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CREATE OR REPLACE WAREHOUSE me_wh WITH warehouse_size='X-LARGE';
CREATE OR REPLACE TABLE "TEST_DATA".NEW_DATA(VARCHAR_DATA VARCHAR(10));
CREATE OR REPLACE TABLE "TEST_DATA".DT_EXECUTE_01(VARCHAR_DATA VARCHAR(100),TIME_DATA TIME,FLOAT_DATA FLOAT,BOOLEAN_DATA BOOLEAN,NUMBER_DATA NUMBER(38,0),DATE_DATA DATE);
TRUNCATE TABLE IF EXISTS "public".simple_data_02;
INSERT OVERWRITE INTO "BIGDATAQA"."TEST_DATA"."OUT_ELT_EXECUTE_SF_003" SELECT * FROM ( SELECT * FROM "BIGDATAQA"."TEST_DATA"."DT_EXECUTE_03" )

Example 1: Updating a Target Table Based on Updates to Another Table

The following Pipeline updates a target (backup) table - OUT_ELT_EXECUTE_SF_003 periodically based on the updates to another table DT_EXECUTE_03 (source). These tables are present in a Snowflake database, and we use data views from this database to present the updates that the Pipeline does in the target table.

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Download this Pipeline.

Example 2: Using one ELT Execute Snap to Create and Fill a Table

In this example Pipeline, we create a new table in the Redshift database and fill data into this table using an ELT Execute Snap. We later read the data from this table using an ELT Select Snap.

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