Quick IMS DB refresher you need for your project

IMSDB+MAINFRAME+JOBS
IMSDB+MAINFRAME+JOBS

I am giving here IMSDB refresher for your super success in interviews. This tutorial contains all key points in IMSDB. Many interviewers follow or touch these questions in selecting IMSDB programmers.

Few points on IMSDB:

[You can read my other article on Hierarchical database Vs RDBMS]

  • hierarchical database architecture widely used in IBM mainframes.
  • data is arranged logically in a top-down format. Data is grouped in records, which are subdivided into a series of segments.
  • the structure of the database is designed to reflect logical dependencies
  • certain data is dependent on the existence of certain other data.

IMS database organization:
The nine types of databases supported by IMS can be grouped by their IMS access method.

Hierarchic Sequential Databases: The earliest IMS database organization types were based on sequential storage and access of database segments. The root and dependent segments of a record are related by physical adjacency. Access to dependent segments is always sequential. Deleted dependent segments are not physically removed but are marked as deleted. Hierarchic sequential databases can be stored on tape or DASD.

Hierarchic sequentially accessed databases include:  HSAM – In a hierarchic sequential access method (HSAM) database, the segments in each record are stored physically adjacent. Records are loaded sequentially with root segments in ascending key sequence. Dependent segments are stored in hierarchic sequence. The record format is fixed-length and unblocked. An HSAM database is updated by rewriting the entire database. Although HSAM databases can be stored on DASD or tape, HSAM is basically a tape-based format.

IMS identifies HSAM segments by creating a two-byte prefix consisting of a segment code and a delete byte at the beginning of each segment. HSAM segments are accessed through two operating system access methods:
Basic sequential access method (BSAM): Basic sequential access method (BSAM) is an access method to read and write datasets sequentially. BSAM is—as its name says—basic, in this specific context meaning unbuffered with no deblocking of reads and no blocking of writes, although buffering is an option, but neither deblocking nor blocking.

 Queued sequential access method (QSAM): QSAM is always used as the access method when the system is processing online,
SHSAM: A Simple HSAM (SHSAM) database contains only one type of segment-a fixed-length root segment.
HISAM: Like HSAM, HISAM databases store segments within each record in physically adjacent sequential order. Unlike HSAM, each HISAM record is indexed, allowing direct access to each record. HISAM databases also provide a method for sequential access when required. HISAM databases are stored on DASD.

A HISAM database is stored in a combination of two data sets. The database index and all segments in a database record that fit into one logical record are stored in a primary data set that is a VSAM KSDS. Remaining segments are stored in the overflow data set, which is a VSAM ESDS. The index points to the CI containing the root segment, and the logical record in the KSDS points to the logical record in the ESDS, if necessary.

SHISAM – A Simple HISAM (SHISAM) database contains only a root segment, and its segment has no prefix portion. SHISAM databases can use only VSAM as their access method. The data must be stored in a KSDS.

GSAM – Generalized sequential access method (GSAM) databases are designed to be compatible with MVS data sets. They are used primarily when converting from an existing MVS-based application to IMS because they allow access to both during the conversion process. To be compatible with MVS data sets, GSAM databases have no hierarchy, database records, segments, or keys. GSAM databases can be based on the VSAM or QSAM/BSAM MVS access methods.

Hierarchic Direct Databases

HD databases share these characteristics:
• Pointers are used to relate segments.
• Deleted segments are physically removed.
• VSAM ESDS or OSAM data sets are used for storage.
• HD databases are stored on DASD.
• HD databases are of a more complex organization than sequentially organized databases.

Hierarchic direct databases include:

HDAM – HDAM databases are typically used when fast access is needed to the root segment of the database record, usually by direct access. In a hierarchic direct access method (HDAM) database, the root segments of records are randomized to a storage location by an algorithm that converts a root’s key into a storage location. No index or sequential ordering of records or segments is involved. The randomizing module reads the root’s key and, through an arithmetic technique, determines the storage address of the root segment. The storage location to which the roots are randomized are called anchor points or root anchor points (RAPs). The randomizing algorithm usually attempts to achieve a random distribution of records across the data set. Theoretically, randomizing the location of records minimizes the number of accesses required to retrieve a root segment.

The randomizing technique results in extremely fast retrieval of data, but it usually does not provide for sequential retrieval of records. This can be achieved in HDAM databases through the use of secondary indexes or by using a physical-key-sequencing randomizer module.

The advantage of HDAM is that it does not require reading an index to access the database. The randomizing module provides fast access to root segments and to the paths of dependent segments. It uses only the paths of the hierarchy needed to reach the segment being accessed, further increasing access speed. The disadvantage is that HDAM databases cannot be processed in key sequence unless the randomizing module stores root segments in physical key sequence.

HIDAM – Unlike HDAM, HIDAM databases use an index to locate root segments. HIDAM databases are typically used to access database records randomly and sequentially and also access segments randomly within a record. The index and the database are stored in separate data sets. The index is stored as a single VSAM KSDS. The database is stored as a VSAM ESDS or OSAM data set. The index stores the value of the key of each root segment, with a four-byte pointer that contains the address of the root segment.

The root segment locations in the index are stored in sequential order, allowing HIDAM databases to be processed directly or sequentially. A disadvantage of HIDAM databases is that the additional step required to scan an index makes access slower than with HDAM databases.

Mentioning PTR=TB or PTR=HB for root segments in HIDAM databases:
When accessing a record by root key, IMS searches for the key in the index and uses the pointer to go directly to the record. If the PTR =TB or PTR=HB (twin backward pointer or hierarchic backward pointer) parameter is defined for the root, the root segments are chained together in ascending order. Sequential processing is done by following this pointer chain.

In HIDAM, Raps are generated only if the PTR=T or PTR=H (twin pointer or hierarchic pointer) parameter is specified for the root. When either of these pointer parameters is defined, IMS puts one RAP at the beginning of the CI or block. Root segments within the CI or block are chained by pointers from the most recently inserted back to the first root on the RAP. The result is that the pointers from one root to the next cannot be used to process roots sequentially. Sequential processing must be performed by using key values, which requires the use of the index and increases access time. For this reason, PTR=TB or PTR=HB should be specified for root segments in HIDAM databases.

PHDAM databases:

PHDAM databases are partitioned HDAM databases. Each PHDAM database is divided into a maximum of 1001 partitions which can be treated as separate databases. A PHDAM database is also referred to as a High Availability Large Database (HALDB).

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Author: Srini

Experienced software developer. Skills in Development, Coding, Testing and Debugging. Good Data analytic skills (Data Warehousing and BI). Also skills in Mainframe.