Optimizing input/output operations per section of remote persistent storage
A computer-implemented method for optimizing input/output (I/O) operations per second (IOPS) of remote storage. The computer-implemented method includes receiving requests for read operations and write operations from users of an application, dynamically creating batches into which the requests can be aggregated, aggregating the requests into the batches and asynchronously passing each completed batch to the remote storage.
1. A computer-implemented method for optimizing input/output (I/O) operations per second (IOPS) of remote storage, the computer-implemented method comprising:
receiving requests for read operations and write operations from users of an application;
dynamically creating batches into which the requests can be aggregated;
aggregating the requests into the batches; and
asynchronously passing each completed batch to the remote storage,
wherein the aggregating of the requests into the batches comprises grouping requests of a same type together and finding a batch for each request,
the finding of the batch for each request comprising sequentially:
first identifying of a first match between a table name describing a type of the request and a table name of a batch list,
second identifying of a second match, in an event the first match is not identified, between the table name describing the type of the request and a table name of a foreign key batch list such that the second identifying differs from the first identifying, and
third identifying of a third match, in an event the second match is not identified, between the table name describing the type of the request and a table name of a schema batch list such that the third identifying differs from the first and second identifying.
2. The computer-implemented method according to claim 1 , further comprising asynchronously passing each completed batch and each uncompleted batch to the remote storage in an event of a restart of the application.
3. The computer-implemented method according to claim 1 , further comprising:
receiving additional requests for read/write operations from the users;
distinguishing the additional requests from the requests; and
passing the additional requests to local storage.
4. The computer-implemented method according to claim 3 , further comprising aggregating the additional requests into batches with the requests.
5. The computer-implemented method according to claim 1 , wherein:
the dynamically creating of the batches is executed in accordance with batch quantity and batch frequency determinations,
the batch quantity determinations are based on pattern identification in database traffic data, and
the batch frequency determinations are based on relative quantities of the read operations and the write operations.
6. A computer program product for optimizing input/output (I/O) operations per second (IOPS) of remote storage, the computer program product comprising one or more computer readable storage media having computer readable program code collectively stored on the one or more computer readable storage media, the computer readable program code being executed by a processor of a computer system to cause the computer system to perform a method comprising:
receiving requests for read operations and write operations from users of an application;
dynamically creating batches into which the requests can be aggregated;
aggregating the requests into the batches; and
asynchronously passing each completed batch to the remote storage,
wherein the aggregating of the requests into the batches comprises grouping requests of a same type together and finding a batch for each request,
the finding of the batch for each request comprising sequentially:
first identifying of a first match between a table name describing a type of the request and a table name of a batch list,
second identifying of a second match, in an event the first match is not identified, between the table name describing the type of the request and a table name of a foreign key batch list such that the second identifying differs from the first identifying, and
third identifying of a third match, in an event the second match is not identified, between the table name describing the type of the request and a table name of a schema batch list such the third identifying differs from the first and second identifying.
7. The computer program product according to claim 6 , further comprising asynchronously passing each completed batch and each uncompleted batch to the remote storage in an event of a restart of the application.
8. The computer program product according to claim 6 , further comprising:
receiving additional requests for read/write operations from the users;
distinguishing the additional requests from the requests; and
passing the additional requests to local storage.
9. The computer program product according to claim 8 , further comprising aggregating the additional requests into batches with the requests.
10. The computer program product according to claim 6 , wherein:
the dynamically creating of the batches is executed in accordance with batch quantity and batch frequency determinations,
the batch quantity determinations are based on pattern identification in database traffic data, and
the batch frequency determinations are based on relative quantities of the read operations and the write operations.
11. A computing system comprising:
a processor;
a memory coupled to the processor; and
one or more computer readable storage media coupled to the processor, the one or more computer readable storage media collectively containing instructions that are executed by the processor via the memory to implement a method for optimizing input/output (I/O) operations per second (IOPS) of remote storage comprising:
receiving requests for read operations and write operations from users of an application;
dynamically creating batches into which the requests can be aggregated;
aggregating the requests into the batches; and
asynchronously passing each completed batch to the remote storage,
wherein the aggregating of the requests into the batches comprises grouping requests of a same type together and finding a batch for each request,
the finding of the batch for each request comprising sequentially:
first identifying of a first match between a table name describing a type of the request and a table name of a batch list,
second identifying of a second match, in an event the first match is not identified, between the table name describing the type of the request and a table name of a foreign key batch list such that the second identifying differs from the first identifying, and
third identifying of a third match, in an event the second match is not identified, between the table name describing the type of the request and a table name of a schema batch list such that the third identifying differs from the first and second identifying.
12. The computing system according to claim 11 , further comprising asynchronously passing each completed batch and each uncompleted batch to the remote storage in an event of a restart of the application.
13. The computing system according to claim 11 , further comprising:
receiving additional requests for read/write operations from the users;
distinguishing the additional requests from the requests;
passing the additional requests to local storage.
14. The computing system according to claim 11 , wherein:
the dynamically creating of the batches is executed in accordance with batch quantity and batch frequency determinations,
the batch quantity determinations are based on pattern identification in database traffic data, and
the batch frequency determinations are based on relative quantities of the read operations and the write operations.
15. The computer-implemented method according to claim 1 , further comprising:
running an additional request on local storage and on the remote storage; and
combining results into a union of the running of the additional request on the local storage and the running of the additional request on the remote storage.
16. The computer program product according to claim 6 , wherein the method for the optimizing of the I/O IOPS of the remote storage further comprises:
running an additional request on local storage and on the remote storage; and
combining results into a union of the running of the additional request on the local storage and the running of the additional request on the remote storage.
17. The computing system according to claim 11 , wherein the method for the optimizing of the I/O IOPS of the remote storage further comprises:
running an additional request on local storage and on the remote storage; and
combining results into a union of the running of the additional request on the local storage and the running of the additional request on the remote storage.