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First, run the R9698711 report to verify that all indexes defined to EnterpriseOne exist in the database Once all indexes have been verified, check the SQL statement to identify whether it is performing a full table scan Do you see code like SELECT * FROM PRODDTAF4211 That statement means: select all rows and all columns
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16: Optimizing EnterpriseOne for Your Business
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from a specific table If the table has 205 columns and several hundred thousand records, you can imagine how long it will take to return the results This issue is generally resolved by educating the end user to use the QBE line (this will add a WHERE statement to the SQL statement generated) or through application redesign Do you really need all of the columns and all of the rows of the table you are hitting If you need only 25 of the columns, you could substantially decrease your database activity Another potential at this juncture occurs if the statement reads SELECT SDDOCO, SDLINID, SDAN8, SDNXTR FROM PRODDTAF4211 Your DBA, EnterpriseOne developer, or CNC administrator can verify whether the PRODDTA F4211 has an index with the same columns If it doesn t, you might be able to increase your application performance by adding a new index that corresponds to the statement Second, if the SQL statement contains a WHERE clause, check the columns in the clause itself Do these columns have a corresponding index If not, you can often substantially increase the performance of this statement by adding an appropriate index to the database Danger, danger, Will Robinson; adding indexes willy-nilly like that is a two-edged blade Adding indexes increases the number of writes to a file So, if you think adding an index for every SELECT statement combination you can imagine will help, it probably will for reads, but it will kill your writes To validate the addition of a specific index, add it to the database directly before modifying the EnterpriseOne table definition If it increases your overall performance, go ahead and modify the EnterpriseOne table definition itself This will ensure that you are able to regenerate this change and migrate it to future releases of the product We often refer to this type of optimization as low-hanging fruit It is easy to identify, test, and implement
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Step 4: Apply Process Redesign
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We can best illustrate the meaning of applying process redesigns with another example Let s take the end-of-day processing requirements of the sales update UBE (R42800) The more records you have to process in this particular UBE, the slower it will go To decrease the number of records, you could sell less, but we don t think management would approve of that solution However, if you apply data selections based on the sales order type and location, you can quickly break it into multiple processes Each of them will run faster than the single UBE Even their combined time will be significantly less than that of the one UBE But wait, there s more Some reports like the R42800 have a corresponding little-known new report that does all the work for you The R42820 will break up the R42800 into smaller chunks and run multiple R42800s simultaneously So do a little investigating before you start slicing and dicing on your own someone may already have done it for you Certain batch jobs, primarily posting jobs, can t be run simultaneously However, many jobs may run concurrently; they just require you to configure the appropriate version If your batch engine server can run multiple processes simultaneously (seven, eight, or more), you can see significant time savings, and if it
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can t, you need to get another server You can also schedule these UBEs using the EnterpriseOne scheduler This will automate much of the overall process and will decrease the additional burdens associated with splitting up the process in the first place You can redesign the process to be easy to administer and time-efficient One more note: if and when you do start splitting up your reports to run concurrently, try to use a common key value to drive the splitting process This does a couple of things; it standardizes the way you run concurrent reports, and if you separate using the same column, you can index that column and possibly get another bump in performance This way, you only have to create or change one index to affect a gain on multiple reports
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