You always have a big data i.e. millions of rows in your tables, how would you partition it for optimum performance?
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Answers ( 9 )
It always depends on Queries that we are going to trigger on data.
For example, if we are having Song Data and we are interested in top daily charts:
SongName |Date|artistName|Album|ListenerId
We are definitely going to filter data based on date i.e. today’s date for today’s chart, Here partition will be date.
It will make less shuffle.
But with the same data, if we are interested in knowing which artist’s has been listened the most, we will definetely be filtering based on artistName, Partition will be on artistName.
Different DB engine stores a table data in file system in such a way, if you run simple filter query on a table it will scan whole file in which table data is stored.
Partitioning a table divide the data into logical chunks based on keys(columns values) and stores the chunks inside file system in such a way, if simple filter query is run on the partitioned table it will only scan the file containing chunk of data that you required.
So In a way partitioning distribute your table’s data across the file system, so when query is run on a table only a fraction of data is processed which result in better performance.
Partitioning allows you to store parts of your table in their own logical space.
With partitioning, you want to divide up your rows based on how you access them.
If you partition your rows and you are still hitting all the partitions, it does you no good.
The goal is that when you query, you will only have to look at a subset of the data to get a result,
and not the whole table.
There are various ways to partition a database like
1)Range – Rows are partitioned based on the range of the column(like Age 10-20,20-30,30-40)
2) Hash – hashes a column and depending upon the result of the hash, has a different partition.
3) LIST, Key
In SQL Server, there are two types of table partitions: Horizontal and vertical.
Vertical partitioning
This type of partition divides the table vertically, which means that the structure of the main table changes in the new ones. An ideal scenario for this type of partition is when you don’t need all the information about the customer in your query. Let’s say if you only need orders from the current year, you could split it into two databases, one would hold customer information and current purchases, and the other would hold data about purchases from previous years.
Horizontal Table Partition:
Dividing table into multiple tables is called Horizontal Table Partition. It is helpful to organize data for quick access. For SQL Server Table Partitioning example, dividing the Sales table into Monthly partition, or Quarterly partition will help the end-user to select records quickly.
MySQL partitioning is about altering – ideally, optimizing – the way the database engine physically stores data. It allows you to distribute portions of table data across the file system based on a set of user-defined rules. In this way, if the queries you perform access only a fraction of table data and the partitioning function is properly set, there will be less to scan and queries will be faster. Partitioning makes the most sense when dealing with millions of data.
Horizontal partitioning means that all rows matching the partitioning function will be assigned to different physical partitions.
Vertical partitioning allows different table columns to be split into different physical partitions.
RANGE Partitioning:
This type of partition assigns rows to partitions based on column values that fall within a stated range. The values should be contiguous, but they should not overlap each other. The VALUES LESS THAN operator will be used to define such ranges in order from lowest to highest.
LIST partitioning:
It is similar to RANGE, except that the partition is selected based on columns matching one of a set of discrete values. In this case, the VALUES IN statement will be used to define matching criteria.
HASH Partitioning:
In HASH partitioning, a partition is selected based on the value returned by a user-defined expression. This expression operates on column values in rows that will be inserted into the table. A HASH partition expression can consist of any valid MySQL expression that yields a nonnegative integer value. HASH is used mainly to evenly distribute data among the number of partitions the user has chosen.
LINEAR HASH:
Instead of using the modulo described above, when MySQL uses LINEAR HASH a powers-of-two algorithm is employed to calculate the partition where the data is to be stored. Syntactically, LINEAR HASH is exactly the same as HASH, except for the addition of the word LINEAR.
Partitioning allows you to store parts of your table in their own logical space. With partitioning, you want to divide up your rows based on how you access them. If you partition your rows and you are still hitting all the partitions, it does you no good. The goal is that when you query, you will only have to look at a subset of the data to get a result, and not the whole table.
There are various ways in MySQL to partition a database, such as:
1) RANGE
2) HASH
3) LIST, KEY
It always depends on queries we are going to ask on data
We can partition on any column from dataset which suits out query and minimizes query time
For example data is always queried on people from different countries then partitioning should be done on country column
Partitioning is the database process where very large tables are divided into multiple smaller parts. By splitting a large table into smaller, individual tables, queries that access only a fraction of the data can run faster because there is less data to scan. The main of goal of partitioning is to aid in maintenance of large tables and to reduce the overall response time to read and load data for particular SQL operations.
There are two types of partitioning – Vertical Partitioning and Horizontal Partitioning.
This link contains a good explanation for the same – https://www.sqlshack.com/database-table-partitioning-sql-server/#:~:text=Partitioning%20is%20the%20database%20process,is%20less%20data%20to%20scan.
Partitioning is a process in which a larger table is divided into small manageable parts.
Why is partitioning useful?
When the table contain millions of rows or/and columns, performing queries can be slow because a full scan of the table is done. But this full scan is not always necessary. If we are only interested in queries from the last year or the last month or last week, performing a full scan of the data would be very slow and useless. This is where partitioning comes into the scene. we can partition the data according to our query which will result in a comparatively smaller table and will be easy to maintain.
Types of partitioning-
Vertical partitioning- It is used to split tables vertically.
Horizontal partitioning- Splits horizontally. It results in fewer rows, It is possible for from date-to this date, this month to that, this year to that,etc.
https://www.c-sharpcorner.com/article/table-partitioning-in-sql-server/