discarding "foreign overhead" from the target study. However, values related to this foreign overhead must be preserved because interactions exist on resource access inside the same computing perimeter. The first step is an overall analysis. Moreover, this first overview allows locating some missing data and finding information from other sources. In this case, some input lacking from the RMF cache analysis reports was compensated by IXFP.

An efficient approach is to build a spreadsheet, doing some consolidation between the cache subsystem activity and device activity reports. In this case study, 46 pairs of LCU level RMF reports were reviewed before selecting 9 of them as relevant. There was no foreign overhead to take into account. Figure 67 on page 148 shows the result of this preliminary step. RMFPP was not used because we just needed to capture global activities at the LCU and at Storage Group levels. The report source line is either "crr" for cache activity, "da" for device activity source, or "crr/da". The fields to review are as follows:

CUID/ADDR is the CU-ID field of the cache subsystem activity report header cross-checked with the DEV NUM of the direct access device activity report.

SSID is the SSID field of the cache subsystem activity report header.

LCU is the LCU field of the direct access device activity report.

rmf_rate is the LCU total device activity rate from the direct access device activity report.

crr_rate is the aggregate LCU I/O rate field from the cache subsystem device overview report. These values are higher than the values RMF captured because control units count at the command level (locate record command) rather than at the channel program level for RMF. Moreover, there is a missing value for the two last LCUs because of some operator interaction during the measurement interval. The fact the "crr" and the "rmf" values are close to each other shows there is no data sharing with other LPARs.

In most cases, a preknowledge of the environment shortens this pruning process.

 

 

REDUCTION

 

 

reports crr/da

crr

da

da

crr

field

CUID/ADD

SSID

LCU

rate

rate

unit

 

 

 

ssch / sI/O / sec

RVA_1

 

 

 

 

 

1st LCU

2B00

0088

0046

15.8

18.2

2nd LCU

2B40

0089

0047

8.8

10.1

3rd LCU

2B80

008A

0048

14.1

15.9

4th LCU

2BC0

008B

0049

7.9

missing

Tot

rva1

 

 

46.6

44.200

RVA_2

 

 

 

 

 

1st LCU

2C00

2007

004A

3.7

4.2

2nd LCU

2C40

2008

004B

14.4

15.9

3rd LCU

2C80

2009

004C

14.5

16.8

4th LCU

2CC0

200A

004D

11.7

missing

Tot

rva2

 

 

44.4

36.900

System

71C0

603C

0055

7.0

22.1

Figure 67. Reducing the RMF Data to Analyze

148Storage Management with DB2 for OS/390

Page 170
Image 170
IBM 5655-DB2, 5695-DF1 manual Reduction

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.