User defined allocations take precedence over default Data Classes. For example, if a Data Class specifies an LRECL of 80 bytes, and the JCL allocation specifies an LRECL of 100 bytes, then 100 bytes are allocated. If the Data Class is altered by the storage administrator, attributes previously allocated by the Class remains unchanged. Alterations are only be honored for new allocations.

5.3.1.2 Planning for Implementation

To identify and reference a particular Data Class, a unique one to eight character name is used, for example, DCDBKSDS.

For each group of data sets that have similar attributes, a Data Class can exist, but is not mandatory. An example where it could be used is with DB2 tablespaces, as they have identical allocation characteristics.

Prior to the definition of Data Classes, an analysis of common data types needs to be undertaken. This should include deciding whether to use ACS routines only for their allocation, or allow users (in this case, the DBA) to assign them as well. There may be a requirement to standardize naming conventions, and agree upon default space allocations.

Attributes include many of the data set characteristics specified on JCL statements, and IDCAMS DEFINE commands. Only those applicable to a particular data set type should be coded, all others should be left blank. Table 8 on page 39 shows a list of attributes for consideration.

Table 8. Data Class Attributes

ATTRIBUTE

COMMENT

 

 

Data set

- VSAM type (KSDS, ESDS, RRDS or LINR)

Organization

- Non VSAM type (Sequential, partitioned)

 

- Record format (RECFM)

 

- Logical record length (LRECL)

 

- Key Length (VSAM)

 

 

Space requirements

- Average record length value

 

- Size of primary allocation

 

- Size of secondary allocation

 

- Number of directory blocks, if a library

 

 

VSAM, data and volume

- Size of Control Interval and Control Area

specifics

- Percentage freespace

 

- Replicate

 

- Imbed

 

- Share options—volume count

 

- Backup while open

 

- Extended addressability

 

- Reuse

 

- Space constraint relief

 

- Spanned/non spanned

 

- Initial load (speed and recovery)

 

 

5.3.2Storage Class

5.3.2.1Description

Prior to SMS, critical and important data sets that required improved performance or availability were allocated to specific volumes manually. Data sets that required low response times were placed on low activity volumes, where caching

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IBM 5695-DF1, 5655-DB2 manual Storage Class, Planning for Implementation

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.