Default Adminer Login Screen

Using Adminer to Manage your Databases

Introduction

If you find yourself interacting with a database system such as MySQL, PostgreSQL, MS SQL, Oracle, or even SQLite, sometimes you find that some of the tasks you perform are more conveniently executed using a GUI rather then using the default management utility (usually run from a CLI) provided by the database system itself. Some of you may already use other tools such as phpMyAdmin, or phpPgAdmin. This article will talk about another web based database management tool known as Adminer. Adminer allows for the management of all the database systems mentioned above.This article covers Debian (& Ubuntu), Fedora, and ArchLinux.

From its website: Adminer (formerly phpMinAdmin) is a full-featured database management tool written in PHP. Conversely to phpMyAdmin, it consist of a single file ready to deploy to the target server. Adminer is available for MySQL, PostgreSQL, SQLite, MS SQL and Oracle.

Adminer has an entire page dedicated to a comparison between itself and phpMyAdmin. Some notable features in Adminer that are either absent or incomplete in phpMyAdmin include: full support for views, full support for triggers, events, functions, routines, and ability to group data and apply functions to data in select data (to name a few). This article will cover its installation, configuration, customization, and some usage example for MySQL and PostgreSQL.

Pre-requisites

  • Have some knowledge in web administration and development (HTML, CSS, PHP, and Apache)
  • This article assumes you have Apache, PHP, your database system of choice configured.
  • I’ll be running Adminer on a local development LAMP stack I run on my netbook

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Big Data Manipulation for Fun and Profit Part 3

Big Data Manipulation for Fun and Profit Part 3

There have been two previous article in this series, which you may want to read first if you have not read them yet; Big Data Manipulation for Fun and Profit Part 1 and Big Data Manipulation for Fun and Profit Part 2.

In this series, we discuss various ideas and practical approaches for handling big data, or more specifically handling, transforming, mangling, munging, parsing, wrangling, transforming and manipulating the data at the Linux command line.

This third article in the series will continue explore Bash tools which can help us when processing and manipulating text-based (or in some cases binary) big data. As mentioned in the previous articles, data transformation in general is an semi-endless topic as there are hundreds of tools for each particular text format. Remember that at times using Bash tools may not be the best solution, as an off-the-shelf tool may do a better job. That said, this series is specifically for all those (many) other times when no tool is available to get your data in the format of your choice.

Finally, if you want to learn more about why big data manipulation can be both fun and profitable… please read Part 1 first.

In this tutorial you will learn:

  • Additional big data wrangling / parsing / handling / manipulation / transformation techniques
  • What Bash tools are available to assist you, specifically for text based applications
  • Various examples, showing different methods and approaches

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How to Make Decimal Calculations In Bash Using bc

How to Make Decimal Calculations In Bash Using bc

Decimal calculations are sometimes required in Bash. The standard calculation Bash programming idiom ($[]) is unable to provide a decimal output. Whilst we can trick it into calculating (but not generating) a decimal output by multiplying the numbers by for example a factor of 1000 and then doing an text based splitting, this is a ugly workaround and creates complex code. There is however a utility in Bash which can natively do decimal based calculations without any tricks or workarounds!

In this tutorial you will learn:

  • How to use bc to perform decimal calculations
  • How to make decimal based calculations at the Bash command line or from in your scripts
  • How to use variables to store the results produced by bc
  • How to use variables in further calculations
  • How to avoid Bash variable quoting errors

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Retrieving Webpages Using wget, curl and lynx

Retrieving Webpages Using wget, curl and lynx

Whether you are an IT professional who needs to download 2000 online bug reports into a flat text file and parse them to see which ones need attention, or a mum who wants to download 20 recipes from an public domain website, you can benefit from knowing the tools which help you download webpages into a text based file. If you are interested in learning more about how to parse the pages you download, you can have a look at our Big Data Manipulation for Fun and Profit Part 1 article.

In this tutorial you will learn:

  • How to retrieve/download webpages using wget, curl and lynx
  • What the main differences between the wget, curl and lynx tools are
  • Examples showing how to use wget, curl and lynx
Retrieving Webpages Using wget, curl and lynx

Retrieving Webpages Using wget, curl and lynx

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Big Data Manipulation for Fun and Profit Part 1

Big Data Manipulation for Fun and Profit Part 1

These days everyone seems to be speaking about Big Data – but what does it really mean? The term is used quite ambiguously in a variety of situations. For the purposes of this article, and the series, we will refer to big data whenever we mean ‘a large amount of textual data, in any format (for example plain ASCII text, XML, HTML, or any other human-readable or semi-human-readable format). Some techniques shown may work well for binary data also, when used with care and knowledge.

So, why fun (ref title)?

Handling gigabytes of raw textual data in a quick and efficient script, or even using a one-liner command (see Linux Complex Bash One Liner Examples to learn more about one-liners in general), can be quite fun, especially when you get things to work well and are able to automate things. We can never learn enough about how to handle big data; the next challenging text parse will always be around the corner.

And, why profit?

Many of the world’s data is stored in large textual flat files. For example, did you know you can download the full Wikipedia database? The problem is that often this data is formatted in some other format like HTML, XML or JSON, or even proprietary data formats! How do you get it from one system to another? Knowing how to parse big data, and parse it well, puts all the power at your fingertips to change data from one format to another. Simple? Often the answer is ‘No’, and thus it helps if you know what you are doing. Straightforward? Idem. Profitable? Regularly, yes, especially if you become good at handling and using big data.

Handling big data is also referred to as ‘data wrangling’. I started working with big data over 17 years ago, so hopefully there is a thing or two you can pickup from this series. In general, data transformation as a topic is semi-endless (hundreds of third-party tools are available for each particular text format), but I will focus on one specific aspect which applies to textual data parsing; using the Bash command line to parse any type of data. At times, this may not be the best solution (i.e. a pre-created tool may do a better job), but this series is specifically for all those (many) other times when no tool is available to get your data ‘just right’.

