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      Understanding Database Sharding


      Introduction

      Any application or website that sees significant growth will eventually need to scale in order to accommodate increases in traffic. For data-driven applications and websites, it’s critical that scaling is done in a way that ensures the security and integrity of their data. It can be difficult to predict how popular a website or application will become or how long it will maintain that popularity, which is why some organizations choose a database architecture that allows them to scale their databases dynamically.

      In this conceptual article, we will discuss one such database architecture: sharded databases. Sharding has been receiving lots of attention in recent years, but many don’t have a clear understanding of what it is or the scenarios in which it might make sense to shard a database. We will go over what sharding is, some of its main benefits and drawbacks, and also a few common sharding methods.

      What is Sharding?

      Sharding is a database architecture pattern related to horizontal partitioning — the practice of separating one table’s rows into multiple different tables, known as partitions. Each partition has the same schema and columns, but also entirely different rows. Likewise, the data held in each is unique and independent of the data held in other partitions.

      It can be helpful to think of horizontal partitioning in terms of how it relates to vertical partitioning. In a vertically-partitioned table, entire columns are separated out and put into new, distinct tables. The data held within one vertical partition is independent from the data in all the others, and each holds both distinct rows and columns. The following diagram illustrates how a table could be partitioned both horizontally and vertically:

      Example tables showing horizontal and vertical partitioning

      Sharding involves breaking up one’s data into two or more smaller chunks, called logical shards. The logical shards are then distributed across separate database nodes, referred to as physical shards, which can hold multiple logical shards. Despite this, the data held within all the shards collectively represent an entire logical dataset.

      Database shards exemplify a shared-nothing architecture. This means that the shards are autonomous; they don’t share any of the same data or computing resources. In some cases, though, it may make sense to replicate certain tables into each shard to serve as reference tables. For example, let’s say there’s a database for an application that depends on fixed conversion rates for weight measurements. By replicating a table containing the necessary conversion rate data into each shard, it would help to ensure that all of the data required for queries is held in every shard.

      Oftentimes, sharding is implemented at the application level, meaning that the application includes code that defines which shard to transmit reads and writes to. However, some database management systems have sharding capabilities built in, allowing you to implement sharding directly at the database level.

      Given this general overview of sharding, let’s go over some of the positives and negatives associated with this database architecture.

      Benefits of Sharding

      The main appeal of sharding a database is that it can help to facilitate horizontal scaling, also known as scaling out. Horizontal scaling is the practice of adding more machines to an existing stack in order to spread out the load and allow for more traffic and faster processing. This is often contrasted with vertical scaling, otherwise known as scaling up, which involves upgrading the hardware of an existing server, usually by adding more RAM or CPU.

      It’s relatively simple to have a relational database running on a single machine and scale it up as necessary by upgrading its computing resources. Ultimately, though, any non-distributed database will be limited in terms of storage and compute power, so having the freedom to scale horizontally makes your setup far more flexible.

      Another reason why some might choose a sharded database architecture is to speed up query response times. When you submit a query on a database that hasn’t been sharded, it may have to search every row in the table you’re querying before it can find the result set you’re looking for. For an application with a large, monolithic database, queries can become prohibitively slow. By sharding one table into multiple, though, queries have to go over fewer rows and their result sets are returned much more quickly.

      Sharding can also help to make an application more reliable by mitigating the impact of outages. If your application or website relies on an unsharded database, an outage has the potential to make the entire application unavailable. With a sharded database, though, an outage is likely to affect only a single shard. Even though this might make some parts of the application or website unavailable to some users, the overall impact would still be less than if the entire database crashed.

      Drawbacks of Sharding

      While sharding a database can make scaling easier and improve performance, it can also impose certain limitations. Here, we’ll discuss some of these and why they might be reasons to avoid sharding altogether.

      The first difficulty that people encounter with sharding is the sheer complexity of properly implementing a sharded database architecture. If done incorrectly, there’s a significant risk that the sharding process can lead to lost data or corrupted tables. Even when done correctly, though, sharding is likely to have a major impact on your team’s workflows. Rather than accessing and managing one’s data from a single entry point, users must manage data across multiple shard locations, which could potentially be disruptive to some teams.

      One problem that users sometimes encounter after having sharded a database is that the shards eventually become unbalanced. By way of example, let’s say you have a database with two separate shards, one for customers whose last names begin with letters A through M and another for those whose names begin with the letters N through Z. However, your application serves an inordinate amount of people whose last names start with the letter G. Accordingly, the A-M shard gradually accrues more data than the N-Z one, causing the application to slow down and stall out for a significant portion of your users. The A-M shard has become what is known as a database hotspot. In this case, any benefits of sharding the database are canceled out by the slowdowns and crashes. The database would likely need to be repaired and resharded to allow for a more even data distribution.

