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IntroductionDisk storage systems can often be the most expensive components of a database solution. DB2 examines entire rows for repeating entries or patterns, and not just particular fields or parts of rows. In this example, not only the repeating values (of "500") in the Dept column are compressed, but the repeating pattern (of "Plano, TX, 24355") that spans the City, State, and ZipCode columns is also compressed as a single value.
Data row compression in DB2 can be turned on when tables are created using the COMPRESS YES option. The compression takes effect only once the table dictionary is built, which is usually during the table REORG phase. Or,REORG TABLE SalesWhen compressing a large table, it may be useful to populate the table with a small set of "representative" or sample data first. DB2 provides the INSPECT tool in order to help you determine the compression ratio estimate for a particular table or data set. The output of the INSPECT tool needs to be formatted using a DB2 utility to see the results. Furthermore, DB2 keeps the data compressed on both disk and memory (DB2 buffer pools), thereby reducing the amount of memory consumed, and freeing it up for other database or system operations.
The amount of space savings using the data row compression feature in DB2 can vary depending on the data.
Besides data row compression introduced as part of "Venom" technology, DB2 provides additional mechanisms for reducing storage requirements even further. Available in DB2 for Linux, UNIX, and Windows since Version 8, with this type of compression no-disk storage is consumed for NULL values, zero length data in variable length columns and system default values. Available since Fixpak 4 of DB2 for Linux, UNIX, and Windows V8, this compression feature results in smaller backup images that not only reduce backup storage requirements, but also make it easier to move backups between systems. The verbose nature of XML implies that XML fragments and documents typically consume a lot of disk space.
A form of index compression has been available in DB2 for Linux, UNIX, and Windows since V8.1.
Data-row compression in DB2 9 is a remarkable new feature that can result in substantial disk space and storage cost savings.


Learn about DB2 Express-C, the no-charge version of DB2 Express Edition for the community.
The article IBM DB2 "Viper" revs XML engineInfoWorld, May 2006, describes many of the new features of DB2 9. DB2 for Linux, UNIX, and Windows resource page to read articles and tutorials, and link to documentation, support, learning resources, and more. The first time you sign in to developerWorks, a profile is created for you, so you need to choose a display name. Keep up with the best and latest technical info to help you tackle your development challenges. The introduction of the microprocessor, a single chip with all the circuitry that formerly occupied large cabinets, led to the proliferation of personal computers after 1975. This article takes a look at how it works, explains the benefits, and shows sample results of space savings. He has been working with DB2 for Linux, UNIX, and Windows since version 1 and has held various roles in DB2 development, technical support, marketing, and product strategy.
For large warehouses or databases with huge volumes of data, the cost of the storage subsystem can easily exceed the combined cost of the hardware server and the data server software. That is, DB2 9 can compress rows in database tables by scanning tables for repetitive, duplicate data and building dictionaries that assign short, numeric keys to those repetitive entries. Even for extremely large tables, the compression dictionary is typically in the order of 100 KB. DB2 has intelligent algorithms to determine such scenarios and does not perform compression when it does not yield any disk-space-saving benefits.
By building a compression dictionary at the table rather than page level, patterns across the entire table are analyzed, generally resulting in improved disk savings with DB2.
The process of building the compression dictionary can be fairly quick using a small data set. This tool collects a sample of the table data, and builds a compression dictionary from it. The size of database logs can also be reduced since DB2 compresses user data within log records.


Customers using beta versions of DB2 9 have reported savings in excess of 50% and up to 80% for certain large database installations.
DB2 9 stores XML data in a parsed hierarchical format, replacing tag names (for example, employee) with integer values (such as 4).
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He works with customers and partners around the globe helping them build and benefit from DB2 and services-based solutions. Therefore, even a small reduction in the storage subsystem can result in substantial cost savings for the entire database solution. Text data tends to compress well because of recurring strings as well as data with lots of repeating characters, or leading or trailing blanks.
And if the set is a good representative sample, the compression will work well even on new data that is added to the table, without DB2 having to analyze the new data. This dictionary is then used to test compression against the records contained in the sample. If, however, the type of data stored in the table evolves over time, the dictionary can be kept up to date using REORG. Storing text -rich tags using integer values not only reduces space consumption but also assists with higher performance when querying data. He holds a Computer Engineering degree from McGill University and MBA from University of Western Ontario. Moreover, the XML tag parsing (replacing with integer values), like data row compression, is done under the covers and is completely transparent to users and applications. How did we do?"A A "What are your thoughts on these new ways of; 'All-Green', All-Sustainable', and 'All-Climate' Community Living Styles?



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