3.8.1 Table Space and Index Space Names

The names for DB2 table spaces and index spaces have the following structure:

Table 3. Table Space and Index Space Names

hlq.DSNDBx.dbname.spname.ynnnn.Ammm

The elements of this name are:

hlq VSAM catalog high level qualifier

DSNDB Standard part of the name

xIdentifies a VSAM cluster or data component

CCluster

DData

dbname Database name

spname Space name. Either a table space name or an index name. Because index names can be more than 8 characters long, DB2 sometimes needs to generate an 8 character name. To avoid randomly generated names, and to be able to correlate the index name to the index space, it is recommended to limit index names to 8 characters. This is also true for table names for implicitly defined table spaces (that is, the creation of the table is done without having created the table space), since DB2 will assign a unique table space name.

yData set type:

IStandard data set

S Shadow data set

T Temporary data set

nnnnnumber = 0001

AStandard character, A

mmmUsed for table spaces or index spaces with multiple data sets; mmm is either 001, the data set number, or the partition number.

3.8.2BSDS Names

The default names for BSDSs have the following structure:

Table 4. BSDS Names

hlq.BSDS0n

hlq

VSAM catalog high level qualifier

BSDS0 Standard part of the name

nBSDS copy, 1 or 2

3.8.3Active Log Names

The default names for active log data sets have the following structure:

Table 5. Active Log Data Set Names

hlq.LOGCOPYn.DSmm

hlq

VSAM catalog high level qualifier

DB2 Storage Objects 23

Page 45
Image 45
IBM 5695-DF1, 5655-DB2 manual Table Space and Index Space Names, Bsds Names, Active Log Names

5695-DF1, 5655-DB2 specifications

IBM 5655-DB2 and 5695-DF1 are significant components within the IBM software ecosystem, predominantly focusing on data management and integration solutions. These offerings cater primarily to enterprise environments that require robust database management systems and associated frameworks to maintain and manipulate data efficiently.

IBM 5655-DB2 is a well-known relational database management system (RDBMS) that excels in managing large volumes of structured data. Its architecture is designed to support high availability, scalability, and performance, crucial for businesses operating in today’s data-driven world. Some of its main features include advanced indexing capabilities, support for complex queries, and dynamic workload management. Additionally, it provides strong concurrency controls, which enable multiple users to access and manipulate data simultaneously without compromising data integrity.

One of the key characteristics of DB2 is its support for various data types, including JSON and XML, making it versatile for modern applications that generate data in diverse formats. It also features robust security mechanisms to protect sensitive data, aligning with compliance standards across industries. Integration with analytics tools further allows businesses to derive insights from their data, enhancing decision-making processes.

On the other hand, IBM 5695-DF1, also known as the InfoSphere DataStage, is a powerful data integration tool that facilitates the extraction, transformation, and loading (ETL) of data from various sources to target systems. It empowers organizations to streamline their data flows, ensuring that clean, consistent information is available for analysis and operational use. Key features of 5695-DF1 include a user-friendly graphical interface that enhances developer productivity and a rich set of connectors for numerous data sources, enabling seamless data integration.

DataStage also supports real-time data integration, allowing businesses to keep their data synchronized across multiple platforms. Its parallel processing capabilities dedicatedly optimize performance, enabling organizations to handle vast datasets efficiently. It incorporates data quality tools that help in validating and cleansing data before it is used for decision-making processes.

Both IBM 5655-DB2 and 5695-DF1 are part of a broader strategy to accommodate the evolving landscape of data management. Businesses leverage these technologies to enhance their data architectures, fostering agility and competitive advantage in their respective markets. Their integration capabilities, along with a focus on security and scalability, position them as vital assets in modern enterprise environments. Whether managing critical data within a database or ensuring seamless data flow across systems, these IBM offerings provide a comprehensive approach to handling complex data challenges.