For this, I create a small Python script to prevent myself from copy & paste trauma.
import os import sys def Generate_File(pNumber): iNumber = 0 pathname = os.path.dirname(sys.argv[0]) pathname = os.path.abspath(pathname) + "\HANA_File.txt" myfile = open(pathname, "a") while iNumber < pNumber: iNumber += 1 myfile.write("insert into HANA_File values (" + str(iNumber) + ",'Test Line');\n") myfile.close() print 'The file ' + pathname + ' was written successfully' Generate_File(1000)
When run, this small program will generate 1000 records.
And the table structure for both SAP HANA and MySQL would as simple as:
Id --> Integer
Text --> Varchar(10)
Let's start with MySQL...
MySQL doesn't give us the total amount of time spend, but we can assume about 3 minutes...
Let's move to SAP HANA...
SAP HANA gives us the total amount of time spend, which was 1:18.484 minutes
So we can deduct that SAP HANA was 60% faster than MySQL...and for sure, that's not the best way to load records on SAP HANA...but even like this, you can see how fast SAP HANA really is...
Greetings,
Blag.
4 comentarios:
Hello Blag. It would be interesting if you could add one additional step plus one additional variance to your test:
1. You need to add to load into HANA db: UPDATE «table» MERGE DELTA INDEX;
2. Have a variance where the second column has unique value in each record of the second column.
Thanks,
-Vitaliy
i think that if you retry this test using PostgreSQL you could have another surprises ;)
i think that if you retry this test using PostgreSQL you could have another surprises ;)
Vitaliy and However else wrote a comment:
I will publish tomorrow a new post with your suggestions -;)
Greetings,
Blag.
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