MySQL database and Go language: how to do data compression?

MySQL is an open source relational database management system used to manage databases, and the Go language is a programming language developed by Google. In practical applications, we may need to store and manage large amounts of data, and these data need to be compressed to save storage space and speed up data access. Therefore, this article will explore how to use MySQL database and Go language for data compression.

1. Data compression of MySQL database

MySQL database provides a variety of data compression technologies, the most commonly used of which is the compression function of the InnoDB storage engine. The InnoDB storage engine is the default storage engine of MySQL. It provides functions such as row-level locking and transaction support, and also supports data compression. Below we use examples to understand how to use it for data compression.

1. Enable the data compression function of the InnoDB storage engine

First, you need to enable the data compression function of the InnoDB storage engine in MySQL. This can be accomplished through the following SQL statement:

ALTER TABLE table_name ROW_FORMAT=COMPRESSED KEY_BLOCK_SIZE=8;

where table_name is the name of the table to be compressed, and KEY_BLOCK_SIZE specifies each index block. Size, this value is generally set to 8 or 16, the specific setting can be determined according to the actual situation.

2. Compress existing data

If there is already a large amount of data that needs to be compressed, it can be done through the following steps:

(1) Create A new copy of the table:

CREATE TABLE new_table LIKE old_table;

(2) Import the data of the old table into the new table:

INSERT INTO new_table SELECT * FROM old_table;

(3) Change the compression format of the new table to COMPRESSED:

ALTER TABLE new_table ROW_FORMAT=COMPRESSED KEY_BLOCK_SIZE=8;

(4) Delete the old table:

DROP TABLE old_table;

(5) Rename the new table to the old table:

ALTER TABLE new_table RENAME TO old_table;

Go through the above steps , we can compress the existing data.

3. Advantages and disadvantages of using the compression function of the InnoDB storage engine

The advantage of the compression function of the InnoDB storage engine is that it can greatly reduce the occupation of storage space and speed up data processing. Reading speed. But there are also some disadvantages, such as compression will increase the cost of data writing and decompression, and the InnoDB storage engine requires more CPU resources when running.

2. Data compression of Go language

Go language provides a variety of data compression technologies, the most commonly used of which is the use of gzip and zlib packages for data compression. gzip is a data compression format that can compress and decompress data by using the gzip package. zlib is another data compression format that can be used to compress and decompress data using the zlib package.

Let’s learn how to use the gzip package and zlib package for data compression through examples.

1. Using the gzip package for data compression

Using the gzip package for data compression is very simple and can be completed by the following steps:

(1) Import gzip package:

import "compress/gzip"

(2) Create a gzip.Writer object:

gzipWriter := gzip.NewWriter(buffer)

Among them, buffer is a byte buffer area used to store compressed data.

(3) Write data to the gzip.Writer object:

gzipWriter.Write(data)

Among them, data is the data to be compressed.

(4) Close the gzip.Writer object:

gzipWriter.Close()

Through the above steps, we can use the gzip package to compress the data.

2. Use the zlib package for data compression

Using the zlib package for data compression is also very simple and can be completed by the following steps:

(1) Import the zlib package:

import "compress/zlib"

(2) Create a zlib.Writer object:

zlibWriter := zlib.NewWriter(buffer)

Among them, buffer is a byte buffer area used to store compressed data.

(3) Write data to the zlib.Writer object:

zlibWriter.Write(data)

Among them, data is the data to be compressed.

(4) Close the zlib.Writer object:

zlibWriter.Close()

Through the above steps, we can use the zlib package to compress the data.

3. Advantages and disadvantages of using gzip package and zlib package

The advantage of using gzip package and zlib package for data compression is that the compression and decompression speed is faster, and it can also be used in Save bandwidth when transmitting. But there are also some disadvantages, such as the inability to perform data retrieval during compression, and the need to use additional code to convert the compressed data into a readable format.

3. Use MySQL and Go language for data compression

In practical applications, we may need to compress the data stored in the MySQL database and perform data access in the Go language at the same time. unzip. Below we use examples to understand how to use MySQL and Go language for data compression.

1. Data compression in MySQL

We can use the compression function of the InnoDB storage engine to compress data in the MySQL database. First, you need to enable the data compression function of the InnoDB storage engine in MySQL, and then perform compression through the above steps.

2. Decompressing data in Go language

Decompressing data in Go language is also very simple. It can be completed by following the following steps:

(1 ) Import gzip or zlib package:

import "compress/gzip"
or
import "compress/zlib"

(2) Create a gzip.Reader or zlib.Reader Object:

gzipReader, _ := gzip.NewReader(buffer)

or

zlibReader, _ := zlib.NewReader(buffer)

where , buffer is a byte array containing compressed data.

(3) Read data from gzip.Reader or zlib.Reader object:

zlibReader.Read(data)

or

gzipReader. Read(data)

Among them, data is a byte array that stores decompressed data.

(4) Close the gzip.Reader or zlib.Reader object:

gzipReader.Close()

or

zlibReader.Close()

Through the above steps, we can decompress data in Go language.

4. Summary

This article introduces how to use MySQL database and Go language for data compression. MySQL provides the compression function of the InnoDB storage engine, which can greatly reduce the storage space occupied. The Go language provides the gzip package and zlib package for data compression and decompression, which can save bandwidth during transmission. The combination of the two allows for more efficient data storage and management.

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