Overview

Hi, it’s too hot summer in Korea. Today I want to talk about an interesting and exciting topic. Try to making your own exporter in Go language.

If you register a specific query, it is a simple program that shows the result of this query as an exporter result metrics. Some of you may still be unfamiliar with what Expoter is.

I will explain about Exporter step by step in today’s post.

Exporter?

You can think of an Exporter as an HTTP server for pulling data from a time series database like Prometheus. Prometheus periodically calls the specific URL of the exporter and saves the result of metrics as a time series.

There are many exporters exist in the everywhere.

Typically, there is mysqld_expoter, which is Prometheus’s Offcial projects, and …

    Pandas is a Python software library for data analysis and manipulation.  It allows you to import data from CSV files, SQL, and Excel.  And it is open source.

    Pandas works well with the MySQL Shell.  After installing Pandas with pip install pandas on my Fedora test system, I was able to load Pandas.  The documentation is excellent at pandas.pydata.org   and I was quickly able to get one of their examples working from within mysqlsh.

Did I mention SQL as a source of data? Reading from MySQL is very easy.  

…

You may have noticed that MySQL 8.0.26 was released today (yea!)  and I recommend reading the release notes but here are some of the highlights.

• TLS version 1 and 1.1 are deprecated. Please use later versions such as 1.2 and 1.3 (you made need OpenSSL 1.1.1 or higher too).
• More information in the server log on client timeouts includes the timeout value, and client user and host when that information is available
• Internal functions to copy values between columns are improved and test at about11% faster (YMMV)

There are a lot of interesting bits of information in the release notes and they show the amount of work that the MySQL Engineering Teams put into a release to give you a better product.
But What Are Those Warnings?

But some of you may be seeing the …

Following the announcement late last year that we’d made our flagship product Tungsten Cluster available on the Amazon Marketplace in an easy-to-access and deploy AMI format, we published some useful resources in the past few months to help users getting started with Tungsten Clustering in the AWS cloud.

Tags: amazon awstungsten cluster amiCloudcloudformation

We might have had one of our largest, most well attended webinars in recent times, for both EMEA and North American timezones, and we thank you for attending. We had many good questions, and we realise that this is a popular topic, so expect to get more blog posts around this. It also helps us drive the development of Galera Manager further, to know what you want (a new release, is just around the corner).

The video recording  of the webinar is available and we encourage you to take a gander.

We did demo a 9-node Galera Cluster running across San Francisco, London and Singapore, and also discussed latency for local nodes, a local Galera Cluster, as well as what penalty you …

This article will show you how to create and manage views in MySQL. A view is a virtual table that does not store its own data but rather displays data that is stored in other tables. Essentially, a view is a result of SQL query execution, which returns the required rows of data from one […]

The post How to Create a View in MySQL appeared first on Devart Blog.

This latest post on MySQL replication follows the ones we did on Amazon Redshift & Amazon Aurora; naturally, we had to cover Amazon RDS as well and so we look here at how to easily and securely replicate from MySQL to Amazon RDS (and vice versa).

Tags: MySQL ReplicationMySQLreal-timetungsten replicatoramazon rds

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Digital14 provides secure solutions, cybersecurity, and digital transformation services to public and commercial sector organizations in the United Arab Emirates. Digital14 supports intelligent and intrinsically secure digital transformations that create great experiences and unlock productivity for...

Somebody needed a job queue in Python: Multiple writers insert into it in random order, and the jobs are written into the MySQL table jobs. From the jobs table, multiple consumers claim jobs in batches of n or smaller (n=100), and process them. After processing, the consumers delete the jobs. We need concurrent job generation and consumption, with proper and efficient locking.

The full source for this example can be seen in mysql-dev-examples

in mysql-claim-jobs.py

.

Base Program

Using our usual includes and setup,

from time import sleep
from random import …