Overview

• This document contains the results of testing Check-in/Check-out and Data Import for MARC Bibliographic records on the Ramsons[NON-ECS] release environment. 

PERF-969 - Getting issue details... STATUS  

Summary

• Data Import with Check In/Check Out tests finished successfully with PTF - Create 2 and PTF - Updates Success - 2 job profiles with files 5K, 10K, 25K, 50K, 100K records.
• Instance type was updated from m6i.2xlarge to r7g.2xlarge
• Comparing with previous testing results Quesnelia and Ramsons releases
  • Check-in duration degraded by 20% and Check-out duration degraded by 40% on average without Data Import
  • Data Import Create jobs duration with CI/CO degraded by 15%-40%, depending on file size
  • Data Import Update jobs durations with CI/CO degraded by two times.
  • Check-in duration degraded by 20% and Check-out duration degraded by 40% on average for Data Import Create
  • Check-in duration degraded by 40% and Check-out duration degraded by 45% on average for Data Import Update

Test Runs 

Test Results

This table contains durations for Data Import with Check-in/Check-out. 

Check-in/Check-out without Data Import

Comparison

This table contains DI durations with CICO comparison between Quesnelia and Ramsons releases.

Test №1-2

Response times

Service CPU Utilization

Service Memory Utilization

DB CPU Utilization

DB Connections

Kafka metrics

OpenSearch Data Nodes metrics

DB load

Top SQL-queries

Top applications

insert into "marc_records_lb" ("id", "content") values (cast($1 as uuid), cast($2 as jsonb)) on conflict ("id") do update set "content" = cast($3 as jsonb)

WITH cte AS (SELECT id,
                    name,
                    name_type_id,
                    authority_id,
                    last_updated_date
             FROM fs09000000_mod_search.contributor
             WHERE last_updated_date > $1
             ORDER BY last_updated_date
             )
SELECT c.id,
       c.name,
       c.name_type_id,
       c.authority_id,
       c.last_updated_date,
       json_agg(
               CASE
                                WHEN sub.instance_count IS NULL THEN NULL
                                ELSE json_build_object(
                       'count', sub.instance_count,
                       'typeId', sub.type_ids,
                       'shared', sub.shared,
                       'tenantId', sub.tenant_id
               )
               END
       ) AS instances
FROM cte c
         LEFT JOIN
     (SELECT cte.id,
             ins.tenant_id,
             ins.shared,
             array_agg(DISTINCT ins.type_id) FILTER (WHERE ins.type_id <> '') AS type_ids,
             count(DISTINCT ins.instance_id)                                  AS instance_count
      FROM fs09000000_mod_search.instance_contributor ins
               INNER JOIN cte
                          ON ins.contributor_id = cte.id
      GROUP BY cte.id,
               ins.tenant_id,
               ins.shared) sub ON c.id = sub.id
GROUP BY c.id,
         c.name,
         c.name_type_id,
         c.authority_id,
         c.last_updated_date
      ORDER BY last_updated_date ASC

Appendix

Methodology/Approach

DI tests scenario (DI MARC Bib Create and Update) were started on Ramsons (rcp1) env with  file splitting features enabled on a NON-ECS environment.

• To run CI/CO - Ubuntu AWS instance was used as load generator
• DI tests were started from UI

Test runs:

• Test 1: Manually tested 5K, 10K, 25K, 50K, 100K consequentially records files, DI (DI MARC Bib Create ) started on Main tenant (fs09000000), and CICO with 8 users on background.
• Test 2: Manually tested 5K, 10K, 25K, 50K, 100K consequentially records files, DI (DI MARC Bib Update) started on Main tenant (fs09000000), and CICO with 8 users on background.

Test artifacts: