Businesses rely on data-driven decision-making, and they collect large volumes of data to leverage in-depth insights into their product and customers. The first step to ensuring a proper data analysis is to extract data from multiple sources and store it in a central database. After you have retrieved and combined data from multiple sources, it is ready to be loaded into your chosen storage system. Data Loading is the process of moving data to a designated Data Warehouse or any other target database. MySQL is one of the most popular relational databases used by companies to store data and draw insights. You can load data into a table with MySQL through the LOAD DATA command.
In this blog, you’ll learn about MySQL, data loading, and two methods using which you can perform the MySQL Load Data process!
Table of Contents
Prerequisites
- Basic understanding of SQL.
What is MySQL?
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MySQL is an open-source, relational database management system with a client-server model. It was originally developed by MySQL AB, a Swedish company that was acquired by Sun Microsystems in 2008. However, Oracle took over Sun Microsystems in 2010, and MySQL is now owned by the US tech giant.
A database is a system where data is stored and organized. The term relational specifies that the stored data is organized as tables and that every table is related in some way. Systems that run the RDBMS software are called clients, and they have to connect to the RDMBS server to access their data.
MySQL is integral to many popular software stacks of Twitter, Wikipedia, Facebook, Flickr, and YouTube. It is responsible for building and maintaining everything from customer-facing web applications to data-driven services. It’s open-source, offers scalability, and has a rich feature set.
Key Features of MySQL
1) Client-Server Architecture
MySQL is based on a client-server architecture, where the client communicates with the server using an Internet connection to access its data. The MySQL server processes the client’s request and returns the desired output. It’s not necessary for clients to be on the same system as the server. Rather, clients can send queries to remote servers.
2) Scalable
MySQL has a scalable architecture that can support powerful applications and databases that have a high read level but a low write level. It has a low memory leakage issue and offers optimum speed. MySQL can manage huge volumes of data. Although the initial limit is 4GB, companies can increase it to a max of 8TB.
3) Open-Source
MySQL is open-source, meaning it can be used, downloaded, and modified by anyone. It’s free to use and quick to grasp. You can easily study MySQL’s source code and change it based on the requirements. The open-source feature makes debugging, maintenance and upgrades easy while enhancing the end-user experience.
4) Data Types and Character Sets
MySQL supports multiple data types: float, double, unsigned integers, signed integers, character, blob, date, time, variable character, text, datetime, timestamp, year, etc. It supports different character sets, including latin1 (cp1252 character encoding), Ujis, German, other Unicode character sets, etc.
5) Compatible
MySQL is extensively compatible with various technologies and architectures. The RDBMS smoothly runs on all major computing platforms like Linux, Windows, and macOS. Its client-server architecture supports a variety of backends and programming interfaces. Thanks to architectural and language similarities, you can directly migrate data from MySQL to its forks (e.g., MariaDB) and other RDBMSs.
6) Secure
MySQL offers a secure and reliable interface and database management system. It also has a flexible password system. It is used in popular web applications like Drupal, Joomla, WordPress, and more. MySQL ensures that it is verified based on the host before users can access the database.
What is Data Loading?
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Data Loading is the method of copying and loading data from a source location to a database or an application. It defines the last component (LOAD) of the ETL process. The extracted and transformed data is loaded into the target database/application in this step.
How to perform the MySQL Load Data Process?
Since Data Loading is part of the ETL process, organizations need to properly understand the types of ETL tools and methods available and which one(s) works best for their budget, needs, and structure.
- Batch processing: Batch processing ETL tools move data at the scheduled time every day or week. These tools function best for large data volumes and organizations that don’t necessarily need real-time access to their data.
- Cloud-based: These ETL tools are built for scalability and speed. They often allow real-time data processing and include the vendor’s expertise and ready-made infrastructure.
- Open source: Open-source ETL tools are cost-effective as their codebase is publicly accessible, adaptable, and shareable. While an excellent alternative to commercial solutions, these tools can still require some customization or hand-coding.
Method 1: Perform MySQL Load Data Process using Hevo’s No-code Data Pipeline
Hevo provides an Automated No-code Data Pipeline that helps you move your data swiftly to MySQL. Hevo is fully-managed and completely automates the process of not only loading data from your 100+ data sources but also enriching the data and transforming it into an analysis-ready form without having to write a single line of code. Its fault-tolerant architecture ensures that the data is handled in a secure, consistent manner with zero data loss.
Hevo’s fault-tolerant architecture will enrich and transform your data securely and consistently and load it to your destination without any assistance from your side. You can entrust us with your data transfer process by both ETL and ELT processes to a data warehouse, Reverse ETL processes to CRMs, etc and enjoy a hassle-free experience.
You just need to follow a simple 3 step process to load your desired data to MySQL using Hevo:
Step 1: Configure the Source
- Login to your Hevo account using the appropriate credentials.
- Navigate to the Asset Palette and click on the Pipelines option.
- Click on the +Create button to create a new pipeline and search for the required source.
Step 2: Configure the Destination
- In the Select Destination Type page, select your destination. Here, we are selecting MySQL.
- In the Configure your MySQL Destination page, specify the MySQL settings to configure your destination.
- Once you have entered all the configuration details, click on Save & Continue.
- In the Destination Table Prefix field, provide a prefix if you want to modify the Destination table or partition name, else, you can leave the field blank.
- Now, click on Continue to proceed further
Step 3: Test the Connection
- After filling in the details, click on the TEST CONNECTION button to test connectivity to the Destination MySQL.
- Once the test is successful, save the Destination by clicking on SAVE DESTINATION.
Once you have followed all the above three steps, you will be able to perform the MySQL Load Data process in no time!
