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roggenkemperpriscilawebdev
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feat(detectors): Update detection algorithm for MN+1 Experimental Detector (#97533)
this pr makes a few changes to the MN+1 Experimental Detector: 1) it updates the `_equivalent` method to differentiate between spans that have the "default" op , which is common in Prisma. This made some detected issues be slightly off because it was finding a "pattern" with two spans that weren't necessarily the same 2) It updates the definition of a valid pattern to exclude those that start with a serialization span. serialization spans come after a query or operation, so it doesn't make sense to start on them 3) it keeps more of the most recent spans when leaving the continuing state which should allow for more accurate pattern finding. these changes should give more accurate results and fix issues we saw where the pattern was starting/ending 1-2 spans from where we expected it.
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‎fixtures/events/performance_problems/m-n-plus-one-db/m-n-plus-one-prisma-client-different-descriptions.json

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{
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"event_id": "1997dd9e1f434f4d9ec638624dbfd8d7",
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"project": 2,
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"release": null,
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"dist": null,
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"platform": "node",
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"message": "",
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"datetime": "2025-08-08T16:00:00.582776+00:00",
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"tags": [
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["browser", "Firefox 137.0"],
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["browser.name", "Firefox"],
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["client_os", "Mac OS X 10.15"],
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["client_os.name", "Mac OS X"],
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["customerType", "small-plan"],
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["environment", "development"],
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["frontendSlowdown", "False"],
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["level", "info"],
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["os", "macOS 15.3.2"],
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["os.name", "macOS"],
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["runtime", "node v18.19.1"],
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["runtime.name", "node"],
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["user", "email:[email protected]"],
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["server_name", "MacBookPro"],
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["transaction", "GET /products"]
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],
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"culprit": "prisma:client:transaction",
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"environment": "production",
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"level": "info",
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"location": "prisma:client:transaction",
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"logger": "",
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"metadata": {
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"location": "prisma:client:transaction",
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"title": "prisma:client:transaction"
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},
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"spans": [
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{
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"timestamp": 1752683532.47828,
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"start_timestamp": 1752683532.371497,
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"op": "default",
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"span_id": "a8b7c6d5e4f39210",
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"trace_id": "a1b2c3d4e5f67890abcdef1234567890",
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"status": "ok",
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"description": "prisma:engine:query",
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"origin": "auto.db.otel.prisma",
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"data": {
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"sentry.origin": "auto.db.otel.prisma"
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},
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"hash": "4808ca9185d0c670"
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},
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{
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"timestamp": 1752683532.394234,
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"start_timestamp": 1752683532.373677,
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"op": "db",
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"span_id": "f3a2b1c0d9e87765",
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"parent_span_id": "a8b7c6d5e4f39210",
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"trace_id": "a1b2c3d4e5f67890abcdef1234567890",
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"status": "ok",
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"description": "UPDATE users SET name = $1, email = $2 WHERE id = $3",
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"origin": "auto.db.otel.prisma",
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"data": {
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"db.system": "postgresql",
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"db.query.text": "UPDATE users SET name = $1, email = $2 WHERE id = $3",
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"otel.kind": "CLIENT",
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"sentry.op": "db",
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"sentry.origin": "auto.db.otel.prisma"
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},
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"hash": "9747ee0db22ccb33"
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},
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{
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"timestamp": 1752683532.394473,
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"start_timestamp": 1752683532.394408,
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"op": "default",
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"span_id": "a4b3c2d1e0f98876",
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"parent_span_id": "a8b7c6d5e4f39210",
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"trace_id": "a1b2c3d4e5f67890abcdef1234567890",
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"status": "ok",
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"description": "prisma:engine:serialize",
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"origin": "auto.db.otel.prisma",
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"data": {
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"sentry.origin": "auto.db.otel.prisma"
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},
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"hash": "ec7cb3896f17c6fd"
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},
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{
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"timestamp": 1752683532.415304,
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"start_timestamp": 1752683532.394817,
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"op": "db",
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"span_id": "b5c4d3e2f1a09987",
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"parent_span_id": "a8b7c6d5e4f39210",
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"trace_id": "a1b2c3d4e5f67890abcdef1234567890",
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"status": "ok",
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"description": "UPDATE users SET name = $1, email = $2 WHERE id = $3",
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"origin": "auto.db.otel.prisma",
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"data": {
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"db.system": "postgresql",
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"db.query.text": "UPDATE users SET name = $1, email = $2 WHERE id = $3",
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"otel.kind": "CLIENT",
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"sentry.op": "db",
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"sentry.origin": "auto.db.otel.prisma"
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},
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"hash": "9747ee0db22ccb33"
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},
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{
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"timestamp": 1752683532.415549,
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"start_timestamp": 1752683532.415481,
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"op": "default",
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"span_id": "c6d5e4f3a2b1a098",
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"parent_span_id": "a8b7c6d5e4f39210",
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"trace_id": "a1b2c3d4e5f67890abcdef1234567890",
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"status": "ok",
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"description": "prisma:engine:serialize",
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"origin": "auto.db.otel.prisma",
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"data": {
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"sentry.origin": "auto.db.otel.prisma"
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},
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"hash": "ec7cb3896f17c6fd"
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},
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{
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"timestamp": 1752683532.436118,
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"start_timestamp": 1752683532.415906,
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"op": "db",
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"span_id": "d7e6f5a4b3c2b1a9",
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"parent_span_id": "a8b7c6d5e4f39210",
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"trace_id": "a1b2c3d4e5f67890abcdef1234567890",
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"status": "ok",
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"description": "UPDATE users SET name = $1, email = $2 WHERE id = $3",
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"origin": "auto.db.otel.prisma",
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"data": {
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"db.system": "postgresql",
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"db.query.text": "UPDATE users SET name = $1, email = $2 WHERE id = $3",
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"otel.kind": "CLIENT",
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"sentry.op": "db",
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"sentry.origin": "auto.db.otel.prisma"
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},
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"hash": "9747ee0db22ccb33"
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},
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{
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"timestamp": 1752683532.436347,
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"start_timestamp": 1752683532.436282,
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"op": "default",
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"span_id": "e8f7a6b5c4d3c2ba",
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"parent_span_id": "a8b7c6d5e4f39210",
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"trace_id": "a1b2c3d4e5f67890abcdef1234567890",
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"status": "ok",
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"description": "prisma:engine:serialize",
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"origin": "auto.db.otel.prisma",
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"data": {
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"sentry.origin": "auto.db.otel.prisma"
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},
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"hash": "ec7cb3896f17c6fd"
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},
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{
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"timestamp": 1752683532.457153,
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"start_timestamp": 1752683532.436713,
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"op": "db",
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"span_id": "f9a8b7c6d5e4d3cb",
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"parent_span_id": "a8b7c6d5e4f39210",
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"trace_id": "a1b2c3d4e5f67890abcdef1234567890",
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"status": "ok",
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"description": "UPDATE users SET name = $1, email = $2 WHERE id = $3",
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"origin": "auto.db.otel.prisma",
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"data": {
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"db.system": "postgresql",
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"db.query.text": "UPDATE users SET name = $1, email = $2 WHERE id = $3",
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"otel.kind": "CLIENT",
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"sentry.op": "db",
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"sentry.origin": "auto.db.otel.prisma"
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},
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"hash": "9747ee0db22ccb33"
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},
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{
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"timestamp": 1752683532.457415,
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"start_timestamp": 1752683532.457346,
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"op": "default",
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"span_id": "a0b9c8d7e6f5e4dc",
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"parent_span_id": "a8b7c6d5e4f39210",
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"trace_id": "a1b2c3d4e5f67890abcdef1234567890",
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"status": "ok",
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"description": "prisma:engine:serialize",
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"origin": "auto.db.otel.prisma",
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"data": {
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"sentry.origin": "auto.db.otel.prisma"
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},
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"hash": "ec7cb3896f17c6fd"
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},
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{
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"timestamp": 1752683532.477919,
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"start_timestamp": 1752683532.457749,
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"op": "db",
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"span_id": "b1c0d9e8f7a6f5ed",
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"parent_span_id": "a8b7c6d5e4f39210",
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"trace_id": "a1b2c3d4e5f67890abcdef1234567890",
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"status": "ok",
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"description": "UPDATE users SET name = $1, email = $2 WHERE id = $3",
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"origin": "auto.db.otel.prisma",
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"data": {
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"db.system": "postgresql",
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"db.query.text": "UPDATE users SET name = $1, email = $2 WHERE id = $3",
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"otel.kind": "CLIENT",
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"sentry.op": "db",
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"sentry.origin": "auto.db.otel.prisma"
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},
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"hash": "9747ee0db22ccb33"
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},
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{
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"timestamp": 1752683532.478153,
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"start_timestamp": 1752683532.478087,
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"op": "default",
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"span_id": "c2d1e0f9a8b7a6fe",
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"parent_span_id": "a8b7c6d5e4f39210",
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"trace_id": "a1b2c3d4e5f67890abcdef1234567890",
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"status": "ok",
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"description": "prisma:engine:serialize",
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"origin": "auto.db.otel.prisma",
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"data": {
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"sentry.origin": "auto.db.otel.prisma"
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},
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"hash": "ec7cb3896f17c6fd"
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}
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]
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}

