How MySQL create index for a partition table, Example if I create 5 hash by ID partitions:
Create 1 global index for all data and 5 partitions will use this index
Create 5 partitioned index with subdata in 5 partitioned tables
Create 5 index with all data in 5 partitioned tables
Thanks
There is no "global" index for a partitioned table in MySQL.
The only indexes you can put on a partitioned table ends up being separate indexes on each partition. Each partition is effectively an independent table.
HASH partitioning is virtually useless; do you have a particular use for which you think it might be beneficial?
Addenda...
The size of the index is similar to that of a table.
Since there are no "global" indexes, you cannot have a UNIQUE key unless it includes the column(s) of the "partition key". Nor can you use FOREIGN KEYs.
There is no type of index that spans more than one table.
Partitioned table in Mysql has only local indexes support.
What does that mean? Every partition of the table stores its own B-Tree for the indexes. This can slow down the process of search if you don't have partition key as part of the index. Also for unique key constraint, you need to add partition key as part of the unique key.
Compared to Mysql, Oracle has concept of Global indexes as well. Global Indexes are very hard to manage.
I am not too sure How helpful Mysql partitions would be if it has ignored Global indexes.
Related
I have a database which use sequence number as its primary key. Other than there is a column called "date_time" which can be duplicated.
Now I need to make partitions by using date_time as follows.
ALTER TABLE data
PARTITION BY RANGE (TO_DAYS('date_time')) (
PARTITION p20220103 VALUES LESS THAN (TO_DAYS('2022-01-04 00:00:00')),
PARTITION p20220104 VALUES LESS THAN (TO_DAYS('2022-01-05 00:00:00')),
PARTITION p20220105 VALUES LESS THAN MAXVALUE
);
Since the date_time is not a primary key in data table, I couldn't create partitions.
ERROR 1503 (HY000): A PRIMARY KEY must include all columns in the table's partitioning function (prefixed columns are not considered).
How should I create partitions without adding date_time as a primary key?
You cannot. The rule is simple, stated in https://dev.mysql.com/doc/refman/8.0/en/partitioning-limitations-partitioning-keys-unique-keys.html:
Every unique key on the table must use every column in the table's partitioning expression.
If the table has a primary key or unique key but that key does not include the column(s) in the partitioning expression, then it cannot enforce uniqueness when you insert a new row without checking every partition for duplicates.
The only way around this, to allow a column like your date_time to be the partitioning expression, is to define the table with no primary or unique key.
This has its own hazards. You may need a unique key so you can address rows individually to update or delete them. Also row-based replication becomes very inefficient if your table has no primary key.
This usually means you cannot partition the table by date_time, or even that you cannot partition the table at all. But this isn't always a bad thing. Partitioning doesn't necessarily give a great benefit. Partitioning can even cause more complexity, because you may have queries that would be bound to search every partition anyway.
Partitioning is not a cure-all, and frequently is a liability.
Table and Index Partitioning
I am planning to use table partitioning for one of my existing databases. All the tables in the database have a clustered index and a non-unique non-clustered index. The non-unique non-clustered index is built on the column which I would like to use as the partition column. The partition column is not part of the Primary Key or clustered index. I am using SQL Server 2016 SP1.
I came across these points while reading, "Partitioned Table and Index Strategies Using SQL Server 2008"
Are these points still applicable to SQL Server 2016 SP1?
Because, when I used the Create Partition wizard, it did not convert the primary key into a non-clustered index and add a clustered index for the partition column.
In a partitioned table, the partition column must be a part of:
The clustered index key.
The primary key.
Unique index and uniqueness constraint keys.
There are also some important requirements for indexes during a SWITCH operation:
All indexes must be aligned.
No foreign keys can reference the partitioned table.
All the tabled I want to partition have foreign keys as well. I have to perform SWITCH operation. Are there any workarounds to perform SWITCH while keeping the foreign keys?
Filtered Index I have to purge the database based on one column (partitioning column) and another column (UserId) to filter data. For example: get 7 days worth of data for UserId 1. The database can have data for up to 100 users. There is already non-clustered index created on UserId but the query performance is poor. Please suggest whether creating a secondary non-clustered filtered index on the UserId column would improve query performance.
I want to create an Index on Id of my table. It's a bigint.
