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RDS/Auroraパフォーマンスインサイトを使ってみる
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hmatsu47
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January 28, 2021
Technology
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RDS/Auroraパフォーマンスインサイトを使ってみる
JAWS-UG 名古屋 いろんなパフォーマンスを学ぶ 2021/01/28
hmatsu47
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January 28, 2021
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Transcript
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https://qiita.com/hmatsu47 ◦ https://qiita.com/hmatsu47/items/ceb75caf46e3c761095d ◦ ◦ https://booth.pm/ja/items/2524481 2
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• ◦ https://docs.aws.amazon.com/ja_jp/AmazonRDS/latest/AuroraUserGuide/USER_ PerfInsights.Overview.html • ◦ • ◦ 4
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• ◦ https://docs.aws.amazon.com/ja_jp/AmazonRDS/latest/AuroraUserGuide /AuroraMySQL.Reference.html#AuroraMySQL.Reference.Waitevents • ◦ https://docs.aws.amazon.com/ja_jp/AmazonRDS/latest/AuroraUserGuide /AuroraPostgreSQL.Reference.html#AuroraPostgreSQL.Reference.Waite vents 9
• ◦ ▪ https://dev.mysql.com/doc/refman/5.7/en/wait-summary-tables.html ▪ https://dev.mysql.com/doc/refman/5.7/en/performance-schema-wait-tables.html ◦ ▪ https://dev.mysql.com/doc/refman/5.6/ja/wait-summary-tables.html ▪
https://dev.mysql.com/doc/refman/5.6/ja/performance-schema-wait-tables.html 10
• ◦ ▪ https://www.postgresql.jp/document/12/html/monitoring-stats.html#MONITORING-STAT S-VIEWS-TABLE ◦ ▪ https://www.postgresql.jp/document/12/html/monitoring-stats.html#WAIT-EVENT-TABLE 11
• ◦ mysqlslap --auto-generate-sql --auto-generate-sql-guid-primary --engine=innodb --number-int-cols=20 --number-char-cols=20 --concurrency=100 --auto-generate-sql-write-number=2500
--auto-generate-sql-execute-number=5000 --auto-generate-sql-load-type=【タイプ】 -u admin -h 【エンドポイント】 -p ◦ ▪ ◦ 12
• ◦ pgbench -i -s 1000 -U postgres -h 【エンドポイント】
-d pgbench ◦ pgbench -N -r -c 10 -j 10 -T 300 -U postgres -h 【エンドポイント】 pgbench ◦ 13
• ◦ ▪ • ◦ https://docs.aws.amazon.com/ja_jp/AmazonRDS/latest/AuroraUserGuide/USER_ PerfInsights.API.html 14
• [ { "Metric": "db.load.avg", "GroupBy": { "Group": "db.wait_event", "Limit":
10 } } ] • aws pi get-resource-metrics \ > --service-type RDS \ > --identifier 【DBリソースID】 \ > --start-time 2021-01-24T06:10:00Z \ > --end-time 2021-01-24T06:11:00Z \ > --period-in-seconds 60 \ > --metric-queries file://query.json 15
{ "Identifier": "db-S7UPJNXAX6J7ZJWZXFUBTODYRI", "AlignedStartTime": 1611468600.0, "MetricList": [ { "Key": {
"Metric": "db.load.avg" }, "DataPoints": [ { "Timestamp": 1611468660.0, "Value": 58.6 } ] }, 16
17 { "Key": { "Metric": "db.load.avg", "Dimensions": { "db.wait_event.type": "synch",
"db.wait_event.name": "wait/synch/sxlock/innodb/fil_space_latch" } }, "DataPoints": [ { "Timestamp": 1611468660.0, "Value": 0.03333333333333333 } ] },
18 { "Key": { "Metric": "db.load.avg", "Dimensions": { "db.wait_event.type": "synch",
"db.wait_event.name": "wait/synch/sxlock/innodb/fil_space_latch" } }, "DataPoints": [ { "Timestamp": 1611468660.0, "Value": 0.03333333333333333 } ] },
{ "Key": { "Metric": "db.load.avg", "Dimensions": { "db.wait_event.type": "synch", "db.wait_event.name":
"wait/synch/mutex/innodb/trx_mutex" } }, "DataPoints": [ { "Timestamp": 1611468660.0, "Value": 0.016666666666666666 } ] } ], 19
{ "Key": { "Metric": "db.load.avg", "Dimensions": { "db.wait_event.type": "synch", "db.wait_event.name":
"wait/synch/mutex/innodb/trx_mutex" } }, "DataPoints": [ { "Timestamp": 1611468660.0, "Value": 0.016666666666666666 } ] } ], 20
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