Jira Legacy |
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server | System JiraJIRA |
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columns | key,summary,type,created,updated,due,assignee,reporter,priority,status,resolution |
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serverId | 01505d01-b853-3c2e-90f1-ee9b165564fc |
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key | MODDATAIMP-124 |
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Testing results are better on the AWS environment because it has more computing power.
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Conclusions
Before concept of batch operations was introduced importing of 30,000 raw MARC records took about 38-40 min on the local environment. Performing steps Steps 4, 8 and 13 at the diagram above with batch save/update dramatically drastically decreased the number of http requests between the modules. Before it took more then 200 requests to process a chunk of 50 records (steps Steps 4, 8, 9 and 13 on the diagram), waiting for the responses significantly slowed down the process. With Steps 4, 8 and 13 steps as batch operations it now requires 53 http requests calls to do the same. It is fair to assume that implementing batch save to mod-inventory-storage (step Step 9 at the diagram) will improve the data-import performance a bit more
Jira Legacy |
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server | System JiraJIRA |
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columns | key,summary,type,created,updated,due,assignee,reporter,priority,status,resolution |
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serverId | 01505d01-b853-3c2e-90f1-ee9b165564fc |
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key | MODINVSTOR-291 |
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until the event driven approach is implemented. . However, main improvements in performance are expected with applying of event driven approach Jira Legacy |
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server | System JIRA |
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columns | key,summary,type,created,updated,due,assignee,reporter,priority,status,resolution |
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serverId | 01505d01-b853-3c2e-90f1-ee9b165564fc |
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key | UXPROD-1806 |
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