On login, generate the locking key and xor it with the stored surrogate key, which gives you the real surrogate key. The benefit of this system is that it allows for easy password changes - just use the old password to decrypt the surrogate key, then generate a new locking key from the new password. Surrogate key from all column hash. I would like to create a surrogate key for a hive table, but one that could be replicated every time the data was put in the table. Other tables would reference this table through the surrogate key, and the table could be regenerated to add more rows, and that association wouldn't be broken.
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- Password Hash Example
Recommendations and examples for using the IDENTITY property to create surrogate keys on tables in Synapse SQL pool.
What is a surrogate key
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A surrogate key on a table is a column with a unique identifier for each row. The key is not generated from the table data. Data modelers like to create surrogate keys on their tables when they design data warehouse models. You can use the IDENTITY property to achieve this goal simply and effectively without affecting load performance.
Creating a table with an IDENTITY column
The IDENTITY property is designed to scale out across all the distributions in the Synapse SQL pool without affecting load performance. Therefore, the implementation of IDENTITY is oriented toward achieving these goals.
You can define a table as having the IDENTITY property when you first create the table by using syntax that is similar to the following statement:
You can then use INSERT..SELECT to populate the table.
This remainder of this section highlights the nuances of the implementation to help you understand them more fully.
Allocation of values
The IDENTITY property doesn't guarantee the order in which the surrogate values are allocated, which reflects the behavior of SQL Server and Azure SQL Database. However, in Synapse SQL pool, the absence of a guarantee is more pronounced.
The following example is an illustration:
In the preceding example, two rows landed in distribution 1. The first row has the surrogate value of 1 in column C1, and the second row has the surrogate value of 61. Both of these values were generated by the IDENTITY property. However, the allocation of the values is not contiguous. This behavior is by design.
Skewed data
The range of values for the data type are spread evenly across the distributions. If a distributed table suffers from skewed data, then the range of values available to the datatype can be exhausted prematurely. For example, if all the data ends up in a single distribution, then effectively the table has access to only one-sixtieth of the values of the data type. For this reason, the IDENTITY property is limited to INT and BIGINT data types only.
SELECT..INTO
When an existing IDENTITY column is selected into a new table, the new column inherits the IDENTITY property, unless one of the following conditions is true:
Creating a table with an IDENTITY column
The IDENTITY property is designed to scale out across all the distributions in the Synapse SQL pool without affecting load performance. Therefore, the implementation of IDENTITY is oriented toward achieving these goals.
You can define a table as having the IDENTITY property when you first create the table by using syntax that is similar to the following statement:
You can then use INSERT..SELECT to populate the table.
This remainder of this section highlights the nuances of the implementation to help you understand them more fully.
Allocation of values
The IDENTITY property doesn't guarantee the order in which the surrogate values are allocated, which reflects the behavior of SQL Server and Azure SQL Database. However, in Synapse SQL pool, the absence of a guarantee is more pronounced.
The following example is an illustration:
In the preceding example, two rows landed in distribution 1. The first row has the surrogate value of 1 in column C1, and the second row has the surrogate value of 61. Both of these values were generated by the IDENTITY property. However, the allocation of the values is not contiguous. This behavior is by design.
Skewed data
The range of values for the data type are spread evenly across the distributions. If a distributed table suffers from skewed data, then the range of values available to the datatype can be exhausted prematurely. For example, if all the data ends up in a single distribution, then effectively the table has access to only one-sixtieth of the values of the data type. For this reason, the IDENTITY property is limited to INT and BIGINT data types only.
SELECT..INTO
When an existing IDENTITY column is selected into a new table, the new column inherits the IDENTITY property, unless one of the following conditions is true:
- The SELECT statement contains a join.
- Multiple SELECT statements are joined by using UNION.
- The IDENTITY column is listed more than one time in the SELECT list.
- The IDENTITY column is part of an expression.
If any one of these conditions is true, the column is created NOT NULL instead of inheriting the IDENTITY property.
CREATE TABLE AS SELECT
CREATE TABLE AS SELECT (CTAS) follows the same SQL Server behavior that's documented for SELECT..INTO. However, you can't specify an IDENTITY property in the column definition of the CREATE TABLE part of the statement. You also can't use the IDENTITY function in the SELECT part of the CTAS. To populate a table, you need to use CREATE TABLE to define the table followed by INSERT..SELECT to populate it.
Explicitly inserting values into an IDENTITY column
Synapse SQL pool supports SET IDENTITY_INSERT ON|OFF syntax. You can use this syntax to explicitly insert values into the IDENTITY column.
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Many data modelers like to use predefined negative values for certain rows in their dimensions. An example is the -1 or 'unknown member' row.
The next script shows how to explicitly add this row by using SET IDENTITY_INSERT:
Loading data
The presence of the IDENTITY property has some implications to yourt be used:
- When the column data type is not INT or BIGINT
- When the column is also the distribution key
- When the table is an external table
The following related functions are not supported in Synapse SQL pool:
Common tasks
This section provides some sample code you can use to perform common tasks when you work with IDENTITY columns.
Column C1 is the IDENTITY in all the following tasks.
Find the highest allocated value for a table
Use the MAX() function to determine the highest value allocated for a distributed table:
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Find the seed and increment for the IDENTITY property
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You can use the catalog views to discover the identity increment and seed configuration values for a table by using the following query:
Password Hash Example
Next steps
