The complexity of the StockCheck job means it would be a very arduous task to convert it into an ELT schema.
StockCheck作业的复杂性意味着将它转换成elt模式是件非常艰巨的作业。
The StockCheck task reports on parts for which the company's suppliers will likely have insufficient stock in the coming quarter.
StockCheck作业报告在下一季度公司的供应商很可能没有足够库存的零件。
StockCheck is a fairly typical data mart population job, using ETL logic to move and transform data from a data warehouse to smaller data marts.
StockCheck是一个相当典型的数据集市填充作业，它使用ETL逻辑将数据从一个数据仓库转移和转换到更小的一些数据集市。
However, it is a relatively simple task to convert StockCheck into a T-ETL schema by only converting a small part of the job; that is, the join between LINEITEM and STOCK.
但是，将StockCheck转换成t - ETL模式则相当简单，只需转换作业中的一小部分，即LINEITEM与STOCK之间的连接。
The output of the StockCheck job is directed to one of five different targets depending upon the region of the supplier, or a reject file if the region of the supplier is not classified.
取决于供应商所在的地区，StockCheck作业的输出被传递到5个不同的目标，或者，如果供应商所在地区不存在危险零件，则生成一个否认文件。
The original StockCheck WebSphere DataStage job executed in 682 seconds, while the T-ETL version of the job executed in 124 seconds; an approximate elapsed time improvement of 82 percent.
原始stockcheckWebSphereDataStage作业执行时间为682秒，而t - ETL版本的作业的执行时间为124秒。消耗的时间大约缩短了82%。
The original StockCheck WebSphere DataStage job executed in 682 seconds, while the T-ETL version of the job executed in 124 seconds; an approximate elapsed time improvement of 82 percent.
原始stockcheckWebSphereDataStage作业执行时间为682秒，而t - ETL版本的作业的执行时间为124秒。消耗的时间大约缩短了82%。
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