‎src/sentry/performance_issues/detectors/experiments/mn_plus_one_db_span_detector.py

Lines changed: 19 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -43,6 +43,9 @@ def _equivalent(self, a: Span, b: Span) -> bool:
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if not first_op or not second_op or first_op != second_op:
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return False
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if first_op == "default":
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return a.get("description") == b.get("description")
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if first_op.startswith("db"):
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return a.get("hash") == b.get("hash")
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found_db_op = False
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found_different_span = False
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# Patterns shouldn't start with a serialize span, since that follows an operation or query.
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first_span_description = pattern[0].get("description", "")
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if (
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first_span_description == "prisma:client:serialize"
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or first_span_description == "prisma:engine:serialize"
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):
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return False
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for span in pattern:
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op = span.get("op") or ""
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description = span.get("description") or ""
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# We've broken the MN pattern, so return to the Searching state. If it
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# is a significant problem, also return a PerformanceProblem.
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times_occurred = int(len(self.spans) / len(self.pattern))
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start_index = len(self.pattern) * times_occurred
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remaining_spans = self.spans[start_index:] + [span]
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# Keep more context for pattern detection by including spans that could be
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# the beginning of a new pattern. Instead of just keeping the incomplete
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# remainder, keep the last pattern_length spans plus the current span.
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# Keep at least the last pattern_length spans (or all if we have fewer)
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pattern_length = len(self.pattern)
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context_start = max(0, len(self.spans) - pattern_length)
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remaining_spans = self.spans[context_start:] + [span]
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return (
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SearchingForMNPlusOne(
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settings=self.settings,

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