I would like to know what is the most good to have this index so that I can retrieve the data as fast as possible.
For example :
CREATE INDEX id_index ON lookup (id) USING BTREE;
Wit respect, you're overthinking this. It happens that InnoDB and MyISAM tables only support BTREE indexes. If you have MEMORY table you could create the index USING HASH but this is probably an ordinary table.
CREATE INDEX id_index ON lookup (id);
gets you what you want.
Aside from the convenient auto-increment and UNIQUE features, does the PK actually speed up the index?
Will the speed be the same whether it's a non-PKed indexed INT or PKed (same column, two different tests)? If I had the same column on the same table on the same system, will it be faster if a UNIQUE INT column with an index also has PK enabled? Does PK make the index it coexists with faster?
Please, actual results only with system stats if you could be so kind.
The primary key for a table represents the column or set of columns that you use in your most vital queries. It has an associated index, for fast query performance. Query performance benefits from the NOT NULL optimization, because it cannot include any NULL values. With the InnoDB storage engine, the table data is physically organized to do ultra-fast lookups and sorts based on the primary key column or columns.
If your table is big and important, but does not have an obvious column or set of columns to use as a primary key, you might create a separate column with auto-increment values to use as the primary key. These unique IDs can serve as pointers to corresponding rows in other tables when you join tables using foreign keys.
Also refer the following locations : http://www.dbasquare.com/2012/04/04/how-important-a-primary-key-can-be-for-mysql-performance/ and http://www.w3schools.com/sql/sql_primarykey.asp
Rows in a base table are uniquely identified by the value of the primary key defined for the table. The primary key for a table is composed of the values of one or more columns.
Primary keys are automatically indexed to facilitate effective information retrieval.
The primary key index is the most effective access path for the table.
Other columns or combinations of columns may be defined as a secondary index to improve performance in data retrieval. Secondary indexes are defined on a table after it has been created (using the CREATE INDEX statement).
An example of when a secondary index may be useful is when a search is regularly performed on a non-keyed column in a table with many rows, defining an index on the column may speed up the search. The search result is not affected by the index but the speed of the search is optimized.
It should be noted, however, that indexes create an overhead for update, delete and insert operations because the index must also be updated.
Indexes are internal structures which cannot be explicitly accessed by the user once created. An index will be used if the internal query optimization process determines it will improve the efficiency of a search.
SQL queries are automatically optimized when they are internally prepared for execution. The optimization process determines the most effective way to execute each query, which may or may not involve using an applicable index.
I am creating an Innodb table with four columns.
Table
column_a (tiny_int)
column_b (medium_int)
column_c (timestamp)
column_d (medium_int)
Primary Key -> column_a, column_b, column_c
From a logical standpoint, columns A, B, C must be made into a PK together.However, to increase performance and be able to read directly from the index (using index) I am considering a PK that comprises of all 4 columns (A, B, C, D).
QUESTION
What would the performance be of appending an additional column to the Primary Key on an Innodb table?
CONSIDERATIONS
Surrogate primary keys are absolutely out of the question
No other indexes will exist on this table
Table is read/write intensive (both about equal)
Thank you!
In InnoDB, the PRIMARY KEY index structure includes all non-key fields and will automatically use them for covering index queries and row elimination. There is no separate "data" structure other than the PRIMARY KEY index structure. It is not necessary to add additional fields to the PRIMARY KEY definition itself. Note that it won't show Using index when it's using the PRIMARY KEY on an InnoDB table, because it's a different code path which doesn't trigger the addition of that message.
A few things to consider:
Unless the query in question uses all of the columns in the index, the index will not be used.
As jeremycole notes: in the Innodb structure all row data is stored in the B-tree leaf nodes of the clustered index (PRIMARY INDEX)
This concept is covered:
http://www.innodb.com/wp/wp-content/uploads/2009/05/innodb-file-formats-and-source-code-structure.pdf
http://blog.johnjosephbachir.org/2006/10/22/everything-you-need-to-know-about-designing-mysql-innodb-primary-keys/
... and in jeremy's blog post here:
http://blog.jcole.us/2013/01/07/the-physical-structure-of-innodb-index-pages/
As such, a query on A, B, C will be sufficient for efficiently obtaining all values on this Innodb table.