      Another major drawback is that once a database has been sharded, it can be very difficult to return it to its unsharded architecture. Any backups of the database made before it was sharded won’t include data written since the partitioning. Consequently, rebuilding the original unsharded architecture would require merging the new partitioned data with the old backups or, alternatively, transforming the partitioned DB back into a single DB, both of which would be costly and time consuming endeavors.

      A final disadvantage to consider is that sharding isn’t natively supported by every database engine. For instance, PostgreSQL does not include automatic sharding as a feature, although it is possible to manually shard a PostgreSQL database. There are a number of Postgres forks that do include automatic sharding, but these often trail behind the latest PostgreSQL release and lack certain other features. Some specialized database technologies — like MySQL Cluster or certain database-as-a-service products like MongoDB Atlas — do include auto-sharding as a feature, but vanilla versions of these database management systems do not. Because of this, sharding often requires a “roll your own” approach. This means that documentation for sharding or tips for troubleshooting problems are often difficult to find.

      These are, of course, only some general issues to consider before sharding. There may be many more potential drawbacks to sharding a database depending on its use case.

      Now that we’ve covered a few of sharding’s drawbacks and benefits, we will go over a few different architectures for sharded databases.

      Sharding Architectures

      Once you’ve decided to shard your database, the next thing you need to figure out is how you’ll go about doing so. When running queries or distributing incoming data to sharded tables or databases, it’s crucial that it goes to the correct shard. Otherwise, it could result in lost data or painfully slow queries. In this section, we’ll go over a few common sharding architectures, each of which uses a slightly different process to distribute data across shards.

      Key Based Sharding

      Key based sharding, also known as hash based sharding, involves using a value taken from newly written data — such as a customer’s ID number, a client application’s IP address, a ZIP code, etc. — and plugging it into a hash function to determine which shard the data should go to. A hash function is a function that takes as input a piece of data (for example, a customer email) and outputs a discrete value, known as a hash value. In the case of sharding, the hash value is a shard ID used to determine which shard the incoming data will be stored on. Altogether, the process looks like this:

      Key based sharding example diagram

      To ensure that entries are placed in the correct shards and in a consistent manner, the values entered into the hash function should all come from the same column. This column is known as a shard key. In simple terms, shard keys are similar to primary keys in that both are columns which are used to establish a unique identifier for individual rows. Broadly speaking, a shard key should be static, meaning it shouldn’t contain values that might change over time. Otherwise, it would increase the amount of work that goes into update operations, and could slow down performance.

      While key based sharding is a fairly common sharding architecture, it can make things tricky when trying to dynamically add or remove additional servers to a database. As you add servers, each one will need a corresponding hash value and many of your existing entries, if not all of them, will need to be remapped to their new, correct hash value and then migrated to the appropriate server. As you begin rebalancing the data, neither the new nor the old hashing functions will be valid. Consequently, your server won’t be able to write any new data during the migration and your application could be subject to downtime.

      The main appeal of this strategy is that it can be used to evenly distribute data so as to prevent hotspots. Also, because it distributes data algorithmically, there’s no need to maintain a map of where all the data is located, as is necessary with other strategies like range or directory based sharding.

      Range Based Sharding

      Range based sharding involves sharding data based on ranges of a given value. To illustrate, let’s say you have a database that stores information about all the products within a retailer’s catalog. You could create a few different shards and divvy up each products’ information based on which price range they fall into, like this:

      Range based sharding example diagram

      The main benefit of range based sharding is that it’s relatively simple to implement. Every shard holds a different set of data but they all have an identical schema as one another, as well as the original database. The application code just reads which range the data falls into and writes it to the corresponding shard.

      On the other hand, range based sharding doesn’t protect data from being unevenly distributed, leading to the aforementioned database hotspots. Looking at the example diagram, even if each shard holds an equal amount of data the odds are that specific products will receive more attention than others. Their respective shards will, in turn, receive a disproportionate number of reads.

      Directory Based Sharding

      To implement directory based sharding, one must create and maintain a lookup table that uses a shard key to keep track of which shard holds which data. In a nutshell, a lookup table is a table that holds a static set of information about where specific data can be found. The following diagram shows a simplistic example of directory based sharding:

      Directory based sharding example diagram

      Here, the Delivery Zone column is defined as a shard key. Data from the shard key is written to the lookup table along with whatever shard each respective row should be written to. This is similar to range based sharding, but instead of determining which range the shard key’s data falls into, each key is tied to its own specific shard. Directory based sharding is a good choice over range based sharding in cases where the shard key has a low cardinality and it doesn’t make sense for a shard to store a range of keys. Note that it’s also distinct from key based sharding in that it doesn’t process the shard key through a hash function; it just checks the key against a lookup table to see where the data needs to be written.

      The main appeal of directory based sharding is its flexibility. Range based sharding architectures limit you to specifying ranges of values, while key based ones limit you to using a fixed hash function which, as mentioned previously, can be exceedingly difficult to change later on. Directory based sharding, on the other hand, allows you to use whatever system or algorithm you want to assign data entries to shards, and it’s relatively easy dynamically add shards using this approach.

