Author: Robert Agar

The Internet of Things (IoT) has grown from an interesting concept to a paradigm that is changing the way individuals and businesses operate in the 21st Century. It is based on connecting IP-capable devices so they can communicate with each other in a variety of ways. They range from automated industrial assembly lines to smart appliances that promise to make life easier and more convenient for consumers.

A common aspect of all IoT implementations is that they make use of large amounts of data collected from network-connected devices. As with most data-centric applications, IoT systems rely on databases to store and process the accumulated information that drives them. MySQL is a valid choice in database platforms when you are designing a system that interacts with the IoT.

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If you want to back up your table and views, stored procedures, or stored function definitions, you can use mysqldump or mysqlpump to export the schema without the data. However, if you just want the views you need to look for another option. This blog shows how MySQL Shell comes to the rescue.

Backup the view definition using MySQL Shell

There are a couple of approaches to get the view definitions. One option is to consider the information_schema.VIEWS view which has the following columns:

mysql> SELECT COLUMN_NAME AS Field, COLUMN_TYPE AS Type
         FROM information_schema.COLUMNS
        WHERE TABLE_SCHEMA = 'information_schema'
              AND TABLE_NAME = 'VIEWS'
        ORDER BY ORDINAL_POSITION; …

In a MySQL 5.7 master-slave setup that uses the default semisynchronous replication setting for rpl_semi_sync_master_wait_point, a crash of the master and failover to the slave is considered to be lossless. However, when the crashed master comes back, you may find that it has transactions that are not present in the current master (which was previously a slave). This behavior may be puzzling, given that semisynchronous replication is supposed to be lossless, but this is actually an expected behavior in MySQL. Why exactly this happens is explained in full detail in the …

It has been possible to enable Transparent Data Encryption (TDE) in Percona Server for MySQL/MySQL for a while now, but have you ever wondered how it works under the hood and what kind of implications TDE can have on your server instance? In this blog posts series, we are going to have a look at how TDE works internally. First, we talk about keyrings, as they are required for any encryption to work. Then we explore in detail how encryption in Percona Server for MySQL/MySQL works and what the extra encryption features are that Percona Server for MySQL provides.

MySQL Keyrings

Keyrings are plugins that allow a server to fetch/create/delete keys in a local file (keyring_file) or on a remote server (for example, HashiCorp Vault). All keys are cached locally inside the keyring’s cache to speed up fetching keys. They can be separated into …

In this part we will discuss how NDB batch handling works. Query execution of
complex SQL queries means that more rows can be delivered than the receiver is
capable of receiving. This means that we need to create a data flow from the
producer where the data resides and the query executor in the MySQL Server.

The MySQL Server uses a record where the storage engine have to copy the result
row into the record. This means that the storage of batches of rows is taken
care of by the storage engine.

When NDB performs a range scan it will decide on the possible parallelism before
the scan is started. The NDB API have to allocate enough memory to ensure that
we have memory prepared to receive the rows as they arrive in a flow of result
rows from the data nodes. It is possible to set batch size of hundreds and even
thousands of rows for a query.

The …

We’re delighted to be able to share that Tungsten Clustering – our flagship product – is named in the DBTA 2020 List of Trend Setting Products!

Congratulations to all the products and their teams that were named in the 2020 list.

We have been at the forefront of the market need since 2004 with our solutions for platform agnostic, highly available, globally scaling, clustered MySQL databases that are driving businesses to the cloud (whether hybrid or not) today; and our software solutions are the expression of that.

Tungsten Clustering allows enterprises running business-critical MySQL database applications to cost-effectively …

As you may know, I’m using MySQL exclusively on GNU/Linux. To be honest for me it’s almos 20 years that the year of Linux on the desktop happened. And I’m very happy with that.

But this week-end, I got a comment on an previous post about upgrading to MySQL 8.0, asking how to proceed on Windows. And in fact, I had no idea !

So I spent some time to install a Windows VM and for the very first time, MySQL on Windows !

The goal was to describe how to upgrade from MySQL 5.7 to MySQL 8.0.

So once MySQL 5.7 was installed (using MySQL Installer), I created some data using MySQL Shell:

Of course I used latest MySQL Shell, 8.0.18 in this case. Don’t forget that if you are using MySQL Shell or MySQL Router, you must always use the latest …

In the previous part we showed how NDB will parallelise a simple
2-way join query from TPC-H. In this part we will describe how
the pushdown of joins to a storage engine works in the MySQL Server.

First a quick introduction to how a SQL engine handles a query.
The query normally goes through 5 different phases:
1) Receive query on the client connection
2) Query parsing
3) Query optimisation
4) Query execution
5) Send result of query on client connection

The result of 1) is a text string that contains the SQL query to
execute. In this simplistic view of the SQL engine we will ignore
any such things as prepared statements and other things making the
model more complex.

The text string is parsed by 2) into a data structure that represents
the query in objects that match concepts in the SQL engine.

Query …

Overview

Over the past few days we have been working with a number of customers on the best way to handle Triggers within their MySQL environment when combined with Tungsten Replicator. We looked at situations where Tungsten Replicator was either part of a Tungsten Clustering installation or a standalone replication pipeline.

This blog dives head first into the minefield of Triggers and Replication.

Summary and Recommendations

The conclusion was that there is no easy one-answer-fits-all solution – It really depends on the complexity of your environment and the amount of flexibility you have in being able to adjust. Our top level summary and recommendations are as follows:

If using Tungsten Clustering and you need to use Triggers:

• Switch to …

In part 1 we showed how NDB can parallelise a simple query with only a single
table involved. In this blog we will build on this and show how NDB can only
parallelise some parts of two-way join query. As example we will use Q12 in
DBT3:

SELECT
        l_shipmode,
        SUM(CASE
                WHEN o_orderpriority = '1-URGENT'
                        OR o_orderpriority = '2-HIGH'
                        THEN 1
                ELSE 0
        END) AS high_line_count,
        SUM(CASE
                WHEN o_orderpriority <> …