Browsing to a list of records within the platform generally causes two initial SQL queries to be triggered against the underlying database:

  • A ‘select count(*)’ query (also known as the ‘pagination’ query) – this returns the number of records which match the users filter for display in the user interface (i.e. records 1 to [x] of [result of pagination query])
  • A ‘select sys_id’ query which returns the sys_ids of rows which should be displayed in the body of the list

When browsing lists of records in large tables the ‘pagination’ query can often take a significant amount of time to execute. This translates into:

  • A slow transaction (results cannot start to be loaded until the ‘pagination’ query completes)
  • Degraded end user experience (the platform appears to be operating slowly)

 In some cases performance of the ‘pagination’ query can be improved via use of a supporting database index however this may not be feasible due to the combinations of filters users tend to use when working with lists of records.


Steps to Reproduce

  1. Browse to a table with millions of rows and attempt to load a list of records
  2. Note that, in general, the corresponding transaction may take many seconds to minutes to complete
  3. Confirm that the majority of transaction processing time is spent executing the ‘pagination’ (select count(*)) via SQL debug or corresponding application node logs


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Related Problem: PRB1240287

Seen In

SR - Security - Integration Framework - Madrid 2019 Q2
SR - Security - Support Common - Madrid 2019 Q2
SR - Security - Support Orchestration - Madrid 2019 Q2
SR - SIR - Security Incident Response - Madrid 2019 Q2
SR - SIR - Security Incident Response PA Content - New York 2019 Q3
SR - SIR - Store SecOps Setup Assistant - Madrid 2019 Q2
SR - SIR - Store Threat Core - Madrid 2019 Q2
SR - SIR - Store Trusted Security Circles Client - New York 2019 Q3
SR - VR - Qualys - New York 2019 Q3
SR - VR - Vulnerability Response - New York 2019 Q3
SR - VR - Vulnerability Response PA Content - Madrid 2019 Q2

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Last Updated:2020-11-16 01:18:48