Udf To Generate Surrogate Keys

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Example Of Surrogate Key In Database
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Goal

Fill in a data warehouse dimension table with data which comes from different source systems and assign a unique record identifier (surrogate key) to each record.

Jun 11, 2015 There's a couple of ways. Write a UDF or probably do a quick google search for one that someone has already made. Use ROWNUMBER function with an empty partitioning clause. IE, code SELECT rownumber OVER FROM table;/code 3. The SURROGATEKEY UDF generates a unique Id for every row that you insert into a table. It generates keys based on the execution environment in a distributed system, which includes a number of factors, such as internal data structures, the state of a table, and the last transaction id. Jul 06, 2006 There is typically no advantage of assigning a surrogate key to the fact rows at a logical level because we have already defined what makes a fact table row unique. And, by its nature, the surrogate key would be worthless for querying. However, there are a few circumstances when assigning a surrogate key to the rows in a fact table is beneficial.

Feb 22, 2019 In line 24 we select the fields of interest and then generate two unique hash keys one for de-duplication or the other as a surrogate key for the sessions dimension. There are two ways to set the Surrogate-Key header: by adding the header in the Fastly web interface, or by generating the keys with your own application. We describe how to use the Fastly web interface in our guide to generating Surrogate-Key headers based on URLs (we have a separate guide for Amazon S3 origins). Jun 24, 2012 A surrogate key is an auto generated value, usually integer, in the dimension table. It is made the primary key of the table and is used to join a dimension to a fact table. Among other benefits, surrogate keys allow you to maintain history in a dimension table. Despite of the their popularity, SSIS doesn't have.

Scenario overview and details

To illustrate this example, we will use two made up sources of information to provide data about customers dimension. Each extract contains customer records with a business key (natural key) assigned to it.
In order to isolate the data warehouse from source systems, we will introduce a technical surrogate key instead of re-using the source system's natural (business) key.
A unique and common surrogate key is a one-field numeric key which is shorter, easier to maintain and understand, and independent from changes in source system than using a business key. Also, if a surrogate key generation process is implemented correctly, adding a new source system to the data warehouse processing will not require major efforts.
Surrogate key generation mechanism may vary depending on the requirements, however the inputs and outputs usually fit into the design shown below:
Inputs:
- an input respresented by an extract from the source system
- datawarehouse table reference for identifying the existing records
- maximum key lookup
Outputs:
- output table or file with newly assigned surrogate keys
- new maximum key
- updated reference table with new records

Proposed solution

Assumptions:
- The surrogate key field for our made up example is WH_CUST_NO.
- To make the example clearer, we will use SCD 1 to handle changing dimensions. This means that new records overwrite the existing data.
The ETL process implementation requires several inputs and outputs.
Input data:
- customers_extract.csv - first source system extract
- customers2.txt - second source system extract
- CUST_REF - a lookup table which contains mapping between natural keys and surrogate keys
- MAX_KEY - a sequence number which represents last key assignment
Output data:
- D_CUSTOMER - table with new records and correctly associated surrogate keys
- CUST_REF - new mappings added
- MAX_KEY sequence increased
The design of an ETL process for generating surrogate keys will be as follows:

The loading process will be executed twice - once for each of the input files

Check if the lookup reference data is correct and available:
- PROD_REF table
- max_key sequence

Read the extract and first check if a record already exists. If it does, assign an existing surrogate key to it and update the desciptive data in the main dimension table.

If it is a new record, then:
- populate a new surrogate key and assign it to the record. The new key will be populated by incrementing the old maximum key by 1.
- insert a new record into the products table
- insert a new record into the mapping table (which stores business and surrogate keys mapping)
- update the new maximum key

Sample Implementations

Generation of surrogate key implementation in various ETL environments:
PDI surrogate key - surrogate key generation example implemented in Pentaho Data Integration

Comments

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Recommendations and examples for using the IDENTITY property to create surrogate keys on tables in Synapse SQL pool.

What is a surrogate key

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:

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 <your table> 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.