In-Progress
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Overview
FOLIO clients often have the need to call an API to look up a record by UUID, one at a time for thousands if not hundred of thousands of records. The obvious disadvantage of retrieving one record at a time is the overhead associates with it. Currently querying for one record incurs a SELECT count_estimate() call, which equals the actual SELECT query time. Additionally, each API call to a storage module incurs a mod-authtoken call, which is needed to verify the token and permission of the caller. Therefore, this testing effort explores whether or not concatenating UUIDs in the CQL query string to retrieve records would be more efficient and if there was any downside to doing this.
This test will piggy back on PERF-98 test case, using the two currently optimized calls: GET /inventory-storage/holdings-storage and GET /inventory-storage/item-storage. It is not designed to behave in the same way as the actual data-exporting workflow, which would pause after each batch to process the retrieved records after each API call. More importantly UUIDs are concatenated in these calls, which deviates from the real use case.
Environment
- mod-inventory-storage-19.3.1
- okapi-3.1.2
- mod-authtoken-2.5.1
- mod-permissions-5.11.2
- 61 back-end modules deployed in 110 ECS services
- 3 okapi ECS services
- 8 m5.large EC2 instances
- 2 db.r5.xlarge AWS RDS instance (1 reader, 1 writer)
- INFO Okapi logging level
Summary
- Concatenating UUIDs in a batch can be done up to 50 records.
- Retrieving one record at a time at a rate of 40 requests/second uses up about 700MB of database RAM in 15 minutes. Retrieving more records at a time or having many concurrent users doing multi-records lookups concurrently will use up more DB memory and likely result the DB crashing when it runs out of memory.
- The optimal range in terms of time and resource is about 10-20 records for 1 user.
- It's up to the application developer to make a decision of concatenating UUIDs, and if so, how many UUIDs. Many applications have different needs, to look up a handful of records or hundreds of thousands of records. This report will lay out the facts for the developer to be informed about the pros and cons of concatenating UUIDs.
Test Results
The following tests were run with 8 virtual users for 15 minutes.
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With one user the request rate was able to be scaled down to a realistic 40 requests/sec (test #7). The average response time was less than 30ms for both API calls. Tests also ran for 40 and 50 UUIDs concatenation, and like the 8 users tests, request rate is cut down by half while the response time increased by half. The surprising thing was that even with 50 records the database did not crash during the test run. This may be because we took the prep step to restart the database before each test run to give it plenty of memory.
Services CPU Utilization
This graph shows the CPU utilization of the modules in the first six tests. The series that we are interested in is mod-inventory-storage which has the highest of all the spikes. With the request rate that was thrown at it and the number of records that it has to deserialize from strings, the CPU utilization is quite high. Okapi CPU utilization is constant across the tests.
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The pattern seen in 8 virtual users tests with varied numbers of UUIDs concatenated is repeated here in the 1 virtual tests. Higher CPU utilization for mod-inventory-storage as more UUIDs are being retrieved and processed, while mod-authtoken's CPU usage decreases.
Database
In the 8 virtual users tests the database CPU utilization across the tests doesn't vary much between 10 and 40 UUIDs concatenation tests. Retrieving 1 record at a time uses less CPU than when searching for many records at a time. Note the spikes and sudden in tests with 20, 30, and 40 records tests. This is due to memory issues, more below.
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Why is the database using up so much memory? There were no slow queries, as the queries used in these lookup operations utilized indexes. The only plausible is that perhaps the count_estimate() calls used up and held up memories because its logic is fairly complex and might be resource intensive: https://github.com/folio-org/raml-module-builder#estimated-totalrecords
Discussions
Concatenating UUIDs seemed like a good idea, up to a point. It certainly returns results a faster due to less trips to mod-inventory-storage, less trips to mod-authtoken, and less calls to SELECT count_estimate(). However, the storage module works much harder to deserialize all the records coming back, and the database uses up memory at a much faster rate and could result in a DB crash minutes into the test run if looking up more than 20 records at once. The amount of load also causes issues. If only one user creating loads (by concatenating UUDIs) then the database could handle it fairly easily, but if there were multiple users generating the same load then database errors would likely be generated. Likewise the more records being concatenated result in the more system resources being consumed, no matter the number of users. Therefore, it's up to the app developer to decide whether or not concatenating UUIDs in lookups make sense while taking into considerations the expected total number of records to look up (which equates to the time running these queries) and the number of concurrent users. This approach does not apply to a use case that has many concurrent users, for example, but may be applicable to background tasks.
Another factor to consider is in the near future, improvements made in caching Okapi tokens will naturally eliminate the need to go to mod-authtoken on every API call to get the same type of resource (
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Recommended Improvements
Jira Legacy server System JIRA serverId 01505d01-b853-3c2e-90f1-ee9b165564fc key RMB-724 Jira Legacy server System JIRA serverId 01505d01-b853-3c2e-90f1-ee9b165564fc key MODAT-83