      While directory based sharding is the most flexible of the sharding methods discussed here, the need to connect to the lookup table before every query or write can have a detrimental impact on an application’s performance. Furthermore, the lookup table can become a single point of failure: if it becomes corrupted or otherwise fails, it can impact one’s ability to write new data or access their existing data.

      Should I Shard?

      Whether or not one should implement a sharded database architecture is almost always a matter of debate. Some see sharding as an inevitable outcome for databases that reach a certain size, while others see it as a headache that should be avoided unless it’s absolutely necessary, due to the operational complexity that sharding adds.

      Because of this added complexity, sharding is usually only performed when dealing with very large amounts of data. Here are some common scenarios where it may be beneficial to shard a database:

      • The amount of application data grows to exceed the storage capacity of a single database node.
      • The volume of writes or reads to the database surpasses what a single node or its read replicas can handle, resulting in slowed response times or timeouts.
      • The network bandwidth required by the application outpaces the bandwidth available to a single database node and any read replicas, resulting in slowed response times or timeouts.

      Before sharding, you should exhaust all other options for optimizing your database. Some optimizations you might want to consider include:

      • Setting up a remote database. If you’re working with a monolithic application in which all of its components reside on the same server, you can improve your database’s performance by moving it over to its own machine. This doesn’t add as much complexity as sharding since the database’s tables remain intact. However, it still allows you to vertically scale your database apart from the rest of your infrastructure.
      • Implementing caching. If your application’s read performance is what’s causing you trouble, caching is one strategy that can help to improve it. Caching involves temporarily storing data that has already been requested in memory, allowing you to access it much more quickly later on.
      • Creating one or more read replicas. Another strategy that can help to improve read performance, this involves copying the data from one database server (the primary server) over to one or more secondary servers. Following this, every new write goes to the primary before being copied over to the secondaries, while reads are made exclusively to the secondary servers. Distributing reads and writes like this keeps any one machine from taking on too much of the load, helping to prevent slowdowns and crashes. Note that creating read replicas involves more computing resources and thus costs more money, which could be a significant constraint for some.
      • Upgrading to a larger server. In most cases, scaling up one’s database server to a machine with more resources requires less effort than sharding. As with creating read replicas, an upgraded server with more resources will likely cost more money. Accordingly, you should only go through with resizing if it truly ends up being your best option.

      Bear in mind that if your application or website grows past a certain point, none of these strategies will be enough to improve performance on their own. In such cases, sharding may indeed be the best option for you.

      Conclusion

      Sharding can be a great solution for those looking to scale their database horizontally. However, it also adds a great deal of complexity and creates more potential failure points for your application. Sharding may be necessary for some, but the time and resources needed to create and maintain a sharded architecture could outweigh the benefits for others.

      By reading this conceptual article, you should have a clearer understanding of the pros and cons of sharding. Moving forward, you can use this insight to make a more informed decision about whether or not a sharded database architecture is right for your application.



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      How To Set Up a Remote Database to Optimize Site Performance with MySQL on Ubuntu 18.04


      Introduction

      As your application or website grows, there may come a point where you’ve outgrown your current server setup. If you are hosting your web server and database backend on the same machine, it may be a good idea to separate these two functions so that each can operate on its own hardware and share the load of responding to your visitors’ requests.

      In this guide, we’ll go over how to configure a remote MySQL database server that your web application can connect to. We will use WordPress as an example in order to have something to work with, but the technique is widely applicable to any application backed by MySQL.

      Prerequisites

      Before beginning this tutorial, you will need:

      • Two Ubuntu 18.04 servers. Each should have a non-root user with sudo privileges and a UFW firewall enabled, as described in our Initial Server Setup with Ubuntu 18.04 tutorial. One of these servers will host your MySQL backend, and throughout this guide we will refer to it as the database server. The other will connect to your database server remotely and act as your web server; likewise, we will refer to it as the web server over the course of this guide.
      • Nginx and PHP installed on your web server. Our tutorial How To Install Linux, Nginx, MySQL, PHP (LEMP stack) in Ubuntu 18.04 will guide you through the process, but note that you should skip Step 2 of this tutorial, which focuses on installing MySQL, as you will install MySQL on your database server.
      • MySQL installed on your database server. Follow “How To Install MySQL on Ubuntu 18.04” to set this up.
      • Optionally (but strongly recommended), TLS/SSL certificates from Let’s Encrypt installed on your web server. You’ll need to purchase a domain name and have DNS records set up for your server, but the certificates themselves are free. Our guide How To Secure Nginx with Let’s Encrypt on Ubuntu 18.04 will show you how to obtain these certificates.

      Step 1 — Configuring MySQL to Listen for Remote Connections

      Having one’s data stored on a separate server is a good way to expand gracefully after hitting the performance ceiling of a one-machine configuration. It also provides the basic structure necessary to load balance and expand your infrastructure even more at a later time. After installing MySQL by following the prerequisite tutorial, you’ll need to change some configuration values to allow connections from other computers.

