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Row compression implementation

  • Straipsnis

Applies to: SQL Server Azure SQL Database Azure SQL Managed Instance

This article summarizes how Database Engine implements row compression. This summary provides basic information to help you plan the storage space that you need for your data.

Enabling compression only changes the physical storage format of the data that is associated with a data type but not its syntax or semantics. Application changes aren't required when one or more tables are enabled for compression. The new record storage format has the following main changes:

  • It reduces the metadata overhead that is associated with the record. This metadata is information about columns, their lengths, and offsets. In some cases, the metadata overhead might be larger than the old storage format.

  • It uses variable-length storage format for numeric types (for example integer, decimal, and float) and the types that are based on numeric (for example datetime and money).

  • It stores fixed character strings by using variable-length format by not storing the blank characters.

Note

NULL and 0 values across all data types are optimized and take no bytes.

How row compression affects storage

The following table describes how row compression affects the existing types in SQL Server and Azure SQL Database. The table doesn't include the savings that can be achieved by using page compression.

Data type Is storage affected? Description
tinyint No 1 byte is the minimum storage needed.
smallint Yes If the value fits in 1 byte, only 1 byte is used.
int Yes Uses only the bytes that are needed. For example, if a value can be stored in 1 byte, storage takes only 1 byte.
bigint Yes Uses only the bytes that are needed. For example, if a value can be stored in 1 byte, storage takes only 1 byte.
decimal Yes Uses only the bytes that are needed, regardless of the precision specified. For example, if a value can be stored in 3 bytes, storage takes only 3 bytes. The storage footprint is exactly the same as the vardecimal storage format.
numeric Yes Uses only the bytes that are needed, regardless of the precision specified. For example, if a value can be stored in 3 bytes, storage takes only 3 bytes. The storage footprint is exactly the same as the vardecimal storage format.
bit Yes The metadata overhead brings this to 4 bits.
smallmoney Yes Uses the integer data representation by using a 4-byte integer. Currency value is multiplied by 10,000 and the resulting integer value is stored by removing any digits after the decimal point. This type has a storage optimization similar to that for integer types.
money Yes Uses the integer data representation by using an 8-byte integer. Currency value is multiplied by 10,000 and the resulting integer value is stored by removing any digits after the decimal point. This type has a larger range than smallmoney. This type has a storage optimization similar to that for integer types.
float Yes Least significant bytes with zeros aren't stored. float compression is applicable mostly for nonfractional values in mantissa.
real Yes Least significant bytes with zeros aren't stored. real compression is applicable mostly for nonfractional values in mantissa.
smalldatetime No Uses the integer data representation by using two 2-byte integers, and is the number of days since 1900-01-01. There's no row compression benefit to the date portion of smalldatetime.

The time is the number of minutes since midnight. Time values that are slightly past 4AM start to use the second byte.

If a smalldatetime is only used to represent a date (a common case), the time is 0.0. Compression saves 2 bytes by storing the time in most significant byte format for row compression.
datetime Yes Uses the integer data representation by using two 4-byte integers. The integer value represents the number of days with base date of 1900-01-01. The first 2 bytes can represent up to the year 2079. Compression can always save 2 bytes here until that point. Each integer value represents 3.33 milliseconds. Compression exhausts the first 2 bytes in first five minutes and needs the fourth byte after 4PM. Therefore, compression can save only 1 byte after 4PM. When datetime is compressed like any other integer, compression saves 2 bytes in the date.
date No Uses the integer data representation by using 3 bytes. This represents the date from 0001-01-01. For contemporary dates, row compression uses all 3 bytes. This achieves no savings.
time No Uses the integer data representation by using 3 - 6 bytes. There are various precisions that start with 0 to 9 that can take 3 - 6 bytes. Compressed space is used as follows:

Precision = 0. Bytes = 3. Each integer value represents a second. Compression can represent time up to 6PM by using 2 bytes, potentially saving 1 byte.

Precision = 1. Bytes = 3. Each integer value represents 1/10 seconds. Compression uses the third byte before 2AM. Results in little savings.

Precision = 2. Bytes = 3. Similar to the previous case, it's unlikely to achieve savings.

Precision = 3. Bytes = 4. Because the first 3 bytes are taken by 5AM, this option achieves little savings.

Precision = 4. Bytes = 4. The first 3 bytes are taken in the first 27 seconds. No savings are expected.

Precision = 5, Bytes = 5. The fifth byte will be used after 12-noon.

Precision = 6 and 7, Bytes = 5. Achieves no savings.

Precision = 8, Bytes = 6. The sixth byte will be used after 3AM.

There's no change in storage for row compression. Overall, not much savings can be expected from compressing the time data type.
datetime2 Yes Uses the integer data representation by using 6 - 9 bytes. The first 4 bytes represent the date. The bytes taken by the time depend on the precision of the time that is specified.

The integer value represents the number of days since 0001-01-01 with an upper bound of 12/31/9999. To represent a date in the year 2005, compression takes 3 bytes.

There are no savings on time because it allows for 2 - 4 bytes for various time precisions. Therefore, for one-second time precision, compression uses 2 bytes for time, which takes the second byte after 255 seconds.
datetimeoffset Yes Resembles datetime2, except that there are 2 bytes of time zone of the format (HH:mm).

Like datetime2, compression can save 2 bytes.

For time zone values, the mm value might be 0 for most cases. Therefore, compression can possibly save 1 byte.

There are no changes in storage for row compression.
char Yes Trailing padding characters are removed. The Database Engine inserts the same padding character regardless of the collation that is used.
varchar No No effect.
text No No effect.
nchar Yes 1 Trailing padding characters are removed. The Database Engine inserts the same padding character regardless of the collation that is used.
nvarchar No 1 No effect.
ntext No No effect.
binary Yes Trailing zeros are removed.
varbinary No No effect.
image No No effect.
cursor No No effect.
timestamp / rowversion Yes Uses the integer data representation by using 8 bytes. There's a timestamp counter that is maintained for each database, and its value starts from 0. This can be compressed like any other integer value.
sql_variant No No effect.
uniqueidentifier No No effect.
table No No effect.
xml No 2 No effect.
User-defined types No This is represented internally as varbinary.
FILESTREAM No This is represented internally as varbinary.

1 Unicode compression supports the fixed-length nchar and nvarchar data types. Data values that are stored off-row or in nvarchar(max) columns aren't compressed. Unicode compression isn't supported for nvarchar(max) data even if it's stored in-row.

2 Off-row data isn't compressed when enabling data compression. For example, an XML record that's larger than 8,060 bytes uses out-of-row pages, which aren't compressed.

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