processing of any other failing cluster. Let us briefly review the storage server subcomponent relationships:

•Host adapters attach channel links and allow them to communicate with either cluster-processor complex. Practically, statistics at this level deal with what is called upper interface busy percentage.

•Device adapters provide storage device interfaces. Statistics captured at this level, very often indirectly measured, are called lower interface busy percentage.

•The cluster-processor complex provides the management functions for the storage facility. It consists of cluster processors, cluster memory, cache, nonvolatile storage (NVS), and related logic.

9.2.2Storage Devices

Storage devices provide the primary nonvolatile storage medium for any host data stored within the storage facility. Storage devices are grouped in arrays (or ranks) and are managed by the storage server as a common resource.

9.2.3 Logical Control Unit

Each LCU has an associated set of devices. Each device has a unique device address on the LCU. All LCUs are accessible over any installed host adapter. Host traffic and performance are controlled at the LCU level.

For OS/390 architecture, an LCU views up to 256 logical volumes (or device numbers); it is physically identified by a subsystem identifier (SSID) at installation time, but dynamically referred to by a LCU number determined at initialization time. As an example of implementation, an IBM RVA Turbo 2 storage server is viewed as four LCUs. Each LCU currently contains 64 functional volumes, to be increased to 256 when the 1024 addresses support is delivered.

9.3 Cache Management

Cache is a storage server memory resource used to buffer data for reuse and a faster access by channel. Cache masks many of the mechanical actions from the I/O access and improves the service time when the data is accessed from cache rather than from the disk. A cache hit (when the required record is found in the cache) comprises the data transfer time plus a small protocol time for both reads and writes. Read misses and write misses have the same response time characteristics as if they were uncached.

Cache performance depends on:

•Locality of reference, the likelihood of references to other records in the same track

•Frequency of reuse, the likelihood of referencing again (re-referencing) the same record or track

Locality of reference and re-referencing are results of the access pattern to the data, which in turn is related to the application. Fast I/O response times usually rely on a high cache hit rate, minimizing the number of accesses to disk.

90Storage Management with DB2 for OS/390

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IBM 5655-DB2, 5695-DF1 manual Cache Management, Storage Devices, Logical Control Unit
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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.
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