MongoDB Vector Search 결과 설명

1
{
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  explainVersion: '1',
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  stages: [
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    {
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      '$vectorSearch': {
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        index: 'vector_index',
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        path: 'plot_embedding_voyage_3_large',
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        queryVector: [
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          -0.034731735,  0.008558298,   -0.0153717, -0.029912498,  0.011549547,
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          ...,
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          -0.006688767,  0.047527634,  0.040714234
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        ],
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        numCandidates: 150,
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        limit: 10,
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        explain: {
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          query: {
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            type: 'WrappedKnnQuery',
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            args: {
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              query: [
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                {
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                  type: 'InstrumentableKnnFloatVectorQuery',
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                  args: {
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                    field: '$type:knnVector/plot_embedding_voyage_3_large',
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                    k: 150
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                  },
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                  stats: {
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                    context: { millisElapsed: 0 },
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                    match: { millisElapsed: 0 },
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                    score: { millisElapsed: 0 }
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                  }
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                },
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                {
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                  type: 'DocAndScoreQuery',
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                  args: {},
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                  stats: {
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                    context: {
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                      millisElapsed: 15.794112,
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                      invocationCounts: {
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                        createWeight: Long('1'),
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                        createScorer: Long('4')
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                      }
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                    },
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                    match: {
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                      millisElapsed: 0.084957,
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                      invocationCounts: { nextDoc: Long('152') }
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                    },
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                    score: {
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                      millisElapsed: 0.688285,
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                      invocationCounts: {
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                        score: Long('150'),
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                        setMinCompetitiveScore: Long('25')
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                      }
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                    }
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                  }
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                }
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              ]
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            },
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            stats: {
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              context: {
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                millisElapsed: 76.547561,
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                invocationCounts: {
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                  vectorExecution: Long('1'),
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                  createWeight: Long('1'),
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                  createScorer: Long('4')
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                }
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              },
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              match: {
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                millisElapsed: 0.084957,
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                invocationCounts: { nextDoc: Long('152') }
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              },
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              score: {
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                millisElapsed: 0.688285,
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                invocationCounts: {
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                  score: Long('150'),
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                  setMinCompetitiveScore: Long('25')
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                }
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              }
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            }
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          },
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          collectors: {
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            allCollectorStats: {
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              millisElapsed: 2.513847,
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              invocationCounts: {
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                collect: Long('150'),
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                competitiveIterator: Long('2'),
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                setScorer: Long('2')
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              }
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            }
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          },
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          metadata: {
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            mongotVersion: '1.49.3',
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            mongotHostName: '<hostname>.mongodb.net',
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            indexName: 'vector_index',
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            lucene: { totalSegments: 2, totalDocs: 3483 }
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          },
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          resourceUsage: {
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            majorFaults: Long('0'),
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            minorFaults: Long('0'),
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            userTimeMs: Long('0'),
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            systemTimeMs: Long('0'),
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            maxReportingThreads: 1,
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            numBatches: 1
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          },
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          luceneVectorSegmentStats: [
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            {
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              executionType: 'Approximate',
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              docCount: 3420,
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              approximateStage: { millisElapsed: 47.246946 }
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            },
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            {
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              executionType: 'Approximate',
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              docCount: 63,
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              approximateStage: { millisElapsed: 0.520547 }
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            }
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          ]
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        }