      Most of the MySQL server’s configuration changes can be made in the mysqld.cnf file, which is stored in the /etc/mysql/mysql.conf.d/ directory by default. Open up this file with root privileges in your preferred editor. Here, we’ll use nano:

      • sudo nano /etc/mysql/mysql.conf.d/mysqld.cnf

      This file is divided into sections denoted by labels in square brackets ([ and ]). Find the section labeled mysqld:

      /etc/mysql/mysql.conf.d/mysqld.cnf

      . . .
      [mysqld]
      . . .
      

      Within this section, look for a parameter called bind-address. This tells the database software which network address to listen for connections on.

      By default, this is set to 127.0.0.1, meaning that MySQL is configured to only look for local connections. You need to change this to reference an external IP address where your server can be reached.

      If both of your servers are in a datacenter with private networking capabilities, use your database server’s private network IP. Otherwise, you can use its public IP address:

      /etc/mysql/mysql.conf.d/mysqld.cnf

      [mysqld]
      . . .
      bind-address = db_server_ip
      

      Because you’ll connect to your database over the internet, it’s recommended that you require encrypted connections to keep your data secure. If you don’t encrypt your MySQL connection, anybody on the network could sniff sensitive information between your web and database servers. To encrypt MySQL connections, add the following line after the bind-address line you just updated:

      /etc/mysql/mysql.conf.d/mysqld.cnf

      [mysqld]
      . . .
      require_secure_transport = on
      . . .
      

      Save and close the file when you are finished. If you’re using nano, do this by pressing CTRL+X, Y, and then ENTER.

      For SSL connections to work, you will need to create some keys and certificates. MySQL comes with a command that will automatically set these up. Run the following command, which creates the necessary files. It also makes them readable by the MySQL server by specifying the UID of the mysql user:

      • sudo mysql_ssl_rsa_setup --uid=mysql

      To force MySQL to update its configuration and read the new SSL information, restart the database:

      • sudo systemctl restart mysql

      To confirm that the server is now listening on the external interface, run the following netstat command:

      • sudo netstat -plunt | grep mysqld

      Output

      tcp 0 0 db_server_ip:3306 0.0.0.0:* LISTEN 27328/mysqld

      netstat prints statistics about your server’s networking system. This output shows us that a process called mysqld is attached to the db_server_ip at port 3306, the standard MySQL port, confirming that the server is listening on the appropriate interface.

      Next, open up that port on the firewall to allow traffic through:

      Those are all the configuration changes you need to make to MySQL. Next, we will go over how to set up a database and some user profiles, one of which you will use to access the server remotely.

      Step 2 — Setting Up a WordPress Database and Remote Credentials

      Even though MySQL itself is now listening on an external IP address, there are currently no remote-enabled users or databases configured. Let's create a database for WordPress, and a pair of users that can access it.

      Begin by connecting to MySQL as the root MySQL user:

      Note: If you have password authentication enabled, as described in Step 3 of the prerequisite MySQL tutorial, you will instead need to use the following command to access the MySQL shell:

      After running this command, you will be asked for your MySQL root password and, after entering it, you'll be given a new mysql> prompt.

      From the MySQL prompt, create a database that WordPress will use. It may be helpful to give this database a recognizable name so that you can easily identify it later on. Here, we will name it wordpress:

      • CREATE DATABASE wordpress;

      Now that you've created your database, you next need to create a pair of users. We will create a local-only user as well as a remote user tied to the web server’s IP address.

      First, create your local user, wordpressuser, and make this account only match local connection attempts by using localhost in the declaration:

      • CREATE USER 'wordpressuser'@'localhost' IDENTIFIED BY 'password';

      Then grant this account full access to the wordpress database:

      • GRANT ALL PRIVILEGES ON wordpress.* TO 'wordpressuser'@'localhost';

      This user can now do any operation on the database for WordPress, but this account cannot be used remotely, as it only matches connections from the local machine. With this in mind, create a companion account that will match connections exclusively from your web server. For this, you'll need your web server's IP address.

      Please note that you must use an IP address that utilizes the same network that you configured in your mysqld.cnf file. This means that if you specified a private networking IP in the mysqld.cnf file, you'll need to include the private IP of your web server in the following two commands. If you configured MySQL to use the public internet, you should match that with the web server's public IP address.

      • CREATE USER 'wordpressuser'@'web-server_ip' IDENTIFIED BY 'password';

      After creating your remote account, give it the same privileges as your local user:

      • GRANT ALL PRIVILEGES ON wordpress.* TO 'wordpressuser'@'web_server_ip';

      Lastly, flush the privileges so MySQL knows to begin using them:

      Then exit the MySQL prompt by typing:

      Now that you've set up a new database and a remote-enabled user, you can move on to testing whether you're able to connect to the database from your web server.

      Step 3 — Testing Remote and Local Connections

      Before continuing, it's best to verify that you can connect to your database from both the local machine — your database server — and from your web server with each of the wordpressuser accounts.

