![]() ![]() Redshift is the Amazon Cloud Data Warehousing server it can interact with Amazon EC2 and S3 components but is managed separately using the Redshift tab of the AWS console. I am not going to talk performance in absolute terms as your mileage is going to vary. In this blog I will look at Amazon Redshift and how it compares with a more traditional DW approach using, as my example, Oracle. Recently, my colleague, Pete Carpenter, described a proof of concept we carried out using Amazon Redshift as the data warehouse storage layer in a system capturing data from Oracle E-Business Suite (EBS) using Attunity CloudBeam in conjunction with Oracle Data Integrator (ODI) for specialised ETL processing and Oracle Business Intelligence (OBI) as the reporting tool. įor example, consider below stored procedure to verify WHILE loop:ĬREATE OR REPLACE PROCEDURE redshift_simple_while()įOR name IN expression. The expression is checked just before each entry to the loop body. With the use of Redshift WHILE statement, you can loop through a sequence of statements until the evaluation of the condition expression is true. CONTINUE label įor example, CONTINUE simple_loop_continue_test WHEN (cnt > 10) Redshift WHILE Loop Statement If you have multiple loop statements, you can jump between them using CONTINUE statement. ![]() Here is the output of above stored procedure: CALL redshift_simple_loop() CREATE OR REPLACE PROCEDURE redshift_simple_loop()ĮXIT simple_loop_exit_continue WHEN (cnt > 10) ![]() įor example, consider following stored procedure with simple loop statement with EXIT and CONTINUE labels. The optional label can be used by EXIT and CONTINUE statements within nested loops to specify which loop the EXIT and CONTINUE statements refer to. The LOOP statement defines an unconditional loop that repeats until terminated by an EXIT or a RETURN statement. Redshift supports following iterative control structures: With the help of iterative control statements, you can control the flow of execution in your plpgsql statements. Amazon Redshift NULL Handling Functions and Examples.Redshift CASE Statement, Usage and Example.You can use the CASE statement in Redshift to evaluate a list of conditions and return a result expression corresponding to the first true condition.įollowing is the basic syntax of the CASE statement in Redshift: CASEįollowing is the example of CASE statement in Amazon Redshift. The case statement is one of the conditional statements in Redshift database. This condition provides more flexibility to test multiple conditions. You can write the statements to run in the ELSE part. IF-THEN-ELSE statements has an ELSE branch to evaluate in cases when condition evaluates to false results. This conditional control works same as in other programming language. UPDATE patient_dim SET mobile= v_mobile where id = v_id ![]() If the condition is true statements between THEN and END IF are executed, otherwise statements following END IF are executed. The IF-THEN statements are simplest form of IF statements. In case there is nested IF then there should be two END IF, one for main IF and other one for nested IF. There are four forms of IF statements available in Redshift supported plpgsql:Įvery plpgsql IF statement should have the corresponding END IF statements. The IF statements can perform particular task based on the certain conditions. The Redshift conditional control flow statements are categorized into two parts: ![]()
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