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Use this Snap to add a JOIN clause to join tables in separate queries coming from the upstream Snaps. This Snap also allows you to preview the result of the output query. You can validate the modified query using this preview functionality.

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Note
titleELT Join Snap requires an account configuration

Starting from 4.24 GA, ensure to configure an account for this Snap.

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Parameter NameData TypeDescriptionDefault ValueExample 
LabelString
Excerpt Include
File Writer
File Writer
nopaneltrue
ELT JoinCombined Dataset
Get preview dataCheck box
Multiexcerpt include macro
namegetpreviewdata
pageELT Intersect
Not selectedSelected
ELT Join TypeString/Drop-down list

Choose the join type to use in the SQL.

Available options are:

  • Inner
  • Left outer
  • Full outer
  • Right outer
  • Natural Full outer
  • Natural Left outer
  • Natural Right outer
  • Natural Inner
  • Cross
  • Left Anti
  • Left Semi

See Snowflake Join Types for details.

See Redshift Join Types for details.

See Azure Synapse Join Types for details. 

See Join Types for Databricks on AWS for details.

Info
titleNatural Joins for Azure Synapse and Databricks Lakehouse Platform

Natural Joins are not natively supported by Azure Synapse and Databricks Lakehouse Platform (DLP). But, this Snap uses a series of query rewrite mechanisms to support these Join Types. You can apply these Natural Joins to your data sets in Azure Synapse or Databricks Lakehouse Platform (DLP), accordingly..


InnerLeft outer
ELT Join ConditionString/Expression

Specify the condition to initiate the JOIN operation. If you do not specify any condition here, the Snap uses ON null as the default condition. You can also use Pipeline parameters in this field to bind values. However, you must be careful to avoid SQL injection. See Preventing SQL Injection for details.

You can specify any SQL expression that has a boolean output (true or false).

Note

The ELT Join Condition is ignored if the join type is:

  • Natural Inner Join
  • Natural Left Outer Join
  • Natural Right Outer Join
  • Natural Full Outer Join
  • Cross Join


N/ACUST_CODE1 = CUST_CODE
Left Table AliasString/ExpressionSpecify the alias to use for the table in the first input view.
This enables you to qualify the columns to join with an alias name and resolve any ambiguity due to identical column names.
N/ATBL1
Right Table AliasString/ExpressionSpecify the alias to use for the table in the second input view.
This enables you to qualify the columns to join with an alias name and resolve any ambiguity due to identical column names.
N/ATBL2
Resultant Column Names Prefix TypeDrop-down list

Not applicable if target database is Databricks Lakehouse Platform (DLP).

Choose an option from the list to prefix the resultant columns names with a table alias; this enables the Snap to prevent collision of identical column names in resultant table.

Available options are:

  • None: Select this option if you do not want to add a prefix to any of the column names.
  • All Columns: Select this option to prefix the alias name to all the resultant column names.
  • Only Duplicate Columns: Select this option to prefix the alias name to only identical column names.
Note
titleFor existing Pipelines

For Pipelines created prior to 4.24 GA, if you choose the All Columns or the Only Duplicate Columns option in this field, ensure that you also configure an account for the Snap.


NoneRT.D_DATE_SKGet preview dataCheck box
Multiexcerpt include macro
namegetpreviewdata
pageELT Intersect
Not selectedSelected

Preventing SQL Injection

You can pass Pipeline parameters as values in an SQL expression; however, if you do not phrase the expression properly it can lead to the parameter's name being bound as a value in the database. This potentially incorrect information being inserted into the database is known as SQL injection. It is thus necessary to take precautions when including Pipeline parameters in your SQL expression to prevent SQL injection. Based upon the intended use of the Pipeline parameter, use one or both the following methods to prevent accidental SQL injection:

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