In a SAP BW 7.4 on SAP ASE database, table partitions are used as a method of storing data, primarily for query performance but also for object (table) management.
In this post I show a simple way to identify tables with many empty partitions, so that you can more quickly drop those empty partitions.
Less empty partitions reduces the downtime of database migrations, and can also increase the performance of business-as-usual queries.
Partitioning in SAP ASE
To use SAP BW on SAP ASE, the “partitioning” license needs to be bought/included in the database license.
The license is automatically included in the runtime license for ASE for SAP Business Suite.
SAP note 2187579 “SYB: Pros and cons of physical partitioning of fact tables” list all of the benefits and the options of partitions for ASE 15.7 and ASE 16.0.
During normal business usage, the database can use less effort to obtain data from a partitioned table, when the partition key column is used as a predicate in the query.
This is because the database knows exactly where the data is held.
It’s in its own table partition and is therefore more manageable.
A good analogy is to imagine that you have two holding pens, one with all cats, and one with all dogs. The partition key is “animal type” and each holding pen is a partition.
Both holding pens together make the table.
If we wanted to get all data from the table where the occupant was a cat, we simply go to the pen with all the cats and read the data.
Now imagine that we had 3 partitions that make up our table, but one of those partitions was actually empty.
In some cases, depending on the database settings, certain types of data queries will still scan for data in that empty partition.
These additional scans do not take a huge amount of time individually, but it does cause extra effort nevertheless.
If we upscale our scenario to a large multi-terabyte SAP BW system, and to a BW FACT table with thousands of partitions.
Imagine if we had thousands of empty partitions and we were accessing all records of the table (a full table scan), this would give a reasonable delay before the query could return the results.
For this exact reason, SAP provide a BW report.
The Standard SAP BW Report
The standard ABAP report SAP_DROP_EMPTY_FPARTITIONS is specifically for the FACT tables of a BW system and it is a recommendation in the ASE Best Practices document for this report to be run before a BW system migration/copy is performed.
By reducing the empty partitions, we also reduce the system export time. Easy winner.
The problem with the SAP standard report, is that you will need to go through each individual BW info-cube and execute the report in “show” mode.
This is really, really painfully slow.
A Better Way
Instead of the standard report, I decided to go straight to the DB layer and use SQL.
The example below is for SAP ASE 16.0 (should work on 15.7 also):
convert(varchar(20),so.name) as tabname,
t_spc.numparts-1 as num_parts,
t_spn.numparts-1 as num_emptyparts
from sysobjects so,
count(sp1.partitionid) as numparts
from syspartitions sp1
where sp1.indid = 0
group by sp1.id
) as t_spc,
count(sp2.partitionid) as numparts
from syspartitions sp2,
where sp2.indid = 0
and sp2.partitionid = sts.partitionid
and sts.indid = 0
and sts.rowcnt = 0
group by sp2.id
) as t_spn
where so.name like '/BIC/F%'
and so.id = t_spc.id
and so.id = t_spn.id
and so.loginame = 'SAPSR3'
and t_spn.numparts > 1
order by t_spn.numparts asc, so.name
It’s fairly crude because it restricts the tables to those owned by SAPSR3 (change this if your schema/owner is different) and it is looking for FACT tables by their name (“/BIC/F*”) which may not be conclusive.
Below is an example output of the SQL versus the report SAP_DROP_EMPTY_FPARTITIONS in “show” mode:
You can see we are only 1 count out (I’ve corrected in the SQL now) but essentially we get a full list of the tables on which we can have the most impact!
Let’s look at a sample SELECT statement against that table:
We used the following SQL:
set statistics time on
select count(*) from [SAPSR3./BIC/FZPSC0201]
Execution time on that statement was 25.9 seconds (elapsed time of 25931 ms).
We spent 2 seconds parsing and compiling the SQL statement (lots of partitions probably doesn’t help this either).
Since the CPU time is only 7 seconds, we have to assume that I/O was the reason for the delay while ASE scanned over the partitions.
Dropping The Partitions
Let’s go ahead and actually drop those empty partitions using another standard ABAP report SAP_DROP_EMPTY_FPARTITIONS.
NOTE: See SAP note 1974523 “SYB: Adaption of SAP_DROP_EMPTY_FPARTITIONS for SAP ASE” for more details on how to use the report.
We need to run this in the background, because dropping over 1,000 partitions will take a while.
Once dropped, we can re-run our select statement:
Total elapsed time is now down to just 6 seconds.
Admittedly there could be some time saving due to the data cache and plan cache already being populated for this table, so I ran ASE stored procedure: sp_unbindcache, which seemed to have done something.
Then I re-ran the query:
Being unsure if the unbind worked or not (I could not bounce the DB to be absolutely sure), I’m going to just accept that we have improved the result by dropping those empty partitions.