Here are more reasons to try Hevo:
- Smooth Schema Management: Hevo takes away the tedious task of schema management & automatically detects the schema of incoming data and maps it to your schema in the desired Data Warehouse.
- Exceptional Data Transformations: Best-in-class & Native Support for Complex Data Transformation at fingertips. Code & No-code Flexibility designed for everyone.
- Quick Setup: Hevo with its automated features, can be set up in minimal time. Moreover, with its simple and interactive UI, it is extremely easy for new customers to work on and perform operations.
- Built To Scale: As the number of sources and the volume of your data grows, Hevo scales horizontally, handling millions of records per minute with very little latency.
- Live Support: The Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
Try Hevo to easily perform the MySQL Load Data process.
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Method 2: Perform MySQL Load Data Process using the Load Data Statement
The LOAD DATA statement in MySQL reads rows from a text file at a very high speed. You can load data from a CSV into MySQL with this command. The file can be read from the client host or server host, depending on whether the LOCAL modifier is provided. The LOCAL modifier also affects error handling and data interpretation. LOAD DATA statement is the complement of SELECT … INTO OUTFILE. You’ll have to use SELECT … INTO OUTFILE to write data from a table to a file. However, you’ll have to use LOAD DATA to read the file back into a table.
LOAD DATA
[LOW_PRIORITY | CONCURRENT] [LOCAL]
INFILE 'file_name'
[REPLACE | IGNORE]
INTO TABLE tbl_name
[PARTITION (partition_name [, partition_name] ...)]
[CHARACTER SET charset_name]
[{FIELDS | COLUMNS}
[TERMINATED BY 'string']
[[OPTIONALLY] ENCLOSED BY 'char']
[ESCAPED BY 'char']
]
[LINES
[STARTING BY 'string']
[TERMINATED BY 'string']
]
[IGNORE number {LINES | ROWS}]
[(col_name_or_user_var
[, col_name_or_user_var] ...)]
[SET col_name={expr | DEFAULT}
[, col_name={expr | DEFAULT}] ...]
The LOAD DATA command will read rows from your text file when the LOCAL modifier is given. The INFILE ‘file_name‘ command works similarly to importing data into an MS Excel spreadsheet. It also comes with a default configuration to prevent people from reading random data across the server’s file system. The INTO TABLE statement specifies the table in which we want to move the data.
The {FIELDS | COLUMNS} section ensures that MySQL parses the start of the next line correctly. With the TERMINATED BY ‘string‘ clause, you can define column, field, and line delimiters to interpret and read the input data correctly. For example, the [TERMINATED BY ‘string‘] clause will load a CSV file where the fields are delimited by commas. The syntax of the LINES and FIELDS clauses is the same even if the LOCAL modifier isn’t given.
The [[OPTIONALLY] ENCLOSED BY ‘char‘] clause allows users to specify a character to enclose the field values. For example, using this clause with “” will result in a CSV file where all the fields are enclosed within a double quotation. The [ESCAPED BY ‘char‘] clause allows you to define an escape character to avoid misinterpretation. Whereas, with the [STARTING BY ‘string‘] clause, you can load lines that contain a specified string (or prefix). The IGNORE number {LINES | ROWS} clause will inform MySQL to ignore the specified lines from the beginning of the input file. You can use it to skip an empty or column name header.
MySQL Load Data Example: Loading data into a Table
Once you create a table, you can use MySQL to load data from CSV. For example, let’s take a vet who has to manage pet records, as shown below, and load the CSV file into MySQL.
| name | owner | species | sex | birth | death |
| Fluffy | Harold | cat | f | 1993-02-04 | |
| Claws | Gwen | cat | m | 1994-03-17 | |
| Buffy | Harold | dog | f | 1989-05-13 | |
| Fang | Benny | dog | m | 1990-08-27 | |
| Bowser | Diane | dog | m | 1979-08-31 | 1995-07-29 |
| Chirpy | Gwen | bird | f | 1998-09-11 | |
| Whistler | Gwen | bird | | 1997-12-09 | |
| Slim | Benny | snake | m | 1996-04-29 | |
You can populate an empty table by creating a text file containing a row for each animal, and then load the contents with a single statement. Let’s start by creating a text file pet.txt with one record per line and values separated by tabs. Values should be in the same order in which the columns were listed in the CREATE TABLE statement. In case of missing values (such as death dates for animals that are still alive), you can use NULL values. Use N (backslash, capital-N) to represent null values.
Whistler Gwen bird N 1997-12-09 N
Use the following statement to load the text file pet.txt into the pet table:
mysql> LOAD DATA LOCAL INFILE '/path/pet.txt' INTO TABLE pet;
If your editor uses rn as a line terminator, use this statement instead:
mysql> LOAD DATA LOCAL INFILE '/path/pet.txt' INTO TABLE pet
LINES TERMINATED BY 'rn';
You can use an INSERT statement to add a new record:
mysql> INSERT INTO pet
VALUES ('Puffball','Diane','hamster','f','1999-03-30',NULL);
This is how you can perform the MySQL Load Data Process using Load Data statement.
Conclusion
This article gives a comprehensive overview of MySQL and Data Loading, along with their benefits. Although today you learned about two methods that you can use to perform the MySQL Load Data process. However, knowing where to start and how to combine consumer data from various applications can be a challenge for many companies. This is where Hevo can help save your day!
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Hevo Data is a No-Code Data Pipeline that offers a faster way to move data from 100+ Data Sources to a destination of your choice such as MySQL. Hevo is fully automated and hence does not require you to code.
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Share with us your experience of learning about the methods used for performing MySQL Load Data process in the comments below.