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Table of Contents
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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.

Note
titleELT Join Snap requires an account configuration

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

Prerequisites

None.

Limitations

None.

Limitation

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Known Issues

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Method-2: Dynamic Substitutions

You must enable expressions when using Pipeline parameters for dynamic substitutions. Format the SQL expression, except the Pipeline parameter's reference, as a string. 

For example, if you want to use the Pipeline parameter, name, which contains the value of a column in the ELT Join Condition field: 

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We need a query that contains a JOIN clause. This example demonstrates how we can use the ELT Join Snap to build a query with the JOIN clause.

First, we build SELECT queries to read the target tables. To do so, we can use two ELT Select Snaps, in this example: Read Part A and Read Part B. Each of these Snaps is configured to output a SELECT * query to read the target table in the database. Additionally, these Snaps are also configured to show a preview of the SELECT query's execution as shown:

Read Part A ConfigurationRead Part B Configuration

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First we use two ELT Select Snaps to retrieve data from the SF store and SF date_dim tables respectively. We configure the ELT Select Snaps as shown below; the respective output views are as shown below.

ELT Select SnapsOutput

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Then, we configure the ELT Filter Snaps with the following filter conditions.

ELT Filter SnapsOutput

Filter condition: "SR_ITEM_SK">=120000

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Filters the records by SR_ITEM_SK column whose values are greater than or equal to 120000.

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Filter condition: "D_YEAR">=2000

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Filters the records by year greater than or equal to 2000.

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Then, we configure the ELT Join Snap to perform a left outer join based on the matching values of the D_DATE_SK column in both the tables by applying a Join condition. Note that we select Only Duplicate Columns for Resultant Column Names Prefix Type to avoid collision of identical columns in the resultant output.

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