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      },
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      nReturned: Long('0'),
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      executionTimeMillisEstimate: Long('306')
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    },
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    {
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      '$_internalSearchIdLookup': { limit: Long('10') },
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      nReturned: Long('0'),
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      executionTimeMillisEstimate: Long('306')
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    }
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  ],
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  queryShapeHash: '2816D59590F550220114018918B7CF7D39CFFD6832A9D0FAAAD28D70B83A3185',
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  serverInfo: {
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    host: '<hostname>.mongodb.net',
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    port: 27017,
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    version: '8.0.3',
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    gitVersion: 'bed99f699da6cb2b74262aa6d473446c41476643'
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  },
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  serverParameters: {
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    internalQueryFacetBufferSizeBytes: 104857600,
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    internalQueryFacetMaxOutputDocSizeBytes: 104857600,
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    internalLookupStageIntermediateDocumentMaxSizeBytes: 16793600,
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    internalDocumentSourceGroupMaxMemoryBytes: 104857600,
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    internalQueryMaxBlockingSortMemoryUsageBytes: 33554432,
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    internalQueryProhibitBlockingMergeOnMongoS: 0,
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    internalQueryMaxAddToSetBytes: 104857600,
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    internalDocumentSourceSetWindowFieldsMaxMemoryBytes: 104857600,
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    internalQueryFrameworkControl: 'trySbeRestricted',
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    internalQueryPlannerIgnoreIndexWithCollationForRegex: 1
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  },
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  command: {
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    aggregate: 'embedded_movies',
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    pipeline: [
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      {
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        '$vectorSearch': {
151
          index: 'vector_index',
152
          path: 'plot_embedding_voyage_3_large',
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          queryVector: [
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            -0.034731735,  0.008558298,   -0.0153717, -0.029912498,  0.011549547,
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            ...,
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            -0.006688767,  0.047527634,  0.040714234
157
          ],
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          numCandidates: 150,
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          limit: 10
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        }
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      }
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    ],
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    cursor: {},
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    '$db': 'sample_mflix'
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  },
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  ok: 1,
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  '$clusterTime': {
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    clusterTime: Timestamp({ t: 1752447925, i: 20 }),
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    signature: {
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      hash: Binary.createFromBase64('JELVXSAkvhOwS5+CSP58Hj7wJZA=', 0),
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      keyId: Long('7485474929970774018')
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    }
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  },
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  operationTime: Timestamp({ t: 1752447925, i: 20 })
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}

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        explain: {
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                args: { queryType: 'FieldExistsQuery' },
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                    invocationCounts: {
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                  score: { millisElapsed: 0 }
                }
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                invocationCounts: { createWeight: Long('1'), createScorer: Long('4') }
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                }
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          },
          collectors: {
            allCollectorStats: {
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              invocationCounts: {
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                competitiveIterator: Long('2'),
                setScorer: Long('2')
              }
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            mongotHostName: '<hostname>.mongodb.net',
            indexName: 'vector_index',
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            systemTimeMs: Long('0'),
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            numBatches: 1
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        }
      },
      nReturned: Long('0'),
      executionTimeMillisEstimate: Long('75')
    },
    {
      '$_internalSearchIdLookup': { limit: Long('10') },
      nReturned: Long('0'),
      executionTimeMillisEstimate: Long('75')
    }
  ],
  queryShapeHash: '2816D59590F550220114018918B7CF7D39CFFD6832A9D0FAAAD28D70B83A3185',
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    internalQueryMaxAddToSetBytes: 104857600,
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        limit: 10,
        explain: {
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  queryShapeHash: '2816D59590F550220114018918B7CF7D39CFFD6832A9D0FAAAD28D70B83A3185',
  serverInfo: {
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    internalDocumentSourceGroupMaxMemoryBytes: 104857600,
    internalQueryMaxBlockingSortMemoryUsageBytes: 33554432,
    internalQueryProhibitBlockingMergeOnMongoS: 0,
    internalQueryMaxAddToSetBytes: 104857600,
    internalDocumentSourceSetWindowFieldsMaxMemoryBytes: 104857600,
    internalQueryFrameworkControl: 'trySbeRestricted',
    internalQueryPlannerIgnoreIndexWithCollationForRegex: 1
  },
  command: {
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    internalDocumentSourceGroupMaxMemoryBytes: 104857600,
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          metadata: {
            mongotVersion: '1.49.3',
            mongotHostName: '<hostname>.mongodb.net',
            indexName: 'vector_index',
            lucene: { totalSegments: 2, totalDocs: 3483 }
          },
          resourceUsage: {
            majorFaults: Long('0'),
            minorFaults: Long('0'),
            userTimeMs: Long('0'),
            systemTimeMs: Long('0'),
            maxReportingThreads: 1,
            numBatches: 1
          }
        }
      },
      nReturned: Long('0'),
      executionTimeMillisEstimate: Long('38')
    },
    {
      '$_internalSearchIdLookup': { limit: Long('10') },
      nReturned: Long('0'),
      executionTimeMillisEstimate: Long('38')
    }
  ],
  queryShapeHash: '2816D59590F550220114018918B7CF7D39CFFD6832A9D0FAAAD28D70B83A3185',
  serverInfo: {
    host: '<hostname>.mongodb.net',
    port: 27017,
    version: '8.0.3',
    gitVersion: 'bed99f699da6cb2b74262aa6d473446c41476643'
  },
  serverParameters: {
    internalQueryFacetBufferSizeBytes: 104857600,
    internalQueryFacetMaxOutputDocSizeBytes: 104857600,
    internalLookupStageIntermediateDocumentMaxSizeBytes: 16793600,
    internalDocumentSourceGroupMaxMemoryBytes: 104857600,
    internalQueryMaxBlockingSortMemoryUsageBytes: 33554432,
    internalQueryProhibitBlockingMergeOnMongoS: 0,
    internalQueryMaxAddToSetBytes: 104857600,
    internalDocumentSourceSetWindowFieldsMaxMemoryBytes: 104857600,
    internalQueryFrameworkControl: 'trySbeRestricted',
    internalQueryPlannerIgnoreIndexWithCollationForRegex: 1
  },
  command: {
    aggregate: 'embedded_movies',
    pipeline: [
      {
        '$vectorSearch': {
          index: 'vector_index',
          path: 'plot_embedding_voyage_3_large',
          queryVector: [
            -0.034731735,  0.008558298,   -0.0153717, -0.029912498,  0.011549547,
            ...,
            -0.006688767,  0.047527634,  0.040714234
          ],
          exact: true,
          limit: 10
        }
      }
    ],
    cursor: {},
    '$db': 'sample_mflix'
  },
  ok: 1,
  '$clusterTime': {
    clusterTime: Timestamp({ t: 1752449065, i: 1 }),
    signature: {
      hash: Binary.createFromBase64('TwyeFcQsr24W6cTIx7ZIb/R0H6I=', 0),
      keyId: Long('7485474929970774018')
    }
  },
  operationTime: Timestamp({ t: 1752449065, i: 1 })
}