Pre-Grant Publication Number: 20070150488
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Prior Art Detail
Summary / Description
| Summary / Description | The 2002 blog of news items released to participants of the SETI@Home project shows benchmarking activity to measure performance and a related database migration with subsequent benchmarking to check improvements of the system |
Basic Information
| Type of Prior Art | Online Publication |
| URL | http://seticlassic.ssl.berkeley... |
| Author/Creator | SETI@Home |
| Title | SETI@Home Technical news reports - 2002 |
| Publication Date | November 15, 2002 |
| Publisher | SETI University of California, Berkeley |
| Directions to Document Location | |
| Additional Information | This is a blog of all the e-mails sent out to SETI@Home participants |
Notes / To Do
| Notes | This does not show the process was also automated. Scripting these actions was state of the art but not needed for this application since it is a one of a kind database and application. |
Excerpt
Excerpt -===-
Feb 25, 2002 - We recently took the step of running our Informix online science database from the NetApp filer only. Our benchmark (insert rate) indicated that this would work and indeed it seems fine thus far. This is true even when the project has enough bandwidth to run full out.
-===-
Jun 3, 2002 - ...
The online science database has had to manage a doubling in transaction rate every year. We think this is proof of Moore's Law showing that PCs are getting faster every year. The other effect (as you have noticed!) is the need for more bandwidth.
...
We then turned off the local drives and ran from about October 2001 to March 2002 on the filer only, as a test. The reliability was excellent and the performance was good. While the Netapp box did not introduce any new data errors, it inherited those from the local drives which could not be detected by the utilities available.
So we moved towards a complete online reorganization, using techniques we learned while building the offline science database. Chief among these techniques was to establish multiple dbspaces. This allowed us to collapse our five spike tables into one and not be bothered again by the 32GB per structure limitation. It also allows informix to run queries in a more parallel fashion.
...
The migration itself was done with SQL scripts that moved each table, row by row. As we went, we hit the last remaining corrupt data pages and omitted them, leaving the new database clean. The new database was created in early April and in about three weeks all the data were copied over. We then validated the migration to ensure that the process had worked correctly and put the system on-line on April 27, 2002.
-===-
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Relevance
Claims
1
A computer-implemented method for optimizing migration of a database from a source system to a target system, comprising:
collecting source parameters related to performance characteristics for the database on the source system;
generating database configuration information on the basis of the collected source parameters and target parameters of the target system, wherein the target parameters will affect the operation of the database on the target system as compared to the operation of the database on the source system; and wherein the database configuration information is applicable to tune the database to operate on the target system; and
configuring the database to run on the target system according to the database configuration information.
Relevance
Benchmarking for performance before migrating a database is not novel. Creating a translation between schemas is not novel either. Computer implementing this process is difficult, but still a trivial step.
Benchmarking for performance before migrating a database is not novel. Creating a translation between schemas is not novel either. Computer implementing this process is difficult, but still a trivial step.
Claim Chart
All
11
A computer-readable medium having a program stored thereon which, when executed, performs operations for optimizing migration of a database from a source system to a target system, the operations comprising:
receiving source parameters related to performance characteristics for the database on the source system; and
generating database configuration information on the basis of the collected source parameters and target parameters of the target system, wherein the target parameters will affect the operation of the database on the target system as compared to the operation of the database on the source system; and wherein the database configuration information is applicable to tune the database to operate on the target system.
Relevance
Benchmarking for performance before migrating a database is not novel. Creating a translation between schemas is not novel either. Computer implementing this process is difficult, but still a trivial step.
Benchmarking for performance before migrating a database is not novel. Creating a translation between schemas is not novel either. Computer implementing this process is difficult, but still a trivial step.
Claim Chart
All
21
A data processing system, comprising:
a source system having a database;
a target system; and
a detection/restoration component for optimizing migration of the database from the source system to the target system, the detection/restoration component being configured to:
collect source parameters related to performance characteristics for the database on the source system;
generate database configuration information on the basis of the collected source parameters and target parameters of the target system, wherein the target parameters will affect the operation of the database on the target system as compared to the operation of the database on the source system; and wherein the database configuration information is applicable to tune the database to operate on the target system; and
configure the database to run on the target system according to the database configuration information.
Relevance
Benchmarking for performance before migrating a database is not novel. Creating a translation between schemas is not novel either. Getting a computer to imement this process is not easy, but still a trivial and obvious step.
Benchmarking for performance before migrating a database is not novel. Creating a translation between schemas is not novel either. Getting a computer to imement this process is not easy, but still a trivial and obvious step.
Claim Chart
All
26
A computer-implemented method for optimizing migration of a database from a source system to a target system, comprising:
collecting source parameters related to performance characteristics for the database on the source system; and
restoring the database on the target system according at least to the source parameters; wherein the restoring accounts for a difference in operating characteristics between the source system and the target system.
Relevance
Benchmarking for performance before migrating a database is not novel. Creating a translation between schemas is not novel either. Getting a computer to imement this process is not easy, but still a trivial and obvious step.
Benchmarking for performance before migrating a database is not novel. Creating a translation between schemas is not novel either. Getting a computer to imement this process is not easy, but still a trivial and obvious step.
Claim Chart
All
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