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Compression and Logging In general, SQL Server logs only uncompressed data because the log needs to be read in an uncompressed format. This means that logging changes to compressed records has a greater performance impact because each row needs to be uncompressed and decoded (from the anchor record and dictionary) prior to writing to the log. This is another reason why compression gives you more bene t on primarily read-only systems, where logging is minimal. SQL Server writes compressed data to the log in a few situations. The most common situation is when a page is split. SQL Server writes the compressed rows as it logs the data movement during the split operation. Compression and the Version Store I will be discussing the version store in 10, when I talk about Snapshot isolation, but I want to mention brie y here how the version store interacts with compression. SQL Server can write compressed rows to the version store and the version store processing can traverse older versions in their compressed form. However, the version store does not support page compression, so the rows in the version store cannot contain encodings of the anchor record pre xes and the page dictionary. So anytime any row from a compressed page needs to be versioned, the page must be uncompressed rst. The version store is used for both varieties of Snapshot isolation (full snapshot and read-committed snapshot) and is also used for storing the before-and-after images of changed data when triggers are red. (These images are visible in the logical tables inserted and deleted.) You should keep this in mind when evaluating the costs of compression. Snapshot isolation has lots of overhead already, and adding page compression into the mix affects performance even more.
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I mentioned backup compression brie y in 1, when discussing con guration options. I believe it bears repeating that the algorithm used for compressing backups is very different than the database compression algorithms discussed in this chapter. Backup compression uses an algorithm very similar to zipping, where it is just looking for patterns in the data. Even after tables and indexes have been compressed using the data compression techniques, they still can be compressed further using the backup compression algorithms. Page compression looks only for pre x patterns, and it can still leave other patterns that are not compressed, including common suf xes. Page compression eliminates redundant strings, but there still are plenty of strings in most cases that are not redundant, and string data compresses very well using zip-type algorithms. In addition, there is a fair amount of space in a database that constitutes overhead, such as unallocated slots on pages and unallocated pages in allocated extents. Depending on whether Instant File Initialization was used, and what was on the disk previously if it was, the background data can actually compress very well. So making a compressed backup of a database that has many compressed tables and indexes can provide additional space savings for the backup set.
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As we ve already seen when looking at the metadata for table and index storage, partitioning is an integral feature of SQL Server space organization. Figure 5-7 in 5 illustrated the relationship between tables and indexes (hobts), partitions, and allocation units. Tables and indexes that are built without any reference to partitions are considered to be stored on a single partition. One of the more useful metadata objects for retrieving information about data storage is the dynamic management view called sys.dm_db_partition_stats, which combines information found in sys.partitions, sys.allocation_units, and sys.indexes. A partitioned object is one that is split internally into separate physical units that can be stored in different locations. Partitioning is invisible to the users and programmers, who can use T-SQL code to select from a partitioned table exactly the same way they select from a nonpartitioned table. Creating large objects on multiple partitions improves the manageability and maintainability of your database system and can greatly enhance the performance of activities such as purging historic data and loading large amounts of data. In SQL Server 2000, partitioning was available only by manually creating a view that combines multiple tables. That functionality is referred to as partitioned views. The SQL Server 2005 and SQL Server 2008 built-in partitioning of tables and indexes has many advantages over partitioned views, including improved execution plans and fewer prerequisites for implementation. In this section, we focus primarily on physical storage of partitioned objects and the partitioning metadata. In 8, The Query Optimizer, we ll examine query plans involving partitioned tables and partitioned indexes.
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