jjs is a JavaScript shell that ships with Oracle Java 1.8. I recently found myself in a situation where it seemed worth while to check it out, so I did. I do not want to use this post to elaborate too much on why I started looking at jjs, but I intend to write about that shortly. For now I just want to share a few observations, as well as a solution to a particular obstacle I encountered. What is jjs?Java 1.8 (both SDK and JRE) ships a new executable called …

A few days ago I came across the announcement that MaxScale 1.3 finally supports Persistent Connection.

ProxySQL has supported Persistent Connection since it was a prototype (sometime back in 2013). I am therefore very happy that the MaxScale Team finally introduced a long awaited feature.

However, MaxScale's implementation has a serious drawback and I consider it a serious bug (more details towards the end of the article). A bug so serious that it shouldn't reach any GA release.

I like running benchmarks, and given the new feature in MaxScale, I thought it a good time to compare ProxySQL vs MaxScale again. It's been around 6 months since the previous benchmark.

ProxySQL vs MaxScale Benchmark setup

The benchmark setup is very simple:

• a physical server (20 CPU cores) running sysbench, proxysql and maxscale
• a physical server (20 CPU cores) running 3 mysqld …

A few days ago I came across the announcement that MaxScale 1.3 finally supports Persistent Connection.

ProxySQL has supported Persistent Connection since it was a prototype (sometime back in 2013). I am therefore very happy that the MaxScale Team finally introduced a long awaited feature.

However, MaxScale's implementation has a serious drawback and I consider it a serious bug (more details towards the end of the article). A bug so serious that it shouldn't reach any GA release.

I like running benchmarks, and given the new feature in MaxScale, I thought it a good time to compare ProxySQL vs MaxScale again. It's been around 6 months since the previous benchmark.

ProxySQL vs MaxScale Benchmark setup

The benchmark setup is very simple:

• a physical server (20 CPU cores) running sysbench, proxysql and maxscale
• a physical server (20 CPU cores) running 3 mysqld …

The source of this post is in this gist on nbviewer.

After reading about the difference between MySQL Connector/Python and MySQLdb on this blog post I wondered how the C Extension option in Connector/Python would perform.

If you want to run the code yourself you'll need: Jupyter/IPython, Python 3, Requests, MySQLdb, Connector/Python, Matplotlib, Pandas and MySQL.

In [1]:

%matplotlib notebook

In [2]:

import random
import gzip
import time

import pandas as pd
import matplotlib.pyplot as plt
import requests
import mysql.connector
import MySQLdb
for imp in [mysql.connector, MySQLdb]:
    print('Using {imp} {version}'.format(imp=imp.__name__, version=imp.__version__))
print('C Extension for …

We recently released the GA version of Percona Server for MongoDB, which comes with a variety of storage engines: RocksDB, PerconaFT and WiredTiger.

Both RocksDB and PerconaFT are write-optimized engines, so I wanted to compare all engines in a workload oriented to data ingestions.

For a benchmark I used iiBench-mongo (https://github.com/mdcallag/iibench-mongodb), and I inserted one billion (bln) rows into a collection with three indexes. Inserts were done in ten parallel threads.

For memory limits, I used a 10GB as the cache size, with a total limit of 20GB available for the mongod process, …

I really like Amazon.com and I have been a Prime member for several years. Along with millions of different items for sale, Amazon has an affiliate program, where you can earn money advertising products on your web site. When a visitor to your site clicks on a link and orders a product from Amazon, you earn a small commission on the total sale. As an affiliate, you have access to Amazon’s Product Advertising API for obtaining product information. But, you can use this information for many other purposes.

The Amazon API is like most other API’s, and their API web site provides you with code examples and explains how it all works. I am going to show you how a Perl program which you can use to access the API data and store it in a …

In our last post, we showed you how to use pt-stalk to help gather a bunch of data that can be used for troubleshooting. But what type of data does it collect? How do we parse the files to make sense of all that data?

This is the twentieth installment in the ‘Become a MySQL DBA’ blog series. Our previous posts in the DBA series include:

• Troubleshooting with pt-stalk,
• Troubleshooting Galera cluster issues - part 2,
• …

As most of us know, we will have the chance to attend to the MySQL conference in April (from 18 to 21).

For the ones like me that had being there from long, this is a moment of reunion with colleagues and friend. It is also a moment of confrontation and sharing.

In the years this conference had be the moment for the ones surfing the MySQL sea in which things can be put on the table and discuss. Very few matter if it was call MySQL conference or, as it is now Percona Live. What matter is the spirit with which the people participate, and the desire to share.

One of the important aspects was and is, to be able to learn from others experience, innovation and experimentations.

The past year had be a very difficult for me, thankfully only work wise, but I had also be able to be in some interesting exercises, that had allow me to come with a list of proposal that I consider quite …

Performance Schema

In many types of database workloads, using a multi-threaded slave from 5.6+ helps improve replication performance. I’ve had a number of users enable this feature, but have not seen anyone ask how each thread is performing. Here’s a quick way with Performance_Schema to measure the amount of multi-threaded slave activity on each thread (after you have already configured MTS on your slave of course ).

First, we need to enable the 

statements

 instruments:

slave1> UPDATE setup_consumers SET ENABLED = 'YES' WHERE NAME LIKE 'events_statements_%';
Query OK, 2 rows affected (0.00 sec)
Rows matched: 3  Changed: 2  Warnings: 0

Next, let’s find the

THREAD_ID

 for our slave workers:

slave1> SELECT THREAD_ID, …

Knowing which privileges a given account has is easy – just issue SHOW GRANTS FOR user@host.  But what about when you need visibility into privileges from the other direction – which accounts can access specific data?  If you’re a DBA – or perform DBA duties, regardless of your title – you may have been asked this question.  It’s an important question to ask in an audit or compliance review – but it can be a difficult question to answer.    This post will walk through how to assess this, but if you’re impatient and need answers to this question immediately, jump to the end – there’s a simple shortcut.

Things to consider

There are a few things you’ll want to consider about the implementation of the MySQL privilege system as you try to sort out who has access to certain data.

Access type

MySQL can restrict privileges based on operations – somebody who has …