      First, test the local connection from your database server by attempting to log in with your new account:

      • mysql -u wordpressuser -p

      When prompted, enter the password that you set up for this account.

      If you are given a MySQL prompt, then the local connection was successful. You can exit out again by typing:

      Next, log into your web server to test remote connections:

      You'll need to install some client tools for MySQL on your web server in order to access the remote database. First, update your local package cache if you haven't done so recently:

      Then install the MySQL client utilities:

      • sudo apt install mysql-client

      Following this, connect to your database server using the following syntax:

      • mysql -u wordpressuser -h db_server_ip -p

      Again, you must make sure that you are using the correct IP address for the database server. If you configured MySQL to listen on the private network, enter your database's private network IP. Otherwise, enter your database server's public IP address.

      You will be asked for the password for your wordpressuser account. After entering it, and if everything is working as expected, you will see the MySQL prompt. Verify that the connection is using SSL with the following command:

      If the connection is indeed using SSL, the SSL: line will indicate this, as shown here:

      Output

      -------------- mysql Ver 14.14 Distrib 5.7.18, for Linux (x86_64) using EditLine wrapper Connection id: 52 Current database: Current user: wordpressuser@203.0.113.111 SSL: Cipher in use is DHE-RSA-AES256-SHA Current pager: stdout Using outfile: '' Using delimiter: ; Server version: 5.7.18-0ubuntu0.16.04.1 (Ubuntu) Protocol version: 10 Connection: 203.0.113.111 via TCP/IP Server characterset: latin1 Db characterset: latin1 Client characterset: utf8 Conn. characterset: utf8 TCP port: 3306 Uptime: 3 hours 43 min 40 sec Threads: 1 Questions: 1858 Slow queries: 0 Opens: 276 Flush tables: 1 Open tables: 184 Queries per second avg: 0.138 --------------

      After verifying that you can connect remotely, go ahead and exit the prompt:

      With that, you've verified local access and access from the web server, but you have not verified that other connections will be refused. For an additional check, try doing the same thing from a third server for which you did not configure a specific user account in order to make sure that this other server is not granted access.

      Note that before running the following command to attempt the connection, you may have to install the MySQL client utilities as you did above:

      • mysql -u wordpressuser -h db_server_ip -p

      This should not complete successfully, and should throw back an error that looks similar to this:

      Output

      ERROR 1130 (HY000): Host '203.0.113.12' is not allowed to connect to this MySQL server

      This is expected, since you haven't created a MySQL user that's allowed to connect from this server, and also desired, since you want to be sure that your database server will deny unauthorized users access to your MySQL server.

      After successfully testing your remote connection, you can proceed to installing WordPress on your web server.

      Step 4 — Installing WordPress

      To demonstrate the capabilities of your new remote-capable MySQL server, we will go through the process of installing and configuring WordPress — the popular content management system — on your web server. This will require you to download and extract the software, configure your connection information, and then run through WordPress's web-based installation.

      On your web server, download the latest release of WordPress to your home directory:

      • cd ~
      • curl -O https://wordpress.org/latest.tar.gz

      Extract the files, which will create a directory called wordpress in your home directory:

      WordPress includes a sample configuration file which we'll use as a starting point. Make a copy of this file, removing -sample from the filename so it will be loaded by WordPress:

      • cp ~/wordpress/wp-config-sample.php ~/wordpress/wp-config.php

      When you open the file, your first order of business will be to adjust some secret keys to provide more security to your installation. WordPress provides a secure generator for these values so that you do not have to try to come up with good values on your own. These are only used internally, so it won't hurt usability to have complex, secure values here.

      To grab secure values from the WordPress secret key generator, type:

      • curl -s https://api.wordpress.org/secret-key/1.1/salt/

      This will print some keys to your output. You will add these to your wp-config.php file momentarily:

      Warning! It is important that you request your own unique values each time. Do not copy the values shown here!

      Output

      define('AUTH_KEY', 'L4|2Yh(giOtMLHg3#] DO NOT COPY THESE VALUES %G00o|te^5YG@)'); define('SECURE_AUTH_KEY', 'DCs-k+MwB90/-E(=!/ DO NOT COPY THESE VALUES +WBzDq:7U[#Wn9'); define('LOGGED_IN_KEY', '*0kP!|VS.K=;#fPMlO DO NOT COPY THESE VALUES +&[%8xF*,18c @'); define('NONCE_KEY', 'fmFPF?UJi&(j-{8=$- DO NOT COPY THESE VALUES CCZ?Q+_~1ZU~;G'); define('AUTH_SALT', '@qA7f}2utTEFNdnbEa DO NOT COPY THESE VALUES t}Vw+8=K%20s=a'); define('SECURE_AUTH_SALT', '%BW6s+d:7K?-`C%zw4 DO NOT COPY THESE VALUES 70U}PO1ejW+7|8'); define('LOGGED_IN_SALT', '-l>F:-dbcWof%4kKmj DO NOT COPY THESE VALUES 8Ypslin3~d|wLD'); define('NONCE_SALT', '4J(<`4&&F (WiK9K#] DO NOT COPY THESE VALUES ^ZikS`es#Fo:V6');

