provide feedback and let me know if there are subjects you would want covered in the near future.

We all do need sometimes to generate raw valid dummy data for our use cases and applications as we start them. Obviously, one can write their own scripts to generate random data, but it is much better to have data, to which human beings can associate with like names, addresses instead of having them filled with random "lorem ipsum" string data :)

While searching for such a tool, I found a site which does exactly this: http://www.generatedata.com/

Documentation: http://benkeen.github.io/generatedata/

This can also be downloaded and installed locally. It supports three types of installations:
- A single, anonymous user account
- A single user account, requires login
- Multiple accounts

Below is the set of wide varied data types it supports for …

via GIPHY I was just responding to some Disqus comments on a recent blog post. Admittedly it had a provocative title Will SQL databases just die already. What do you think? Join 34,000 others and follow Sean Hull on twitter @hullsean. A reader pointed out that some No-SQL databases do support joins. Huh? My face … Continue reading A roughneck walk down database alley →

With tons of new No-SQL database offerings everyday, developers & architects have a lot of options. Cassandra, Mongodb, Couchdb, Dynamodb & Firebase to name a few. Join 33,000 others and follow Sean Hull on twitter @hullsean. What’s more in the data warehouse space, you have Hadoop, which can churn through terabytes of data and get … Continue reading Will SQL just die already? →

In this blog post, we’ll look at the performance of SST data transfer using encryption.

In my previous post, we reviewed SST data transfer in an unsecured environment. Now let’s take a closer look at a setup with encrypted network connections between the donor and joiner nodes.

The base setup is the same as the previous time:

• Database server: Percona XtraDB Cluster 5.7 on donor node
• Database: sysbench database – 100 tables 4M rows each (total ~122GB)
• Network: donor/joiner hosts are connected with dedicated 10Gbit LAN
• Hardware: donor/joiner hosts – boxes with 28 Cores+HT/RAM 256GB/Samsung SSD 850/Ubuntu 16.04

The setup details for the encryption aspects in our testing:

• Cryptography libraries: openssl-1.0.2, …

In this blog post, we’ll look at how Prophet can forecast metrics.

Facebook recently released a forecasting tool called Prophet. Prophet can forecast a particular metric in which we have an interest. It works by fitting time-series data to get a prediction of how that metric will look in the future.

For example, it could be used to:

• Predict how much HTTP traffic we will get, and scale accordingly when needed
• See if a particular feature of our application will have success or if its usage will decline
• Get an approximate date when our database server’s resources will be exhausted
• Forecast new customer’s sign up and resize the staff accordingly
• See what next year’s Black Friday or Cyber Monday will look like, and if we have the resources to handle them
…

Sometimes we are not sure if the database design we have created and our site has been using is correct and optimised. We all do have this feeling at times don't we :)


Well, MySQL provides with PROCEDURE ANALYSE() to help us detect inconsistencies in our database design by suggesting for an optimal datatype and data length for columns.

The syntax for using PROCEDURE ANALYSE() is as below:

SELECT ... FROM ... WHERE ... PROCEDURE
ANALYSE([max_elements,[max_memory]])

Ref: …

The MySQL Document Store functionality allows developers to use a relation database with or without SQL (structured Query Language), also known as NoSQL. The example in this blog is hopefully a simple look at this new feature of MySQL. The example data used is from JSONStudio.com and is a JSON formatted data set for US zip (postal) codes (656K compressed). So download your copy of this data set and lets get to work.

Create a collectionCollections are tables and below we create a collection name 'zip' in the test database in the Python dialect.

mysqlsh -u root -p --py test
Creating an X Session to root@localhost:33060/test
Enter password:
Default schema `test` accessible through db.

Welcome to MySQL Shell 1.0.4 Development Preview

Copyright (c) 2016, Oracle and/or its affiliates. …

Is it cheating? Is using MySQL without Structured Query Language (SQL) or putting all your data into one column proper? Impossible a year ago and probably thought as a poor/crazy practice until recently, this is a new type of MySQL usage. NoSQL has had a big impact in the SQL world with several relational products from vendors like MySQL, Microsoft, Postgresql and others offering NoSQL interfaces and JSON data types to their databases.

Several old timers have come to me asking if putting lots of data in a JSON column is cheating? After all data normalization is part of relational databases and the way to efficiency and speed is well organized data. This higgledy–piggledy fashion of putting an entire document in a column without breaking it down to its component sections does violate the first rule of data normalization. And that has …

Introduction

The early architecture of Uber consisted of a monolithic backend application written in Python that used Postgres for data persistence. Since that time, the architecture of Uber has changed significantly, to a model of microservices and new data platforms. …

The post Why Uber Engineering Switched from Postgres to MySQL appeared first on Uber Engineering Blog.