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Parallel Processing of Large Volume ETL Jobs

ETL processing, generally involves copying/moving, transforming, cleaning the records/transactions from one or multiple sources. Most of the batch processing or warehousing projects involve such data processing in millions on daily/weekly basis. Typically, there is a Staging area and production area. Records are cleaned, transformed, filtered and verified from staging to production area. This demands SQL Set theory based queries, parallel processing with multiple processors/CPU. The article focuses on need of SQL Set theory approach and parallel processing while processing large volume of ETL records using programming approach.

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SQL Puzzle 7

After a gap of sixteen months, Lionel Clarke, the creator of the only 3-D maze game to be written in TSQL, returns with a new SQL puzzle. It is very simple. You have to move as much of the data as you can from the source tables to the destination tables.

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Question of the Day

Using OPENJSON

I have some data in a table that looks like this:

BeerID BeerName    brewer               beerdescription
1      Becks       Interbrew            Beck's is a German-style pilsner beer 
2      Fat Tire    New Belgium          Toasty malt, gentle sweetness, flash of fresh hop bitterness.
3      Mac n Jacks Mac & Jack's Brewery This beer erupts with a floral, hoppy taste
4      Alaskan Amber Alaskan Brewing     Alaskan Brewing Amber Ale is an "alt" style beer
8      Kirin       Kirin Brewing         Kirin Ichiban is a Lager-type beer
If I run this, what is returned?
select t1.key
    from openjson((select t.* FROM Beer AS t for json path)) t1

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