      Copy the output you received to your clipboard, then open the configuration file in your text editor:

      • nano ~/wordpress/wp-config.php

      Find the section that contains the dummy values for those settings. It will look something like this:

      /wordpress/wp-config.php

      . . .
      define('AUTH_KEY',         'put your unique phrase here');
      define('SECURE_AUTH_KEY',  'put your unique phrase here');
      define('LOGGED_IN_KEY',    'put your unique phrase here');
      define('NONCE_KEY',        'put your unique phrase here');
      define('AUTH_SALT',        'put your unique phrase here');
      define('SECURE_AUTH_SALT', 'put your unique phrase here');
      define('LOGGED_IN_SALT',   'put your unique phrase here');
      define('NONCE_SALT',       'put your unique phrase here');
      . . .
      

      Delete those lines and paste in the values you copied from the command line.

      Next, enter the connection information for your remote database. These configuration lines are at the top of the file, just above where you pasted in your keys. Remember to use the same IP address you used in your remote database test earlier:

      /wordpress/wp-config.php

      . . .
      /** The name of the database for WordPress */
      define('DB_NAME', 'wordpress');
      
      /** MySQL database username */
      define('DB_USER', 'wordpressuser');
      
      /** MySQL database password */
      define('DB_PASSWORD', 'password');
      
      /** MySQL hostname */
      define('DB_HOST', 'db_server_ip');
      . . .
      

      And finally, anywhere in the file, add the following line which tells WordPress to use an SSL connection to our MySQL database:

      /wordpress/wp-config.php

      define('MYSQL_CLIENT_FLAGS', MYSQLI_CLIENT_SSL);
      

      Save and close the file.

      Next, copy the files and directories found in your ~/wordpress directory to Nginx's document root. Note that this command includes the -a flag to make sure all the existing permissions are carried over:

      • sudo cp -a ~/wordpress/* /var/www/html

      After this, the only thing left to do is modify the file ownership. Change the ownership of all the files in the document root over to www-data, Ubuntu's default web server user:

      • sudo chown -R www-data:www-data /var/www/html

      With that, WordPress is installed and you're ready to run through its web-based setup routine.

      Step 5 — Setting Up WordPress Through the Web Interface

      WordPress has a web-based setup process. As you go through it, it will ask a few questions and install all the tables it needs in your database. Here, we will go over the initial steps of setting up WordPress, which you can use as a starting point for building your own custom website that uses a remote database backend.

      Navigate to the domain name (or public IP address) associated with your web server:

      http://example.com
      

      You will see a language selection screen for the WordPress installer. Select the appropriate language and click through to the main installation screen:

      WordPress install screen

      Once you have submitted your information, you will need to log into the WordPress admin interface using the account you just created. You will then be taken to a dashboard where you can customize your new WordPress site.

      Conclusion

      By following this tutorial, you've set up a MySQL database to accept SSL-protected connections from a remote WordPress installation. The commands and techniques used in this guide are applicable to any web application written in any programming language, but the specific implementation details will differ. Refer to your application or language's database documentation for more information.



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      How to Manage an SQL Database


      Introduction

      SQL databases come installed with all the commands you need to add, modify, delete, and query your data. This cheat sheet-style guide provides a quick reference to some of the most commonly-used SQL commands.

      How to Use This Guide:

      • This guide is in cheat sheet format with self-contained command-line snippets
      • Jump to any section that is relevant to the task you are trying to complete
      • When you see highlighted text in this guide’s commands, keep in mind that this text should refer to the columns, tables, and data in your own database.
      • Throughout this guide, the example data values given are all wrapped in apostrophes ('). In SQL, it is necessary to wrap any data values that consist of strings in apostrophes. This isn’t required for numeric data, but it also won’t cause any issues if you do include apostrophes.

      Please note that, while SQL is recognized as a standard, most SQL database programs have their own proprietary extensions. This guide uses MySQL as the example relational database management system (RDBMS), but the commands given will work with other relational database programs, including PostgreSQL, MariaDB, and SQLite. Where there are significant differences between RDBMSs, we have included the alternative commands.

      Opening up the Database Prompt (using Socket/Trust Authentication)

      By default on Ubuntu 18.04, the root MySQL user can authenticate without a password using the following command:

      To open up a PostgreSQL prompt, use the following command. This example will log you in as the postgres user, which is the included superuser role, but you can replace that with any already-created role:

      Opening up the Database Prompt (using Password Authentication)

      If your root MySQL user is set to authenticate with a password, you can do so with the following command:

      If you've already set up a non-root user account for your database, you can also use this method to log in as that user:

      The above command will prompt you for your password after you run it. If you'd like to supply your password as part of the command, immediately follow the -p option with your password, with no space between them:

      Creating a Database

      The following command creates a database with default settings.

