‎2005 Dec 19 6:32 AM
Hi,
Could any just let me know regarding the Basic Diff. B/w
Pool & Clsuter Table.
Thanks & Regards
Irfan Hussain
‎2005 Dec 19 6:37 AM
hi,
A transparent table is a table that stores data directly. You can read these tables directly on the database from outside SAP with for instance an SQL statement.
Transparent table is a one to one relation table i.e. when you create one transparent table then exactly same table will create in data base and if is basically used to store transaction data.
A clustered and a pooled table cannot be read from outside SAP because certain data are clustered and pooled in one field.
One of the possible reasons is for instance that their content can be variable in length and build up. Database manipulations in Abap are limited as well.
But pool and cluster table is a many to one relationship table. This means many pool table store in a database table which is know as table pool.
All the pool table stored table in table pool does not need to have any foreign key relationship but in the case of cluster table it is must. And pool and cluster table is basically use to store application data.
Table pool can contain 10 to 1000 small pool table which has 10 to 100 records. But cluster table can contain very big but few (1 to 10) cluster table.
For pool and cluster table you can create secondary index and you can use select distinct, group for pool and cluster table. You can use native SQL statement for pool and cluster table.
A structure is a table without data. It is only filled by program logic at the moment it is needed starting from tables.
A view is a way of looking at the contents of tables. It only contains the combination of the tables at the basis and the way the data needs to be represented. You actually call directly upon the underlying tables.
Hope this will help.
Regards,
Amit
‎2005 Dec 19 6:38 AM
Hi,
Table Pools
The data is stored as a table pool in the database server which consists of
all the (physical) records from the tables present in that particular table pool.
Technically, The table name and the field name are the key fields in case
of pooled tables.
Table Clusters
Logical data records from different tables are stored as single PHYSICAL record
in the table clusters.
Technically. There can be n number keys (usually generated by the system ) for a
record in a cluster table and field called pageno is used to track the continuation
of the records.
BOTH TABLE POOLS AND TABLE CLUSTERS ARE NOT PHYSICALLY AVAILABLE IN THE DB SERVER
BUT THEY ARE LOGICALLY POOLED OR CLUSTERED.
Pooled tables in the dictionary has a many-to-one relation with the table in database. Table in the database has the different name as in the dictionary.
A pooled table is used to combine several logical tables in the ABAP/4 dictionary. Pooled tables are logical tables that must be assigned to a table pool when they are defined.
Cluster tables:
Cluster table are logical tables that must be assigned to a table cluster when they are defined.
Cluster table can be used to store control data they can also used to store temporary data or text such as documentation
Thanks,
If this helps u reward with points.
‎2005 Dec 19 6:45 AM
Hi Irfan,
Table pools (pools) and table clusters (clusters) are special table types in the ABAP Dictionary. The data from several different tables can be stored together in a table pool or table cluster. Tables assigned to a table pool or table cluster are referred to as pooled tables or cluster tables.
A table pool or table cluster should be used exclusively for storing internal control information (screen sequences, program parameters, temporary data, continuous texts such as documentation). Data of commercial relevance is usually stored in transparent tables.
<b>Table Pool</b>
A table in the database in which all records from the pooled tables assigned to the table pool are stored corresponds to a table pool.
The definition of a pool consists essentially of two key fields (Tabname and Varkey) and a long argument field (Vardata).
<b>Cluster table:</b>
Several logical data records from different cluster tables can be stored together in one physical record in a table cluster.
A cluster key consists of a series of freely definable key fields and a field (Pageno) for distinguishing continuation records. A cluster also contains a long field (Vardata) that contains the contents of the data fields of the cluster tables for this key. If the data does not fit into the long field, continuation records are created. Control information on the structure of the data string is still written at the beginning of the Vardata field.
Hope this helps u,
Regards,
Nagarajan.
‎2005 Dec 19 7:01 AM
Hi Irfan,
Pooled Table :-
A pooled table in R/3 has a many-to-one
relationship.
When you look at a pooled table in R/3, you see a
description of a table.
R/3 uses table pools to hold a large number (tens to
thousands) of very small tables (about 10 to 100
rows each).
Table pools reduce the amount of database resources
needed when many small tables have to be open at the
same time.
SAP uses them for system data.
You might create a table pool if you need to create
hundreds of small tables that each hold only a few
rows of data.
Pooled tables are primarily used by SAP to hold
customizing data.
Cluster Table :-
A cluster table is similar to a pooled table.
It has a many-to-one relationship with a table in
the database.
Many cluster tables are stored in a single table in
the database called a table cluster.
It holds many tables within it.
The tables it holds are all cluster tables.
Like pooled tables, cluster tables are another
proprietary SAP construct.
They are used to hold data from a few (approximately
2 to 10) very large tables.
They would be used when these tables have a part of
their primary keys in common, and if the data in
these tables are all accessed simultaneously.
Table clusters contain fewer tables than table pools
and, unlike table pools, the primary key of each
table within the table cluster begins with the same
field or fields.
A cluster is advantageous in the case where data is
accessed from multiple tables simultaneously and
those tables have at least one of their primary key
fields in common.
Cluster tables reduce the number of database reads
and thereby improve performance.
Pooled and cluster tables are usually used only by
SAP and not used by customers, probably because of
the proprietary format of these tables within the
database and because of technical restrictions
placed upon their use within ABAP/4 programs.
Cluster table can only be read and display via your
ABAP program.
For furthur details visit this link...
<a href="http://www.sap-img.com/abap/the-different-types-of-sap-tables.htm">http://www.sap-img.com/abap/the-different-types-of-sap-tables.htm</a>
Best Regards,
Maheswaran.B
‎2005 Dec 19 7:41 AM
Hi Irfan,
1. First thing to understand is this that
Either Pooled data, or cluster Data.
Both have SOME PHYSICAL table in the database.
(The table name will be different)
2. POOL TABLE
Suppose we have 15 different
tables in ABAP Dictionary
and only 1 table in physcial table.
So, the data of all these 15 tables
will be stored in the 1 physical table.
(it will be stored in a raw data format,
but it will be provided to the programs
in a structured way)
This concept is called POOL.
If all these 15 tables have 10 records each,
Then,
In the poooled table there will be
15 x 10 = 150 records.
Each record of the physical table
contains,
name of the table
Primary key value of the table
so that to identify the record.
3. CLUSTER
In a cluster table,
there is 1 physical table.
Each record contains a RAW Data.
The format of raw data is such
that it contains (NESTED DEEP STRUCTURE)
ie.
this raw data of 1 record,
contains data of many INTERNAL TABLES.
(These tables are just defined as structure
in database dictionary so that its definition
is there while saving and extracting)
Eg.
Salary of 1 employee, 1 month
will have 1 record in database table.
But this 1 record raw data will contain
information about these many internal tables.
Company data
salary figures
bank figures data
Provident fund data
etc. etc.
I hope it helps.
Regards,
Amit M.