How to solve the query statistics after sub-database

How to solve the query statistics after sub-database? I believe that many inexperienced people are at a loss about this, so this article summarizes the causes and solutions of the problem. Through this article, I hope you can solve this problem.

It is easy to use the aggregator to do the summary calculation in the next step, such as the grouping summary problem just mentioned, which can be written out in just a few lines:

ABC1= [connect ("orclA"), connect ("orclB")]

/ connect multiple data sources 2select sales.dept,sum (orders.amount) amount from orders,sales where orders.salesID=sales.salesID group by sales.dept/ packet summary SQL3fork A1=A3.query@x (A2) / parallel computing 4=A3.conj ()

/ merge result 5=A4.groups (DEPT;sum (AMOUNT): AMOUNT)

/ second grouping summary

The code that implements the grouping here also allows for the sub-library to execute SQL in parallel.

Using the aggregator to realize the sub-library summary contains several typical examples to illustrate the use of the sub-database summary. The operation of the cross-database data table is a more detailed explanation of the statistical query after the sub-database, as well as the key points and difficulties of the statistical query after video sub-database. The aggregator is also easily embedded in Java applications, and there are ways to use and get it how Java invokes the SPL script.

The above is to solve the sub-database after the query statistics method introduction, the detailed use of the need for you to use their own hands in order to understand. If you want to know more about it, welcome to follow the industry information channel!