What’s In a Title? Mainframe GDGs Get the Job Accomplished

Mainframes are completely different. They’re the biggest, quickest, most succesful programs on the planet, they usually nonetheless run many, if not most, of crucial functions within the business world.

One purpose mainframes stay dominant? Their lengthy historical past of successfully coping with enterprise information.

In large-scale enterprise information processing environments, a typical requirement is the necessity to take care of many various successive units of the identical kind of knowledge. Day by day information result in weekly information, which then roll up into month-to-month and yearly information, all of which should be simply accessible both individually or as a gaggle, within the desired order.

For the reason that early days of mainframes, the Technology Information Group (GDG) has been the technique of managing these successive occurrences (or ‘generations’) of the identical information. Just by utilizing the dataset title, functions can choose a present or prior era, create new generations, or use all the assortment of datasets (a ‘GDG-all’) request.

This highly effective but easy technique of managing information is exclusive to z/OS.

Easy methods to Create a Mainframe GDG

Earlier than the person datasets that comprise a GDG could be created, a GDG ‘base’ entry is created within the catalog by IDCAMS. As soon as the GDG base is created, particular person era datasets (GDSs), that are usually bizarre sequential datasets, could be created.

A DEFINE assertion, just like the one beneath, accomplishes just a few various things:

• Creates the GDG base entry
• Units the variety of generations to maintain observe of
• Specifies what to do when the utmost variety of era datasets is reached

DEFINE GDG(NAME(MY.BUSINESS.DATA)) LIMIT(255) NOEMPTY SCRATCH

Within the instance above, every particular person era information set (GDS) is catalogued because it’s created, and a most of 255 generations (the LIMIT worth) are retained within the GDG base catalog entry.

As soon as 255 datasets have been created, the GDG base entry is ‘full’ and the oldest era should ‘roll off’ of the GDG and is deleted (SCRATCH). Optionally, if EMPTY is specified reasonably than NOEMPTY, all generations (not simply the latest) will roll off when the GDG is full.

The era datasets belonging to the GDG above have dataset names of the shape MY.BUSINESS.DATA.G0001V00, the place the final qualifier (known as the ‘goovoo’ degree) specifies the absolute era quantity – which can vary from 0001 to 9999 as generations are created, rolled off, and deleted. The model quantity (‘Vxx’) isn’t used. 

Whereas potential to consult with a specific era dataset by its absolute title and model, it’s extra widespread to make use of relative era numbers within the dataset title.

The relative era is specified by putting it in parentheses following the GDG base title.

The latest, or present era, is era zero – in our instance that is MY.BUSINESS.DATA(0).

• Older era numbers are prefixed by a minus signal – so, the era previous the present era could be BUSINESS.DATA(-1)
• New generations are created by specifying a plus signal: BUSINESS.DATA(+1) and MY.BUSINESS.DATA(+2).

When creating new generations, make certain to specify every new era quantity in ascending order because the dataset names seem within the JCL, notably in a multi-step job, in order that the generations are catalogued appropriately.

Technology datasets are generally used not just for bizarre enterprise functions, however for system information as effectively – notably SMF information. They’re particularly versatile, since any particular person era dataset inside a GDG can reside on disk or tape, could be SMS-managed or non-SMS, and might have differing block sizes or different traits.

But, GDSs are simply and robotically managed by advantage of their naming conference. Generations are:

• Saved in chronological order
• Robotically deleted as obligatory
• Referred to individually or as a gaggle

Processing All Generations

Whereas most day-to-day processing will in all probability take care of era datasets one by one, functions that course of weekly or month-to-month might wish to take care of the entire generations belonging to a GDG without delay.

That is achieved by merely specifying the GDG base title within the JCL, with none relative or absolute era quantity. For instance:

//INPUT DD DSN=MY.BUSINESS.DATA,DISP=SHR

This ‘GDG-all’ processing treats the DD assertion as if it have been a mixed enter of the entire generations belonging to the GDG.

By default, the generations are processed from the latest to the oldest (LIFO order). They’ll, nonetheless, be processed from oldest to latest by specifying FIFO both when the GDG base is outlined or on the GDGORDER parameter within the JCL.

In more moderen releases of z/OS, IBM has continued so as to add options to GDG processing, together with LIFO order and using Prolonged GDGs which might hold observe of as much as 999 generations reasonably than the earlier restrict of 255.

Further GDG-related parameters have been added to the JCL language. Defaults for GDG DEFINE can now be set within the IGGCATxx member of SYS1.PARMLIB. As well as, customers of Exactly Syncsort Allocation Management Heart (ACC) can reap the benefits of systemwide allocation requirements enforced by the ACC Coverage Guidelines Engine to set insurance policies for the creation and traits of not solely era datasets, however all varieties of different SMS or non-SMS information.

GDG: A Core Power of z/OS

GDG processing is a singular power of the z/OS system.

With little or no effort, a number of iterations of associated information could be grouped collectively, tracked, and managed utilizing bizarre batch job and catalog processing.

GDGs are easy to grasp and helpful for a variety of each enterprise and system information. They’re usually the spine of a few of the most vital functions that run on in the present day’s z/OS.

To study extra and take the subsequent step past GDGs, see how Syncsort Storage Administration helps you optimize IBM Z storage and keep away from pricey space-related failures.

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