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So, at the point in time when this message appeared, processing was suspended in the database while DBWn hurriedly finished its checkpoint Oracle gave all the processing power it could to DBWn at that point in the hope it would finish faster This is a message you never want to see in a nicely tuned database instance If you do see it, you know for a fact that you have introduced artificial, unnecessary waits for your end users This can always be avoided The goal (and this is for the DBA, not the developer necessarily) is to have enough online redo log files allocated so that you never attempt to reuse a log file before the checkpoint initiated by it completes.



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Now for the interesting bit: We added two files to the root of the PetClinic web application index.html and local.js which contain the application-specific functions to complement the DWR-provided ones. In the <head> section of the HTML file, we add references to all of the script libraries required, as shown in Listing B-4. Listing B-4. Script Library References <head> ... <script <script <script <script </head>

While not as common as one-to-many, many-to-many relationships occur quite frequently in enterprise applications. In this type of relationship, both sides might have multiple references to related entities. In our ActionBazaar example, the relationship between Category and Item is many-to-many, as shown in figure 7.7.





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If you see this message frequently, it means a DBA has not allocated sufficient online redo logs for the application, or that DBWn needs to be tuned to work more efficiently Different applications will generate different amounts of redo log A Decision Support System (DSS, query only) or DW system will naturally generate significantly less online redo log than an OLTP (transaction processing) system would, day to day A system that does a lot of image manipulation in Binary Large Objects (BLOBs) in the database may generate radically more redo than a simple order-entry system An order-entry system with 100 users will probably generate a tenth the amount of redo 1,000 users would generate There is no right size for your redo logs, although you do want to ensure they are large enough for your unique workload.

Figure 7.7 The relationship between Category and Item is many-to-many because every category may have one or more items, whereas each item may belong to more than one category.

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You must take many things into consideration when setting both the size of and the number of online redo logs Many of them are beyond the scope of this particular book, but I ll list some of them to give you an idea: Peak workloads: You would like your system to not have to wait for checkpoint notcomplete messages, to not get bottlenecked during your peak processing You will be sizing your redo logs not for average hourly throughput, but rather for your peak processing If you generate 24GB of log per day, but 10GB of that log is generated between 9:00 am and 11:00 am, you ll want to size your redo logs large enough to carry you through that two-hour peak Sizing them for an average of 1GB per hour would probably not be sufficient.

That is, a category can contain multiple items and an item can belong to multiple categories. For example, a category named Sixties Fashion could contain items like Bellbottom Pants and Platform Shoes. Bellbottom Pants and Platform Shoes could also be listed under Uncomfortable and Outdated Clothing. Although many-to-many relationships can be unidirectional, they are often bidirectional because of their crossconnecting, mutually independent nature. Not too surprisingly, a bidirectional many-to-many relationship is often represented by @ManyToMany annotations on opposite sides of the relationship. As with the one-toone and one-many relationships, you can identify the owning side of the relationship by specifying mappedBy on the subordinate entity; you may have to use the targetEntity attribute if you re not using Java generics. The definition for @ManyToMany is identical to OneToMany and holds no special intricacies beyond those already discussed:

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Lots of users modifying the same blocks: Here you might want large redo log files Since everyone is modifying the same blocks, you would like to update them as many times as possible before writing them out to disk Each log switch will fire a checkpoint, so you would like to switch logs infrequently This may, however, affect your recovery time Mean time to recover: If you must ensure that a recovery takes as little time as possible, you may be swayed toward smaller redo log files, even if the previous point is true It will take less time to process one or two small redo log files than a gargantuan one upon recovery The overall system will run slower than it absolutely could day to day perhaps (due to excessive checkpointing), but the amount of time spent in recovery will be shorter.

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