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== Unofficial Benchmarks == | == Unofficial Benchmarks == | ||
For getting a rough idea about CPU speed, I have a physical table about German ZIP codes, | For getting a rough idea about CPU speed, I have a physical table about German ZIP codes, including long distance telephone prefixes, filled with nearly 20,000 records in six fields, summing up to 2.25 MiB of data. From the original source in the internet, there were a lot of duplicate records. Birgitta Hauser came up with a quick and dirty idea how to eliminate these dupes.<ref>She admitted, ''it might be a bit slow''.</ref> | ||
Since the SQL proved to be running really slow, I came up to use it as a benchmark. Of course, it's not 100  fair, because of different OS releases and accompanying improvements in SQL handling. But it gives a rough idea. | Since the SQL proved to be running really slow, I came up to use it as a benchmark. Of course, it's not 100  fair, because of different OS releases and accompanying improvements in SQL handling. But it gives a rough idea. | ||
| Line 18: | Line 18: | ||
|2270 | |2270 | ||
|V4R5 | |V4R5 | ||
| | |About 118 hrs. | ||
| | | | ||
|- | |- | ||
|9406-S20 | |9406-S20 | ||
|2161 | |2161 | ||
|V4R4 | |V4R4 | ||
|About 13.5 hrs | |About 13.5 hrs. | ||
| | | | ||
|- | |- | ||
| Line 30: | Line 30: | ||
|7408 | |7408 | ||
|V5R2 | |V5R2 | ||
|About 2 hrs | |About 2 hrs. | ||
|  | |  | ||
|- | |- | ||
| Line 39: | Line 39: | ||
|LPAR with two CPU cores assigned. | |LPAR with two CPU cores assigned. | ||
|} | |} | ||
=== Used files === | |||
* DDS for the database as follows: | |||
A UNIQUE | |||
A R PLZTBL | |||
A ORT 32A | |||
A LAND 17A | |||
A VORWAHL 6A ALWNULL | |||
A PLZ 5A | |||
A ID 5S 0 | |||
A ZUSATZ 30A ALWNULL | |||
A K ID | |||
* SQL for ''RUNSQLSTM'' as follows: | |||
DELETE FROM PLZPF A | |||
WHERE A.ID = ( | |||
SELECT MAX(ID) FROM PLZPF | |||
GROUP BY ORT, LAND, VORWAHL, PLZ, ZUSATZ | |||
HAVING COUNT(*) > 1 AND MAX(ID) = A.ID) | |||
* Submit Command for ''RUNSQLSTM'' as follows: | |||
SBMJOB JOB(DLTPLZDUPS) CMD(RUNSQLSTM SRCFILE(PLZ/SOURCES) SRCMBR(DLTDUPS) COMMIT(*NONE) NAMING(*SQL) DFTRDBCOL(PLZ)) | |||
I can provide a save file of the whole library on request. | |||
== Footnotes == | == Footnotes == | ||
<references /> | <references /> | ||
Revision as of 11:45, 2 August 2020
I am the principal maintainer of this Wiki.
Unofficial Benchmarks
For getting a rough idea about CPU speed, I have a physical table about German ZIP codes, including long distance telephone prefixes, filled with nearly 20,000 records in six fields, summing up to 2.25 MiB of data. From the original source in the internet, there were a lot of duplicate records. Birgitta Hauser came up with a quick and dirty idea how to eliminate these dupes.[1]
Since the SQL proved to be running really slow, I came up to use it as a benchmark. Of course, it's not 100 fair, because of different OS releases and accompanying improvements in SQL handling. But it gives a rough idea.
The SQL was run from a source PF member as standard batch job (default parameters) on idling machines (no additional work).
| Machine | Proc. Feat. | OS | Runtime (ca.) | Comments |
|---|---|---|---|---|
| 9401-150 | 2270 | V4R5 | About 118 hrs. | |
| 9406-S20 | 2161 | V4R4 | About 13.5 hrs. | |
| 9406-800 | 7408 | V5R2 | About 2 hrs. | |
| 8203-E4A | 5587 | V7R2 | 1-2 Minutes | LPAR with two CPU cores assigned. |
Used files
- DDS for the database as follows:
A UNIQUE A R PLZTBL A ORT 32A A LAND 17A A VORWAHL 6A ALWNULL A PLZ 5A A ID 5S 0 A ZUSATZ 30A ALWNULL A K ID
- SQL for RUNSQLSTM as follows:
DELETE FROM PLZPF A WHERE A.ID = ( SELECT MAX(ID) FROM PLZPF GROUP BY ORT, LAND, VORWAHL, PLZ, ZUSATZ HAVING COUNT(*) > 1 AND MAX(ID) = A.ID)
- Submit Command for RUNSQLSTM as follows:
SBMJOB JOB(DLTPLZDUPS) CMD(RUNSQLSTM SRCFILE(PLZ/SOURCES) SRCMBR(DLTDUPS) COMMIT(*NONE) NAMING(*SQL) DFTRDBCOL(PLZ))
I can provide a save file of the whole library on request.
Footnotes
- ↑ She admitted, it might be a bit slow.