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Session dynamicSession = session.getSession(EntityMode.MAP); Map seller = (Map) dynamicSession.load("UserEntity", user.getId() ); Map newItemMap = new HashMap(); newItemMap.put("description", "An item for auction"); newItemMap.put("initialPrice", new BigDecimal(99)); newItemMap.put("seller", seller); dynamicSession.save("ItemEntity", newItemMap); Long storedItemId = (Long) newItemMap.get("id"); Map loadedItemMap = (Map) dynamicSession.load("ItemEntity", storedItemId); List queriedItemMaps = dynamicSession .createQuery("from ItemEntity where initialPrice >= :p") .setParameter("p", new BigDecimal(100)) .list();

The temporary dynamicSession that is opened with getSession() doesn t need to be flushed or closed; it inherits the context of the original Session. You use it

The estimated query cost for the insert statement in this test was 1.58, and SQL Server touched 65,125 pages in the Test.IndexInsertTest table while performing the inserts. This is roughly both twice the cost and number of pages compared with Test #1. Following is the third test, with five non-clustered indexes defined on the table. The execution plan for this insert statement is shown in Figure 7-8.

Managing and Implementing Disaster Recovery (5.0)

As for all component mappings, you can define extra mapping attributes on the fields (or getter methods) of this class. To map the composite key of User, set the generation strategy to application assigned by omitting the @GeneratedValue annotation:

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-- 1. Drop and recreate the Test.IndexInsertTest table. -- 2. Add five non-clustered indexes. CREATE NONCLUSTERED INDEX NCIdx1 ON Test.IndexInsertTest CREATE NONCLUSTERED INDEX NCIdx2 ON Test.IndexInsertTest CREATE NONCLUSTERED INDEX NCIdx3 ON Test.IndexInsertTest CREATE NONCLUSTERED INDEX NCIdx4 ON Test.IndexInsertTest CREATE NONCLUSTERED INDEX NCIdx5 ON Test.IndexInsertTest -- 3. Execute the insert statement. INSERT Test.IndexInsertTest (Col1) SELECT PKCol FROM Test.OtherTable;

@Id @AttributeOverrides({ @AttributeOverride(name column @AttributeOverride(name column }) private UserId userId;

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B. Correct: Until this mirror is removed a new mirror cannot be created C. Correct: Doing this will restore fault tolerance by recreating the mirror set with a

(Col1); (Col1); (Col1); (Col1); (Col1);

"username", @Column(name="USERNAME") ), "departmentNr", @Column(name="DEP_NR") )

7

Just as you did with regular component mappings earlier in the book, you can override particular attribute mappings of the component class, if you like. The second composite-key mapping strategy doesn t require that you mark up the UserId primary key class. Hence, no @Embeddable and no other annotation on that class is needed. In the owning entity, you map the composite identifier property with @EmbeddedId, again, with optional overrides:

C. Incorrect: This process will not restore the fault tolerance of the original setup. D. Incorrect: This process will not restore the fault tolerance of the original setup.

@EmbeddedId @AttributeOverrides({ @AttributeOverride(name column @AttributeOverride(name column }) private UserId userId;

This time, the estimated query cost for the insert statement was 4.47, and SQL Server touched a staggering 196,853 pages in the Test.IndexInsertTest table while performing the inserts. As you can see, the cost for performing the inserts is roughly doubled with each new non-clustered index. However, in this case, each non-clustered index is roughly the same size (same width) as the table itself. For typical tables, the non-clustered indexes are narrower than the table and will not hurt performance (percentage-wise) to the same degree as in this test. Because the ratio between read and write operations varies greatly between systems, and even tables, it is a good idea to create indexes to optimize read performance and then test the effect that the created indexes has on write performance. As long as the write performance is acceptable (and you have enough disk space to manage the created indexes), you can keep the created indexes. It is also advisable to run such a test every so often to verify that the read versus write ratio for the table hasn t changed. You should also note that both update and delete statements will benefit from certain indexes to locate the rows in the table that they need to update or delete.

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