      • CREATE DATABASE database_name;

      If you want your database to use a character set and collation different than the defaults, you can specify those using this syntax:

      • CREATE DATABASE database_name CHARACTER SET character_set COLLATE collation;

      Listing Databases

      To see what databases exist in your MySQL or MariaDB installation, run the following command:

      In PostgreSQL, you can see what databases have been created with the following command:

      Deleting a Database

      To delete a database, including any tables and data held within it, run a command that follows this structure:

      • DROP DATABASE IF EXISTS database;

      Creating a User

      To create a user profile for your database without specifying any privileges for it, run the following command:

      • CREATE USER username IDENTIFIED BY 'password';

      PostgreSQL uses a similar, but slightly different, syntax:

      • CREATE USER user WITH PASSWORD 'password';

      If you want to create a new user and grant them privileges in one command, you can do so by issuing a GRANT statement. The following command creates a new user and grants them full privileges to every database and table in the RDBMS:

      • GRANT ALL PRIVILEGES ON *.* TO 'username'@'localhost' IDENTIFIED BY 'password';

      Deleting a User

      Use the following syntax to delete a database user profile:

      • DROP USER IF EXISTS username;

      Note that this command will not by default delete any tables created by the deleted user, and attempts to access such tables may result in errors.

      Selecting a Database

      Before you can create a table, you first have to tell the RDBMS the database in which you'd like to create it. In MySQL and MariaDB, do so with the following syntax:

      In PostgreSQL, you must use the following command to select your desired database:

      Creating a Table

      The following command structure creates a new table with the name table, and includes two columns, each with their own specific data type:

      • CREATE TABLE table ( column_1 column_1_data_type, column_2 column_2_data_taype );

      Deleting a Table

      To delete a table entirely, including all its data, run the following:

      • DROP TABLE IF EXISTS table

      Inserting Data into a Table

      Use the following syntax to populate a table with one row of data:

      • INSERT INTO table ( column_A, column_B, column_C ) VALUES ( 'data_A', 'data_B', 'data_C' );

      You can also populate a table with multiple rows of data using a single command, like this:

      • INSERT INTO table ( column_A, column_B, column_C ) VALUES ( 'data_1A', 'data_1B', 'data_1C' ), ( 'data_2A', 'data_2B', 'data_2C' ), ( 'data_3A', 'data_3B', 'data_3C' );

      Deleting Data from a Table

      To delete a row of data from a table, use the following command structure. Note that value should be the value held in the specified column in the row that you want to delete:

      • DELETE FROM table WHERE column='value';

      Note: If you do not include a WHERE clause in a DELETE statement, as in the following example, it will delete all the data held in a table, but not the columns or the table itself:

      Changing Data in a Table

      Use the following syntax to update the data held in a given row. Note that the WHERE clause at the end of the command tells SQL which row to update. value is the value held in column_A that aligns with the row you want to change.

      Note: If you fail to include a WHERE clause in an UPDATE statement, the command will replace the data held in every row of the table.

      • UPDATE table SET column_1 = value_1, column_2 = value_2 WHERE column_A=value;

      Inserting a Column

      The following command syntax will add a new column to a table:

      • ALTER TABLE table ADD COLUMN column data_type;

      Deleting a Column

      A command following this structure will delete a column from a table:

      • ALTER TABLE table DROP COLUMN column;

      Performing Basic Queries

      To view all the data from a single column in a table, use the following syntax:

      • SELECT column FROM table;

      To query multiple columns from the same table, separate the column names with a comma:

      • SELECT column_1, column_2 FROM table;

      You can also query every column in a table by replacing the names of the columns with an asterisk (*). In SQL, asterisks act as placeholders to represent “all”:

      Using WHERE Clauses

      You can narrow down the results of a query by appending the SELECT statement with a WHERE clause, like this:

      • SELECT column FROM table WHERE conditions_that_apply;

      For example, you can query all the data from a single row with a syntax like the following. Note that value should be a value held in both the specified column and the row you want to query:

      • SELECT * FROM table WHERE column = value;

      Working with Comparison Operators

      A comparison operator in a WHERE clause defines how the specified column should be compared against the value. Here are some common SQL comparison operators:

      Operator What it does
      = tests for equality
      != tests for inequality
      < tests for less-than
      > tests for greater-than
      <= tests for less-than or equal-to
      >= tests for greater-than or equal-to
      BETWEEN tests whether a value lies within a given range
      IN tests whether a row's value is contained in a set of specified values
      EXISTS tests whether rows exist, given the specified conditions
      LIKE tests whether a value matches a specified string
      IS NULL tests for NULL values
      IS NOT NULL tests for all values other than NULL

      Working with Wildcards

      SQL allows the use of wildcard characters. These are useful if you're trying to find a specific entry in a table, but aren't sure of what that entry is exactly.