In this tutorial you will learn:

Big Data Manipulation for Fun and Profit Part 1

Big Data Manipulation for Fun and Profit Part 1

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Big Data Manipulation for Fun and Profit Part 2

Big Data Manipulation for Fun and Profit Part 2

In the first part of this big data manipulation series – which you may want to read first if you haven’t read it yet; Big Data Manipulation for Fun and Profit Part 1 – we discussed at some length the various terminologies and some of the ideas surrounding big data, or more specifically as it relates to handling, transforming, mangling, munging, parsing, wrangling, transforming and manipulating the data. Often these terms are use interchangeably and often their use overlaps. We also looked at the first set of Bash tools which may help us with work related to these terms.

This article will explore a further set of Bash tools which can help us when processing and manipulating text-based (or in some cases binary) big data. As mentioned in the previous article, data transformation in general is an semi-endless topic as there are hundreds of tools for each particular text format. Remember that at times using Bash tools may not be the best solution, as an off-the-shelf tool may do a better job. That said, this series is specifically for all those (many) other times when no tool is available to get your data in the format of your choice.

And, if you want to learn why big data manipulation can be both profitable and fun… please read Part 1 first.

In this tutorial you will learn:

  • More big data wrangling / parsing / handling / manipulation / transformation techniques
  • What Bash tools are available to help you, specifically for text based applications
  • Examples showing different methods and approaches
Big Data Manipulation for Fun and Profit Part 2

Big Data Manipulation for Fun and Profit Part 2

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Apache Solr installed on Linux

Apache Solr Linux install

Apache Solr is open source search software. It’s capable of being implemented as an enterprise-level search engine thanks to its high scalability, advanced indexing, fast queries, and ability to integrate with a large variety of applications. It’s capable of tackling big data and also has high availability with its load balancing and failover configurations.

The platform is written in Java and can be installed on Linux systems. In this guide, we’ll show the step by step instructions for installing Apache Solr on some of the most popular Linux distros, including Ubuntu, Debian, CentOS, and Red Hat.

In this tutorial you will learn:

  • How to install Apache Solr on Debian based systems
  • How to install Apache Solr on Red Hat based systems
  • Initial configuration of Apache Solr
Apache Solr installed on Linux

Apache Solr installed on Linux

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Installing XAMPP on Ubuntu Linux

How to install XAMPP on Ubuntu Linux

Hosting a website on a Linux system usually involves multiple software packages that operate together to deliver a web browsing experience to potential viewers. For example, it’s common for PHP to dynamically render web content but retrieve data from a database. These are two separate components and they must both be installed to present a website as intended.

XAMPP is a software stack that can run on Ubuntu Linux and make your life a little easier when it comes to web hosting. XAMPP stands for cross-platform (X), Apache (A), MariaDB (M), PHP (P), and Perl (P). These are all common components used in web hosting, and combining them into a single installation makes the initial setup less complicated. XAMPP also comes with Bitnami, which allows you to install content managements systems, such as WordPress, as well as other apps on top of your XAMPP installation if you choose.

In this guide, we’ll cover the installation of XAMPP on Ubuntu Linux. Follow along with our step by step instructions to get it setup on your own system.

In this tutorial you will learn:

  • How to install XAMPP on Ubuntu Linux
  • How to manage your XAMPP installation
Installing XAMPP on Ubuntu Linux

Installing XAMPP on Ubuntu Linux

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Redis on Ubuntu

How to install Redis on Ubuntu Linux

Redis is open source software used as a database and cache that sits in memory, allowing for exceptional performance. When you’re ready to give this lightning fast program a try, the developers recommend installing Redis on a Linux system, and what better candidate than Ubuntu Linux?

In this tutorial, we’ll guide you through the step by step instructions of installing Redis (both server and client) on Ubuntu. Then, we’ll verify that it’s connectable and configure the UFW firewall to allow incoming connections.

In this tutorial you will learn:

  • How to install Redis Server and Client on Ubuntu Linux
  • How to perform a connection test and configure UFW to allow Redis

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Deleting a user from MySQL

How to delete MySQL/MariaDB user

If you have an outdated or unused account in your MySQL or MariaDB database, it’s best to get rid of it. Having even one extra user is an additional vulnerability and attack surface in the database. In this guide, we’ll show you the step by the step instructions to delete a specific user from a MySQL or MariaDB database from the command line on a Linux system.

DID YOU KNOW?
If you’ve forgotten the password to a user account and need to reset it, there’s no need to delete it and start over. We have separate guides for changing a user password in MySQL and changing the root password in MySQL.

In this tutorial you will learn:

  • How to delete a user from MySQL/MariaDB database

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Changing MySQL user password

MySQL: change user password

Have you or one of your MySQL users forgotten the password to a MySQL account? It’s very easy to reset a MySQL user password on Linux, and we’ll show you the commands and step by step instructions below.

Changing the MySQL root password is a bit more involved, so we’ve written a separate guide on how to change MySQL root password.

In this tutorial you will learn:

  • How to change MySQL user password

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How to install MongoDB on Ubuntu Linux

How to install MongoDB on Ubuntu Linux

MongoDB is popular database software capable of running on a variety of systems, including Linux. In this guide, we’ll be taking you through the steps of installing MongoDB on Ubuntu Linux, as well as some basic configuration after it’s up and running.

In this tutorial you will learn:

  • How to install MongoDB
  • How to control MongoDB (start, stop, etc)
  • How to connect to MongoDB remotely
  • How to change MongoDB default port

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