Table partitioning is to distribute large tables in multiple physical files according to rules to improve performance. Its importance lies in optimizing queries and simplifying maintenance. When choosing a suitable partition key, you need to consider the data access mode: 1. Priority is used for RANGE partitioning with the time field; 2. Avoid frequent updates of fields; 3. Select hash or list partitions based on common fields for query. Common types include RANGE suitable for dates, LIST for enumeration values, evenly distributed HASH and KEY partitions. During maintenance, partitions need to be added, merged and deleted old data regularly. Note that the partition key should be the primary key part and the query must have a partition key to achieve cropping.

Table Partitioning is a very effective optimization method when processing large data sets in MySQL. It improves query performance and simplifies maintenance operations by logically dividing a large table into multiple smaller parts. However, to do a good job in partition management, the key is to understand the data access pattern and choose the appropriate partitioning strategy.

What is table partitioning? Why is it important?

MySQL table partitioning distributes the data of a large table in multiple physical files according to certain rules. Although it is still a table logically, from the storage level, each partition is independent. This is especially useful for large datasets, as it can:

• Improve query efficiency: only scan related partitions, not the entire table
• Speed ??up archive and deletion operations: just delete the entire partition
• Improve maintainability: such as backing up or re-indexing a partition

However, if the partitioning strategy is unreasonable, it may bring additional overhead and even affect performance.

How to choose the right partition key?

The selection of partition key directly affects the effect of partition. Here are some common suggestions:

• Try to use the time field : If you frequently query the time range, such as log data, use RANGE or RANGE COLUMNS partition, using the date as the partition key is a good choice.
• Avoid frequent updates : For example, user ID, if changed frequently, will cause records to move between different partitions, increasing I/O and lock competition.
• Consider query mode : If your query is mostly based on a certain field, such as region, category, etc., you can use these fields as the basis for hashing or list partitioning.

For example: You have an order table with millions of new records added every day, and the query is mainly concentrated on the data in recent days. In this case, it is very appropriate to use the order creation time to perform RANGE partitioning.

Common partition types and applicable scenarios

MySQL supports a variety of partitioning methods, each with its own characteristics and scope of application:

• RANGE Partition
  According to the interval of the value, data in obvious order are suitable, such as dates, numbers, etc. For example, put data before 2023 in one partition, and put data in another partition in 2024.

• LIST Partition
  Grouped by predefined discrete values, suitable for enumerated fields. For example, sales data are divided by province, and each province is allocated a partition.

• HASH partition
  Calculate the partition number based on the hash function, which is suitable for situations where data is desired to be distributed evenly. For example, using user ID as hash partitions can make the data more evenly spread among each partition.

• KEY Partition
  Similar to HASH, but determined by MySQL internal algorithms, all column types except TEXT/BLOB are supported.

?? Note: Once the partition method is specified after the table is created, it cannot be changed at will unless the table is rebuilt. So you have to plan well in the early stage of design.

Partition maintenance and precautions

Partitioning is not a one-time thing and requires regular maintenance and adjustment:

• Add a new partition : In particular, the RANGE partition must be added manually when the data is outside the current partition range.
• Merge/Split Partitions : You can merge or split partitions through ALTER TABLE ... REORGANIZE PARTITION , but pay attention to data consistency.
• Delete old partitions : For historical data, you can directly delete the corresponding partition, which is much more efficient than DELETE operations.
• Monitor partition usage : Use SHOW CREATE TABLE to view the partition structure, or view the size and number of rows of each partition through an information schema table (such as INFORMATION_SCHEMA.PARTITIONS ).

In addition, please note:

• The partition field must be part of the table's primary key (if it is the InnoDB engine)
• The query statement should be equipped with partition keys as much as possible, otherwise the advantage of partitioning cannot be taken advantage of (called "partition cropping")

Let's summarize

Table partitioning is an important tool for optimizing large data scenarios, but the premise is that you must be clear about your query and write mode. Only by choosing the right partition key, reasonably designing the partition structure, and regularly maintaining it can it truly play its role. Don't underestimate this step. Sometimes the performance gap can be several orders of magnitude.

Basically that's it.

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