      Asterisks (*) are placeholders that represent “all,” this will query every column in a table:

      Percentage signs (%) represent zero or more unknown characters.

      • SELECT * FROM table WHERE column LIKE val%;

      Underscores (_) are used to represent a single unknown character:

      • SELECT * FROM table WHERE column LIKE v_lue;

      Counting Entries in a Column

      The COUNT function is used to find the number of entries in a given column. The following syntax will return the total number of values held in column:

      • SELECT COUNT(column) FROM table;

      You can narrow down the results of a COUNT function by appending a WHERE clause, like this:

      • SELECT COUNT(column) FROM table WHERE column=value;

      Finding the Average Value in a Column

      The AVG function is used to find the average (in this case, the mean) amongst values held in a specific column. Note that the AVG function will only work with columns holding numeric values; when used on a column holding string values, it may return an error or 0:

      • SELECT AVG(column) FROM table;

      Finding the Sum of Values in a Column

      The SUM function is used to find the sum total of all the numeric values held in a column:

      • SELECT SUM(column) FROM table;

      As with the AVG function, if you run the SUM function on a column holding string values it may return an error or just 0, depending on your RDBMS.

      Finding the Largest Value in a Column

      To find the largest numeric value in a column or the last value alphabetically, use the MAX function:

      • SELECT MAX(column) FROM table;

      Finding the Smallest Value in a Column

      To find the smallest numeric value in a column or the first value alphabetically, use the MIN function:

      • SELECT MIN(column) FROM table;

      Sorting Results with ORDER BY Clauses

      An ORDER BY clause is used to sort query results. The following query syntax returns the values from column_1 and column_2 and sorts the results by the values held in column_1 in ascending order or, for string values, in alphabetical order:

      • SELECT column_1, column_2 FROM table ORDER BY column_1;

      To perform the same action, but order the results in descending or reverse alphabetical order, append the query with DESC:

      • SELECT column_1, column_2 FROM table ORDER BY column_1 DESC;

      Sorting Results with GROUP BY Clauses

      The GROUP BY clause is similar to the ORDER BY clause, but it is used to sort the results of a query that includes an aggregate function such as COUNT, MAX, MIN, or SUM. On their own, the aggregate functions described in the previous section will only return a single value. However, you can view the results of an aggregate function performed on every matching value in a column by including a GROUP BY clause.

      The following syntax will count the number of matching values in column_2 and group them in ascending or alphabetical order:

      • SELECT COUNT(column_1), column_2 FROM table GROUP BY column_2;

      To perform the same action, but group the results in descending or reverse alphabetical order, append the query with DESC:

      • SELECT COUNT(column_1), column_2 FROM table GROUP BY column_2 DESC;

      Querying Multiple Tables with JOIN Clauses

      JOIN clauses are used to create result-sets that combine rows from two or more tables. A JOIN clause will only work if the two tables each have a column with an identical name and data type, as in this example:

      • SELECT table_1.column_1, table_2.column_2 FROM table_1 JOIN table_2 ON table_1.common_column=table_2.common_column;

      This is an example of an INNER JOIN clause. An INNER JOIN will return all the records that have matching values in both tables, but won't show any records that don't have matching values.

      It's possible to return all the records from one of two tables, including values that do not have a corresponding match in the other table, by using an outer JOIN clause. Outer JOIN clauses are written as either LEFT JOIN or RIGHT JOIN.

      A LEFT JOIN clause returns all the records from the “left” table and only the matching records from the “right” table. In the context of outer JOIN clauses, the left table is the one referenced in the FROM clause, and the right table is any other table referenced after the JOIN statement. The following will show every record from table_1 and only the matching values from table_2. Any values that do not have a match in table_2 will appear as NULL in the result-set:

      • SELECT table_1.column_1, table_2.column_2 FROM table_1 LEFT JOIN table_2 ON table_1.common_column=table_2.common_column;

      A RIGHT JOIN clause functions the same as a LEFT JOIN, but it prints the all the results from the right table, and only the matching values from the left:

      • SELECT table_1.column_1, table_2.column_2 FROM table_1 RIGHT JOIN table_2 ON table_1.common_column=table_2.common_column;

      Combining Multiple SELECT Statements with UNION Clauses

      A UNION operator is useful for combining the results of two (or more) SELECT statements into a single result-set:

      • SELECT column_1 FROM table UNION SELECT column_2 FROM table;

      Additionally, the UNION clause can combine two (or more) SELECT statements querying different tables into the same result-set:

      • SELECT column FROM table_1 UNION SELECT column FROM table_2;

      Conclusion

      This guide covers some of the more common commands in SQL used to manage databases, users, and tables, and query the contents held in those tables. There are, however, many combinations of clauses and operators that all produce unique result-sets. If you're looking for a more comprehensive guide to working with SQL, we encourage you to check out Oracle's Database SQL Reference.

      Additionally, if there are common SQL commands you'd like to see in this guide, please ask or make suggestions in the comments below.



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